Search Results

< Back Natasa Tagasovska, PhD WiML Secretary Visit my Profile

< Back Danielle Belgrave, PhD WiML Director (2019-2020, 2021-2024)

< Back Sarah Brown, PhD WiML Treasurer (2016-2019) Visit my Profile

< Back Sara Jennings WiML Director (2021-2022) Visit my Profile

< Back Ilene Cartright WiML Director (2019-2022)

 4th Women in Machine Learning Un-Workshop, ICML 2023 4th Women in Machine Learning Un-Workshop, ICML 2023 The 4th WiML Un-Workshop is co-located with ICML on Friday, July 28th, 2023. Speakers Logistics Program Call for Participation Committee FAQ Machine learning is one of the fastest growing areas of computer science research. Search engines, text mining, social media analytics, face recognition, DNA sequence analysis, speech and handwriting recognition, healthcare analytics are just some of the applications in which machine learning is routinely used. In spite of the wide reach of machine learning and the variety of theory and applications, it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models. The annual Women in Machine Learning Un-Workshop is the flagship event in un-conference style of Women in Machine Learning , primarily intended to foster active participant engagement in the program. This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia and learn from each other. Underrepresented minorities and undergraduates interested in machine learning research are encouraged to attend. We welcome all genders; however, any formal presentations, i.e. talks and posters, are given by women. We strive to create an atmosphere in which participants feel comfortable to engage in technical and career-related conversations. Now in its 4th year, the 2023 un-workshop is co-located with IC ML . Besides this annual un-workshop, Women in Machine Learning also organizes annual workshop at NeurIPS, events such as lunch or social at the AISTATS or AAAI conferences, maintains a public directory of women active in ML, profiles the research of women in ML, and maintains a list of resources for women working in ML. All participants are required to abide by the WiML Code of Conduct . I'm a paragraph. Click here to add your own text and edit me. It's easy. Invited Speakers Rihab Gorsane Jennifer Doudna Joelle Pineau Location This workshop will be in-person only, co-located with ICML at the Hawaii Convention Centre , Honolulu. Type of registration required to attend Any type of in-person registration (tutorial / workshop / conference / all) grants you in-person access to the un-workshop. PROGRAM PANELISTS BREAKOUT SESSIONS COFFEE MEET & MINGLE SOCIAL The program follows the following color scheme: talks , breakout sessions , program breaks , sponsor round table , and panel discussion . The schedule is in local time zone (HST) . The program book is available at Program Book 2023 . 09:15 - 09.30 [Introduction & Opening Remarks - Priyadarshini Kumari (Sony AI) and Giulia Luise (Microsoft) - Hall 316C ] 09:30 - 10.00 [Invited Talk - Joelle Pineau (Meta AI and McGill University, Canada)] A culture of open and reproducible research in the era of large AI generative models - Hall 316C ] We have seen in the last year an incredible pace of progress in large AI models, with increasing abilities to generate high-quality images, videos, text, sound, and more. The best of these models display signs of creativity, reasoning, generalization, and plasticity beyond what we could imagine just a few years ago. Yet many challenges and open questions remain, both on the technological aspects and the societal impact of these models. Further progress, especially in mitigating the social risks of these models, is hampered by a lack of transparency and reproducibility. In this talk, Joelle will describe ongoing efforts to increase best practices towards the responsible training and deployment of AI research systems, drawing on her experience with the ML reproducibility program and the recent release of several state-of-the-art large models. 10.00 - 10.30 [Coffee Break and Networking] 10:30 - 11.00 [Invited Talk - Jennifer Doudna (UC Berkeley, USA)] Science and Snorkeling: My Journey with CRISPR - Hall - 316C ] In this talk, Jennifer will discuss her professional and personal journey working on CRISPR technology, from its genesis to its applications today, and focus on ethical challenges that mirror challenges with AI/ML. 11:00 - 12:00 [ Breakout session #2 (Three parallel sessions)] 1. 1) Leveraging Large Scale Models for Identifying and Fixing Deep Neural Networks Biases . [Hall 316C] Leader: Polina Kirichenko, Co-leads: Reyhane Askari Hemmat, Megan Richards. Facilitators: Vitória Barin Pacela , Mohammad Pezeshki 1. 2) The Role of Mentorship and Building Long-term Professional Relationships. [Hall 326A] Leader: Arushi Jain. Co-leads: Sangnie Bhardwaj Facilitators: Motahareh Sohrabi , Padideh Nouri 1. 3) Robustness in Machine Learning. [Hall 326B] Leader: Yao Qin. Co-lead: Qi Lei Facilitators: Christina Baek 12:00 - 13:30 [ Lunch and Sponsor Round Table Hall 316C ] Round Table A: Apple -- Finding Mentors and Being a Mentor Rishika Agarwal ( Engineer) Ivy Zhang (Engineer) Round Table B: D. E. Shaw Research -- Machine Learning at D. E. Shaw Research Jocelyn Sunseri (Machine Learning Research Engineer) Round Table C: Google DeepMind -- Keeping Up With the Pace of Change in Industry Kate Baumli (Research Engineer) Kavya Kopparupu (Research Engineer) Round Table D: Google Research -- Life and Work at Google Alicia Parrish (Research Scientist, Responsible AI) Round Table E: Microsoft -- Exploring Pathways: Career Opportunities, Growth, and Work-Life Balance at Microsoft Research Lili Wu (Data and Applied Scientist, Microsoft Research) Cyril Zhang (Senior Researcher, Microsoft Research) Round Table F: Two Sigma -- Your Next Big ML Move: Innovation in Finance Brittany Clarke (Diversity Recruiting Program Manager) Alyssa Lees (Engineering Manager, News Engineering: a NLP Technology Team) 13:30 - 14:00 [Invited Talk - Rihab Gorsane (Instadeep, Tunisia)] My journey at an African AI startup - Hall 316C ] In the talk, Rihab will share her personal journey as a mid-career woman coming from Africa in the field of Artificial Intelligence (AI) and highlight the remarkable experiences she has gained working at an African AI startup. With a focus on both technical accomplishments and driving forces that have propelled her forward, I aim to inspire the audience while providing valuable insights into her professional growth - particularly to women who aspire to build their careers in AI. 14:00 - 15:00 [ Breakout session #3 (Three parallel sessions)] 2. 1) Key Challenges for Applicable Reinforcement Learning . [Hall 316C] Leader: Fengdi Che. Co-leads: Arushi Jain Facilitators: Yueying Tian 2. 2) Data Diversity and Downstream Impact. [Hall 326B] Leader: Judy Shen. Co-lead: Paula Gradu Facilitators: Kristina Ulicna 2. 3) Deploying Research and Making Real-world Impact [Hall 326A] Leader: Fei Fang. Co-leads: Diyi Yang Facilitators: Bingbin Liu 15.00 - 15.30 [ Coffee Break and Networking] 15:30 - 16:30 [ Panel Discussion: Fostering Women's Leadership in the Realm of Emerging Trends and Technologies - Hall 316C ] Panelists: Joelle Pineau (Meta, McGill University), Pascale Fung (HKUST), Yao Qin (UC Santa Barbara, Google Research), Rihab Gorsane (Instadeep) Moderator: Natasa Tagasovska (Prescient Design, Genentech) The panel session will comprise 45 minutes of moderated discussion and a 15-minute Q&A with the audience. The session aims to bring together two significant themes: advancing women's leadership in AI and the future of machine learning with its emerging trends and technologies. The discussion will focus on empowering women in AI leadership positions to navigate these emerging trends effectively and reshape the landscape of AI. 16:30 - 16:45 [President Remarks: Sarah Tan (Cambia Health, Cornell University) - Hall 316C ] Joelle Pineau Joelle Pineau is the Vice President of AI Research at Meta, supporting labs across North America and Europe. She is also a faculty member at Mila and a Professor and William Dawson Scholar at the School of Computer Science at McGill University, where she co-directs the Reasoning and Learning Lab. She holds a BASc in Engineering from the University of Waterloo, and an MSc and PhD in Robotics from Carnegie Mellon University. Dr. Pineau's research focuses on developing new models and algorithms for planning and learning in complex partially-observable domains, and on applying these algorithms to complex problems in robotics, health care, games and conversational agents. Learn more about her work at: https://www.cs.mcgill.ca/~jpineau/ Pascale Fung Pascale Fung is a Chair Professor at the Department of Electronic & Computer Engineering at The Hong Kong University of Science & Technology (HKUST), and a visiting professor at the Central Academy of Fine Arts in Beijing. She is an elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) for her "significant contributions to the field of conversational AI and to the development of ethical AI principles and algorithms", an elected Fellow of the Association for Computational Linguistics (ACL) for her significant contributions towards statistical NLP, comparable corpora, and building intelligent systems that can understand and empathize with humans. She is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE), an elected Fellow of the International Speech Communication Association and the Director of HKUST Centre for AI Research (CAiRE), an interdisciplinary research centre on top of all four schools at HKUST. Learn more about her work at: https://pascale.home.ece.ust.hk/ Yao Qin Yao Qin is an Assistant Professor at the Department of Electrical and Computer Engineering at UC Santa Barbara, affiliated with the Department of Computer Science. She is also a senior research scientist at Google Research. She obtained her PhD degree at UC San Diego in Computer Science in 2020 and worked at Google Research afterwards. Her research interests primarily focus on robustness in multi-modality models, fairness in generative modeling and AI for healthcare, particularly for diabetes. She has served as Area Chair for ICLR-2023 and ICCV-2023 and co-local Chair for KDD-2023. In addition, she has been recognized as EECS Rising Star at MIT, 2021. Learn more about her at: https://www.ece.ucsb.edu/people/faculty/yao-qin Rihab Gorsane Rihab Gorsane is a Research Engineer and a team lead at InstaDeep. She is currently working on Reinforcement Learning based projects for industrial applications where she is helping to automate the scheduling, routing, and dispatching of trains at a large scale for a national rail operator. Rihab is also involved in research projects within the company focusing on Multi-Agent RL evaluation. She is passionate about AI skills development in Africa, is a Google developer expert in Machine Learning, and has taught DL/RL courses at Tunisian universities. Nataša Tagasovska (moderator) Nataša is a Senior Machine Learning Scientist at Prescient Design, Genentech since January 2022 where she joined the effort of applying ML to accelerate drug design. Her research interests are related to causal learning, generative models and multi-property optimization. Before she was a Senior Data Scientist at the SDSC at EPFL-ETHZ where she worked on translational projects applying ML to domain-specific and social science research efforts. She holds a PhD in Statistics from University of Lausanne and a BS and MSC in Computer Science and Engineering. During her studies she interend at Facebook (Meta) AI Research and NATO. During the day of the WiML Un-Workshop @ ICML 2023 there will be three different Breakout Sessions slots! We list the sessions, topics, leaders, and facilitators. Breakout Session #1 (11.00 - 12.00 HST) Leveraging Large Scale Models for Identifying and Fixing Deep Neural Networks Biases [Hall 316C] Leader: Polina Kirichenko Co-leads: Reyhane Askari Hemmat, Megann Richards Facilitators: Vitória Barin Pacela , Mohammad Pezeshki The Role of Mentorship and Building Long-term Professional Relationships [Hall 326A] Leader: Arushi Jain Co-leader: Sangnie Bhardwaj Facilitators: Motahareh Sohrabi, Padideh Nouri Robustness in Machine Learning [Hall 326B] Leader: Yao Qin. Co-leads: Qi Lei Facilitator: Christina Baek Breakout Session #2 (14.00 - 15.00 HST) Key Challenges for Applicable Reinforcement Learning [Hall 316C] Leader: Fengdi Che Co-leader: Arushi Jain Facilitators: Yueying Tian Deploying Research and Making Real-world Impact [Hall 326A] Leader: Fei Fang Co-leads: Diyi Yang Facilitator: Bingbin Liu Data Diversity and Downstream impact [Hall 326B] Leader: Judy Shen Co-leads: Paula Gradu Facilitator: Kristina Ulicna During the workshop program, there are two "program breaks" listed in the agenda : one in the morning (10:00 - 10:30 HST), and one in the afternoon (15:00 - 15:30 HST). These program breaks as an excellent opportunity to facilitate optional community-building activities for workshop attendees. We chose the coffee break activities inspired by the following principles: Optional participation . For both coffee breaks, participation will be encouraged, but is optional. Attendees who wish to simply "take a break" can stay in the room and not participate in the activities. We also have organized activities where participants can organically "walk away" and engage in other conversations at any time. Ease . We also hope to facilitate as low of a barrier to participation as possible, by reducing logistical barriers whenever possible (i.e. holding activities in the same room as the next talk). Inclusivity . We understand that WiML attendees are in significantly different places in their career. We've attempted to design all activities so that all attendees can participate, regardless of their seniority or experience working in ML. We hope the activities can facilitate new connections. Morning Coffee Break: Ask Me About (AMA)... Location: Main Room, 316C TL;DR: Learn from & with your fellow WiML attendees by completing an "Ask Me Anything" name tag at the registration desk! No matter where you are in your career, you never know how your experiences may be helpful to another attendee. Afternoon Coffee Break: Bingo Location: Main Room, 316C TL;DR: Make new friends & connections during our WiML "bingo" icebreaker game! We'll have prizes for the first attendees to finish their cards. Please join us for a reception hosted by the Women in Machine Learning (WiML) organization. The reception will take place before the WiML 2023 Un-Workshop on Thursday, July 27th, from 6 pm - 9 pm HST at Hawaiian Brian's , down the street from the Hawaii Convention Center. Dinner and drink tickets will be provided . Important notes: Registration for this reception is separate from registration for the workshop. To attend the reception, please register here . Due to extremely limited capacity, we ask that you only register if you are committed to attending. Registration is free. Do register early, as we may reach capacity soon. All participants are required to abide by the [WiML Code of Conduct] . 18:25-18:30 (5 minutes) Intro by Arianna Bunnell 18:35-18:50 (15 minutes) Remarks by Frankie Zhu (Assitant Professor at University of Hawaii) 18:50-18:55 (5 minutes) Remarks by Sarah Tan (WiML President, Cambia Health, Cornell University ) Call for Participation WiML 4th Un-Workshop @ ICML 2023 [submissions are now closed ] The Women in Machine Learning will be organizing the fourth un-workshop at ICML 2023. The un-workshop is based on the concept of an un-conference , a form of discussion on a pre-selected topic that is primarily driven by participants. Different from the traditional workshop format, the un-workshop ’s main focus is topical breakout sessions with short invited talks and casual, informal discussions. This is an event format to encourage more participant interaction and we are excited to be able to explore this format fully in-person this year! This year’s goal: the purpose of the un-workshop is to bring together researchers who identify as a woman, non-binary and/or gender non-conforming, fostering an environment for constructive discussions on research and career advancement. This year we particularly encourage mid-career researchers that identify as a woman, non-binary and/or gender non-conforming participate and contribute in the un-workshop! However, everyone, regardless of their career stage or gender, is warmly welcomed to participate and join in the discussions! We'd love for you to submit a one-page proposal to lead one of the breakout sessions. This is just one of the many ways you can contribute to the conversation - check out the other options below! While the presentations will be led by woman, non-binary and/or gender non-conforming individuals, all genders are invited to attend! IMPORTANT DATES June 3rd, 2023 -- Application Form opens! June 19th, 2023 June 24th, 2023 -- Deadline ( Anywhere on Earth ) to apply for a breakout session, registration fee funding, or volunteering June 24th, 2023 June 30th 2023 -- Notification of acceptance for all of the above (midnight Anywhere on Earth ) July 28th, 2023 -- WiML Un-Workshop Day Participate in the WiML Unworkshop Lead or engage in a breakout session : submit a proposal to lead a breakout session on a certain topic, either research oriented or about career development. Volunteer : seize this opportunity to contribute to the success of this WiML event! Help is needed with the technical setup and to fulfill the diverse needs that pop up during the event! Attend : participate in breakout session discussions, attend talks and/or panel discussions, come around for a chat with coffee! 1. Breakout session proposals: A breakout session is a 1-hour free-form discussion overseen by 1-3 leaders , with contributions from named participants, and with assistance from 1-2 facilitators to take notes and encourage participant interactions. We strongly encourage women, nonbinary and/or gender non-conforming individuals in all areas of machine learning to submit a proposal to lead or be a named participant in a topical breakout session. Compared to breakout sessions in previous years, we are making the following exciting changes for this year! First, we are expanding beyond technical and research topics. This year, we also encourage proposals related to growth , career development, and other non-technical topics that would be of interest to women, non-binary and/or gender non-confirming individuals in ML (particularly those who are mid-career). Second, we are introducing a new way of participating in breakout sessions: named participants . If you have an interesting idea or project that you think can spark productive discussion, or there is a topic that really interest you and you would be up for discussing it, we encourage you to submit a summary/position paper/poster. This can include both technical and non-technical topics. If there is a good match between your submission and the breakout session proposals, you will be matched with a breakout session leader and asked to contribute to the breakout session as a named participant. The exact nature of your contribution will be determined by your assigned session leader. You may apply to be a breakout session leader and/or apply to be a named participant. Guidance for applying to be a breakout session leader : your one-page proposal PDF should include a description of your proposed topic, why it is important/relevant, potential discussion questions, and how you would incorporate named participants (as described above). Guidance for applying to be a named participant : identify a topic, idea, or project that would be a good starting point for a discussion. This can be anything ranging from a summary of the topic and why you think it is relevant for WiML community, an unpolished idea, or a completed research project. Focus on explaining how your idea/project is relevant to a broader audience and what questions it sparks. Submissions must be one-page PDFs. Try to explain in simple language with minimal technical jargon. More information for leaders: A complete proposal consists of a 1 page PDF, along with the names and bios of leaders and facilitators submitted separately in the application form . Proposals need not be anonymized. We strongly recommend having at least 2 leaders, with a diverse set of leaders preferred (see selection criteria below). The names of facilitators should also be provided. WiML registration fee funding is prioritized for accepted breakout session leaders who fulfill certain eligibility criteria (see details below). Only one proposal submission per leader is allowed. If there are multiple leaders, only one leader needs to submit the proposal. There are no proceedings. Guidelines for and roles of leaders: Breakout session leaders must identify as a woman, non-binary and/or gender non-conforming Point-out key characteristics of your topic and make connections with other topics Describe the key challenges and approaches in this research area or career topic on a high-level Highlight possible points of discussion/goals to achieve during the session Use graphics/imagery and materials, e.g. slides, as needed Encourage inclusive (rather than unilateral) discussions Leaders should anticipate a small additional time commitment before the un-workshop to receive briefing/training and a possible dry run Submission instructions for breakout sessions: Proposals must be no more than 1 page (including any references, tables, and figures) submitted as a PDF. Main body text must be minimum 11 point font size and page margins must be minimum 0.75 inches (all sides). Your proposal should stand alone, without linking to a longer paper or supplement. You should provide a brief description of the topics you’d like to discuss, any relevant references, a plan for how you would organize the time (1 hour) allocated for a session, as well as some ideas on how you would encourage discussion and participant interaction during the session. Selection criteria for breakout sessions: The degree to which it is expected that participants will find the topic interesting and valuable. Diversity of leaders and facilitators, including diversity of experience/seniority, affiliation, race, viewpoint and thinking regarding the topic, etc. Plans for encouraging discussion and participant interaction during the session. More information for named participants: Guidelines for and roles of named participants: Breakout session named participants must be women, non-binary and/or gender non-conforming Point out key characteristics of your topic and make connections with other topics. Describe how your work or knowledge contributes to this area. Highlight possible points of discussion/goals to achieve during the session. Use graphics/imagery and materials e.g. slides as needed Encourage inclusive (rather than unilateral) discussions Submission instructions: Proposals must be no more than 1 page (including any references, tables, and figures) submitted as a PDF. Main body text must be minimum 11 point font size and page margins must be minimum 0.75 inches (all sides). Your proposal should stand alone, without linking to a longer paper or supplement. You should provide a brief description of the topics you’d like to discuss, any relevant references, and specifics around how you could contribute to the conversation. 2. Volunteering: We are seeking volunteers to help with technical setup and help during the event. You can indicate if you can help in any way in the corresponding section of the application form . Note: We also encourage you to apply for ICML volunteer and funding opportunities, which are separate and independent of WiML funding. Check the ICML website directly for details. 3. Participation instructions: To participate in ANY of the above roles and/or apply for registration fee funding, please fill in the application form by June 19, 2023 . Selected breakout session leaders, breakout session participants, volunteers, and funding recipients will be notified individually by the dates mentioned above. If you only wish to attend, we still recommend you fill in this form to provide your topic preferences. All participants are required to abide by the WiML Code of Conduct. 4. Registration fee funding: To apply for funding, you should identify as a woman, non-binary and/or gender non-conforming and commit to participating in at least one breakout session as a leader, named participant, facilitator, or attendee. Due to limited funding, we may not be able to support everyone eligible; however, we hope to support as many eligible applicants as possible. Accepted breakout session leaders or named participants who do not have other sources of registration fee funding will be prioritized for WiML funding. Other participants are also encouraged to apply. In your application, please indicate any funding sources you may have and how WiML's support is needed. Please note that WiML is able to fund registration fees only (not travel and accommodation) for selected participants. Further questions? Check out the FAQs ( https://wimlworkshop.org/faq/ ) or reach us at workshop@wimlworkshop.org 5. A sneak peak of other activities that the workshop will host: We will give more details closer to the event but the workshop will include a sponsor roundtable, where you will have the opportunity to interact and network with our sponsors. Furthermore, we will facilitate networking, mentoring, and impromptu discussions during the event . Stay tuned! PLATINUM SPONSORS PLATINUM SPONSORS PLATINUM SPONSORS Committee ORGANIZERS Giulia Luise General Chair Priyadarshini Kumari Senior Program Chair Stephanie Milani Breakout Program and Logistics Co-Chair Tiffany Ding Finance and Sponsorship Chair WiML RECEPTION ORGANIZER Arianna Bunnell Social Chair ADVISORY Danielle Belgrave D&I chair Bahare Fatemi D&I chair Mandana Samiei WiML Board POC SUPER VOLUNTEERS Mojgan Saeidi Nari Johnson FAQs How do I participate to the un-workshop? Start with filling the application form , especially if you are interested in presenting! The workshop will take place on July 28th 2023, co-located with ICML at the Hawaii Convention Centre in Honolulu. We will give more details nearer to the event. Does registering for the WiML un-workshop also mean I'm registered for ICML? Unfortunately not. You would still need to register separately for ICML – their registration process can be found here. You should only register to ICML if you are interested in attending ICML activities beyond WiML un-workshop. What does un-workshop mean? The un-workshop is based on the concept of an un-conference , a form of discussion on a pre-selected topic that is primarily driven by participants. Please check our Call for Participation for more details! How much travel funding is available? We will be able to sponsor the ICML registration fee for selected participants. Please fill the application form to apply for funding! How do I reach the WiML network? Use our mailing list . How can I sponsor WiML? Thank you for your interest in sponsoring WiML! See this page for more information. I am a man. Can I attend WiML un-workshop? Yes. Allies are welcome to attend! Note, however, that all speakers and poster presenters will primarily identify as women, nonbinary, or gender-nonconforming, as our goal is to promote them and their work within the machine learning community. What are the mentorship roundtables? We will update the format of this year's Sponsor Roundtable closer to the event! Is WiML an archival venue? No, WiML is a non-archival venue. Moreover, the un-workshop format does not include paper submissions. Check the Call for Participation to learn how to contribute to the un-workshop! Is there a Code of Conduct? Yes, you can find it here . I have a question that isn't answered here. How do I reach you? We receive a lot of email. Help us help you by reaching out through the appropriate channels. Job posting, announcement, CFP, etc: Post directly to WiML mailing list . Have event pictures to share: post on Twitter and tag @wimlworkshop Workshop enquiries: workshop@wimlworkshop.org If you are a company interested in sponsoring WiML: sponsorship@wimlworkshop.org Any other enquiries: info@wimlworkshop.org If you email us, don’t cc multiple email addresses — this saves us time routing your email to one mailbox, and reduces the chances of your email getting lost. Thank you in advance!

Empowering Women in Machine Learning: Amplifying Achievements, Elevating Voices, Building Leaders, and Bridging Gaps to enhance the experience of women in machine learning. 15th Women in Machine Learning Workshop (WiML 2020) The 15th WiML Workshop is co-located with the virtual NeurIPS conference on December 9th, 2020. Logistics Program Call for Participation FAQ Code Of Conduct Machine learning is one of the fastest growing areas of computer science research. In spite of the wide reach of machine learning and the variety of theory and applications it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models. The annual Women in Machine Learning (WiML) Workshop, co-located with NeurIPS, is our flagship event. This day-long technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, exchange ideas and learn from each other. The workshop started at the 2006 Grace Hopper Celebration and moved to NeurIPS in 2008. A History of WiML poster was created in 2015 to celebrate the 10th workshop. In 2020, WiML introduced an “un-workshop” at ICML based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants. The overall goal of the un-workshop is to advance research through collaboration and increased interaction among participants from diverse backgrounds. Location The workshop takes place virtually. See program for more details. PROGRAM The full program book for WiML 2020 is now available. Call for Participation Please fill out this form and register for NeurIPS if you would like to attend. All are welcome, and we look forward to your involvement! PLATINUM SPONSORS DIAMOND SPONSORS GOLD SPONSORS SILVER SPONSORS SILVER SPONSORS Back To Top

Empowering Women in Machine Learning: Amplifying Achievements, Elevating Voices, Building Leaders, and Bridging Gaps to enhance the experience of women in machine learning. 10th Annual Workshop for Women in Machine Learning (WiML 2015) Sunday, December 6 Co-Located with NIPS in Palais des Congrès de Montréal, Canada Speakers Logistics Program Call for Participation Committee FAQ Code Of Conduct Machine learning is one of the fastest growing areas of computer science research. Search engines, text mining, social media analytics, face recognition, DNA sequence analysis, speech and handwriting recognition, healthcare analytics are just some of the applications in which machine learning is routinely used. In spite of the wide reach of machine learning and the variety of theory and applications it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models. The annual Women in Machine Learning Workshop is the flagship event of Women in Machine Learning . This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia and learn from each other. Underrepresented minorities and undergraduates interested in machine learning research are encouraged to attend. We welcome all genders; however, any formal presentations, i.e. talks and posters, are given by women. We strive to create an atmosphere in which participants feel comfortable to engage in technical and career-related conversations. Now in its 11th year, the 2016 workshop is co-located with NIPS in Barcelona, Spain on December 5, 2016. A History of WiML poster was created to celebrate the 10th workshop , held in 2015 in Montreal, Canada 2015. Besides this un-workshop and annual workshop which is co-located with NeurIPS, Women in Machine Learning also organizes events such as breakfast at ICML and AAAI conferences and local meetup events, maintains a public directory of women active in ML, profiles the research of women in ML, and maintains a list of resources for women working in ML. Invited Speakers Jennifer Chayes Microsoft Research Maya Gupta Google Research Anima Anandkumar Amazon / UC Irvine Education_(42).jpg Suchi Saria John Hopkins Univ Location The workshop takes place in Centre de Convencions Internacional Barcelona , located at Plaça de Willy Brandt, 11-14, 08019 Barcelona, Spain. PROGRAM RESEARCH ROUNDTABLES CAREER & ADVICE ROUNDTABLES POSTERS Sunday, Dec 4 12.00 – 14.00 Registration desk open. Entrance Hall (enter from Entrance C) 14.00 – 19.00 Workshop on Effective Communication by Katherine Gorman of Talking Machines and Amazon (Optional). Invitation-only, RSVP required 16.00 – 18.00 Amazon Panel & Networking (Optional). Invitation-only, RSVP required 17.00 – 19.00 Facebook Lean-In Circles (Optional). Invitation-only, RSVP required 19.15 – 22.00 WiML Dinner (Optional). Separate registration required . Dedicated to Amazon 22.00 – 23.30 OpenAI Happy Hour (Optional). Invitation-only, RSVP required Monday, Dec 5 All events are held in Rooms 111 and 112, level P1, CCIB except for the poster session, which takes place in Area 5+6+7+8, level P0. 07.00 – 08.00 Registration and Breakfast. Dedicated to Microsoft and OpenAI. Registration desk at Entrance Hall (enter from Entrance C); Breakfast in Rooms 111 and 112, level P1 08.00 – 08.05 Opening Remarks 08.05 – 08.40 Invited Talk: Maya Gupta , Google Research. Designing Algorithms for Practical Machine Learning. [Abstract] [Video] 08.40 – 08.55 Contributed Talk: Maithra Raghu, Cornell Univ / Google Brain. On the Expressive Power of Deep Neural Networks. [Abstract] [Video] 08.55 – 09.10 Contributed Talk: Sara Magliacane, VU Univ Amsterdam. Ancestral Causal Inference. [Abstract] [Video] [Slides] 09.10 – 09.15 Break 09.15 – 10.15 Research Roundtables (Coffee served until 9.40am). Dedicated to Apple and Facebook 10.15 – 10.50 Invited Talk: Suchi Saria , John Hopkins Univ. Towards a Reasoning Engine for Individualizing Healthcare. [Abstract] [Video] 10.50 – 11.05 Contributed Talk: Madalina Fiterau, Stanford Univ. Learning Representations from Time Series Data through Contextualized LSTMs. [Abstract] [Video] 11.05 – 11.10 Break 11.10 – 11.25 Contributed Talk: Konstantina Christakopoulou, Univ Minnesota. Towards Conversational Recommender Systems. [Abstract] [Video] [Slides] 11.25 – 12.00 Invited Talk: Anima Anandkumar , Amazon / UC Irvine. Large-Scale Machine Learning through Spectral Methods: Theory & Practice. [Abstract] [Video] [Slides] 12.00 – 13.00 Career & Advice Roundtables 13.00 – 13.30 Lunch and Poster Setup. Dedicated to DeepMind and Google 13.30 – 15.30 Poster Session (Coffee served until 2pm). Open to WiML and NIPS attendees. Dedicated to our Silver Sponsors: Capital One, D.E. Shaw, Intel, Twitter. Area 5+6+7+8, level P0; Round 1: 1.40pm – 2.30pm; Round 2: 2.30pm – 3.20pm; Poster Removal: 3.20pm – 3.30pm 15.30 – 15.45 Raffle and WiML Updates : Tamara Broderick , MIT and Sinead Williamson , UT Austin. [Video] 15.45 – 16.00 Contributed Talk: Amy Zhang, Facebook. Using Convolutional Neural Networks to Estimate Population Density from High Resolution Satellite Images. [Abstract] [Video] 16.00 – 16.35 Invited Talk: Jennifer Chayes , Microsoft Research. Graphons and Machine Learning: Estimation of Sparse Massive Networks. [Abstract] [Video] 16.35 – 16.40 Closing Remarks NIPS Main Conference (NIPS registration required) 17.00 NIPS Opening Remarks. Area 1 + 2, level P0 WiML 2016 Poster Session Monday, Dec 5, 1.30pm to 3:30pm, Area 5+6+7+8, level P0, open to WiML and NIPS attendees 200+ posters covering theory, methodology, and applications of machine learning will be presented in 2 rounds. Accepted posters Accepted posters (with abstracts) . Abstracts listed here are for archival purposes and do not constitute proceedings for this workshop. Information for poster presenters: Posters for both rounds should be setup 1-1.40pm and removed 3.20-3.30pm. Each poster board is shared by 2-3 presenters. Please check the program book for your round number and poster number. Look for that number in the poster room with ‘W’ appended to the front, e.g. W1, W2, etc. Poster size: up to 37.9 inches width and 35.8 inches height (or 96.3 cm x 91.0 cm), portrait or landscape. Table 1: Deep learning I – Katja Hofmann, Microsoft Research, Oriol Vinyals, DeepMind Table 2: Deep learning II – Junli Gu, Tesla, Sergio Guadarrama, Google Research, Niv Sundaram, Intel Table 3: Reinforcement learning – Emma Brunskill, Carnegie Mellon / Stanford, Yisong Yue, Caltech Table 4: Bayesian methods I – Barbara Engelhardt, Princeton, Lamiae Azizi, University of Sydney Table 5: Bayesian methods II – Ferenc Huszar, Twitter / Magic Pony Table 6: Graphical models – Margaret Mitchell, Google Research, Danielle Belgrave, Imperial College London Table 7: Learning theory – Cynthia Rush, Columbia University, Corinna Cortes, Google Research Table 8: Statistical inference and estimation – Katherine M. Kinnaird, Brown University, Alessandra Tosi, Mind Foundry, Oxford Table 9: Optimization – Anima Anandkumar, Amazon / UC Irvine, Puja Das, Apple Table 10: Neuroscience – Irina Higgins, DeepMind, Jascha Sohl-Dickstein, Google Brain Table 11: Robotics – Raia Hadsell, DeepMind, Julie Bernauer, NVIDIA Table 12: Natural language processing I – Catherine Breslin, Amazon, Olivia Buzek, IBM Watson Table 13: Natural language processing II – Pallika Kanani, Oracle Labs, Ana Peleteiro Ramallo, Zalando, Aline Villavicencio, Federal University of Rio Grande do Sul, Brazil Table 14: Healthcare/biology applications – Tania Cerquitelli, Politecnico di Torino, Jennifer Healey, Intel Table 15: Music applications – Luba Elliott, iambicai, Kat Ellis, Amazon Music, Emilia Gomez, Universitat Pompeu Fabra, Barcelona Table 16: Social science applications – Allison Chaney, Princeton University, Isabel Valera, Max Planck Institute for Software Systems Table 17: Fairness, accountability, transparency in machine learning – Sarah Bird, Microsoft, Ekaterina Kochmar, University of Cambridge Table 18: Computational sustainability – Erin LeDell, H2O.ai, Jennifer Dy, Northeastern University Table 19: Computer vision – Judy Hoffman, Stanford University, Manohar Paluri, Facebook Table 20: Human-in-the-Loop Learning – Been Kim, Allen Institute for AI / Univ of Washington, Saleema Amershi, Microsoft Research Table 1: Machine Learning @Amazon: Jumpstarting your career in industry – Anima Anandkumar, Catherine Breslin, Enrica Maria Fillipi Table 2: Careers@Apple – Meriko Borogove, Anh Nguyen Table 3: Machine Learning @DeepMind: Research in industry vs. academia – Nando De Freitas, Viorica Patraucean, Kimberly Stachenfeld Table 4: Machine Learning @Facebook: Sponsorship vs. Mentorship Throughout Your Career – Angela Fan, Amy Zhang, Christy Sauper, Natalia Neverova, Manohar Paluri Table 5: Machine Learning @Google: Industrial Research and Academic Impact – Corinna Cortes, Google Table 6: Machine Learning and Deep Learning @Microsoft – Christopher Bishop, Mir Rosenberg, Anusua Trivedi Table 7: Delivering phenomenal customer experiences with Machine Learning @Capital One – Jennifer Hill, Marcie Apelt Table 8: Networking I – Olivia Buzek, IBM Watson, Jennifer Healey, Intel Table 9: Networking II – Pallika Kanani, Oracle Labs, Been Kim, Allen Institute for AI / Univ of Washington Table 10: Work/Life Balance (academia) – Namrata Vaswani, Iowa State University, Beka Steorts, Duke University Table 11: Work/Life Balance (industry) I – Yuanyuan Pao, Lyft, Antonio Penta, United Technologies Research Centre, Ireland Table 12: Work/Life Balance (industry) II – Kat Ellis, Amazon Music, Puja Das, Apple Table 13: Choosing between academia/industry I – Katherine M. Kinnaird, Brown University, Jascha Sohl-Dickstein, Google Brain Table 14: Choosing between academia/industry II – Sarah Bird, Microsoft, Oriol Vinyals, DeepMind Table 15: Life with Kids – Jenn Wortman Vaughan, Microsoft Research, Julie Bernauer, NVIDIA Table 16: Getting a job (academia) I – Jennifer Chayes, Microsoft Research, Yisong Yue, Caltech Table 17: Getting a job (academia) II – Tamara Broderick, MIT, Cynthia Rush, Columbia University Table 18: Getting a job (industry) I – Anne-Marie Tousch, Criteo, Sergio Guadarrama, Google Research Table 19: Getting a job (industry) II – Margaret Mitchell, Google Research, Erin LeDell, H2O.ai Table 20: Doing a postdoc – Cristina Savin, IST Austria / NYU, Judy Hoffman, Stanford University Table 21: Doing research in industry – Junli Gu, Tesla, Samy Bengio, Google Brain Table 22: Keeping up with academia while in industry – Irina Higgins, DeepMind, Alessandra Tosi, Mind Foundry, Oxford Table 23: Surviving graduate school – Allison Chaney, Princeton University, Viktoriya Krakovna, DeepMind Table 24: Seeking funding: fellowships and grants – Aline Villavicencio, Federal University of Rio Grande do Sul, Brazil, Danielle Belgrave, Imperial College London Table 25: Establishing collaborations – Barbara Engelhardt, Princeton University, Ekaterina Kochmar, University of Cambridge Table 26: Joining startups – Alyssa Frazee, Stripe, Ferenc Huszar, Twitter / Magic Pony Table 27: Scientific communication – Katherine Gorman, Talking Machines, Ana Peleteiro Ramallo, Zalando Table 28: Building your professional brand – Luba Elliott, iambicai, Lamiae Azizi, The University of Sydney Table 29: Commercializing your research – Katherine Boyle, General Catalyst, Zehan Wang, Twitter / Magic Pony Table 30: Long-term career planning – Inmar Givoni, Kindred.ai, Jennifer Dy, Northeastern University Call for Participation The 11th WiML Workshop is co-located with NIPS in Barcelona, Spain on Monday, December 05, 2016. The workshop is a full-day event with invited speakers, oral presentations, and posters. The event brings together faculty, graduate students, and research scientists for an opportunity to connect and exchange ideas. There will also be a panel discussion and a mentoring session to discuss current research trends and career choices in machine learning. Underrepresented minorities and undergraduates interested in pursuing machine learning research are encouraged to participate. While all presenters will be female, all genders are invited to attend. This is a technical workshop with exciting technical talks. Important Dates August 29, 2016 11:59pm PST – Abstract submission deadline September 26, 2016 – Notification of abstract acceptance October 5, 2016 11:59pm PST- Travel grant/oral presentation application deadline October 15, 2016 – End of abstract editing period October 24, 2016 – Notification of travel grant/oral presentation acceptance November 1, 2016 (or before, if we run out of space) – Registration deadline December 4, 2016 – Pre-workshop dinner and events December 5, 2016 – Workshop Submission Instructions We strongly encourage female students, post-docs and researchers in all areas of machine learning to submit an abstract (500 words or less) describing new, previously, or concurrently published research. We welcome abstract submissions in theory, methodology, as well as applications. Authors of accepted abstracts will be asked to present their work in a poster session. A few authors will be selected to give 15 minutes oral presentations. Submission page: https://easychair.org/conferences/?conf=wiml2016 Evaluation criteria: Submissions will be peer reviewed. Abstracts will be evaluated on scientific merit and relevance to the community. To facilitate the peer review process, we encourage authors to sign up as reviewers when submitting abstracts. Examples of accepted abstracts from previous years. Note that despite the option to upload a paper in the submission system, this is not required. Due to the volume of submissions anticipated, we are unable to review any submitted materials besides the requested abstract. Travel Scholarships Registration is free. Partial scholarships will be provided to female students and postdoctoral attendees with accepted abstracts to offset travel costs. GOLD SPONSORS SILVER SPONSORS BRONZE SPONSORS SUPPORTER Committee ORGANIZERS Diana Cai Statistics PhD student University of Chicago Deborah Hanus Computer Science PhD student Harvard University Sarah Tan Statistics PhD student Cornell University Isabel Valera Postdoctoral Fellow Max Planck Institute for Software Systems Rose Yu Computer Science PhD student University of Southern California AREA CHAIRS Danielle Belgrave (Imperial College London) Tamara Broderick (Massachusetts Institute of Technology) Allison Chaney (Princeton University) Deborah Hanus (Harvard University) Pallika Kanani (Oracle Labs) Katherine M. Kinnaird (Brown University) Lizhen Lin (University of Texas at Austin) Maria Lomeli (University of Cambridge) Konstantina Palla (University of Oxford) Sara Wade (University of Warwick) Sinead Williamson (University of Texas at Austin) Svitlana Volkova (Pacific Northwest National Laboratory) FAQs Do you have a list of members? How can I join WiML? WiML doesn’t have “members” per se, any women working in machine learning can be part of the WiML network. We have a mailing list for anyone to post announcements of interest to the WiML network and an opt-in, necessarily incomplete directory of women working in machine learning . How can I join the WiML mailing list? Join the mailing list directly here . What kind of events do you organize? Our flagship event is the annual WiML Workshop, typically co-located with NeurIPS, a machine learning conference. We also organize an “un-workshop” at ICML, as well as small events (e.g. lunches and receptions) at other machine learning conferences, such as CoRL, COLT, etc. Check out our events page for up-to-date listings of events. Do you have local meetups? No, but check out WiMLDS (website, Twitter), another organization that supports women in machine learning by organizing local meetups. How do I reach the WiML network? Use our mailing list . How can I sponsor WiML? Thank you for your interest in sponsoring WiML! See this page for more information. I am looking for an invited speaker / panelist / area chair / program committee member etc. Can WiML help me? Use our directory of women in machine learning or post this opportunity to our mailing list . I want to circulate a job posting. Can WiML help me? Post directly to our mailing list . How can I support WiML? You can: Post interesting opportunities and job postings to our mailing list . Use our directory of women in machine learning to find invited speakers, panelists, area chairs, program committee members, etc, or post these opportunities to our mailing list . Sponsor us. See this page for more information. Volunteer at one of our events. Check out our events page for up-to-date listings of events. Apply to be an area chair or reviewer at WiML Workshop (see this year’s workshop website for info). Take pictures at our events and share with us (tag @wimlworkshop on Twitter). If you see us mentioned in the media, send us a link at info@wimlworkshop.org . And many others! How did WiML start? What's the founding story? Hanna Wallach, Jennifer Wortman Vaughan, Lisa Wainer, and Angela Yu shared a room at NIPS 2005. Late one night, they talked about how exciting it was that there were FOUR female students at NIPS that year. They tried to list all the women in machine learning they know of and got to 10, then started talking about creating a meeting or gathering for all these women and perhaps others that they didn’t know about. Jenn, Lisa, and Hanna put together a proposal for a session at the 2006 Grace Hopper Celebration of Women in Computing that would feature talks and posters by female researchers and students in machine learning. The 1st WiML workshop was co-located with the 2006 Grace Hopper Celeberation. In 2008, WiML Workshop moved to NIPS (renamed NeurIPS in 2018) and there has been a WiML Workshop at NeurIPS every year since. In 2020, WiML introduced an “un-workshop” at ICML based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants. Read more WiML history here ! I am a man. Can I attend WiML? Yes. Allies are welcome to attend! Note, however, that all speakers and poster presenters will primarily identify as women, nonbinary, or gender-nonconforming, as our goal is to promote them and their work within the machine learning community. What are the mentorship roundtables? Each table seats 8-10 people (including mentors), with two mentors leading the discussion on a particular topic at each table. WiML attendees rotate between tables every 15-20 minutes. This allows attendees to gain exposure to different topics, and mentors to meet a large number of WiML attendees. Is WiML an archival venue? No, WiML is a non-archival venue. This means that, if your contribution is accepted, we will not be asking you to submit a camera-ready version of it, nor will we publish it anywhere (neither online nor in proceedings of any sort). We will only make the title and authors’ names available in the program book. I have a question that isn't answered here. How do I reach you? We receive a lot of email. Help us help you by reaching out through the appropriate channels. Job posting, announcement, CFP, etc: Post directly to WiML mailing list . Have event pictures to share: post on Twitter and tag @wimlworkshop Workshop enquiries: workshop@wimlworkshop.org If you are a company interested in sponsoring WiML: sponsorship@wimlworkshop.org Any other enquiries: info@wimlworkshop.org If you email us, don’t cc multiple email addresses — this saves us time routing your email to one mailbox, and reduces the chances of your email getting lost. Thank you in advance! Back To Top

< Back Jane Wang, PhD WiML Director (2020-2022) Visit my Profile

< Back Judy Hanwen Shen WiML Director Visit my Profile

Empowering Women in Machine Learning: Amplifying Achievements, Elevating Voices, Building Leaders, and Bridging Gaps to enhance the experience of women in machine learning. 2nd Women in Machine Learning Un-Workshop The 2nd WiML virtual Un-Workshop is co-located with virtual ICML on Wednesday July 21st, 2021. Speakers Logistics Program Call for Participation Committee FAQ Code Of Conduct Machine learning is one of the fastest growing areas of computer science research. Search engines, text mining, social media analytics, face recognition, DNA sequence analysis, speech and handwriting recognition, healthcare analytics are just some of the applications in which machine learning is routinely used. In spite of the wide reach of machine learning and the variety of theory and applications, it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models. The annual Women in Machine Learning Workshop is the flagship event of Women in Machine Learning . This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia and learn from each other. Underrepresented minorities and undergraduates interested in machine learning research are encouraged to attend. We welcome all genders; however, any formal presentations, i.e. talks and posters, are given by women. We strive to create an atmosphere in which participants feel comfortable to engage in technical and career-related conversations. The workshop started at the 2006 Grace Hopper Celebration and moved to NeurIPS in 2008. A History of WiML poster was created in 2015 to celebrate the 10th workshop. This is the 2nd WiML Un-Workshop and is co-located with ICML . This event along with ICML are virtual events due to COVID-19. The term “un-workshop” is based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants. The overall goal of the un-workshop is to advance research through collaboration and increased interaction among participants from diverse backgrounds. Different from the workshop, the un-workshop’s main focus is topical breakout sessions, with short invited talks and casual, informal poster presentations. Besides this un-workshop and annual workshop which is co-located with NeurIPS, Women in Machine Learning also organizes events such as lunch at AAAI conference, maintains a public directory of women active in ML, profiles the research of women in ML, and maintains a list of resources for women working in ML. Invited Speakers Celia Cintas Research Scientist, IBM Research - Nairobi Yingzhen Li Lecturer at Department of Computing. Imperial College London, UK Sarah Hooker Research Scientist at Google Brain Luciana Benotti Associate Professor at the Universidad National de Cordoba (UNC) Argentina Location This un-workshop takes place virtually due to COVID-19. Please check the program book for a complete overview of the program. Rocket.chat info desk and tech support If you have general questions or technical difficulties on the day of the event, drop by the Rocket.chat window on the workshop page on icml.cc . Best Practices for virtual events Virtual conferences can be tricky, and there are a lot of unintuitive ways to make your experience (and the experience of others) a little better. You can read some of our tips here . Information on Talks, Panel and Breakout Sessions We will be hosting the talks, panel as a Zoom webinar. We will also host breakout sessions on Zoom. You can join these sessions by clicking the links on the ICML Un-Workshop webpage . As an attendee, you will not be able to unmute yourself. If you have questions about the content of the talk, please submit the questions using the Zoom Q&A feature. Time permitting, and depending on the volume of questions, the moderator will either ask your question for you or confirm with you to ask the question yourself and unmute you at a suitable time. Note that Q&A will be moderated by us so you will only be able to see some of the questions of the other attendees. If you want to send messages to the moderators during the seminar, please use the Zoom chat feature. If you have not used Zoom before, we highly recommend downloading and installing the Zoom client before the meeting. Additional instructions on how to use Zoom during a webinar can be found here . Information on Poster Session and Mentorship Social The WIML Un-Workshop poster session, mentorship social and The Joint Affinity Groups Poster Session takes place in Gather.Town. You can join these sessions by clicking the links on the ICML Un-Workshop webpage . See Gather.Town guidelines to troubleshoot common access issues. If you face any issues, check these common video/audio issues or Gather.Town FAQ . An Important Note on ICML Registration Please note that the application form does not constitute registration for the WiML Un-Workshop. To attend the un-workshop, you need to register for ICML at https://icml.cc . There is no separate registration for the un-workshop. PROGRAM PANELISTS MENTORS ACCEPTED POSTERS The 2021 WiML Un-Workshop at ICML will be held virtually on Wednesday, July 21th, 2021. WiML will also participate in the ICML Affinity Groups Joint Poster Session with Queer in AI on Monday, July 19th. All participants are required to abide by the WiML Code of Conduct . Please use this link to access the Un-Workshop on ICML. Wednesday, July 21th, 2021 Time (ET/New York ) - Event 09:40 – 09:50: Introduction and Opening Remarks 09:50 – 10:00: WiML D&I Chairs Remarks 10:00 – 10:25: Invited talk – Yingzhen Li 10:25 – 11:30: Breakout sessions #1 11:30 – 12:00: Virtual Coffee Break and Poster Session #1 12:00 – 12:25: Invited Talk – Celia Cintas 12:25 – 13:30: Breakout Sessions #2 13:30 – 14:30: Sponsor Expo: Presentations by Microsoft, QuantumBlack, Apple, and Facebook 14:30 – 15:30: Mentoring Social 15:30 – 18:45: Break + Informal Social 18:45 – 19:25: Invited Talk – Sara Hooker 19:25 – 20:30: Breakout Sessions #3 20:30 – 21:00: Virtual Coffee Break and Poster Session #2 21:00 – 21:25: Invited Talk – Luciana Benotti 21:25 – 22:30: Breakout Sessions #4 22:30 – 23:30: Panel Discussion – Sarah Dean, Sarah Aerni, Sylvia Herbert, Kalesha Bullard, Amy Zhang (moderator) 23:30 – 23:45: Closing Remarks Our sponsor booths are open during the Un-Workshop. Please find information on their schedules and events here . For more details about the breakout sessions (e.g. affiliations), please use this link . You can submit your questions to the panelists through this link . Breakout session #1, 10:25 AM – 11:30 AM ET ID - Session title - Leaders - Facilitators 1.1 Catching Out-of-Context Misinformation with Self-supervised LearningShivangi AnejaMamatha Thota, Vishwali Mhasawade 1.2 School mapping using computer vision technologySafa SulimanMaryam Daniali 1.3 Data Integration and Predictive Modeling for Precision Medicine in OncologyMehreen Ali Esther Oduntan 1.4 Unsupervised Learning in Computer VisionAyca Takmaz, Clara Fernandez Labrador Naina Dhingra 1.5 Machine Learning for Privacy: An Information Theoretic PerspectiveEcenaz Erdemir, Fatemehsadat Mireshghallah Cemre Cadir 1.6 Fundamentals of Contrastive Learning in VisionSamrudhdhi Rangrej, Ibtihel Amara, Zahra Vaseqi Farzaneh Askari 1.7 Exploring probabilistic sparse inferencing through the triangulation of neuroscience, computing and philosophyGagana B, Stuti Gupta Akash Smaran 1.8 Neural Machine Translation for Low-Resource LanguagesEn-Shiun Annie Lee, Surangika Ranathunga, Rishemjit Kaur, Marjana Prifti SkenduliNiti M KC, Jivat Neet Kaur Breakout session #2, 12:25 PM – 1:30 PM ET ID - Session title - Leaders - Facilitators 2.1 Geometry and Machine LearningMelanie WeberAnkita Shukla 2.2 Leveraging Open-Source Tools for Natural Language ProcessingJennifer Glenskii RanaAneri Rana, Niti M KC 2.3 Challenges and Opportunities in ML for Health Care: How to address interpretability in clinical decision making?Annika Marie Schoene, En-Shiun Annie Lee, Peiyuan Zhou Malinda Vania 2.4 Leading the Way for the Next Generation of Black Women in STEMLouvere Walker-Hannon, Dr. Tracee Gilbert Mozhgan Saeidi 2.5 Un-bookclub Algorithms of OppressionRajasi Desai, Esther Oduntan, Anoush Najarian Sindhuja Parimalarangan 2.6 Research within community: how to cultivate a nurturing environment for your researchRosanne LiuMehreen Ali 2.7 Explainable machine learning: do we have the right tools?Michal Moshkovitz, Chhavi Yadav Shreya Ghosh 2.8 Decision-Making in Social Settings: Addressing Strategic Feedback EffectsMeena Jagadeesan, Celestine Mendler-Dünner Frances Ding Breakout session #3, 7:25 PM – 8:30 PM ET ID - Session title - Leaders - Facilitators 3.1 Does your model know what it doesn’t know? Uncertainty estimation and out-of-distribution (OOD) detection in deep learningJie Ren, Polina Kirichenko, Sharon Yixuan Li, Sergul Aydore, Haleh Akrami Liyan Chen 3.2 ML Applications in Big CodeSonia Kim, Mozhgan Saeidi Shima Shahfar 3.3 Connecting Novel Perspectives on GNNs: A Cross-Domain OverviewIlke Demir, Nesreen Ahmed, Vasuki Narasimha Swamy, Subarna Tripathi Ancy Tom 3.4 Bridging the gap between academia and industryChip Huyen, Sharon Zhou Sasha Luccioni 3.5 Variational Inference for Neural NetworksSahar Karimi, Audrey Flower Gargi Balasubramaniam 3.6 Responsible AI in production: Technical and Ethical considerationsParul Pandey, Himani Agrawal Wanda Wang Breakout session #4, 9:25 PM – 10:30 PM ET ID - Session title - Leaders - Facilitators 4.1 AI and Creativity: Approaches to Generative ArtAneta NeumannAncy Tom 4.2 Attrition of women and minoritized individuals in AIJeff Brown, Christine Custis, Madu Srikumar, Himani AgrawalJeff Brown, Christine Custis, Madu Srikumar 4.3 Safely navigating scalability-reliability trade-offs in ML methodsRuqi Zhang, A. Feder CooperMonica Munnangi Sponsor Expo Presentations, 1:30 PM – 2:30 PM ET Time (ET/New York ) - Sponsor - Speaker - Title 13:30 – 13:45 Microsoft Jennifer Neville Improving Productivity with Graph ML over Content-Interaction Networks 13:45 – 14:00 Quantum Black Viktoriia Oliinyk Algorithmic Fairness: Machine Learning with a Human Face 14:00 – 14:15 Apple Lizi Ottens Machine Learning at Apple 14:15 – 14:30 Facebook Ning Zhang Future of AI-Powered Shopping Mentorship Social, 2:30 PM – 3:30 PM ET ID - Mentor - Topic 1 Dina Obeid (Harvard) A non-linear career path in Machine Learning 2 Shakir Mohamed (DeepMind) Socio-Technical AI Research 3 Been Kim (Google Brain) Industry Research and Managing Up 4 Anna Goldenberg (U Toronto) Two body problem in academia, Raising a family, Grant strategies, Looking for a job to deploying ML in a hospital setting 5 Lalana Kagal (MIT) Maintaining work-life balance 6 Angelique Taylor (Cornell University) Transitioning from PhD to Assistant Professor Invited talk: Celia Cintas Towards fairness & robustness in machine learning for dermatology Abstract: Recent years have seen an overwhelming body of work on fairness and robustness in Machine Learning (ML) models. This is not unexpected, as it is an increasingly important concern as ML models are used to support decision-making in high-stakes applications such as mortgage lending, hiring, and diagnosis in healthcare. Currently, most ML models assume ideal conditions and rely on the assumption that test/clinical data comes from the same distribution of the training samples. However, this assumption is not satisfied in most real-world applications; in a clinical setting, we can find different hardware devices, diverse patient populations, or samples from unknown medical conditions. On the other hand, we need to assess potential disparities in outcomes that can be translated and deepen in our ML solutions. In this presentation, we will discuss how to evaluate skin-tone representation in ML solutions for dermatology and how we can enhance the existing models’ robustness by detecting out-out-distribution test samples (e.g., new clinical protocols or unknown disease types) over off-the-shelf ML models. Invited talk: Yingzhen Li Evaluating approximate inference for BNNs Abstract:Bayesian Neural Network is one of the major approaches for obtaining uncertainty estimates for deep learning models. Key to the success is the selection of the approximate inference algorithms used to compute the approximate posterior, with mean-field variational inference (MFVI) and MC-dropout being the most popular variants. But is the good downstream uncertainty estimation performance of BNNs attributed to good approximate inference? In this talk I will discuss some of our recent results towards answer this question. I will also discuss briefly the computational reasons of the preference of MFVI/MC-dropout and describe our latest work to make BNNs more memory efficient. Invited talk: Sara Hooker Characterizing the Generalization Trade-offs Incurred By Compression Abstract: To-date, a discussion around the relative merits of different compression methods has centered on the trade-off between level of compression and top-line metrics such as top-1 and top-5 accuracy. Along this dimension, compression techniques such as pruning and quantization are remarkably successful. It is possible to prune or heavily quantize with negligible decreases to test-set accuracy. However, top-line metrics obscure critical differences in generalization between compressed and non-compressed networks. In this talk, we will go beyond test-set accuracy and discuss some of my recent work measuring the trade-offs between compression, robustness and algorithmic bias. Characterizing these trade-offs provide insight into how capacity is used in deep neural networks — the majority of parameters are used to represent a small fraction of the training set. Formal auditing tools like Compression Identified Exemplars (CIE) also catalyze progress in training models that mitigate some of the trade-offs incurred by compression. Invited talk: Luciana Benotti Errors are a crucial part of dialogue Abstract: Collaborative grounding is a fundamental aspect of human-human dialogue which allows people to negotiate meaning; in this talk, I argue that current deep learning approaches to dialogue systems don’t deal with it adequately. Making errors, and being able to recover from them collaboratively, is a key ingredient in grounding meaning, but current dialogue systems can’t do this. I will illustrate the pitfalls of being unable to ground collaboratively, discuss what can be learned from the language acquisition and dialog systems literature, and reflect on how to move forward. I will urge the community to proceed by addressing a research gap: how clarification mechanisms can be learned from data. Novel research methodologies which highlight the importance of the role of clarification mechanisms are needed for this. I will present an annotation methodology, based on a theoretical analysis of clarification requests, which unifies a number of previous accounts. Dialogue clarification mechanisms are an understudied research problem and a key missing piece in the giant jigsaw puzzle of natural language understanding. I will conclude this talk with an open call for collaborators that share the vision presented. WiML Accepted Posters in Poster Session s (11:30 AM – 12:00 PM ET and 20:30 PM – 21:00 PM ET) and Joint Affinity Poster Session on Gather.Town (Monday 19 Jul 9:00 PM — 11:00 PM ET) Machine Learning Applications in Animal Sciences A mbreen Hamadani* (PhD Scholar, Animal Genetics and Breeding, SKUAST-K), Nazir A Ganai (Professor, Animal Genetics and Breeding, SKUAST-K) Emulating Aerosol Microphysics with Machine Learning Paula Harder* (University of Kaiserslautern) Duncan Watson-Parris (University of Oxford), Domink Strassel (Fraunhofer ITWM), Nicolas Gauger (University of Kaiserslautern), Philip Stier (University of Oxford), Janis Keuper (Offenburg University) Network Experiment Design for estimating Direct Treatment Effects Zahra Fatemi*(University of Illinois at Chicago), Elena Zheleva (Universty of llinois at Chicago) Adversarial Robust Model Compression using In-Train Pruning Manoj Rohit Vemparala (BMW Group), Nael Fasfous (Technical University of Munich), Alexander Frickenstein (BMW Group), Sreetama Sarkar* (BMW Group), Qi Zhao (Karlsruhe Institute of Technology), Sabine Kuhn (BMW Group), Lukas Frickenstein (BMW Group), Anmol Singh (BMW Group), Christian Unger (BMW), Naveen Shankar Nagaraja (BMW Group), Christian Wressnegger (Karlsruhe Institute of Technology), WALTER STECHELE (Technical University of Munich) Iterative symbolic regression for learning transport equations Mehrad Ansari*, Heta A. Gandhi*, David Foster, Andrew D. White; Department of Chemical Engineering, University of Rochester, Rochester, NY 14627 Cost Aware Asynchronous Multi-Agent Active Search Arundhati Banerjee*(School of Computer Science,Carnegie Mellon University), Ramina Ghods (School of Computer Science, Carnegie Mellon University), Jeff Schneider (School of Computer Science, Carnegie Mellon University) Exploration and preference satisfaction trade-off in reward-free learning Noor Sajid (WCHN, U CL), Panagiotis Tigas (OATML, Oxford University), Alexey Zakharov (Huawei, Imperial College), Zafeirios Fountas (Huawei, WCHN, UCL), Karl Friston (WCHN, UCL) HYBRIDNET: A NETWORK THAT LEVERAGES ON CLASSICAL AND NON-CLASSICAL COMPUTER VISION TECHNIQUES FOR FEW SHOT LEARNING ON INFRARED IMAGERY Maliha Arif * (PhD Candidate, Center for Research in Computer Vision – UCF) , Abhijit Mahalanobis ( Associate Professor, Center for Research in Computer Vision – UCF) Reinforcement Learning from Formal Specifications Kishor Jothimurugan (University of Pennsylvania), Suguman Bansal* (University of Pennsylvania), Obsert Bastani (University of Pennsylvania), Rajeev Alur (University of Pennsylvania) Clustering With Financial Fundamentals Jennifer Glenski* (Georgia Institute of Technology), Sara Srivastav (Georgia Institute of Technology), Rachel Riitano (Georgia Institute of Technology), Blake Heimann (Georgia Institute of Technology), Jenil Patel (Georgia Institute of Technology) Application of Knowledge Graph in Industry Samira Korani Contrastive Domain Adaptation Mamatha Thota(University of Lincoln), Georgios Leontidis(University of Aberdeen) Risk Analytics for Renewal of Purchase OrdersRisk Analytics for Renewal of Purchase Orders Shubhi Asthana (IBM Research), Pawan Chowdhary(IBM Research), Taiga Nakamura(IBM Research), Roberta Fadden (IBM) On the (Un-)Avoidability of Adversarial Examples Sadia Chowdhury* (York University), Ruth Urner (Assistant Professor, EECS Department, York University) Extraction of Adverse Drug Reactions from Tweets using Aspect Based Sentiment Analysis Sukannya Purkayastha (TCS Innovation Labs, Kolkata) Interpretation and transparency in acoustic emotion recognition Sneha Das* (Technical University of Denmark), Nicole Nadine Lønfeldt (Child and Adolescent Mental Health Center, Copenhagen University Hospital, Capital Region), Anne Katrine Pagsberg (Child and Adolescent Mental Health Center, Copenhagen University Hospital, Capital Region & Faculty of Health, Department of Clinical Medicine, Copenhagen University), Line H. Clemmensen (Technical University of Denmark) Seasonal forecasts of New Zealand’s local climate conditions with limited GCM inputs using Convolutional Neural Networks Fareeda Begum*(University of Canterbury), Varvara Vetrova (University of Canterbury), Nicolas Fauchereau (NIWA), Eibe Frank (University of Waikato), Tiger Xu(University of Waikato) Assessing the Carbon Intensity of Models Across Different Languages Gauri Gupta [1] (Manipal Institute of Technology), Krithika Ramesh* [1](Manipal Institute of Technology), Mirza Yusuf [1] (Manipal Institute of Technology), Praatibh Surana [1](Manipal Institute of Technology) (Equal contribution for all) A Low-rank Support Tensor Network Kirandeep Kour, Dr. Sergey Dolgov (University of Bath, UK), Prof. Dr. Martin Stoll (TU Chemnitz, Germany), Prof. Dr. Peter Benner (Max Planck Institute and TU Chemnitz, Germany) CricNet : Segment and Classify Cricket Events Sai Siddhartha Maram, Shambhavi Mishra*(Guru Gobind Singh Indraprastha University) Episodically optimized dynamical networks for robust motor control Sruti Mallik(*) (Electrical & Systems Engineering, Washington University in St Louis), ShiNung Ching (Electrical & Systems Engineering, Biomedical Engineering, Washington University in St. Louis) Open Set Detection via Similarity Learning Sepideh Esmaeilpour* (University of Illinois at Chicago), Lei Shu (Amazon AWS AI), Bing Liu(University of Illinois at Chicago) A modified limited memory Nesterov’s accelerated quasi-Newton *S. Indrapriyadarsini (Shizuoka University), Shahrzad Mahboubi (Shonan Institute of Technology), Hiroshi Ninomiya (Shonan Institute of Technology), Takeshi Kamio (Hiroshima University), Hideki Asai (Shizuoka University) Time-series Forecasting of Ionospheric Space Weather using Ensemble Machine Learning Randa Natras* (Technical University of Munich, Germany), Michael Schmidt (Technical University of Munich, Germany) SocialBERT : An Effective Few Shot Learning Framework Applied to a Social TV Setting Debarati Das* (Department of Computer Science, University of Minnesota Twin Cities), Roopana Chenchu (Department of Computer Science, University of Minnesota Twin Cities), Maral Abdollahi (Hubbard School of Journalism, University of Minnesota, Twin Cities), Jisu Huh (Hubbard School of Journalism, University of Minnesota, Twin Cities) and Jaideep Srivastava (Department of Computer Science, University of Minnesota Twin Cities) Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification Cristina Garbacea (University of Michigan Ann Arbor), Mengtian Guo (University of North Carolina at Chapel Hill), Samuel Carton (University of Colorado Boulder), Qiaozhu Mei (University of Michigan Ann Arbor) Alignment of Language Agents in V ideogames Gema Parreno ( Mempathy ) Using Weak Supervision to Identify Drug Mentions from Class Imbalanced Twitter Data Ramya Tekumalla* (Georgia State University), Juan M Banda (Georgia State University)) Call for Participation The 2nd WiML Un-Workshop is co-located with ICML on Wednesday, July 21st, 2021. The Women in Machine Learning will be organizing the second “un-workshop” at ICML 2021. This is an event format to encourage more participant interaction, especially with ICML going virtual this year. The un-workshop is based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants. Different from the workshop, the un-workshop’s main focus is topical breakout sessions, with short invited talks and casual, informal poster presentations. The overall goal of the un-workshop is to advance research through collaboration and increased interaction among participants from diverse backgrounds. Students, postdocs and researchers in all areas of Machine Learning who primarily identify as a woman and/or nonbinary are encouraged to submit one-page proposal to lead a breakout session on a certain research topic. While all presenters will identify primarily as a woman and/or nonbinary, all genders are invited to attend. Important dates June 14th, 2021 – Application form opens July 4th, 2021 – Deadline (anywhere on Earth) to apply for a breakout session, poster, registration fee funding, facilitating or volunteering July 10th, 2021 – Notification of acceptance of breakout session’s proposals July 10th, 2021 – Notification of acceptance of posters, registration fee funding, facilitators, volunteers July 21st, 2021 – WiML Un-Workshop Day Various ways of participating in WiML un-workshop Lead a breakout session: submit a proposal to lead a breakout session on a certain research topic. Facilitate a breakout session: assist breakout session leaders by taking notes and encouraging participant interactions and taking attendance. Present a poster: present a poster in a casual, informal setting. Volunteer: help with technical setup and in-event needs. Attend: participate in breakout session discussions. Breakout session proposals A breakout session is a 1-hour free-form discussion overseen by 1-3 leaders and with assistance from 1-2 facilitators to take notes and encourage participant interactions. We strongly encourage students, postdocs, and researchers who primarily identify as women and/or nonbinary in all areas of machine learning to submit a proposal to lead a topical breakout session. A complete proposal consists of a 1 page blind PDF (example here ) and the names and bios of leaders submitted separately in the application form. We strongly recommend having at least 2 leaders, with a diverse set of leaders preferred (see selection criteria below). The names of facilitators can also be provided if known at submission time. Otherwise, the organizers will match facilitators to breakout sessions. Breakout session leaders must identify primarily as women and/or nonbinary; facilitators can be of any gender. Only one proposal submission per leader is allowed. If there are multiple leaders, only one leader needs to submit the proposal. There are no proceedings. WiML registration fee funding is prioritized for accepted breakout session leaders who fulfill certain eligibility criteria (see details below) and do not have any other sources of funding. Breakout session guidelines: Role of leaders: Point-out key characteristics of your topic and make connections with other topics. Describe the key challenges in this research area on a high-level. Describe the key approaches on a high-level to provide intuition. Highlight possible points of discussion/goals to achieve during the session. Use graphics/imagery and materials e.g. slides as needed Encourage inclusive (rather than unilateral) discussions Role of facilitators: take notes and encourage participant interactions. Leaders and facilitators should anticipate a small additional time commitment before the un-workshop to receive briefing/training and a possible dry run. While the exact technology is still being determined, we anticipate using video-conferencing software (e.g. Zoom). Submission instructions for breakout sessions: Proposals must be no more than 1 page (including any references, tables, and figures) submitted as a PDF. Main body text must be minimum 11 point font size and page margins must be minimum 0.75 inches (all sides). Your proposal should stand alone, without linking to a longer paper or supplement. You should provide a brief description of the topics you’d like to discuss, any relevant references, a plan for how you’d organize the time (1 hour) allocated for a session, as well as some ideas on how you’d encourage discussion and participant interaction during the session. The PDF must not include identifying information, as it will be reviewed blind. In particular, the PDF should not contain information of the leaders or facilitators. Instead, submit their information in the application form. Selection criteria for breakout sessions: The degree to which it is expected that participants will find the topic interesting and valuable. Diversity of leaders and facilitators, including diversity of experience/seniority, affiliation, race, viewpoint and thinking regarding the topic, etc. Plans for encouraging discussion and participant interaction during the session. Facilitators If you are interested in facilitating a breakout session but have not yet connected with anyone submitting a breakout session proposal, you can indicate your interest in the application form. Organizers will match selected facilitators to breakout sessions. Facilitators should anticipate a small additional time commitment before the un-workshop to receive briefing/training and a possible dry run. Posters If you wish to present a poster, submit EITHER a short abstract (max 1500 characters) OR a PDF of the poster (only if you have it already). The poster may describe new, previously, concurrently published, or work-in-progress research. Posters in theory, methods, and applications are welcome. The poster presenter must identify primarily as a woman and/or nonbinary; other authors can be of any gender. The poster presenter does not need to be the first author of the work. Only one poster submission per presenter is allowed. Accepted posters will be presented in a casual, informal setting. This setting is very different from formal poster sessions, e.g. at WiML Workshop at NeurIPS. While the exact presentation format is still being determined, it may be as simple as a webpage with poster PDF and pre-recorded video. There are no oral or spotlight presentations. There are no proceedings. Submission instructions for posters: Submitted materials may contain identifying information, as posters for this un-workshop are not reviewed blind. Your submission should stand alone, without linking to a longer paper or supplement. You should convey motivation and give some technical details of the approach used. While we acknowledge that space is limited, some experimental results are likely to improve reviewers’ opinions of your poster. Registration fee funding The virtual nature of ICML and this un-workshop allows individuals from all over the world to attend. By funding a number of ICML registrations, WiML hopes to further expand the range of participants at this un-workshop. To apply for funding, you should: identify primarily as a woman and/or nonbinary; be a student, postdoc, or have an equivalent position (equivalent positions include unemployed recent grads and early career researchers from underrepresented geographical regions). Accepted breakout session leaders who fulfill the above eligibility criteria and do not have any other sources of funding will be prioritized for WiML funding. Other participants are also encouraged to apply. Priority will be given to individuals from underrepresented regions or groups, first-time attendees of ICML or similar conferences, and individuals who would benefit the most from this funding. Funding recipients must participate in at least one breakout session as a leader, facilitator, or attendee. Due to limited funding, we may not be able to support everyone eligible; however, we hope to support as many eligible applicants as possible. We also encourage you to apply for ICML volunteer and funding opportunities, which are separate and independent of WiML funding. Check the ICML website directly for details. Volunteering We are seeking volunteers to help with technical setup and virtual technology testing before the event, as well as help during the event, e.g. letting people into Zoom rooms, etc. We may also need emergency reviewers for breakout session proposals. You can indicate if you can help in any way in the application form here . Participation instructions To participate in ANY of the above roles and/or apply for registration fee funding, please fill in this application form by **July 4, 2021**. Selected breakout session leaders, facilitators, poster presenters, volunteers, and funding recipients will be notified individually by the dates mentioned above. If you only wish to attend, we still recommend you fill in this form to provide your timezone and topic preferences. All participants are required to abide by the WiML Code of Conduct . Important note: This form does not constitute registration for the WiML Un-Workshop. To attend the un-workshop, you need to register for ICML at https://icml.cc . Submission is now open! Organizers Beliz Gokkaya, Facebook Wenshuo Guo, University of California, Berkeley Arushi Majha, University of Cambridge Liyue Shen, Stanford Olivia Choudhury, Amazon Berivan Isik, Stanford Hadia Mohmmed Osman Ahmed Samil, Mila Vaidheeswaran Archana, Continental Automotive Questions? Check out the FAQs or reach us at workshop[at]wimlworkshop[dot]org PLATINUM SPONSORS Committee ORGANIZERS Beliz Gokkaya Software Engineer at Facebook, General Chair Wenshuo Guo PhD Student at University of California, Berkeley, Program Chair Hadia Mohmmed Osman Ahmed Samil Breakout Program and Logistics Co-Chair Berivan Isik PhD Student at Stanford University, Breakout Program and Logistics Co-Chair Olivia Choudhury Researcher at Amazon, Senior Program and Networking Chair Arushi Majha PhD Student at University of Cambridge, Finance and Sponsorship Chair Liyue Shen PhD Student at Stanford University, Funding and Volunteers Chair Vaidheeswaran Archana AI Engineer at Continental Automotive, Virtual Experience Chair Diversity and Inclusion Chair Danielle Belgrave, Principal Research Manager at Microsoft Research Supervolunteers We would like to acknowledge and warmly thank our super-volunteers who worked tirelessly to ensure a high quality un-workshop. Belen Saldias, MIT Elre Oldewage, University of Cambridge Mandana Samiei, McGill and Mila Niveditha Kalavakonda, University of Washington Seattle Weiwei Zong, Henry Ford Health System FAQs How do I register for the un-workshop? You need to register to ICML to attend to WiML and then please fill the application form provided. Please refer to call for participation for more details. Is filling the application form enough for register to WiML? No, you need to register to ICML . What is an un-workshop? The un-workshop is based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants. The overall goal of the un-workshop is to advance research through collaboration and increased interaction among participants from diverse backgrounds. How is an un-workshop different from WiML workshop at NeurlPS? WiML Workshop at NeurIPS is a one-day event with invited speakers, oral presentations, and posters. This year WiML is bringing a new event format to ICML to encourage more participant interaction, especially with ICML going virtual this year. Different from the workshop, the un-workshop’s main focus is topical breakout sessions, with short invited talks and casual, informal poster presentations. I'm a man. Can I attend WiML? Yes. All genders are welcome to attend! To do so, please register for ICML and fill the application form . Note, however, that all speakers, breakout session leaders and poster presenters will primarily identify as a woman and/or nonbinary, as our goal is to promote them and their work within the machine learning community. Where will the un-workshop take place? This is a virtual event. How much funding is available? Funding is distributed based on geographic location. Support varies from year to year and this year due to COVID-19, it will be a virtual event and ICML registration fee funding is available for participants who fulfill eligibility criteria. Is there a code of conduct? Yes. WiML requires all participants and reviewers to abide by our code of conduct . Is WiML an archival venue? No, WiML is a non-archival venue. This means that, if your contribution is accepted, we will not be asking you to submit a camera-ready version of it, nor will we publish it anywhere (neither online nor in proceedings of any sort). We will only make the title and authors’ names available in the program book. How can I get more information on un-workshop logistics? Please check out the logistics page! I want to support WiML by providing sponsorship / recruiting at the un-workshop. Who should I talk to? Thank you for your support! Please contact us . How can I join the WiML network? Join our Google Group . When and where do I submit my proposal? You can find more information on call for participation. Submission to the 2021 WiML un-workshop is now closed. How many breakout sessions will be on the day of the un-workshop? There are 4-time slots for 1-hour breakout sessions (marked as Breakout Sessions #1 to #4). Each of these 4-time slots will have several parallel breakout sessions. Why do breakout sessions involve Zoom and Slack? Zoom rooms are mainly for the breakout sessions for the specific one hour period. However, leaders can use Slack a few days before and after to ask participants to read some papers, ask them specific questions and keep the discussions going. Also, participants can ask questions regarding the breakout session’s topic in the Slack channel before the actual session. Can I make breakout rooms in the breakout session as a leader? Yes, leaders can make smaller breakout rooms to engage participants in smaller group discussions. How many attendees will be in each breakout session? We can’t promise the exact number but we are hoping for smaller groups (max 20) to increase interaction between participants. What is the whiteboard in Zoom rooms? Whiteboard is like a digital board and leaders and participants can write on it and explain a specific topic. More instructions are available here. Will we as leaders be given a chance to advertise our proposal topic before the un-workshop? Sure, you can advertise your session’s topic on Twitter for example and tag us on @WiMLworkshop and we can retweet that. Also, attendees will have access to the breakout session topics at least a week before the un-workshop. Can anyone who did not fill the WiML form still join the un-workshop? Anyone who is registered to ICML can join the un-workshop. I am new to the Gather.town platform being used for the live poster session. How can I prepare for it? Check out these guidelines. I have a question that's not answered here. How do I reach you? Contact us . Back To Top

WiML is dedicated to providing an experience for all participants that is free from harassment, bullying, discrimination, and retaliation. WiML Code of Conduct The open exchange of ideas, the freedom of thought and expression, and respectful scientific debate are central to the goals of Women in Machine Learning, Inc. (“WiML”) activities; this requires a community and an environment that recognizes and respects the inherent worth of every person. The purpose of this Code of Conduct (CoC) is to outline expected standards of behaviour during WiML activities. Scope This CoC applies to all WiML activities, including but not limited to: Events organized, hosted, co-branded, or in cooperation with WiML Submissions and reviewing processes run by WiML. Communications sent through communication channels associated with WiML, including but not limited to social media. Meetings and discussions associated with WiML activities. If an activity is in cooperation with another organization, if the other organization has its own CoC, the union of both CoCs apply. Responsibility All attendees, speakers, mentors, panelists, area chairs, reviewers, sponsors, contractors, organizers, volunteers, members of the WiML Board of Directors and Senior Advisory Council (referred to as “Participants” collectively throughout this document) involved in WiML activities as described above are required to comply with this CoC. Reviews should actively avoid subtle discrimination, however inadvertent. In particular, reviewers should avoid comments in reviews about English style or grammar that may be interpreted as implying that the author is “foreign” or “non-native”. Sponsors are equally subject to this CoC. In particular, sponsors should not use images, activities, or other materials that reinforce gender stereotypes or are of a sexual, racial, or otherwise offensive nature at WiML events. Booth staff, including but not limited to volunteers, should not create a sexualized environment. Unacceptable Behavior WiML is dedicated to providing an experience for all participants that is free from harassment, bullying, discrimination, and retaliation. This includes offensive comments related to gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), politics, technology choices, or any other personal characteristics or considerations made unlawful by federal, state, or local laws, ordinances, or regulations. Inappropriate or unprofessional behavior that interferes with another participant’s full participation will not be tolerated. This includes bullying, intimidation, personal attacks, harassment, sustained disruption of talks or other events, sexual harassment, stalking, following, harassing photography or recording, inappropriate physical contact, unwelcome sexual attention, public vulgar exchanges, derogatory name-calling, or diminutive characterizations, all of which are unwelcome in this community. Advocating for, or encouraging, any of the above behaviour, is also considered harassment. No use of images, activities, or other materials that are of a sexual, racial, or otherwise offensive nature that may create an inappropriate or toxic environment is permitted. Disorderly, boisterous, or disruptive conduct including but not limited to fighting, coercion, theft, damage to property, or any mistreatment or non-businesslike behavior towards other participants is not tolerated. Scientific misconduct—including but not limited to fabrication, falsification, or plagiarism of paper submissions or research presentations—is prohibited. Reporting If you have concerns related to your participation or interaction at a WiML activity, observe someone else’s difficulties, or have any other concerns you wish to share, you can make a report: Anytime: By email at codeofconduct@wimlworkshop.org ‬ During an event: In-person to organizers, volunteers, or any member of the WiML Board of Directors. They will then direct you to the designated responder(s) for that event. Organizers and volunteers can be identified by special badges marked as “ORGANIZER” or “VOLUNTEER”. Members of the WiML Board of Directors can be identified by special badges marked as “WiML Board”. There is no deadline by which to make a report. If the person receiving your report is not the designated responder for that event, they will direct you to a designated responder and/or provide you immediate medical or security help and assist you to feel safe for the duration of the activity. Designated responders will follow WiML procedures to respond to and investigate your report. Enforcement Any participant asked by any member of the community to stop any unacceptable behavior is expected to comply immediately. A response of “just joking” will not be accepted; behavior can be harassing without an intent to offend. If a participant engages in behaviour that violates this CoC, WiML retains the right to take any action deemed appropriate, including but not limited to: Formal or informal warnings Barring or limiting continued attendance and participation, including but not limited to expulsion from the event Barring from participating in or deriving benefits from future WiML activities Exclusion from WiML opportunities, e.g. leadership, organizing, volunteering, speaking, reviewing, sponsoring, etc. Reporting the incident to the offender’s local institution or funding agencies Reporting the incident to local law enforcement The same actions may be taken toward any individual who engages in retaliation or who knowingly makes a false allegation of harassment. If action is taken, an appeals process will be made available. Investigation Reports of violations will be handled at the discretion of the WiML Board of Directors, who will investigate reports and bring the issue to resolution. Reports made during the activity will be responded to within 24 hours; reports made at other times will be responded to in less than five weeks. All reports will be handled as confidentially as possible and information will be disclosed only as it is necessary to complete the investigation and bring to resolution. There may be situations (such as those involving Title IX issues in the United States and venue- or employer-specific policies) where the member of the WiML Board of Directors informed of the violation will be under an obligation to file a report with another individual or organization outside of WiML. Ongoing Review The WiML Board of Directors welcomes feedback from the community on this CoC policy and procedures; please contact us by email at info@wimlworkshop.org . Acknowledgements This CoC policy was written by adapting the wording and structure from other CoC policies and procedures by Geek Feminism Wiki (created by the Ada Initiative), NeurIPS , ACM , Montreal AI Symposium , and Deep Learning Indaba .