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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 Workshop 2013 Lake Tahoe, Nevada December 9, 2013 08:00 am — 06:00 pm The 8th annual Women in Machine Learning workshop was colocated with NIPS 2013 in Lake Tahoe, Nevada in December 2013. The workshop website is no longer maintained. The organizers were: Jennifer Healey, Katie Kinnaird, Zornitsa Kozareva, Talieh S. Tabatabaei, Sonia Todorova. 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 Breakfast @ ICML 2013 Atlanta, Georgia June 18, 2013 07:00 am — 08:30 am WiML is hosting a breakfast at ICML 2013 in Atlanta, Georgia. The event features brief talks by, and directed discussion with, fellow women in machine learning. The invited speaker is Corinna Cortes. Date: Tuesday, June 18, 2013, 7am-8.30amVenue: Atlanta, GeorgiaEvent details: https://icml.cc/2013/index.html%3Fp=757.htmlRegistration : http://tinyurl.com/wiml-icml-2013 If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org SPONSORS 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

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 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

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 4th WiML Mentorship Program for Job Seekers: Panel on Applying to Jobs in Machine Learning Virtual November 18, 2024 9:00 am - 10:00 am This event, part of the WiML’s 2024-2025 Mentorship Program on the theme of Industry Jobs Applications, takes place 9-10am PT in Zoom. Mentors and mentees of the 2024-2025 Mentorship Program are invited to attend. Panelists: Dr. Kaoutar El Maghraoui (IBM Research), Jaya Shankar (Nvidia), Catherine Breslin (Kingfisher Labs) Moderator: Anoush Najarian (MathWorks) We will cover: Overview on career pathways in Machine Learning and AI Key tips and advice to apply to jobs in the industry sector, including improving your CV and writing a cover letter Building your skills and tips on the emerging trends in Machine Learning Building your personal network Q&A session to answer participant questions Previous Next

All events WiML Workshop 2016 Barcelona, Spain December 5, 2016 08:00 am — 05:00 pm The 11th annual Women in Machine Learning workshop will be colocated with NIPS 2016 in Barcelona, Spain in December 2016. See the workshop website for details! The organizers are: Diana Cai, Deborah Hanus, Sarah Tan, Isabel Valera, and Rose Yu. The invited speakers are: Jennifer Chayes, Maya Gupta, Anima Anandkumar, and Suchi Saria, with Tamara Broderick and Sinead Williamson giving remarks on WiML updates. Recorded talks can be found at this link . Previous Next

All events WiML Workshop @ NeurIPS 2024 Vancouver, Canada December 10, 2024 19th Women in Machine Learning Workshop (WiML 2024) — the workshop is co-located with NeurIPS on Tuesday, December 10th, 2024. For more information or to register, please visit the event’s website here. 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 WiML Luncheon @ COLT 2016 New York, New York June 24, 2016 12:30 pm — 02:30 pm WiML is hosting a luncheon at COLT 2016 in New York. The organizer is Kamalika Chaudhuri. Date: Friday, June 24, 2016, 12.30pm-2.30pm Venue: Columbia University, New York Event details: http://www.learningtheory.org/wp-content/uploads/handout.pdf Registration: Register during COLT registration ( www.learningtheory.org/colt2016/ ). 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