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< Back Sarah Tan, PhD WiML President Visit my Profile

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

< Back Jessica Montgomery WiML Vice President of Research & Policy (2020-2021), Director (2019-2020, 2021-2022)

All events WiML Virtual Workshop @ NeurIPS 2020 Virtual December 9, 2020 9:40 am - 2:30 pm The 15th annual Women in Machine Learning workshop will be virtually co-located with NeurIPS 2020 in December 2020. See the workshop website for details! The organizers are: Erin Grant, Xinyi Chen, Kristy Choi, Krystal Maughan, Judy Hanwen Shen, Xenia Miscouridou, Raquel Aoki, Belen Saldias, Mel Woghiren, Elizabeth Wood. 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 Savannah Thais, PhD WiML Director (2019-2021) Visit my Profile

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 4th WiML Mentorship Program for PhD Applications: Panel on Funding and Work-Life Balance Virtual October 23, 2024 9:00 am - 10:00 am This event, part of the WiML’s 2024-2025 Mentorship Program on the theme of PhD applications, takes place 9-10am PT in Zoom. Mentors and mentees of the 2024-2025 Mentorship Program are invited to attend. Panelists: Paul Pu Liang (MIT Media Lab), Serina Chang (UC Berkeley), Tim Dettmers (Allen Institute for Artificial Intelligence, Carnegie Mellon University) Moderator: Judy Shen (Stanford University) We will cover: How to find and reach out to professors you are interested in working with (PhD Admissions) Key tips and advice to apply to and access funding (scholarships, fellowship, salary etc) Overview on programs and resources (classes, health care, travel allowance etc) Q&A session to answer participant questions Previous Next