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< Back Caroline Weis, PhD WiML Director (2022-2026)

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< Back Claire Vernade, PhD WiML Director Visit my Profile

< Back Catherine Wah, PhD WiML Director (2022-2024) Visit my Profile

< Back Katherine M. Kinnaird, PhD WiML President (2016-2019), Director (2014-2015) Visit my Profile

< Back Katherine M. Kinnaird, PhD WiML President (2016-2019), Director (2014-2015)

< Back Savannah Thais, PhD WiML Director (2019-2021)

< Back Sharmita Dey Postdoctoral Researcher at ETH Zurich WiML Mentorship Program 2nd WiML Mentorship: PhD Applications, 2022–2023, 3rd WiML Mentorship: PhD Applications, 2023–2024 Sharmita Dey completed her Master’s degree at the Institute of Artificial Intelligence, TU Dresden, Germany. She conducted her master’s thesis on ""Generalized Decoding of Control Signals from Surface Electromyography Signals"" at the DLR Institute of Robotics and Mechatronics in Oberpfaffenhofen, Germany. Following this, she earned her Ph.D. degree from the Department of Computer Science, University of Göttingen, Germany, focusing on ""Learning-Based Biomimetic Strategies for Developing Control Schemes from Lower Extremity Rehabilitation Robotic Devices,"" for which she was awarded summa cum laude. During her Ph.D., she interned at NASA's Jet Propulsion Laboratory, contributing to projects enhancing ground robot traversability in challenging environments. In this role, she became a part of team CoSTAR taking part in the DARPA Subterranean Robotics Challenge 2021. She then held a postdoctoral position at the University of Göttingen, Germany, where her research focused on vision-based, label-efficient learning and object-centric models for understanding the interactions and dynamics of moving objects. Further, as a postdoc at the University of Göttingen, her research explored domain adaptation, multitask learning, multimodal learning, and learning from simulated interactions using world models, to enhance predictive and adaptive learning. Currently, at ETH Zurich, her research focuses on multimodal self-supervised learning methods for biosignals. She also serves as a reviewer for leading AI and robotics venues, including NeurIPS, ICLR, ICML, AISTATS, ICRA, and IROS. What was your favorite part about serving as a WiML Mentor? “Serving as a WiML mentor is deeply rewarding; I enjoy helping emerging researchers find their voice, navigate challenges, and grow in confidence. The exchange of ideas is mutual and inspiring, reminding me that inclusion fuels creativity, scientific depth, and lasting impact in AI” Previous Next

< Back Danielle Belgrave, PhD WiML Director (2019-2020, 2021-2024) Visit my Profile

17th Women in Machine Learning Workshop (WiML 2022) 17th Women in Machine Learning Workshop (WiML 2022) The Workshop is co-located with NeurIPS on Monday, November 28th, 2022 at the New Orleans Convention Center in Louisiana, USA. Speakers Logistics Program Call for Participation Committee FAQ Machine learning is one of the fastest growing areas of computer science research. Search engines, text mining, social media analytics, face recognition, DNA sequence analysis, speech and handwriting recognition, healthcare analytics are just some of the applications in which machine learning is routinely used. In spite of the wide reach of machine learning and the variety of theory and applications, it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models. The annual Women in Machine Learning Un-Workshop is the flagship event in un-conference style of Women in Machine Learning , primarily intended to foster active participant engagement in the program. This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia and learn from each other. Underrepresented minorities and undergraduates interested in machine learning research are encouraged to attend. We welcome all genders; however, any formal presentations, i.e. talks and posters, are given by women. We strive to create an atmosphere in which participants feel comfortable to engage in technical and career-related conversations. Now in its 4th year, the 2023 un-workshop is co-located with IC ML . Besides this annual un-workshop, Women in Machine Learning also organizes annual workshop at NeurIPS, events such as lunch or social at the AISTATS or AAAI conferences, maintains a public directory of women active in ML, profiles the research of women in ML, and maintains a list of resources for women working in ML. All participants are required to abide by the WiML Code of Conduct . I'm a paragraph. Click here to add your own text and edit me. It's easy. Invited Speakers Location Type of registration required to attend PROGRAM PANELISTS BREAKOUT SESSIONS COFFEE MEET & MINGLE SOCIAL Program Monday, November 28, 2022 [ in-person ] ( Time in CT) Morning Session 7:30 am - 8:30 am Registration & Breakfast 8:30 am - 8:45 am Opening Remarks - Konstantina Palla (Senior Program Chair) 8:45 am - 9:00 am D&I Chair remarks - Danielle Belgrave 9:00 am - 9:10 am Contributed talk ( Tejaswi Kasarla ) - "Maximum Class Separation as Inductive Bias in One Matrix" 9:10 am - 9:20 am Contributed talk ( Taiwo Kolajo ) - "Pre-processing of Social Media Feeds based on Integrated Local Knowledge Base" 9:20 am - 9:55 am Invited talk - Alice Oh - " The importance of multiple languages and multiple cultures in NLP research " 9:55 am - 10:10 am Coffee break 10:10 am - 10:25 am WiML Board Remarks - Jessica Schrouff 10:25 am - 11:00 am Invited talk - Raesetje Sefala - " Constructing visual datasets to answer research questions " 11:00 am - 11:10 am Contributed talk ( Pascale Gourdeau ) - "When are Local Queries Useful for Robust Learning?" 11:10 am - 11:20 am Contributed talk ( Annie S Chen ) - "You Only Live Once: Single-Life Reinforcement Learning" 11:20 am - 1:20 pm Mentorship roundtables & Lunch - Mentors: Adam Roberts, Stephanie Hyland, Bianca Zadrozny, Sima Behpour, Mercy Asiedu, Franziska Boenisch, Eleni Triantafillou, Isabela Albuquerque, Yisong Yue, Amy Zhang, Zelda Mariet, Tristan Naumann, Danielle Belgrave, Shakir Mohamed, Tong Sun, Gintare Karolina Dziugaite, Samy Bengio, Rianne van den Berg, Maja Rudolph, Luisa Cutillo, Ioana Bica, Clara Hu, Rosanne Liu, Jennifer Wei, Alice Oh, SueYeon Chung, Erin Grant, Sasha Luccioni, Michela Paganini, Mounia Lalmas-Roelke, Claire Vernade, Alekh Agarwal, Neema Mduma, Vinod Prabhakaran, Savannah Thais, Jonathan Frankle, Ce Zhang, Rose Yu, Jessica Schrouff, Bo Li, Katherine Heller, Ben Poole, Setareh Ariafar, Christina Pavlopoulou, Isabel Morlidge, Kavya Srinet, Cheng Zhang, Elise van der Pol, Diana Montanes, Lise Diagne, Le Yu, Megan Forrester. Afternoon Session 1:20 pm - 1:55 pm Invited talk - Bianca Zadrozny - " Machine Learning for Climate Risk " 1:55 pm - 2:05 pm Contributed talk ( Elizabeth Bondi-Kelly ) - "Human-AI Interaction in Selective Prediction Systems" 2:05 pm - 2:15 pm Contributed talk ( Gowthami Somepalli ) - "Investigating Reproducibility from the Decision Boundary Perspective." 2:15 pm - 2:35 pm Coffee break 2:35 pm - 3:10 pm Invited talk - Hima Lakkaraju - " A Brief History of Explainable AI: From Simple Rules to Large Pretrained Models " 3:10 pm - 4:10 pm Panel discussion 4:10 pm - 4:20 pm Closing Remarks 4:20 pm - 4:30 pm Poster setup 4:30 pm - 6:00 pm Joint Affinity Groups Poster Session Mentorship Roundtables AI and Creativity: Adam Roberts (Google Brain) Choosing between Academia and Industry: Stephanie Hyland (Microsoft Research) and Bianca Zadrozny (IBM Research) Continual Learning & Open-World Learning: Sima Behpour (Bosch) Founding and Funding Startups: Mercy Asiedu (Google) Gender-related challenges: Franziska Boenisch (Vector Institute) Generalization & Robustness: Eleni Triantafillou (Google Brain) and Isabela Albuquerque (DeepMind) Getting a job (academia): Yisong Yue (Caltech) and Amy Zhang (UT Austin) Getting a job (industry): Zelda Mariet (Google) Healthcare/clinical applications: Danielle Belgrave (DeepMind) and Tristan Naumann (Microsoft Research) Leadership: Shakir Mohamed (DeepMind) and Tong Sun (Adobe) Learning theory: Karolina Dziguaite (Google Brain) Life in industry research: Samy Bengio (Apple) and Rianne van den Berg (Microsoft Research) Life with kids: Maja Rudolph (BCAI) and Luisa Cutillo (University of Leeds) Mental health & surviving in grad school: Ioana Bica (DeepMind), Clara Hu (Google Brain), and Rosanne Liu (Google Brain) ML for Science: Jennifer Wei (Google) Natural language processing: Alice Oh (KAIST) Negotations in ML: Nicole Bannon (81cents) Neuroscience & cognitive science: Erin Grant (UCL), SueYeon Chung (NYU/Flatiron Institute), and Noga Zaslavsky Non-traditional paths in machine learning: Sasha Luccioni (HuggingFace) and Michela Paganini (DeepMind) Recommender systems: Mounia Lalmas-Roelke (Spotify) Reinforcement learning: Claire Vernade (DeepMind), Alekh Agarwal (Google), and Elise van der Pol (Microsoft Research) Seeking funding in academia: Neema Mduma (The Nelson Mandela African Institution of Science and Technology) Social science applications: Vinod Prabhakaran (Google Research), Savannah Thais (Columbia University), and Sarah Brown (University of Rhode Island) Systems and machine learning: Jonathan Frankle (Harvard University/MosaicML) and Ce Zhang (ETH Zurich) Time Series: Rose Yu (UCSD) Trustworthy machine learning: Jessica Schrouff (DeepMind), Bo Li (UIUC), and Katherine Heller (Google Research) Monday, December 5, 2022 [virtual](Time in ET) 9:30 am - 9:40 am Opening Remarks 9:40 am - 9:55 am Contributed talk ( Okechinyere J Achilonu ) - "Natural language processing for automated information extraction of cancer parameters from free-text pathology reports" 9:55 am - 10:10 am Contributed talk ( Paula Harder ) - "Physics-Constrained Deep Learning for Climate Downscaling" 10:10 am - 10:25 am Contributed talk ( Silvia Tulli ) - "Explanation-Guided Learning for Human-AI collaboration" 10:25 am - 10:40 am Contributed talk ( Mina Ghadimi Atigh ) - "Hyperbolic Image Segmentation" 10:40 am - 10:50 am Set up (for mentorship session) 10:50 am - 11:50 am Mentorship Panel (Discussion + Q&A) withJenn Wortman Vaughan (Microsoft Research),Colin Raffel (University of North Carolina)Kristen Grauman (University of Texas at Austin) 11:50 am - 12:00 pm Break 12:00 pm - 12:35 pm Sponsor Talks 2:00 pm - 4:00 pm Joint Affinity Groups Poster Session Call for Participation PLATINUM SPONSORS PLATINUM SPONSORS PLATINUM SPONSORS Committee ORGANIZERS WiML RECEPTION ORGANIZER ADVISORY SUPER VOLUNTEERS FAQs

< Back Michela Benedetti WiML Director Visit my Profile