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Message preview	Hi there, You are invited to a Zoom webinar. When: Apr 12, 2021 03:30 PM Pacific Time (US and Canada) Topic: The Accuracy, Fairness, and Limits of Machine Learning in Criminal Justice Register in advance for this webinar: https://ucsb.zoom.us/webinar/register/WN_jVQr_U18TJ63KqX5CK5PTg Or an H.323/SIP room system: H.323: 162.255.37.11 (US West) 162.255.36.11 (US East) 221.122.88.195 (China) 115.114.131.7 (India Mumbai) 115.114.115.7 (India Hyderabad) 213.19.144.110 (Amsterdam Netherlands) 213.244.140.110 (Germany) 103.122.166.55 (Australia Sydney) 103.122.167.55 (Australia Melbourne) 209.9.211.110 (Hong Kong SAR) 64.211.144.160 (Brazil) 69.174.57.160 (Canada Toronto) 65.39.152.160 (Canada Vancouver) 207.226.132.110 (Japan Tokyo) 149.137.24.110 (Japan Osaka) Meeting ID: 821 2179 0464 SIP: 82121790464@zoomcrc.com After registering, you will receive a confirmation email containing information about joining the webinar. ---------- Webinar Speakers Hany Farid (Professor @UC Berkeley) Hany Farid is a Professor at the University of California, Berkeley with a joint appointment in Electrical Engineering & Computer Sciences and the School of Information. His research focuses on digital forensics, forensic science, misinformation, image analysis, and human perception. He received his undergraduate degree in Computer Science and Applied Mathematics from the University of Rochester in 1989, and his Ph.D. in Computer Science from the University of Pennsylvania in 1997. Following a two-year post-doctoral fellowship in Brain and Cognitive Sciences at MIT, he joined the faculty at Dartmouth College in 1999 where he remained until 2019. He is the recipient of an Alfred P. Sloan Fellowship, a John Simon Guggenheim Fellowship, and is a Fellow of the National Academy of Inventors. Sharad Goel (Professor @Stanford) Sharad Goel is an assistant professor at Stanford University in the Department of Management Science & Engineering, with courtesy appointments in Computer Science, Sociology, and the Law School. He's the founder and faculty director of the Stanford Computational Policy Lab, a group that develops technology to tackle pressing issues in criminal justice, education, voting rights, and beyond. In his research, Sharad looks at public policy through the lens of computer science, bringing a new, computational perspective to a diverse range of contemporary social issues, including policing practices, electoral integrity, online privacy, and media bias. Before joining the Stanford faculty, Sharad completed a Ph.D. in applied mathematics at Cornell University, and worked as a senior researcher at Microsoft.

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