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

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All events WiML-CWS Social @ AISTATS 2022 Virtual March 29, 2022 6:00 pm - 7:00 pm Women in Machine Learning (WiML) and the Caucus for Women in Statistics (CWS) are excited to announce a 1-hour social event at AISTATS 2022 on Tuesday, 29 March, starting at 6 PM UTC. The event will start with a couple of icebreaker sessions to encourage networking among participants. In the main part of the event there will be a Q&A with WiML sponsors, WiML board members and CWS board members in an open format: participants are encouraged to come with questions on topics ranging from career advice, time-management, to conducting research topics. Event Format Agenda (all times approximate) 6:00 – 6:10 pm UTC – (10 min) Welcome and opening remarks 6:10 – 6:25 pm UTC – (15 min) small group discussions 6:25 – 6:55 pm UTC – (30 min) Q&A with WiML sponsors, WiML board members and CWS board members 6:55 – 7:00 pm UTC – (5 min) Closing remarks Joining Instructions How to join: You can find the Zoom link on the AISTATS portal: https://virtual.aistats.org/virtual/2022/affinity-event/3686 (AISTATS registration required to access). Event limited to 300 participants. Participant instructions: We suggest preparing one or two lines to describe your work and research, as well as any other topics you may want to discuss. During the Q&A, you can type-in or verbally ask questions for WiML board members and/or our sponsors, so bring any questions you may have! Questions? Email workshop@wimlworkshop.org . By joining the event, you agree to abide by the AISTATS Code of Conduct and WiML Code of Conduct . SPONSORS -Platinum- Previous Next

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