All events WiML Workshop 2012 Lake Tahoe, Nevada December 3, 2012 08:00 am — 06:00 pm The 7th annual Women in Machine Learning workshop was colocated with NIPS 2012 in Lake Tahoe, Nevada in December 2012. The workshop website is no longer maintained. The organizers were: Tamara Broderick, Minmin Chen, Pallika Kanani, and Tejaswini Narayanan, with faculty advisor Raquel Urtasun. 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 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 4th WiML Mentorship Program for PhD Applications: Panel on CV and Cover Letters Virtual October 8, 2024 8:00 am - 9:00 am This event, part of the WiML’s 2024-2025 Mentorship Program on the theme of PhD applications, takes place 8-9am PT in Zoom. Mentors and mentees of the 2024-2025 Mentorship Program are invited to attend. Panelists: Arpita Singhal (Stanford), Tijana Zrnic (Stanford), Duroux Diane Magali Anna (ELLIS) Moderator: Luisa Cutillo (University of Leeds) We will cover: Key tips and advice for the graduate programs application process Overview of research areas and opportunities in ML at the ELLIS program (Europe) and other US-based institutions Q&A session to answer participant questions Previous Next

All events WiML Social @ ICLR 2026 Rio de Janeiro April 24, 2026 12:00 PM – 3:00 PM Date: April 24, 2026 Time: 12:00 PM – 3:00 PM Location: Room 203C, Centro de Convenções / Convention Center The Women in Machine Learning (WiML) Social at ICLR 2026 is an opportunity to connect with members of the WiML community in an informal and welcoming setting. The event will bring together researchers and practitioners from academia and industry to foster meaningful conversations, exchange experiences, and build new connections. This year’s social will feature a panel discussion on: There’s no single path: Navigating careers in academia, industry, and beyond. The panel will explore different career trajectories in machine learning, highlighting transitions across academia, industry, and other paths. Panelists will share their experiences, challenges, and perspectives on building a career in ML, followed by an open discussion with the audience. Program 12:00 PM – 12:10 PM Opening Remarks 12:10 PM – 12:30 PM Icebreaker Game 12:30 PM – 1:45 PM Networking & Lunch 1:45 PM – 2:45 PM Panel Discussion 2:50 PM – 2:55 PM Closing Remarks Panelists Aleksandra Faust Aleksandra Faust is a Director of Research at Google DeepMind, where she leads Frontier AI Health efforts. Her research focuses on foundation models and world models for complex adaptive systems, treating the AI design pipeline as a learnable, sequential, and self-improving decision-making process. This methodology has driven state-of-the-art improvements across drug discovery, robotics, autonomous driving, and web agents, and led to her founding the field of Automated Reinforcement Learning (AutoRL). Notably, she co-authored the seminal "Levels of AGI" framework and led the Gemini Self-improvement research team, developing the reinforcement learning methods behind the Gemini model family. Previously, Aleksandra served as Chief AI Officer at Genesis Molecular AI and held foundational leadership roles at Google Brain, Google Robotics, and Waymo/X. Earlier in her career, she was a Senior R&D Engineer at Sandia National Laboratories. Faust holds a Ph.D. in Computer Science with distinction from the University of New Mexico and an M.S. from the University of Illinois at Urbana-Champaign. She is an IEEE Fellow and a recipient of the IEEE RAS Early Career Award for Industry and the Tom L. Popejoy Dissertation Award, and was named a Distinguished Alumna of the UNM School of Engineering. Her work has been featured in The New York Times, The Economist, and Forbes, and has received multiple Best Paper Awards at premier robotics, machine learning, and systems architecture venues. https://www.afaust.info/ Franziska Boenisch Franziska Boenisch is a tenure-track faculty at the CISPA Helmholtz Center for Information Security, where she co-leads the SprintML lab. Her research focuses on private and trustworthy machine learning; during her Ph.D. at Freie Universität Berlin and Fraunhofer AISEC she pioneered the notion of individualized privacy in ML. Before joining CISPA, she was a Postdoctoral Fellow at the University of Toronto and the Vector Institute. She received an ERC Starting Grant in 2025 for research on privacy in foundation models and has been recognized with the Fraunhofer ICT Dissertation Award (2023), a GI Junior Fellowship (2024), and a Werner‑von‑Siemens Fellowship (2025). https://franziska-boenisch.de/ Noa Garcia Noa Garcia is an Associate Professor at the Institute for Advanced Co-Creation Studies and D3 Center, The University of Osaka (Japan). She earned her Ph.D. in Computer Science from Aston University (UK), specializing in multimodal retrieval and instance-level recognition. She moved to Japan in 2018 as a postdoc, and has been conducting research at The University of Osaka since then. Her research sits at the intersection of computer vision, natural language processing, fairness, and art. Her recent work includes investigating demographic bias in computer vision, analyzing visual datasets, and exploring how generative models can reinforce social stereotypes. https://www.noagarciad.com/ Valentina Pyatkin Valentina Pyatkin is a postdoctoral researcher at the Allen Institute for AI and the University of Washington. Additionally, she is affiliated with the ETH AI Center, where she mentors students and works on post-training for the Swiss AI Initiative. She obtained her PhD in Computer Science from Bar Ilan University. Her work has been awarded an ACL Outstanding Paper Award and the ACL Best Theme Paper Award, and has been supported by a Schmidt Sciences Postdoctoral Award. During her doctoral studies, she conducted research internships at Google and the Allen Institute for AI, where she received the AI2 Outstanding Intern of the Year Award. https://valentinapy.github.io/ Moderator Karen Ullrich Karen is a research scientist at FAIR NY and she is actively collaborating with researchers from the Vector Institute and the University of Amsterdam. Her main research focus lies in the intersection of information theory and probabilistic machine learning / deep learning. She completed her PhD under the supervision of Prof. Max Welling. Prior to that, she worked at the Austrian Research Institute for AI, Intelligent Music Processing and Machine Learning Group lead by Prof. Gerhard Widmer. https://karenullrich.info/ WiML Social Organizers Ivona Najdenkoska Ivona is a postdoctoral researcher at the University of Amsterdam. Her research focuses on multimodal foundation models and generative AI, with an emphasis on scalable vision–language understanding and generation. She also works on AI-generated image detection, developing robust methods for distinguishing synthetic from real content. She recently completed her PhD at the University of Amsterdam under the supervision of Marcel Worring and Yuki Asano, where her work focused on learning from context with multimodal foundation models. During her PhD, she spent time at Meta working on context-aware image generation. She is also a member of the ELLIS Society, and her research has been published at leading AI conferences, such as ICLR and ECCV. Paula Feldman Paula is a postdoctoral researcher working at the intersection of AI and medical imaging at Weill Cornell Medicine. Her work focuses on generative AI and cardiovascular applications, collaborating closely with clinical teams as part of the group led by Mert Sabuncu. She completed her PhD at Universidad Torcuato Di Tella and Universidad Nacional del Sur under the supervision of Emmanuel Iarussi and Claudio Delrieux, where her research focused on deep generative modeling of 3D vascular structures. Her research has been published in leading conferences and journals in the field, including venues such as MICCAI and the journal Medical Image Analysis. More broadly, she is interested in multimodal learning and synthetic data generation. Mila Soares de Oliveira de Souza Mila de Oliveira is a research software engineer currently working on AI applications to address public health challenges in Brazil. She completed her MSc in Electrical Engineering (Computer Vision) at the Universidade Federal do Rio de Janeiro, where she developed baseline methodologies for real-time detection of breeding sites of Aedes aegypti (primary vector of dengue, the most pressing public health threat in Brazil) under the supervision of Eduardo Antonio Barros da Silva and Sergio Lima Netto. She has extensive experience in software engineering for AI products in industry, having previously worked at Apple and Microsoft Advanced Technology Labs. Her current interests include GPU programming, machine learning compilers and formal verification of algorithms using proof assistants, as well as broader applications of ML in healthcare and science. We welcome all ICLR attendees to join us for an afternoon of discussion, networking, and community building. Additionally, we are collecting CVs to share with our sponsors who are actively recruiting: 👉 https://forms.gle/4FasmbmiLBh5zqyu6 Thanks to our 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 Virtual Roundtable @ CoRL 2020 Virtual November 18, 2020 6:00 am - 7:00 am WiML is hosting a virtual roundtable as part of the Inclusion@CoRL events at CoRL 2020. Date: November 18, 6am-7am PT Hosted by: Raia Hadsell, WiML board member and CoRL steering member Joining information: See https://www.robot-learning.org/attending/inclusioncorl/ . All CoRL attendees welcome; WiML code of conduct must be followed. Inclusion@CoRL will sponsor all registration fees for members of the research community which identify as part of historically underrepresented and/or underserved groups in robotics (including, but not limited to, LGBTQIA+, women or non-binary, differently abled, people of color, indigenous peoples, etc.). To apply for a sponsored registration, see https://www.robot-learning.org/attending/inclusioncorl or email inclusion@robot-learning.org for assistance. If you are a woman working in machine learning, regardless of whether you are attending CoRL or the WiML event, you can submit your resume to our WiML@CoRL 2020 resume book. The resume book will be shared with WiML sponsors. Submit here by November 18: https://forms.gle/ox4kZUxQ3PqeTVTV7 . SPONSORS -Platinum- -Diamond- Previous Next

All events WiML Un-Workshop @ ICML 2023 Honolulu, Hawai'i July 28, 2023 9:35 am - 10:50 am The 4th WiML Un-Workshop is co-located with ICML on Friday, July 28th, 2023. For more information or to register, please go here. 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 @ CoRL 2019 Osaka, Japan November 1, 2019 12:00 pm — 01:30 pm WiML is hosting a luncheon at CoRL 2019 in Osaka, Japan to bring together women in machine learning from different research areas and across all stages of their careers to meet, find mentorship, and learn from each other. The invited speakers are Anca Dragan, Yukie Nagai, and Chelsea Finn. Date: Nov 1, 12-1:30pm Venue: Senri Hankyu Hotel Osaka Registration: https://www.eventbrite.com/e/wiml-at-corl-an-event-to-celebrate-the-women-in-the-corl-community-registration-77723345619 SPONSORS -Platinum- Previous Next

All events WiML Virtual Social @ ICLR 2020 Virtual April 30, 2020 09:00 am — 11:00 am WiML is hosting a virtual social, involving a panel and mentoring session, at ICLR 2020. The organizers are Catherine Wah, Ovo Ojameruaye, and Ioana Bica. During the event, we hope to encourage discussions about how COVID-19 has impacted our daily lives and our work and about ongoing research on COVID-19. The panel features ML researchers at various career stages who will talk about their research related to COVID-19 and healthcare, and about the challenges of navigating research, career and personal life in these times. During the mentoring session, the panelists will each lead a small group discussion with up to 20 people. The panel will be moderated by Sinead Williamson (Assistant Professor of Statistics, University of Texas at Austin). The panelists are: Sasha Luccioni (Director of Scientific Projects in AI for Humanity / Post Doc, MILA) Lily Peng (Product Manager, Google Health) Morine Amutorine (Data Analytics Assistant, Pulse Lab Kampala) Cecilia Mascolo (Full Professor of Mobile Systems, University of Cambridge) Katherine Heller (Assistant Professor in Statistical Science, Duke University and Research Scientist, Google Research) Date: Thursday, April 30th, 2020, 9.00am-11.00am Pacific Time.Joining information: Everyone registered for ICLR is encouraged to attend! The event is limited to 500 attendees and will operate on a first-come first-served basis. Information about how to participate in the event will be posted on: https://iclr.cc/virtual/socials.html . We expect all attendees to adhere to the WiML Code of Conduct . Please join the #wiml channel in the ICLR chat for more event announcements. If you are a woman working in machine learning, regardless of whether you are attending ICLR or the WiML social, you can submit your resume to our WiML@ICLR 2020 resume book. The resume book will be shared with WiML sponsors. Submit here by April 30: https://forms.gle/4t2CEc1g9tpbYi2G6 SPONSORS -Platinum- -Diamond- 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 Social @ ICLR 2022 Virtual April 25, 2022 7:00 pm - 9:00 pm A one hour Virtual Panel session (45 min + 15 min Q&A from the audience) which will take place on April 25th, 19:00-20:00 GMT. The topic of the panel will be the interplay of academia and geographic location. During the Virtual Panel we hope to encourage discussions about geographically specific challenges experienced in academia. To apply for registration funding go to: https://forms.gle/A6zyMdXt21kHQZNSA Moderated by Dr. Caroline Weis Panelists Include: Akiko Eriguchi, Senior Researcher, Microsoft. Akiko is a Senior Researcher at Microsoft.　Her research interests lie in multilingual NLP and deep learning. With her position in the Microsoft Translator team, she has developed MT systems and multilingual NLP applications. Her work has been published in ACL, EMNLP, etc. She has served as a reviewer for ACL, EMNLP, NeurIPS, AAAI. She is also a 2021-2022 co-organizer of the Workshop on Asian Translation. Prior to joining Microsoft, she was a Research Fellow (DC1) at the Japan Society for the Promotion of Science. She obtained her doctoral degree from the University of Tokyo, Japan, where her PhD thesis received the sixth AAMT Nagao Student award from the Asia-Pacific Association for Machine Translation. Nora Hollenstein, Assistant Professor, University of Copenhagen. Nora is an assistant professor in NLP & Cognitive Science at the University of Copenhagen. Before joining the Center for Language Technology at the University of Copenhagen, Nora was a PhD candidate at DS3Lab at ETH Zurich working on cognitively inspired natural language processing. She was also a lecturer at the Institute of Computational Linguistics of the University of Zurich. The focus of her research lies in enhancing NLP applications with cognitive data such as eye-tracking and brain activity recordings. She is especially interested in multi-modal learning, learning from limited data, and the interpretability and cognitive plausibility of machine learning models. Jessica Schrouff, Senior Research Scientist, Google Research. Jessica is a Senior Research Scientist at Google Research working on machine learning for healthcare. Before joining Google in 2019, she was a Marie Curie post-doctoral fellow at University College London (UK) and Stanford University (USA), developing machine learning techniques for neuroscience discovery and clinical predictions. Throughout her career, Jessica’s interests have lied not only in the technical advancement of machine learning methods, but also in critical aspects of their deployment such as their credibility, fairness, robustness or interpretability. Previous Next