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All events WiML Virtual Un-Workshop @ ICML 2020 Virtual July 13, 2020 8:00 pm - 6:00 pm The 1st Women in Machine Learning virtual Un-Workshop is co-located with virtual ICML on Monday, July 13th, 2020. See the un-workshop website for details. The organizers are Fariba Yousefi, Caroline Weis, Tatjana Chavdarova, Mandana Samiei, Larissa Schiavo. Previous Next

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 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 The workshop website is no longer maintained.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 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 The workshop website is no longer maintained.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 Luncheon @ ICML 2011 Bellevue, Washington June 30, 2011 12:00 pm — 01:40 pm WiML is hosting a luncheon at ICML 2011 in Bellevue, Washington. All women working on machine learning are invited. Date: Tuesday, June 30, 2011, 12pm-1.40pm Venue: Maple Room,Hyatt Regency Bellevue, Bellevue Event details: http://www.icml-2011.org/forms/Brochure_Final4.pdf 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 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

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 Workshop 2019 Vancouver, Canada December 9, 2019 08:00 am — 06:00 pm The 14th annual Women in Machine Learning workshop will be colocated with NeurIPS 2019 in Vancouver, Canada in December 2019. See the workshop website for details! The organizers are: Michela Paganini, Sarah Aerni, Forough Poursabzi Sangdeh, Nezihe Merve Gürel, and Bahare Fatemi. Previous Next

All events WiML Social @ ICLR 2024 Vienna, Austria May 8, 2024 12:45PM Date: May 08th, 2024 (Wed.) Time: 12:45 PM- 2:15 PM Place: Hall B, Messe Wien Exhibition Congress Center@Vienna, Austria The topic of the panel will be AI Unplugged: Navigating Everyday Life & Professional Paths. During the panel, we aim to facilitate discussions on various topics, such as mentorship advice and how AI t echnologies are impacting personal and professional domains. Program: 12:45 – 12:50 PM Opening Remarks - Tatjana Chavdarova (WiML board) 12:50 – 1:25 PM Networking & Lunch 12:50 – 1:00 PM Icebreaker games 1:00 – 1:25 PM Networking themed roundtables 1:25 – 2:15 PM Panel discussion: “AI Unplugged: Navigating Everyday Life & Professional Paths” PANELISTS Bahare Fatemi Bahare Fatemi is a Research Scientist at Google Research in Montreal, specializing in graph representation learning and natural language processing. She received her Ph.D. From the University of British Columbia. Her work has been featured in top AI conferences and journals including NeurIPS, ICLR, AAAI, and JMLR. She co-organized the Mining and Learning with Graphs workshop at KDD, Women in Machine Learning (WiML) workshop, and the Montreal AI Symposium. Devi Parikh Devi Parikh, an Associate Professor at Georgia Tech's School of Interactive Computing, previously served as Senior Director of Generative AI at Meta until March 2024. Her diverse career includes roles as Director at Meta's FAIR lab, Assistant Professor at Virginia Tech, and Research Assistant Professor at TTIC. She has held visiting positions at esteemed institutions such as Cornell, UT Austin, Microsoft Research, MIT, Carnegie Mellon, and Facebook AI Research. Her research focuses on generative AI, AI for creativity, multimodal AI, and human-AI collaboration. She boasts numerous awards, including NSF CAREER, Sloan Research Fellowship, and IJCAI Computers and Thought award, among others. Priya Donti Priya Donti is an Assistant Professor and the Silverman (1968) Family Career Development Professor at MIT EECS and LIDS. Her research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Priya is also the co-founder and Chair of Climate Change AI, a global nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning. Priya received her Ph.D. in Computer Science and Public Policy from Carnegie Mellon University. She hold several awards and fellowships including the MIT Technology Review’s 2021 “35 Innovators Under 35” award and the ACM SIGEnergy Doctoral Dissertation Award. MODERATOR Aya Abdelsalam Ismail Aya Abdelsalam Ismail is a research scientist at Prescient Design in the frontier group. Prior to Prescient, she received her Ph.D. from the University of Maryland where she was advised by Soheil Feizi and Héctor Corrada Bravo. During her Ph.D. her research focused on the interpretability of neural models for sequential data. WiML SOCIAL ORGANIZERS Yutong Zhou Yutong Zhou is a Postdoc Researcher at the Leibniz Centre for Agricultural Landscape Research (ZALF), Germany. Her research interests focus on computer vision and deep learning, particularly in Generative Models, Multi-modal Vision and Language. She is concentrating on Artificial Intelligence × Biodiversity × Smart agriculture, surrounding the goals of ‘Global Sustainability for Better AI’ and ‘AI for Best Global Sustainability’. Lisa Weijler Lisa Weijler is a PreDoc researcher at the Computer Vision Lab (CVL), TU Wien, Austria. Her research interests are computer vision and machine learning for 3D and unstructured data, especially point clouds. Additionally, she is passionate about combining her research with medical, social or political science in interdisciplinary projects. She has applied her research for cancer cell detection in pediatric leukemia patients as well as for methodological advancements like SE(3) equivariant convolutions or OOD 3D scene understanding. Her main research focus currently is open vocabulary 3D scene understanding. WiML BOARD ORGANIZERS Hewitt Tusiime – WiML ICLR liaison Erin Grant – D&I chair Tatjana Chavdarova – VP Events WiML Thanks to our sponsors! Previous Next

All events WiML @ LIDA Data Science Careers Fair 2025 University of Leeds March 17, 2025 On 17 March 2025, WiML had the pleasure of being part of the LIDA Data Science Careers Fair 2025 at the University of Leeds. The fair brought together students, alumni, and industry representatives from across sectors including food, retail, finance, civil service, consultancy, data, and technology, all eager to explore career opportunities in data science and tech. Representing WiML, Luisa Cutillo engaged with attendees to share our mission, discuss pathways for women and underrepresented genders in machine learning, and highlight the importance of community and support for early-career data professionals.) WiML is proud to stand alongside a diverse group of institutions and companies (e.g., Google, KPMG, NHS England, Morrisons, The Data City, Answer Digital, and others) in supporting and inspiring the next generation of data scientists. A big thanks to the University of Leeds and the Leeds Institute for Data Analytics (LIDA) for organizing this successful event and for inviting WiML to contribute! More info here: https://www.leeds.ac.uk/events-staff/events/event/490/lida-data-science-careers-fair-2025 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