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  • Linh Tran, PhD | WiML

    < Back Linh Tran, PhD WiML Director (2022-2023)

  • WiML Partner Event: Virtual Women in Science Fireside Chat with Amazon | WiML

    < Back WiML Partner Event: Virtual Women in Science Fireside Chat with Amazon Virtual WiML is excited to announce the Virtual Women in Science Fireside Chat by WiML Partner Amazon. Previous Next

  • WiML Luncheon @ COLT 2016 | WiML

    < Back WiML Luncheon @ COLT 2016 New York, New York WiML is hosting a luncheon at COLT 2016 in New York. The organizer is Kamalika Chaudhuri. Previous Next

  • WiML-CWS Event: Community-Driven Mentoring Event and Panel @ AISTATS 2021 | WiML

    All events WiML-CWS Event: Community-Driven Mentoring Event and Panel @ AISTATS 2021 Virtual April 13, 2021 12:30 pm - 2:00 pm WiML is excited to announce a joint event with the Caucus for Women in Statistics at AISTATS 2021. The event has two components: community-driven mentoring , and a panel . The event will be held on the Icebreaker.video platform on Tuesday, April 13, 2021, 12.30pm – 2pm PT. Event Format Agenda (all times approximate) 12:30 – 12:45pm PT – 1:1 mentor-mentee random pairings 12:45 – 1:10pm PT – Small group mentoring on time management tips and conducting research 1:10 – 1:45pm PT – Panel on publishing and reviewing 1:45 – 2pm PT – Small group debrief on panel What is community-driven mentoring? It means anyone can be a mentor on a topic of their expertise! Upon entering the Icebreaker link, you will be asked to indicate if you want to be a mentor or mentee. The Icebreaker platform will distribute mentors among groups as much as possible. There will be a series of mentoring sessions, both 1:1s and in small groups. Read more about the mentoring prompts below. Who can mentor? Mentoring topics will range from general life-work balance to general research questions, thus we encourage a larger number of participants, ranging from mid-PhD to senior levels, to participate as mentors. Mentors can be of any gender. What is the panel on? The panel, moderated by Sinead Williamson (University of Texas at Austin) with panelists Bin Yu (UC Berkeley), Tomi Mori (St. Jude Children’s Research Hospital), Po-Ling Loh (University of Cambridge), Jessica Kohlschmidt (Ohio State University), is on the topic of “Reviewing and Publishing”. The rapid growth of the machine learning and statistics community has made the reviewing process of peer-reviewed conferences more challenging. Besides sharing their experiences, panelists will discuss publishing venues in ML and Statistics, as well as take questions from the audience. Read more about the panelists below. Joining Instructions How to join: You can find the Icebreaker link on the AISTATS portal: https://virtual.aistats.org/virtual/2021/affinityworkshop/2033 (AISTATS registration required to access). Event limited to 200 participants. You’ll be asked to sign in to Google, and give Icebreaker permission to access your camera and microphone. Google Chrome browser recommended. Participant instructions: Whether you will participate as a mentor or mentee, 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 panel, you can type questions for the panelists in Icebreaker chat, so bring any questions on reviewing and publishing! See below for more information on Icebreaker. Questions? Email workshop@wimlworkshop.org or cws@cwstat.org . Note that this is a separate event from the AISTATS mentoring sessions . By joining the event, you agree to abide by the AISTATS Code of Conduct and WiML Code of Conduct . Icebreaker how-to guide and mentoring prompts Upon joining the platform, you will be given an option to join as either a “Mentee” or a “Mentor”. Select your preferred option, enter your full name, and click on “join event”. For each mentoring session, you can choose if you want to participate or wait for the next one. Panelists and Moderator bios Professor Bin Yu, UC Berkeley Bin Yu is Chancellor’s Distinguished Professor and Class of 1936 Second Chair in the departments of statistics and EECS at UC Berkeley. She leads the Yu Group which consists of 15-20 students and postdocs from Statistics and EECS. She was formally trained as a statistician, but her research extends beyond the realm of statistics. Together with her group, her work has leveraged new computational developments to solve important scientific problems by combining novel statistical machine learning approaches with the domain expertise of her many collaborators in neuroscience, genomics, and precision medicine. She and her team develop relevant theory to understand random forests and deep learning for insight into and guidance for practice. She is a member of the U.S. National Academy of Sciences and of the American Academy of Arts and Sciences. She is Past President of the Institute of Mathematical Statistics (IMS), Guggenheim Fellow, Tukey Memorial Lecturer of the Bernoulli Society, Rietz Lecturer of IMS, and a COPSS E. L. Scott prize winner. She is serving on the editorial board of Proceedings of National Academy of Sciences (PNAS) and the scientific advisory committee of the UK Turing Institute for Data Science and AI. Professor Tomi Mori, St. Jude Children’s Research Hospital Tomi Mori is a Member and Endowed Chair of the Department of Biostatistics at St. Jude Children’s Research Hospital in Memphis TN. She is an elected Fellow of the American Statistical Association and is currently President of the Caucus for Women in Statistics. Her statistical research interests include: designs of early phase clinical trial designs for drug combinations and precision oncology strategies, biomarker discovery and validation, predictive modeling, and risk stratification. Professor Po-Ling Loh, University of Cambridge Po-Ling Loh received her Ph.D. in Statistics from UC Berkeley in 2014. From 2014-2016, she was an Assistant Professor of Statistics at the University of Pennsylvania. From 2016-2018, she was an Assistant Professor of Electrical & Computer Engineering at UW-Madison, and from 2019-2020, she was an Associate Professor of Statistics at UW-Madison and a Visiting Associate Professor of Statistics at Columbia University. She began a position as a Lecturer in the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge in January 2021. Po-Ling’s current research interests include high-dimensional statistics, robustness, and differential privacy. She is a recipient of an NSF CAREER Award, an ARO Young Investigator Award, the IMS Tweedie and Bernoulli Society New Researcher Awards, and a Hertz Fellowship. Dr. Jessica Kohlschmidt, Ohio State University Comprehensive Cancer Center Jessica Kohlschmidt is a Ph.D. Biostatistician at the Clara D. Bloomfield Center for Leukemia Outcomes Research at The Ohio State University Comprehensive Cancer Center. Her research group looks retrospectively at patient data to try to determine what gene mutations and expression (or combinations) predict which patients will have better survival. Jessica also teaches business analytics for the Fisher College of Business at The Ohio State University. She is a long time officer of the Caucus for Women in Statistics (CWS), serving for 10 years as Secretary and in 2018 became the first Executive Director and currently oversees the operations of CWS. Jessica is currently serving on the committee for the International Year of Women in Statistics and Data Science (IYWSDS) of ISI. She is also actively involved with the American Statistical Association (ASA) and is serving as Treasurer for the ASA Survey Research Methods Section, as well as President of the ASA Columbus Chapter and as Chair of the ASA History of Statistics Interest Group. Professor Sinead Williamson, University of Texas at Austin Sinead Williamson is an Assistant Professor of Statistics at the University of Texas at Austin, in the IROM Department and the Division of Statistics and Scientific Computation. She obtained her Ph.D. from the Computational and Biological Learning group at the University of Cambridge and spent two years as a postdoc in the SAILING laboratory at Carnegie Mellon University. Previous Next

  • WiML Workshop 2008 | WiML

    All events WiML Workshop 2008 Vancouver, Canada December 8, 2008 08:00 am — 05:00 pm The 3rd annual Women in Machine Learning workshop was colocated with NIPS 2008 in Vancouver, Canada in December 2008. The workshop website is no longer maintained. The organizers were: Luiza Antonie, Anna Koop, and Jo-Anne Ting, with faculty advisor Joelle Pineau. The invited speakers were: Fei-Fei Li, Kristin Bennett, Daphne Koller, and Corinna Cortes. 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

  • WiCS AI Research Day @ SFU | WiML

    All events WiCS AI Research Day @ SFU SFU Burnaby Campus, Burnaby, British Columbia, Canada February 20, 2026 9 AM - 3:30 PM PST A one-day event for undergraduate students at SFU who are passionate about Artificial Intelligence (AI) and Machine Learning (ML). The initiative will support students in defining and improving personal AI projects, with access to mentorship during the event to ask questions and get help. The event aims to: Encourage hands-on learning and creativity in AI. Provide mentorship on ML concepts, project design, and research thinking. Connect students with academic and industry professionals. Celebrate student innovation and support future publication efforts. Key Highlights of WiCS AI Research Day: Expert Talks: Topics include Machine Learning (ML) areas such as Natural Language Processing (NLP), Computer Vision, Human-Computer Interaction (HCI), Robotics, and Speech, featuring experts like Dr. Angelica Lim and Dr. Marzena Karpinska. Student Panel: Opportunities to hear directly from students about their experiences, challenges, and advice in the tech field. Interactive Sessions: Participants can engage in project creation and pitch preparation, aiming to turn ideas into practical ML solutions. Networking: An opportunity to connect with peers and professionals in academia and industry. Previous Next

  • WiML Virtual Gathering @ COLT 2020 | WiML

    All events WiML Virtual Gathering @ COLT 2020 Virtual July 8, 2020 11:00 am — 12:00 pm WiML is hosting a virtual gathering at COLT 2020. The organizers are Claire Vernade and Ruth Urner. A panel discussion will be held on topics including career advice and mentoring. The panelists are: Alina Beygelzimer Alexandra Carpentier Kamalika Chaudhuri Sandra Zilles Date: July 8, 11am ET Registration: https://forms.gle/EecL5Nkj4yLGp3Xa8 SPONSORS -Platinum- -Diamond- Previous Next

  • WiML Luncheon @ CoRL 2019 | WiML

    All events WiML Luncheon @ CoRL 2019 Osaka, Japan November 1, 2019 12:00 pm — 01:30 pm WiML is hosting a luncheon at CoRL 2019 in Osaka, Japan to bring together women in machine learning from different research areas and across all stages of their careers to meet, find mentorship, and learn from each other. The invited speakers are Anca Dragan, Yukie Nagai, and Chelsea Finn. Date: Nov 1, 12-1:30pm Venue: Senri Hankyu Hotel Osaka Registration: https://www.eventbrite.com/e/wiml-at-corl-an-event-to-celebrate-the-women-in-the-corl-community-registration-77723345619 SPONSORS -Platinum- Previous Next

  • WiML Luncheon @ CoRL 2018 | WiML

    < Back WiML Luncheon @ CoRL 2018 Zurich, Switzerland WiML is hosting a luncheon at CoRL 2018 in Zurich, Switzerland. The organizer is Aude Billard. Previous Next

  • WiML Partner Event: New England Women in ML Event with IBM Research | WiML

    All events WiML Partner Event: New England Women in ML Event with IBM Research Cambridge, Massachusetts April 19, 2019 03:45 pm — 06:00 pm WiML is excited to announce an event by WiML Partner IBM Research 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, providing opportunities to present their own research, and connecting them to mentors, role models and colleagues. Join the event this Thurs 6/20. Speakers and activities include: – A talk by Tamara Broderick (Assistant Professor, MIT) on “Approximate Cross Validation for Large Data and High Dimensions”. – Reception immediately after the event. When: Thursday June 20, 2019, 4:00pm – 5:00pm with reception immediately after the event Where: IBM Research Cafe, 75 Binney St. Cambridge, MA 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), Kristen Severson (IBM Research). IBM Research is a WiML Platinum Partner. Previous Next

  • 3rd WiML Mentorship Program for PhD Applications: Panel on Research Statements | WiML

    All events 3rd WiML Mentorship Program for PhD Applications: Panel on Research Statements Virtual October 23, 2023 4:00 pm - 5:00 pm This event, part of the WiML’s 2023-2024 Mentorship Program on the theme of PhD applications, takes place 4-5pm UTC in Zoom. Mentors and mentees of the 2023-2024 Mentorship Program are invited to attend. The panel topic is on “How to write a research statement for Master’s & Ph.D applications in ML”. Panelists: Emma Pierson (Cornell Tech), Sinead Williamson (UT Austin) Moderator: Erin Grant (UC Berkeley) Previous Next

  • WiML Luncheon @ COLT 2025 | WiML

    < Back WiML Luncheon @ COLT 2025 lyon, France WiML is hosting a luncheon at COLT 2025 in Lyon, France. The event is meant to be a social and networking event for women and/or non-binary researchers in learning theory, as well as allies. Previous Next

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