Women in Data Science (WiDS) aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. The inaugural 24-hour virtual WiDS Worldwide 2021 conference will feature excellent technical thought leaders in data science from academia, industry, non-profits, and government. WiDS Worldwide will cover a wide range of technology and application areas, from healthcare and agriculture to security and fintech, and from data ethics and democratization to reproducibility and robustness of algorithms. All genders are welcome and encouraged to attend.
Register for WiDS Worldwide 2021
WiDS Worldwide registrants get 24-hour access to the full conference including the main stage with WiDS Worldwide 2021 keynote addresses, technical talks, and panel discussions; in-platform chat throughout the broadcast, including the question-and-answer sessions; breakout sessions for smaller discussions; education track with workshops, tutorials, and meet-the-speaker sessions; one-on-one networking, and access to the in-platform expo, including recruiters from sponsor companies.
In addition to the main Stanford University conference, WiDS Worldwide regional events will feature regional speakers, content, and networking. WiDS regional events will be posted here as they are announced.
Mainstage Events via Livestream
For those who will not need access to the full conference or regional content, WiDS Worldwide 2021 main stage events (including keynote addresses, technical talks, and panel discussions) will also be available via live stream on Livestream/Vimeo, YouTube Live, and Facebook Live. To receive notifications about when we go live, with links, subscribe to the WiDS Worldwide newsletter.
Rediet Abebe is an Assistant Professor of Computer Science at the University of California, Berkeley, and a Junior Fellow (2019-22) at the Harvard Society of Fellows. Abebe holds a Ph.D. in computer science from Cornell University and graduate degrees in mathematics from Harvard University and the University of Cambridge. Her research is in artificial intelligence and algorithms, with a focus on equity and justice concerns. Abebe is a co-founder and co-organizer of the multi-institutional, interdisciplinary research initiative Mechanism Design for Social Good (MD4SG). Her dissertation, Designing Algorithms for Social Good, received the 2020 ACM SIGKDD Dissertation Award and an honorable mention for the ACM SIGEcom Dissertation Award for offering the foundations of this emerging research area. Abebe's work has informed policy and practice at the National Institute of Health (NIH) and the Ethiopian Ministry of Education. She has been honored in the MIT Technology Review's 35 Innovators Under 35 list as a pioneer and the Bloomberg 50 list as a one to watch. Her work has been featured in BBC, ELLE, Forbes, and Shondaland and presented at venues including the National Academy of Sciences, United Nations, and Museum of Modern Art. Abebe also co-founded Black in AI, a non-profit organization tackling representation and equity issues in AI. Her research is influenced by her upbringing in her hometown of Addis Ababa, Ethiopia.