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< Back Jo-Anne Ting, PhD WiML Treasurer (2009-2012)

17th Women in Machine Learning Workshop (WiML 2022) 17th Women in Machine Learning Workshop (WiML 2022) The Workshop is co-located with NeurIPS on Monday, November 28th, 2022 at the New Orleans Convention Center in Louisiana, USA. 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 Location Type of registration required to attend PROGRAM PANELISTS BREAKOUT SESSIONS COFFEE MEET & MINGLE SOCIAL Program Monday, November 28, 2022 [ in-person ] ( Time in CT) Morning Session 7:30 am - 8:30 am Registration & Breakfast 8:30 am - 8:45 am Opening Remarks - Konstantina Palla (Senior Program Chair) 8:45 am - 9:00 am D&I Chair remarks - Danielle Belgrave 9:00 am - 9:10 am Contributed talk ( Tejaswi Kasarla ) - "Maximum Class Separation as Inductive Bias in One Matrix" 9:10 am - 9:20 am Contributed talk ( Taiwo Kolajo ) - "Pre-processing of Social Media Feeds based on Integrated Local Knowledge Base" 9:20 am - 9:55 am Invited talk - Alice Oh - " The importance of multiple languages and multiple cultures in NLP research " 9:55 am - 10:10 am Coffee break 10:10 am - 10:25 am WiML Board Remarks - Jessica Schrouff 10:25 am - 11:00 am Invited talk - Raesetje Sefala - " Constructing visual datasets to answer research questions " 11:00 am - 11:10 am Contributed talk ( Pascale Gourdeau ) - "When are Local Queries Useful for Robust Learning?" 11:10 am - 11:20 am Contributed talk ( Annie S Chen ) - "You Only Live Once: Single-Life Reinforcement Learning" 11:20 am - 1:20 pm Mentorship roundtables & Lunch - Mentors: Adam Roberts, Stephanie Hyland, Bianca Zadrozny, Sima Behpour, Mercy Asiedu, Franziska Boenisch, Eleni Triantafillou, Isabela Albuquerque, Yisong Yue, Amy Zhang, Zelda Mariet, Tristan Naumann, Danielle Belgrave, Shakir Mohamed, Tong Sun, Gintare Karolina Dziugaite, Samy Bengio, Rianne van den Berg, Maja Rudolph, Luisa Cutillo, Ioana Bica, Clara Hu, Rosanne Liu, Jennifer Wei, Alice Oh, SueYeon Chung, Erin Grant, Sasha Luccioni, Michela Paganini, Mounia Lalmas-Roelke, Claire Vernade, Alekh Agarwal, Neema Mduma, Vinod Prabhakaran, Savannah Thais, Jonathan Frankle, Ce Zhang, Rose Yu, Jessica Schrouff, Bo Li, Katherine Heller, Ben Poole, Setareh Ariafar, Christina Pavlopoulou, Isabel Morlidge, Kavya Srinet, Cheng Zhang, Elise van der Pol, Diana Montanes, Lise Diagne, Le Yu, Megan Forrester. Afternoon Session 1:20 pm - 1:55 pm Invited talk - Bianca Zadrozny - " Machine Learning for Climate Risk " 1:55 pm - 2:05 pm Contributed talk ( Elizabeth Bondi-Kelly ) - "Human-AI Interaction in Selective Prediction Systems" 2:05 pm - 2:15 pm Contributed talk ( Gowthami Somepalli ) - "Investigating Reproducibility from the Decision Boundary Perspective." 2:15 pm - 2:35 pm Coffee break 2:35 pm - 3:10 pm Invited talk - Hima Lakkaraju - " A Brief History of Explainable AI: From Simple Rules to Large Pretrained Models " 3:10 pm - 4:10 pm Panel discussion 4:10 pm - 4:20 pm Closing Remarks 4:20 pm - 4:30 pm Poster setup 4:30 pm - 6:00 pm Joint Affinity Groups Poster Session Mentorship Roundtables AI and Creativity: Adam Roberts (Google Brain) Choosing between Academia and Industry: Stephanie Hyland (Microsoft Research) and Bianca Zadrozny (IBM Research) Continual Learning & Open-World Learning: Sima Behpour (Bosch) Founding and Funding Startups: Mercy Asiedu (Google) Gender-related challenges: Franziska Boenisch (Vector Institute) Generalization & Robustness: Eleni Triantafillou (Google Brain) and Isabela Albuquerque (DeepMind) Getting a job (academia): Yisong Yue (Caltech) and Amy Zhang (UT Austin) Getting a job (industry): Zelda Mariet (Google) Healthcare/clinical applications: Danielle Belgrave (DeepMind) and Tristan Naumann (Microsoft Research) Leadership: Shakir Mohamed (DeepMind) and Tong Sun (Adobe) Learning theory: Karolina Dziguaite (Google Brain) Life in industry research: Samy Bengio (Apple) and Rianne van den Berg (Microsoft Research) Life with kids: Maja Rudolph (BCAI) and Luisa Cutillo (University of Leeds) Mental health & surviving in grad school: Ioana Bica (DeepMind), Clara Hu (Google Brain), and Rosanne Liu (Google Brain) ML for Science: Jennifer Wei (Google) Natural language processing: Alice Oh (KAIST) Negotations in ML: Nicole Bannon (81cents) Neuroscience & cognitive science: Erin Grant (UCL), SueYeon Chung (NYU/Flatiron Institute), and Noga Zaslavsky Non-traditional paths in machine learning: Sasha Luccioni (HuggingFace) and Michela Paganini (DeepMind) Recommender systems: Mounia Lalmas-Roelke (Spotify) Reinforcement learning: Claire Vernade (DeepMind), Alekh Agarwal (Google), and Elise van der Pol (Microsoft Research) Seeking funding in academia: Neema Mduma (The Nelson Mandela African Institution of Science and Technology) Social science applications: Vinod Prabhakaran (Google Research), Savannah Thais (Columbia University), and Sarah Brown (University of Rhode Island) Systems and machine learning: Jonathan Frankle (Harvard University/MosaicML) and Ce Zhang (ETH Zurich) Time Series: Rose Yu (UCSD) Trustworthy machine learning: Jessica Schrouff (DeepMind), Bo Li (UIUC), and Katherine Heller (Google Research) Monday, December 5, 2022 [virtual](Time in ET) 9:30 am - 9:40 am Opening Remarks 9:40 am - 9:55 am Contributed talk ( Okechinyere J Achilonu ) - "Natural language processing for automated information extraction of cancer parameters from free-text pathology reports" 9:55 am - 10:10 am Contributed talk ( Paula Harder ) - "Physics-Constrained Deep Learning for Climate Downscaling" 10:10 am - 10:25 am Contributed talk ( Silvia Tulli ) - "Explanation-Guided Learning for Human-AI collaboration" 10:25 am - 10:40 am Contributed talk ( Mina Ghadimi Atigh ) - "Hyperbolic Image Segmentation" 10:40 am - 10:50 am Set up (for mentorship session) 10:50 am - 11:50 am Mentorship Panel (Discussion + Q&A) withJenn Wortman Vaughan (Microsoft Research),Colin Raffel (University of North Carolina)Kristen Grauman (University of Texas at Austin) 11:50 am - 12:00 pm Break 12:00 pm - 12:35 pm Sponsor Talks 2:00 pm - 4:00 pm Joint Affinity Groups Poster Session Call for Participation PLATINUM SPONSORS PLATINUM SPONSORS PLATINUM SPONSORS Committee ORGANIZERS WiML RECEPTION ORGANIZER ADVISORY SUPER VOLUNTEERS FAQs

< Back Po-Ling Loh, PhD WiML Treasurer (2023-2024), Director (2020-2023, 2024-2025)

< Back Sidhika Balachandar PhD Student at UC Berkeley "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?" Previous Next

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

This page is a list of partners from prior years. Former Partners Our generous partners sponsor WiML’s events, activities and programs on an annual basis. We also seek sponsors specifically for WiML Workshop, our flagship annual workshop co-located with NeurIPS. For any inquiries regarding yearlong partners or workshop sponsorship, contact sponsorship@wimlworkshop.org. For any other enquiries, contact info@wimlworkshop.org . Former Partners 2024-2025 Former Partners 2023-2024 Former Partners 2022-2023 Former Partners 2021-2022 Former Partners 2020-2021 Former Partners 2019-2020

We work to increase awareness and appreciation of the achievements of women in machine learning. Our programs help women build their technical confidence and their voice, and our publicity efforts help ensure that women in machine learning and their achievements are known in the community. Empowering Women in Machine Learning: Amplifying Achievements, Elevating Voices Our Projects ABOUT WIML Shining a Spotlight on Women's Excellence in Machine Learning: Inspiring the Next Generation We work to increase awareness and appreciation of the achievements of women in machine learning. Our programs help women build their technical confidence and their voice, and our publicity efforts help ensure that women in machine learning and their achievements are known in the community. See Our Events OUR PROJECTS Building Leaders, Bridging Gaps MENTORSHIP We run yearlong mentorship programs to help women working in machine learning give and receive advice, gain knowledge, and make connections. DIRECTORY We maintain a directory of women working in machine learning. Are you a woman or gender minority in the field of Machine Learning? Add yourself to the Directory by creating an account. PROFILES We post profiles highlighting the research and technical accomplishments of women working in machine learning. Read their profiles here and follow us on Facebook to receive updates when new profiles are posted.

Our generous partners sponsor WiML’s events, activities and programs on an annual basis. We also seek sponsors specifically for WiML Workshop, our flagship annual workshop co-located with NeurIPS. For any inquiries regarding yearlong partners or workshop sponsorship, contact sponsorship@wimlworkshop.org. For any other enquiries, contact info@wimlworkshop.org. Partners Our generous partners sponsor WiML’s events, activities and programs on an annual basis. We also seek sponsors specifically for WiML Workshop, our flagship annual workshop co-located with NeurIPS. For any inquiries regarding yearlong partners or workshop sponsorship, contact sponsorship@wimlworkshop.org. For any other enquiries, contact info@wimlworkshop.org . Corporate Partners Former Partners Our generous partners sponsor WiML’s events, activities and programs on an annual basis. For a list of partners that have supported us in the past click here .

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

Enhance the experience of women in machine learning. Toward this goal, we create opportunities for women to engage in substantive technical and professional conversations in a positive, supportive environment. We also work to increase awareness and appreciation of the achievements of women in machine learning. Our programs help women build their technical confidence and their voice so that their achievements are known in the community. Our Mission Enhance the experience of women in machine learning Increase the number of women in machine learning Help women in machine learning succeed professionally Increase the impact of women in machine learning in the community Our Mission Toward this goal, we create opportunities for women to engage in substantive technical and professional conversations in a positive, supportive environment (e.g. annual workshop, small events, mentoring program). We also work to increase awareness and appreciation of the achievements of women in machine learning (e.g. directory and profiles of women in machine learning). Our programs help women build their technical confidence and their voice, and our publicity efforts help ensure that women in machine learning and their achievements are known in the community. WiML is proud to support and promote all women in machine learning, regardless of nationality, ethnicity, race, religion, sexual orientation, or politics.

19th Women in Machine Learning Workshop (WiML 2024) The Workshop is co-located with NeurIPS on Tuesday, December 10th, 2024 at the Vancouver Convention Center in Vancouver, BC, Canada. 19th Women in Machine Learning Workshop (WiML 2024) The workshop is co-located with NeurIPS on Tuesday, December 10th, 2024 at the Vancouver Convention Center in Vancouver, BC, Canada. 19th Women in Machine Learning Workshop (WiML 2024) — the workshop is co-located with NeurIPS on Tuesday, December 10th, 2024. For more information or to register, please visit the event’s website here. Back To Top

WiML Statements and Calls serves as a repository for the organization's official statements on inclusivity and related matters, as well as announcements for leadership and employment opportunities within WiML. This page reflects WiML's dedication to promoting diversity, ethical standards, and active participation in leadership roles within the machine learning community.​ WiML+2 WiML Statements and Calls Statements on Inclusivity from WiML: First Statement from the Women In Machine Learning Executive Board on Inclusivity Second Statement from the Women In Machine Learning Executive Board on Inclusivity Black Lives Matter Statement for Dr. Timnit Gebru Calls for WiML Board of Directors: 2022 WIML Board of Directors–General 2021 WiML Board of Directors — General 2019 WiML Board of Directors — Policy and Research Committee 2019 WiML Board of Directors — Treasurer Call for WiML Full-time Employee: 2021 WiML Operations Administrator