< Back Sidhika Balachandar PhD Student at UC Berkeley WiML Mentorship Program 2nd WiML Mentorship: PhD Applications, 2022–2023, 3rd WiML Mentorship: PhD Applications, 2023–2024, 4th WiML Mentorship: Ph.D. Applications and Job Seekers 2024–2025 "Hello! My name is Sidhika. I am a fourth-year Computer Science PhD student at UC Berkeley. I work on problems at the intersection of machine learning, fairness, and healthcare. I am advised by Emma Pierson and Nikhil Garg. I am fortunate to be supported by the NSF GRFP. I am interested in creating models in settings where outcome data is missing or biased (e.g., ICLR 2024). In particular, my research has focused on the following questions: What are the challenges of using outcome data collected from human decision makers or crowdsourced platforms? What identification approaches can we use to create models in these settings? Can we leverage external, domain specific information or data?" What was your favorite part about serving as a WiML Mentor? "As a WiML mentor, I have been able to meet and learn from some amazing peers! My mentees have shaped my research vision, given me book recs, and have been a pleasure to get to know!" Previous Next

All events 3rd WiML Mentorship Program for PhD Applications: Panel on Recommendation Letters Virtual November 9, 2023 5:00 pm - 6 pm This event, part of the WiML’s 2023-2024 Mentorship Program on the theme of PhD applications, takes place 5-6pm UTC in Zoom. Mentors and mentees of the 2023-2024 Mentorship Program are invited to attend. The panel topic is on “How to ask for a recommendation letter in Master’s & Ph.D applications in ML”. Panelists: Yingzhen Li (Imperial College London), Martha White (University of Alberta), Rose Yu (UC San Diego) Moderator: Erin Grant (UC Berkeley) Previous Next

All events WiML @ Mujeres en Inteligencia Artificial (Women in Artificial Intelligence) El Montonero Restaurant, Alameda Pardo 123, Cercado, Peru and Virtual February 20, 2025 19:00 - 21:30hrs The event will feature a 35-minute panel discussion with three female experts in AI. The panel will explore strategies for empowering women to thrive in the field of Artificial Intelligence and Machine Learning, drawing insights from the speakers' professional journeys. Additionally, the discussion will delve into technical trends and advancements, with each speaker sharing their perspectives on the future of AI within their specialized areas, such as Natural Language Processing (NLP), Computer Vision (CV), and Responsible AI. The session will conclude with a Q&A segment, followed by a dinner and networking opportunity to foster meaningful connections. Organizers: Rosa Paccotacya Yanque, Nils Murrugarra Llerena Additional information can be found by email at nem177@pitt.edu or rypaccotacya@ucsp.edu.pe . Previous Next

< Back WiML Workshop 2012 Lake Tahoe, Nevada The 7th annual Women in Machine Learning workshop was colocated with NIPS 2012 in Lake Tahoe, Nevada in December 2012. Previous Next

All events WiML Social @ ICLR 2025 Singapore April 25, 2025 12:30 PM - 2:00 PM Date: April 25, 2025 Time: 12:30 - 2:00p, Location: At the front of Hall 1 Apex Grab lunch, meet fellow researchers, and hear perspectives on navigating academia vs. industry. 🍽️ Lunch provided! Topics: "Papers, patents, or products? Making the right career call across academia & industry" The panel explores key career decisions in today's ML landscape: choosing between research publications and product development, weighing academic freedom against industry resources. The program is: 12:30 pm - 12:35 pm Opening Remarks 12:35 pm - 1:20 pm Networking & Lunch 1:20 pm – 2:00 pm Panel Discussions Panelists Reyhane Askari Rayhane Askari is is a postdoctoral researcher at FAIR (Meta AI), working at the intersection of generative models, synthetic data, and responsible AI. Her research focuses on improving data efficiency through diffusion-based generation with applications in vision-language modeling. She holds a Ph.D. in Computer Science from the University of Montreal (Mila), where she explored theoretical and practical aspects of generative modeling. https://x.com/reyhaneaskari?lang=en Katherine Driscoll Katherine Driscoll serves as Head of AI at Graph Therapeutics, a Vienna-based techbio startup, where she works on optimizing experimental design for drug discovery through AI. Her research combines active learning approaches and foundation models with domain knowledge to enhance target discovery processes. Previously, she completed her Ph.D. in condensed matter physics, focusing on modeling strongly correlated quantum systems. In addition to her professional work, she volunteers with TechBio Transformers, supporting the development of a global community for those interested in the intersection of AI and biology. linkedin.com/in/katherine-driscoll-58482275/ Nouha Dziri Nouha Dziri is an AI research scientist at the Allen Institute for AI (Ai2). Her research investigates a wide variety of problems across NLP and AI including building state-of-the-art language models and understanding their limits and inner workings. She also works on AI safety to ensure the responsible deployment of LLMs while enhancing their reasoning capabilities. Prior to Ai2, she worked at Google DeepMind, Microsoft Research and Mila. She earned her PhD from the University of Alberta and the Alberta Machine Intelligence Institute. Her work has been published in top-tier AI venues including NeurIPS, ICML, ICLR, TACL, ACL, NAACL and EMNLP. She won the best paper award in NAACL 2025. https://x.com/nouhadziri?lang=en https://www.linkedin.com/in/nouha-dziri-3587427b/ Claire Vernade Claire Vernade is a Group Leader at the University of Tübingen, in the Cluster of Excellence Machine Learning for Science (*). She was awarded an Emmy Noether award under the AI Initiative call in 2022 for the project FoLiReL , and an ERC Starting Grant in 2024 for the project ConSequentIAL . Her research is on sequential decision making. It mostly spans bandit problems, and theoretical Reinforcement Learning, but her research interests extend to Learning Theory and principled learning algorithms. Her work " Eigengame: PCA as a Nash Equilibrium " was recognized by an Outstanding Paper Award at ICLR 2021 (with I.Gemp, B.McWilliams and T.Graepel). Her goal is to contribute to the understanding and development of interactive and adaptive learning systems. Between November 2018 and December 2022, she was a Research Scientist at DeepMind in London UK in the Foundations team lead by Prof. Csaba Szepesvari . She did a post-doc in 2018 with Prof. Alexandra Carpentier at the University of Magdeburg in Germany while working part-time as an Applied Scientist at Amazon in Berlin. She received her PhD from Telecom ParisTech in October 2017, under the guidance of Prof. Olivier Cappé. https://x.com/vernadec?lang=en https://www.linkedin.com/in/claire-vernade-82559949/ Erin Grant Erin Grant is a Senior Research Fellow at the Gatsby Computational Neuroscience Unit and the Sainsbury Wellcome Centre at University College London. Erin studies prior knowledge and learning mechanisms in minds, brains, and machines using a combination of behavioral experiments, computational simulations, and analytical techniques, with the goal of grounding higher-level cognitive phenomena in a neural implementation. Erin earned her Ph.D. from the University of California, Berkeley in 2022 with support from Canada’s Natural Sciences and Engineering Research Council . During her Ph.D., Erin spent time at OpenAI , Google Brain , and DeepMind . Erin currently serves on the Women in Machine Learning Board of Directors. https://x.com/ermgrant?lang=en https://www.linkedin.com/in/ermgrant/ WiML Social Organizers Vasiliki Tassopoulou Vasiliki Tassopoulou is a Ph.D. Candidate in Bioengineering at the University of Pennsylvania, conducting research within the Center for AI and Data Science for Integrated Diagnostics Her research focuses on generative modeling of longitudinal neuroimaging data, with applications in neurodegenerative diseases. In parallel with her Ph.D., she completed an M.Sc. in Statistics and Data Science at the Wharton School, concentrating on Bayesian statistics and statistical inference and conformal prediction. She also holds a M.Eng. in Electrical and Computer Engineering from the National Technical University of Athens. https://x.com/vtassop https://www.linkedin.com/in/vasilikitassopoulou/ Melis IIayda Bal Melis Ilayda Bal is a second-year PhD candidate at the Max Planck Institute for Intelligent Systems, in Tübingen, Germany, at the Learning and Dynamical Systems (LDS) research group and a doctoral fellow through the Amazon-MPI Science Hub. She hold an M.Sc . in Operations Research and a B.Sc . in Industrial Engineering, with a minor in Computer Engineering, from Middle East Technical University (METU). Her research focuses on optimization for machine learning, specifically aimed at developing techniques that enhance the robustness and training efficiency of machine learning models. https://x.com/melisilaydabal?lang=en https://www.linkedin.com/in/melis-ilayda-bal-436889123/ Thanks to our sponsors! Previous Next

All events 3rd WiML Mentorship Program for PhD Applications: Panel on Research Statements Virtual October 23, 2023 4:00 pm - 5:00 pm This event, part of the WiML’s 2023-2024 Mentorship Program on the theme of PhD applications, takes place 4-5pm UTC in Zoom. Mentors and mentees of the 2023-2024 Mentorship Program are invited to attend. The panel topic is on “How to write a research statement for Master’s & Ph.D applications in ML”. Panelists: Emma Pierson (Cornell Tech), Sinead Williamson (UT Austin) Moderator: Erin Grant (UC Berkeley) Previous Next

All events 2nd WiML Mentoring Program for PhD Applications: Panel on Next Steps Virtual January 26, 2023 9:00 am - 10:00 am This event, part of the WiML’s 2022-2023 Mentorship Program on the theme of PhD applications, takes place 9-10am PT in Zoom. Mentors and mentees of the 2022-2023 Mentorship Program are invited to attend. Panelists: Isabel Valera (Saarland University), Maggie Makar (University of Michigan), Po-Ling Loh (University of Cambridge), Andrew Gordon Wilson (New York University) Moderator: Alessandra Tosi (Mind Foundry) Previous Next

All events WiML Luncheon @ ICML 2017 Sydney, Australia August 8, 2017 12:00 pm — 02:00 pm WiML is hosting a luncheon at ICML 2017 in Sydney, Australia. The goal of this event is to bring together female faculty members, research scientists, data scientists, and graduate students to meet, find mentorship, and learn from each other. Date: Tuesday, August 8, 2017, 12pm-2pm Venue: Grand Ballroom at The Westin Sydney, Sydney Registration: https://www.eventbrite.com/e/wiml-icml-luncheon-2017-tickets-36123495347# If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org SPONSORS -Gold- -Silver- Previous Next

All events WiML-CWS Event: Community-Driven Mentoring Event and Panel @ AISTATS 2021 Virtual April 13, 2021 12:30 pm - 2:00 pm WiML is excited to announce a joint event with the Caucus for Women in Statistics at AISTATS 2021. The event has two components: community-driven mentoring , and a panel . The event will be held on the Icebreaker.video platform on Tuesday, April 13, 2021, 12.30pm – 2pm PT. Event Format Agenda (all times approximate) 12:30 – 12:45pm PT – 1:1 mentor-mentee random pairings 12:45 – 1:10pm PT – Small group mentoring on time management tips and conducting research 1:10 – 1:45pm PT – Panel on publishing and reviewing 1:45 – 2pm PT – Small group debrief on panel What is community-driven mentoring? It means anyone can be a mentor on a topic of their expertise! Upon entering the Icebreaker link, you will be asked to indicate if you want to be a mentor or mentee. The Icebreaker platform will distribute mentors among groups as much as possible. There will be a series of mentoring sessions, both 1:1s and in small groups. Read more about the mentoring prompts below. Who can mentor? Mentoring topics will range from general life-work balance to general research questions, thus we encourage a larger number of participants, ranging from mid-PhD to senior levels, to participate as mentors. Mentors can be of any gender. What is the panel on? The panel, moderated by Sinead Williamson (University of Texas at Austin) with panelists Bin Yu (UC Berkeley), Tomi Mori (St. Jude Children’s Research Hospital), Po-Ling Loh (University of Cambridge), Jessica Kohlschmidt (Ohio State University), is on the topic of “Reviewing and Publishing”. The rapid growth of the machine learning and statistics community has made the reviewing process of peer-reviewed conferences more challenging. Besides sharing their experiences, panelists will discuss publishing venues in ML and Statistics, as well as take questions from the audience. Read more about the panelists below. Joining Instructions How to join: You can find the Icebreaker link on the AISTATS portal: https://virtual.aistats.org/virtual/2021/affinityworkshop/2033 (AISTATS registration required to access). Event limited to 200 participants. You’ll be asked to sign in to Google, and give Icebreaker permission to access your camera and microphone. Google Chrome browser recommended. Participant instructions: Whether you will participate as a mentor or mentee, we suggest preparing one or two lines to describe your work and research, as well as any other topics you may want to discuss. During the panel, you can type questions for the panelists in Icebreaker chat, so bring any questions on reviewing and publishing! See below for more information on Icebreaker. Questions? Email workshop@wimlworkshop.org or cws@cwstat.org . Note that this is a separate event from the AISTATS mentoring sessions . By joining the event, you agree to abide by the AISTATS Code of Conduct and WiML Code of Conduct . Icebreaker how-to guide and mentoring prompts Upon joining the platform, you will be given an option to join as either a “Mentee” or a “Mentor”. Select your preferred option, enter your full name, and click on “join event”. For each mentoring session, you can choose if you want to participate or wait for the next one. Panelists and Moderator bios Professor Bin Yu, UC Berkeley Bin Yu is Chancellor’s Distinguished Professor and Class of 1936 Second Chair in the departments of statistics and EECS at UC Berkeley. She leads the Yu Group which consists of 15-20 students and postdocs from Statistics and EECS. She was formally trained as a statistician, but her research extends beyond the realm of statistics. Together with her group, her work has leveraged new computational developments to solve important scientific problems by combining novel statistical machine learning approaches with the domain expertise of her many collaborators in neuroscience, genomics, and precision medicine. She and her team develop relevant theory to understand random forests and deep learning for insight into and guidance for practice. She is a member of the U.S. National Academy of Sciences and of the American Academy of Arts and Sciences. She is Past President of the Institute of Mathematical Statistics (IMS), Guggenheim Fellow, Tukey Memorial Lecturer of the Bernoulli Society, Rietz Lecturer of IMS, and a COPSS E. L. Scott prize winner. She is serving on the editorial board of Proceedings of National Academy of Sciences (PNAS) and the scientific advisory committee of the UK Turing Institute for Data Science and AI. Professor Tomi Mori, St. Jude Children’s Research Hospital Tomi Mori is a Member and Endowed Chair of the Department of Biostatistics at St. Jude Children’s Research Hospital in Memphis TN. She is an elected Fellow of the American Statistical Association and is currently President of the Caucus for Women in Statistics. Her statistical research interests include: designs of early phase clinical trial designs for drug combinations and precision oncology strategies, biomarker discovery and validation, predictive modeling, and risk stratification. Professor Po-Ling Loh, University of Cambridge Po-Ling Loh received her Ph.D. in Statistics from UC Berkeley in 2014. From 2014-2016, she was an Assistant Professor of Statistics at the University of Pennsylvania. From 2016-2018, she was an Assistant Professor of Electrical & Computer Engineering at UW-Madison, and from 2019-2020, she was an Associate Professor of Statistics at UW-Madison and a Visiting Associate Professor of Statistics at Columbia University. She began a position as a Lecturer in the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge in January 2021. Po-Ling’s current research interests include high-dimensional statistics, robustness, and differential privacy. She is a recipient of an NSF CAREER Award, an ARO Young Investigator Award, the IMS Tweedie and Bernoulli Society New Researcher Awards, and a Hertz Fellowship. Dr. Jessica Kohlschmidt, Ohio State University Comprehensive Cancer Center Jessica Kohlschmidt is a Ph.D. Biostatistician at the Clara D. Bloomfield Center for Leukemia Outcomes Research at The Ohio State University Comprehensive Cancer Center. Her research group looks retrospectively at patient data to try to determine what gene mutations and expression (or combinations) predict which patients will have better survival. Jessica also teaches business analytics for the Fisher College of Business at The Ohio State University. She is a long time officer of the Caucus for Women in Statistics (CWS), serving for 10 years as Secretary and in 2018 became the first Executive Director and currently oversees the operations of CWS. Jessica is currently serving on the committee for the International Year of Women in Statistics and Data Science (IYWSDS) of ISI. She is also actively involved with the American Statistical Association (ASA) and is serving as Treasurer for the ASA Survey Research Methods Section, as well as President of the ASA Columbus Chapter and as Chair of the ASA History of Statistics Interest Group. Professor Sinead Williamson, University of Texas at Austin Sinead Williamson is an Assistant Professor of Statistics at the University of Texas at Austin, in the IROM Department and the Division of Statistics and Scientific Computation. She obtained her Ph.D. from the Computational and Biological Learning group at the University of Cambridge and spent two years as a postdoc in the SAILING laboratory at Carnegie Mellon University. Previous Next

All events WiML Workshop 2011 Granada, Spain December 12, 2011 08:00 am — 06:00 pm The 6th annual Women in Machine Learning workshop was colocated with NIPS 2011 in Granada, Spain in December 2011. The workshop website is no longer maintained. The organizers were: Nevena Lazic, Monica Babes-Vroman, Rongjing Xiang, with faculty advisor Hanna Wallach. If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org Previous Next

All events 5th WiML Mentorship Program for Post-Graduate Applications: Panel on navigating Master’s and PhD applications Online October 24, 2025 The 5th WiML Mentorship Program hosted its first panel discussion event , bringing together an engaged audience of women and non-binary individuals interested in pursuing research-oriented postgraduate degrees in Machine Learning and AI. The session focused on key aspects of navigating Master’s and PhD applications , with a rich and practical discussion that covered: Crafting an effective CV Preparing a compelling Statement of Purpose Approaching potential supervisors Requesting and managing recommendation letters An open Q&A session addressing participant concerns We were delighted to be joined by two outstanding panelists who generously shared their experiences and insights: Dr. Angelina Wang , Assistant Professor, Cornell Tech Dr. Simran Arora , Senior Research Scientist at Together AI and Assistant Professor at Caltech Moderator: Judy Shen, PhD student at Stanford University. This event marked an exciting start to our new mentorship series, aimed at supporting aspiring researchers as they navigate their academic journeys in ML and AI. We look forward to hosting more events that foster connection, guidance, and community across the WiML network. (edited) Previous Next

 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!