WIML Events Filter items by Event Type. Endorsed Events Mentorship Program Networking Socials & Networking Symposium Workshops WiML Networking Lunch at RLC Outdoor space near the Jean-Brillant Building, Université de Montréal August 17, 2026 Read More WiML Symposium @ ICML 2026 Seoul, South Korea July 8, 2026 Read More WiML Social @ ICLR 2026 Rio de Janeiro April 24, 2026 Read More WiML @ Data & AI Careers Festival 2026 Woodhouse, England March 24, 2026 Read More WiCS AI Research Day @ SFU SFU Burnaby Campus, Burnaby, British Columbia, Canada February 20, 2026 Read More WiML Social @ EurIPS 2025 Treehouse, Bella Center, Copenhagen December 3, 2025 Read More 15 Page 1

All events WiML Networking Lunch at RLC Outdoor space near the Jean-Brillant Building, Université de Montréal August 17, 2026 12:00-1:00 PM Women in Machine Learning (WiML) will host an informal networking lunch during RLC, giving attendees a chance to meet others in the community, make new connections, and take a social break together during the conference. Attendees can pick up their lunch from RLC and bring it with them to the gathering. Plan for the Hour 12:00–12:25 PM — Welcome + Networking Attendees grab their RLC lunch and meet at the WiML gathering point. We’ll have a brief welcome and introduction to WiML, followed by informal networking and conversation prompts to help people meet others beyond their existing circles. 12:25–12:45 PM — Interactive Wooclap Trivia A fun, interactive trivia game using Wooclap , designed as an icebreaker and an easy way to get the whole group engaging together. 12:45–1:00 PM — Open Networking Time to continue conversations, exchange contact information, and connect around research, mentorship, collaboration, and the broader ML/RL community. The event is intended to be casual, welcoming, and open to women and allies attending RLC. Attendees can simply bring their conference lunch and join us! :) Organizers: Mahvash Siavashpour, University of Alberta & Amii Afaf Taïk, Université de Sherbrooke & Mila - Quebec AI Institute Gaelle Patricia Talotsing, McGill University - Calcul Quebec Liaison: Sophia Abraham Previous Next

Past Mentors Here we highlight Past Mentors of WiML Sharmita Dey Postdoctoral Researcher at ETH Zurich Read More Love Allen Chijioke Ahakonye Senior Researcher at Kumoh National Institute of Technology Read More Sandhya Prabhakaran Applied Research Scientist at Moffitt Cancer Center, Tampa, Florida Read More Clarissa Guevara Gomez Professor at Tec de Monterrey Read More Sidhika Balachandar PhD Student at UC Berkeley Read More

Board of Directors Established in 2009, the goals of the Board of Directors are to: (i) facilitate long-term activities, such as multi-year funding grants; (ii) ensure the continuity of the workshop across years; (iii) organize activities such as a mentorship network and additional activities unrelated to the workshop. Current board members are listed below. Tatjana Chavdarova, PhD WiML President Read More Alessandra Tosi, PhD WiML Vice President of Programs Read More Michela Benedetti WiML Director Read More Luisa Cutillo, PhD WiML Director Read More Tiffany Ding WiML Director Read More Giulia Clerici, PhD WiML Director Read More Kairan Zhao WiML Director Read More Man Lou, PhD WiML Director Read More Natasa Tagasovska, PhD WiML Secretary Read More Arushi GK Majha, PhD WiML Treasurer Read More Eda Okur WiML Director Read More Laya Rafiee Sevyeri, PhD WiML Director Read More Shweta Khushu WiML Director Read More Claire Vernade, PhD WiML Director Read More Yolanne Lee WiML Director Read More Sophia Abraham, PhD WiML Director Read More Mandana Samiei WiML Vice President of Events Read More Erin Grant, PhD WiML Director Read More Judy Hanwen Shen WiML Director Read More Elizabeth Healey, PhD WiML Director Read More Nikita Saxena WiML Director Read More Irene Ballester WiML Director Read More Kimberly Ferguson-Walter, PhD WiML Director Read More Amy Zhang, PhD WiML Director Read More

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

All events WiML Workshop @ NeurIPS 2023 New Orleans, Louisiana December 11, 2023 8:00 am - 4:30 pm 18th Women in Machine Learning Workshop (WiML 2023) — the workshop is co-located with NeurIPS on Monday, December 11th, 2023. For more information or to register, please visit the event’s website here. Previous Next

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

< Back WiML Social @ ICLR 2026 Rio de Janeiro Previous Next

< Back WiML Breakfast @ AAAI 2016 Phoenix, Arizona WiML is co-hosting a breakfast at AAAI 2016 in Phoenix, Arizona, “Breakfast with Champions: A Women’s Mentoring Event”. Previous Next

< Back Sarah Aerni, PhD WiML Director (2021-2023) Visit my Profile

All events WiML Partner Event: Women in ML&AI @Cambridge Event with IBM Research Cambridge, Massachusetts October 4, 2018 03:00 pm — 06:00 pm WiML is excited to announce a new initiative by WiML Partner IBM Research: a Women in ML and AI community for the Boston-Cambridge area. Starting with this inaugural event during IBM AI Research Week 2018, IBM Research will begin hosting events for Women in ML and AI 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, opportunities to present their own research, and find mentors, role models and colleagues. Join the kickoff event this Thurs 10/4. Speakers and activities include: – Talks by Sasha Mojsilović (IBM Fellow, IBM Research AI) and Katherine Gorman (Talking Machines) on AI for social good and how to present your research. – Panel “Next Steps and Great Leaps for AI and Us” with AI/ML experts from academia and industry: Jennifer Dy (Northeastern), Yiling Chen (Harvard), Vivienne Sze (MIT), Eni Mustafaraj (Wellesley), Janet Slifka (Janet Slifka), Kate Saenko (Boston U), Tina Eliassi-Rad (Northeastern), Sravana Reddy (Spotify) – Mentoring Roundtables: Actively engage with AI/ML researchers and engineers on a range of technical and career-related topics. When: Thursday, October 4, 2018, 3pm-6pm Where: IBM Research Cambridge, 75 Binney St, First Floor Auditorium, Cambridge Event details: https://ibm.co/2RiTPXQ Registration: The event is open and free but registration is required at https://www.eventbrite.com/e/women-in-machine-learning-and-ai-cambridge-workshop-registration-50360270926 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), Amanda Papp (IBM), Ehimwenma Nosakhare (MIT). IBM Research is a WiML Platinum Partner. 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