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Give and receive advice, gain knowledge, and make connections. Our annual long-term mentorship program fosters meaningful long-term connections and provides targeted advice to early career researchers. MENTORSHIP Give and receive advice, gain knowledge, and make connections WiML is committed to advancing the careers of women and non-binary people studying and working in machine learning. Many of our events have mentorship roundtables that bring together mentors and attendees in close conversation on technical and career topics. Outside of events, our annual long-term mentorship program fosters meaningful long-term connections and provides targeted mentorship on specific topics that are selected every year, ranging from PhD applications to job seeking. 6th Annual WiML Mentorship Program (2026-2027) Whether you're seeking mentorship or ready to mentor, there's a place for you. Visit the 2026–2027 WiML Mentorship Program page to learn more about eligibility, key dates, and how to apply. Learn More & Apply Mentorship History 5th WiML Mentorship: Post-graduate degree applicants and job seeker 2025–2026 The goal of this program is to provide mentorship to early-career women and non-binary people studying and/or working in machine learning. The program will run between September 2025 and May 2026. Application deadlines are indicated in the "Timeline" section. The website for the 5th mentorship can be found here . 4th WiML Mentorship: Ph.D. Applications and Job Seekers 2024–2025 The 2024-2025 mentorship grew its focus not only to support graduate degree program applicants, but job seekers, in partnership with WiML corporate partners. The website for the 4th mentorship can be found here [website ]. 3rd WiML Mentorship: PhD Applications, 2023–2024 The 2023-2024 mentorship continued with a focus on supporting members of our community applying to research-oriented degree programs in machine learning, including PhD and Masters programs. This year, WiML also received a grant from NeurIPS to support this work, and started funding mentees’ application fee expenses. The website for the 3rd mentorship can be found here [website ]. The success of the mentorship so far was described here [NeurIPS website ]. 2nd WiML Mentorship: PhD Applications, 2022–2023 Building on the success of our pilot, the 2022–2023 mentorship narrowed its focus to support PhD applicants. This allowed us to provide tailored guidance throughout the PhD application process. 1st WiML Mentorship: Pilot, 2021–2022 Our pilot program in 2021–2022 was our first step toward establishing a formal, long-term mentorship community within WiML. The focus of the pilot was on general career development in machine learning, and the participants ranged from students to professionals.

All events WIML Workshop @ NeurIPS 2021 Virtual December 9, 2021 2:00 am - 11:00 pm UTC The 16th annual Women in Machine Learning workshop will be virtually co-located with NeurIPS 2021 in December 2021. See the workshop website for details! The organizers are: Boyi Li, Mariya Vasileva, Linh Tran, Akiko Eriguchi, Meera Desai, Aga Lee, Jieyu Zhao, Salomey Osei, Sirisha Rambhatla, Geeticka Chauhan, Nwamaka Okafor. Previous Next

All events WiML Social @ EurIPS 2025 Treehouse, Bella Center, Copenhagen December 3, 2025 10:00-14:30 We are happy to invite you to the Women in Machine Learning (WiML) social co-located with EurIPS 2025 at The Tree House, Bella Center, Copenhagen. Registration WiML Social @ EurIPS — Wednesday, December 3, 2025 Register here → https://luma.com/rs5val4p Be aware that, to attend the event, you must be registered to the EurIPS conference: https://eurips.cc/ The WiML @ EurIPS 2025 social will be held in person with invited speakers, oral presentations, and posters. The event brings together members of the academic and industry research landscape for an opportunity to connect and exchange ideas, and learn from each other. Underrepresented minorities and undergraduates interested in pursuing machine learning research are encouraged to participate. All genders are invited to attend. Program 10:00 - 10:10: Opening remarks 10:10 - 10:40: Invited talk - Lina Jaurigue: “Reservoir Computing for On-Device ML for Hearing Aid Improvement” 10:40 - 11:00: Best Posters Short Talks (10min each) 11:00 - 11:30: Panel: “Navigating uncertainty and long-term career sustainability in Europe’s evolving ML landscape” - Panelists: Isabel Valera, Lina Jaurigue, Vinti Agarwal 11:30 - 12:30: Networking/mentoring activities 12:30 - 13:30: Lunch +Closing Remarks 13:30 - 14:30: Poster session We’re delighted to host Google’s sponsor booth from 11:30 to 13:30! Organizing Committee WiML Social Organizers Ana Lucic ( Website : https://a-lucic.github.io/ ) I am an assistant professor in AI at the University of Amsterdam, with a joint position between the Institute for Logic, Language, and Computation, and the Informatics Institute. My work focuses on interpretable machine learning for the natural sciences. Previously, I was a researcher at Microsoft Research AI for Science, where I was one of the core scientists behind the Aurora foundation model. I was also a research fellow at the Partnership on AI. I have a PhD in explainable ML from the University of Amsterdam, supervised by Maarten de Rijke and Hinda Haned. My MSc and BSc are both in mathematics from McMaster University. Stella Grasshof ( Website : https://stellagrasshof.com/ ) I am an Assistant Professor in the Data Science section at the IT University of Copenhagen and at the Pioneer Centre for Artificial Intelligence. I hold an M.Sc . in Computational Life Science from Universität zu Lübeck and a Dr.-Ing. (PhD) from the Leibniz Universität Hannover (Germany). My research lies at the intersection of human-centred machine learning and visual computing, with a focus on generative AI for images and video, human faces and motion, computer vision, and applications in mental health. Additionally, I am part of the Lundbeck Foundation Investigator Network (LFIN), where I serve as a board member. WiML Board Liaisons – WiML EurIPS liaison Giulia Clerici ( Website: https://clericigiulia.com/ ) -WiML Vice President of Events Tatjana Chavdarova ( Website: https://chavdarova.github.io/ ) -WiML Vice President of Programs Alessandra Tosi - (Website: https://www.linkedin.com/in/alessandra-tosi-824a78a3/ ) Thanks to our Sponsors! Platinum Gold Silver Bronze Previous Next

All events WiCS AI Research Day @ SFU SFU Burnaby Campus, Burnaby, British Columbia, Canada February 20, 2026 9 AM - 3:30 PM PST A one-day event for undergraduate students at SFU who are passionate about Artificial Intelligence (AI) and Machine Learning (ML). The initiative will support students in defining and improving personal AI projects, with access to mentorship during the event to ask questions and get help. The event aims to: Encourage hands-on learning and creativity in AI. Provide mentorship on ML concepts, project design, and research thinking. Connect students with academic and industry professionals. Celebrate student innovation and support future publication efforts. Key Highlights of WiCS AI Research Day: Expert Talks: Topics include Machine Learning (ML) areas such as Natural Language Processing (NLP), Computer Vision, Human-Computer Interaction (HCI), Robotics, and Speech, featuring experts like Dr. Angelica Lim and Dr. Marzena Karpinska. Student Panel: Opportunities to hear directly from students about their experiences, challenges, and advice in the tech field. Interactive Sessions: Participants can engage in project creation and pitch preparation, aiming to turn ideas into practical ML solutions. Networking: An opportunity to connect with peers and professionals in academia and industry. Previous Next

All events WiML Partner Event: New England Women in ML Event with IBM Research Cambridge, Massachusetts April 19, 2019 03:45 pm — 06:00 pm WiML is excited to announce an event by WiML Partner IBM Research in the Cambridge area. The goal is to encourage and support local women, especially students, post-docs, early career researchers and engineers, by offering seminars from thought-leading women in ML, providing opportunities to present their own research, and connecting them to mentors, role models and colleagues. Join the event this Thurs 6/20. Speakers and activities include: – A talk by Tamara Broderick (Assistant Professor, MIT) on “Approximate Cross Validation for Large Data and High Dimensions”. – Reception immediately after the event. When: Thursday June 20, 2019, 4:00pm – 5:00pm with reception immediately after the event Where: IBM Research Cafe, 75 Binney St. Cambridge, MA Organized by IBM Research. Questions? Contact Preethi Raghavan at praghav@us.ibm.com . Thanks to the organizers Lisa Amini (IBM Research), Preethi Raghavan (IBM Research), Kristen Severson (IBM Research). IBM Research is a WiML Platinum Partner. Previous Next

All events WiML Workshop 2006 San Diego, California December 4, 2006 08:45 am — 06:00 pm The 1st Women in Machine Learning workshop was colocated with Grace Hopper Celebration of Women in Computing 2006 in San Diego, California in October 2006. The workshop website is no longer maintained. The organizers were: Hanna Wallach, Jenn Wortman, and Lisa Wainer, with faculty advisor Amy Greenwald. The invited speakers were: Jennifer Dy, Amy Greenwald, Lise Getoor, and Marie desJardins. 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 WiML Symposium @ ICML 2024 Vienna July 24, 2024 Symposium The WiML Symposium at ICML will occur on Wednesday, July 24th, 2024 at the Messe Wien Exhibition Congress Center, Vienna, Austria. For more information or to register, please go here. Previous Next

All events WiML Workshop 2014 Montreal, Canada December 8, 2014 08:00 am — 06:00 pm The 9th annual Women in Machine Learning workshop was colocated with NIPS 2014 in Montreal, Canada in December 2014. The workshop website is no longer maintained. The organizers were: Allison Chaney, Marzyeh Ghassemi, Sarah Brown, and Jessica Thompson. The invited speakers were: Carla Brodley, Tina Eliassi-Rad, Diane Hu, and Claudia Perlich, with Finale Doshi-Velez giving the opening remarks. 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 Luncheon @ ICML 2016 New York, New York June 21, 2016 12:00 pm — 02:00 pm WiML is hosting a luncheon at ICML 2016 in New York, New York. This event gives female faculty, research scientists, data scientist, and graduate students in the machine learning community an opportunity to meet, exchange ideas and learn from each other. Date: Tuesday, June 21, 2016, 12pm-2pm Venue: Microsoft building (5th floor), 11 Times Square, New York Registration: https://www.eventbrite.com/e/wiml-icml-luncheon-2016-tickets-25415537557# If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org SPONSORS -Silver- -Bronze- 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 WiML Workshop 2018 Montreal, Canada December 3, 2018 09:00 am — 10:00 pm The 13th annual Women in Machine Learning workshop will be colocated with NeurIPS 2018 in Montreal, Canada in December 2018. See the workshop website for details! The organizers are: Aude Hofleitner, Audrey Durand, Nyalleng Moorosi, Sarah Poole, and Amy Zhang. The invited speakers are: Isabel Kloumann, Po-Ling Loh, Raquel Urtasun, and Emma Brunskill, with Katie Kinnaird giving the closing remarks. Recorded talks can be found at this link . Previous Next