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< Back Sarah Poole, PhD WiML Director (2020-2022) Visit my Profile

< Back Allison Chaney, PhD WiML Secretary (2017-2018), Vice President of Research & Policy (2018-2019), Director (2016)

All events 5th WiML Mentorship Program for Post-Graduate Applications: Panel on navigating Master’s and PhD applications Online October 24, 2025 The 5th WiML Mentorship Program hosted its first panel discussion event , bringing together an engaged audience of women and non-binary individuals interested in pursuing research-oriented postgraduate degrees in Machine Learning and AI. The session focused on key aspects of navigating Master’s and PhD applications , with a rich and practical discussion that covered: Crafting an effective CV Preparing a compelling Statement of Purpose Approaching potential supervisors Requesting and managing recommendation letters An open Q&A session addressing participant concerns We were delighted to be joined by two outstanding panelists who generously shared their experiences and insights: Dr. Angelina Wang , Assistant Professor, Cornell Tech Dr. Simran Arora , Senior Research Scientist at Together AI and Assistant Professor at Caltech Moderator: Judy Shen, PhD student at Stanford University. This event marked an exciting start to our new mentorship series, aimed at supporting aspiring researchers as they navigate their academic journeys in ML and AI. We look forward to hosting more events that foster connection, guidance, and community across the WiML network. (edited) Previous Next

< Back Jenn Wortman Vaughan, PhD WiML Co-Founder, Director (2009-2012, 2014-2018)

All events WiML Workshop 2007 Orlando, Florida October 17, 2007 09:00 am — 05:40 pm The 2nd annual Women in Machine Learning workshop was colocated with Grace Hopper Celebration of Women in Computing 2007 in Orlando, Florida in October 2007. The workshop website is no longer maintained. The organizers were: Hila Becker and Bethany Leffler, with faculty advisor Joelle Pineau. The invited speakers were: Kiri Wagstaff, Marta Arias, Nina Mishra, and Sally Goldman. 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 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 The workshop website is no longer maintained.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

< Back Hewitt Tusiime WiML Director (2024)

All events WiML Symposium @ ICML 2025 Vancouver, Canada July 16, 2025 9:30 AM - 5:00 PM The Women in Machine Learning Symposium @ ICML 2025 is an inclusive, community-centered event that is happening on Wednesday, July 16th, in person as part of the ICML 2025 conference in Vancouver, Canada. The program features invited talks, a panel discussion, poster sessions, mentoring round tables, breakout Q&As, and community networking opportunities. Additional information can be found here . Previous Next

All events WiML Social @ ICLR 2023 Kigali, Rwanda May 3, 2023 3:00 pm - 5:00 pm Date: May 3, 2023 Time: 3:00-5:00pm Loc: Larder Terrace (in the Hotel of the conference center) The topic of the panel will be AI moving forward, leaving no one behind . We hope to get a conversation going regarding ChatGPT, international collaborations, copyright issues of foundational models etc. The program is: 3:00 pm - 3.45 pm Introduction and networking 3.45 pm - 4.30 pm panel discussion on “AI moving forward, leaving no one behind” 4.30 pm – 5:00 pm Networking roundtables Panelist Bios Panelist: Tegan Maharaj Tegan is an Assistant Professor in the Faculty of Information at the University of Toronto, an affiliate of the Vector Institute and Schwartz-Reisman Institute for Technology and Society, and a visiting researcher at the Centre for the Study of Existential Risk at Cambridge University. She is also a managing editor at the Journal of Machine Learning Research (JMLR), the top scholarly journal in machine learning, and co-founding member of Climate Change AI (CCAI), an organization which catalyzes impactful work applying machine learning to problems of climate change. Prior to joining the iSchool, Tegan did her Ph.D. at Mila and Polytechnique Montreal, where she was an NSERC and IVADO-awarded scholar with Chris Pal. Her recent research has two themes (1) Real-world generalization, learning theory, and practical auditing tools (e.g. unit tests, sandboxes) to empirically evaluate learning behavior or simulate deployment of an AI system (2) Deep representation learning & predictive methods in ecological dynamical systems for impact assessment, policy analysis, and risk mitigation, especially for climate and common-good problems. Panelist: Kathleen Siminyu Kathleen Siminyu is an AI Researcher focused on Natural Language Processing(NLP) for African Languages. She works at Mozilla Foundation as a Machine Learning Fellow to support the development of a Kiswahili Speech Recognition dataset and to build transcription models for end use cases in the agricultural and financial domains. In this role, she is keen to ensure the diversity of Kiswahili speakers, in terms of age, gender, accent and language variant/dialect, is catered for in the dataset and models created. She would welcome opportunities exploring the application of speech technologies in education. Kathleen is also currently part of a committee constituted by the African Union to develop an Artificial Intelligence continental strategy for Africa. Before joining Mozilla, Kathleen was Regional Coordinator of AI4D Africa , where she worked with ML and AI communities in Africa to run research programs. One of these, a fellowship for African language dataset creation, led to the creation of over 9 African language datasets. For this work, Kathleen was listed as one of the MIT Technology Review 35 Innovators under 35 for 2022 . She has vast experience as a community organiser having co-organised the Nairobi Women in Machine Learning and Data Science community for three years and she continues to organise as part of the committees of the Deep Learning Indaba and the Masakhane Research Foundation . Supervolunteer: Hewitt Tusiime Hewitt Tusiime is a research assistant at the Makerere Artificial Intelligence Research lab at Makerere University with a particular interest in data science for finance and AI governance and ethics. She graduated from Makerere University with a Bachelor of Science in Software Engineering. She has worked on several research projects related to the application of machine learning algorithms in agriculture, natural language processing, and finance. She also has extensive experience designing and developing protocols for system deployment, ensuring effectiveness, and a smooth user adoption process. She is passionate about the ethical and social implications of AI on different groups of people. She also oversees community engagement while working to achieve research project objectives and strengthen bonds of trust between communities and the project teams. Organiser: Caroline Weis Dr. Caroline Weis is currently an AI/ML Engineer at GSK.ai , working on clinical machine learning applications. Centered around multi-omics and multimodal clinical data, her projects leverage approaches from biomarker discovery, model interpretability and personalised healthcare. Caroline joined GSK.ai after obtaining a PhD in Machine Learning for Healthcare from ETH Zurich, where she developed early clinical machine learning applications for antimicrobial resistance prediction, through developing new kernel methods, adversarial domain adaptation and representation learning. Her research was elected for the Remarkable Outputs award of 2021 by the Swiss Institute of Bioinformatics. Prior to that, she has built an academic background bridging microbiology, biomathematics, and biophysics. She worked on protein X-ray scattering at Lawrence Berkeley National Laboratory and gained experience developing machine learning applications for screening images at Genedata in Basel. She holds an MSc in Biotechnology and a BSc in Integrated Life Sciences. Previous Next

< Back Allison Chaney, PhD WiML Secretary (2017-2018), Vice President of Research & Policy (2018-2019), Director (2016) Visit my Profile

< Back Bahare Fatemi, PhD WiML Director (2023-2024)

< Back Barbara Engelhardt, PhD WiML Director (2013-2016)