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All events WiML Reception @ CoRL 2017 Mountain View, California November 13, 2017 08:00 pm — 11:00 pm WiML is hosting a networking reception at the 2017 Conference on Robot Learning (CoRL). The organizers are Chelsea Finn and Coline Devin. Date: Monday, November 13, 2017, 8pm-11pm Venue: Steins Beer Garden, Mountain View Registration: Register during CoRL registration ( https://sites.google.com/a/robot-learning.org/corl2017/home/corl2017 ) If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org SPONSORS Previous Next

All events WiML Workshop 2009 Vancouver, Canada December 7, 2009 08:00 am — 06:00 pm The 4th annual Women in Machine Learning workshop was colocated with NIPS 2009 in Vancouver, Canada in December 2009. The workshop website is no longer maintained. The organizers were: Finale Doshi, Inmar Givoni, and Farheen Omar, with faculty advisor Daphne Koller. The invited speakers were: Kristen Grauman, Dana Pe’er, Odelia Schwartz, and Michèle Sebag, 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 Reception @ NeurIPS Mexico City 2025 Ciudad de México, México November 30, 2025 9 am to 12.30 pm LatinX in AI is proud to share its joint affinity group half-day workshop, with Women in Machine Learning and Queer in AI, happening at the official co-location of the NeurIPS 2025 conference in Mexico City. For more information, please visit the event’s website here. This event will take place on November 30th at the Hilton Mexico City Reforma from 9:00 AM to 12:30 PM. Registration WiML and LatinX in AI Reception — Sunday, November 30 Register here → https://luma.com/4g8258pe WiML and Queer in AI at LatinX in AI Workshop — Sunday, November 30 Register here→ https://www.latinxinai.org/registration Previous Next

All events WiML Luncheon @ COLT 2016 New York, New York June 24, 2016 12:30 pm — 02:30 pm WiML is hosting a luncheon at COLT 2016 in New York. The organizer is Kamalika Chaudhuri. Date: Friday, June 24, 2016, 12.30pm-2.30pm Venue: Columbia University, New York Event details: http://www.learningtheory.org/wp-content/uploads/handout.pdf Registration: Register during COLT registration ( www.learningtheory.org/colt2016/ ). 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 Workshop 2017 Long Beach, California December 4, 2017 08:00 am — 05:30 pm The 12th annual Women in Machine Learning workshop will be colocated with NIPS 2017 in Long Beach, California in December 2017. See the workshop website for details! The organizers are: Genna Gliner, Ehi Nosakhare, Maja Rudolph, Danielle Belgrave, Negar Rostamzadeh. The invited speakers are: Tamara Broderick, Hanna Wallach, Joelle Pineau, and Nina Mishra, with Jenn Wortman Vaughan and Raia Hadsell giving the opening remarks. Recorded talks can be found at this link . Previous Next

All events 2nd WiML Mentoring Program for PhD Applications: Panel on Essay Writing Virtual October 6, 2022 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: Sinead Williamson (University of Texas Austin), Mihaela van der Schaar (University of Cambridge), Sanmi Koyejo (University of Illinois Urbana-Champaign; Stanford University), Awa Dieng (Mila) Moderator: Kristy Choi (Stanford University) 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 2016 Barcelona, Spain December 5, 2016 08:00 am — 05:00 pm The 11th annual Women in Machine Learning workshop will be colocated with NIPS 2016 in Barcelona, Spain in December 2016. See the workshop website for details! The organizers are: Diana Cai, Deborah Hanus, Sarah Tan, Isabel Valera, and Rose Yu. The invited speakers are: Jennifer Chayes, Maya Gupta, Anima Anandkumar, and Suchi Saria, with Tamara Broderick and Sinead Williamson giving remarks on WiML updates. Recorded talks can be found at this link . Previous Next

All events WiML Virtual Social @ ICLR 2021 Virtual May 3, 2021 9:00 am - 11:00 am WiML is hosting a virtual social, involving a panel discussion and socializing, at ICLR 2021 on Monday, May 3, 9.00am – 11.00am Eastern Time . The panel will take place in Zoom. After the panel, we will adjourn to the Icebreaker/Gatheround platform for socializing. Event Format Agenda (all times approximate) 9:00 – 9:05am ET – Meet in Zoom. Welcome and introductions 9:05 – 9:50am ET – Panel on “Starting and Navigating Careers Through COVID-19″ 9:50 – 10:00am ET – Wrap-up and adjourn to Icebreaker/Gatheround platform 10:00 – 11:00am ET – Socializing in Icebreaker/Gatheround platform What is the panel on? The panel, moderated by Ehi Nosakhare (Data Science Manager, Microsoft) with panelists: Candace Ross (PhD student in Computer Science, MIT) Christina Papadimitriou (Machine Learning Engineer, JPMorgan Chase) Claire Vernade (Research Scientist, DeepMind) Po-Ling Loh (Lecturer in the Department of Pure Mathematics and Mathematical Statistics, University of Cambridge) Sinead Williamson (Assistant Professor of Statistics, University of Texas at Austin) is on the topic of “Starting and Navigating Careers Through COVID-19”. The panel features ML researchers at various career stages who will talk about their experience networking, job hunting, collaborating and/or starting a new position in a primarily online environment. Read more about the panelists below. Joining Information How to join: Everyone registered for ICLR is encouraged to attend! Event limited to 200 participants. You can find the Zoom link on the ICLR portal: https://iclr.cc/virtual/2021/social/4398 (ICLR registration required to access). The Icebreaker/Gatheround link will be shared in Zoom at the end of the panel. Icebreaker/Gatheround will ask you to give it permission to access your camera and microphone. Google Chrome browser recommended. Participant instructions: During the panel, you can type questions for the panelists, so bring any questions on starting and navigating careers through COVID-19! If you will participate in the post-panel social, we suggest preparing one or two lines to describe your work and research, as well as any other topics you may want to discuss. Additional opportunities: WiML is also offering two more opportunities at ICLR 2021 for women and/or non-binary individuals: Thanks to ICLR’s DEI action fund ( https://iclr.cc/public/DiversityInclusion ) as well as WiML sponsors, WiML is able to fund registrations for eligible individuals to attend ICLR. If you are a student, postdoc, or early-career, underrepresented individual in machine learning, apply here by April 26: https://forms.gle/B2eJ4xWuPBodVeyGA Regardless of whether you are attending ICLR or the WiML social, you can submit your resume to our WiML@ICLR 2021 resume book. The resume book will be shared with WiML sponsors. Submit here by May 1: https://forms.gle/ARs8BcnfgSyraPUDA Questions? Email workshop@wimlworkshop.org . By joining the event, you agree to abide by the WiML Code of Conduct . Panelists and Moderator bios Candace Ross, MIT Candace Ross is an EECS Phd Student in the InfoLab at MIT. She works on language grounding, particularly grounding in vision, and weakly supervised models for language acquisition. Outside of research, she plays lacrosse, participates in efforts for community diversity and inclusion, and enjoys traveling (which surprisingly can be done as a grad student)! Christina Papadimitriou, JP Morgan Christina Papadimitriou (she/her) is a Machine Learning Engineer on the Artificial Intelligence Acceleration team at JPMorgan Chase. Her team accelerates the adoption of AI into the firm’s products and services. Christina is the co-chair of PRIDE, JPMorgan’s LGBTQ+ Business Resource Group in the NY Metro area, and she is the firm’s representative for OPEN Finance. She is also in the NY Leadership Team for Out in Tech, and she serves on the Board of Directors for WiML. Christina holds a Masters in Data Science from UC Berkeley, a Masters in Operations Research from Columbia University, and a Bachelor of Engineering in Chemical Engineering from the University of South Carolina. Claire Vernade, DeepMind Claire Vernade is a Research Scientist at DeepMind in London UK. She received her PhD from Telecom ParisTech in October 2017, under the guidance of Prof. Olivier Cappé. From January 2018-October 2018, she worked part-time as an Applied Scientist at Amazon in Berlin, while doing a postdoc with Alexandra Carpentier at the University of Magdeburg in Germany. She is involved in WiML-T, which connects women in Learning Theory and organizes social and career events at conferences like COLT and ALT. Her research is on sequential decision making. It mostly spans bandit problems, but Claire’s interest also extends to Reinforcement Learning and Learning Theory. While keeping in mind concrete problems — often inspired by interactions with product teams — she focuses on theoretical approaches, aiming for provably optimal algorithms. 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. She currently serves on the Board of Directors for WiML. Professor Sinead Williamson, University of Texas at Austin Sinead Williamson is an assistant professor of Statistics at the University of Texas at Austin. She works on Bayesian methods for machine learning, with particular interests in Bayesian nonparametrics, scalable sampling methods, and modeling structured data with complex dependency structures. Sinead has recently worked as a research scientist at Amazon and CognitiveScale, and served on the Board of Directors for WiML. Ehi Nosakhare, Microsoft Ehi Nosakhare is a Senior Data and Applied Science Manager at the Microsoft AI development and Acceleration Program (MAIDAP). She leads a team that designs, develops, and implements ML solutions in application projects across Microsoft’s products and services. Prior to joining Microsoft, she earned her PhD in Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT). Her thesis work focused on using Latent Variable Modeling to uncover behavioral influences on mental health and well-being. She is deeply passionate about using ML to solve real-world problems and studying the ethical implications of ML/AI. She currently serves on the Board of Directors for WiML. SPONSORS -Platinum- Previous Next

All events WiML Workshop 2010 Vancouver, Canada December 6, 2010 07:30 am — 05:30 pm The 5th annual Women in Machine Learning workshop was colocated with NIPS 2010 in Vancouver, Canada in December 2010. The workshop website is no longer maintained. The organizers were: Diane Oyen, En-Shiun Annie Lee, and Kate Saenko, with faculty advisor Marie desJardins. The invited speakers were: Sally A. Goldman, Raquel Urtasun, Ming Hua, and Isabelle Guyon. 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 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 Virtual Un-Workshop @ ICML 2021 Virtual July 21, 2021 8:00 am- 6:00 pm The 2nd Women in Machine Learning virtual Un-Workshop is co-located with virtual ICML on Monday, July 21th, 2021. See the un-workshop website for details. The organizers are Olivia Choudhury, Vaidheeswaran Archana, Hadia Mohmmed Osman Ahmed Samil, Berivan Isik, Liyue Shen, Arushi Majha, Beliz Gokkaya and Wenshuo Guo. Previous Next