Sep 23–26, 2019
Alex Beutel

Alex Beutel
Staff Research Scientist, Google Brain

Alex Beutel is a staff research scientist on the SIR team at Google Brain, leading a team working on ML fairness and researching neural recommendation and ML for systems. He earned a PhD from Carnegie Mellon University’s Computer Science Department and his BS from Duke University in computer science and physics. His PhD thesis on large-scale user behavior modeling, covering recommender systems, fraud detection, and scalable machine learning, was given the SIGKDD 2017 Doctoral Dissertation Award Runner-Up. He received the Best Paper Award at KDD 2016 and ACM GIS 2010, was a finalist for best paper in KDD 2014 and ASONAM 2012, and was awarded the Facebook Fellowship in 2013 and the NSF Graduate Research Fellowship in 2011. More details can be found at alexbeutel.com.

Sessions

1:15pm1:55pm Wednesday, September 25, 2019
Location: 1E 14
Secondary topics:  Ethics, Privacy and Security
Andrew Burt (Immuta), Brenda Leong (Future of Privacy Forum), David Florsek (IDEMIA NSS), Alex Beutel (Google Brain), Chris Wheeler (Mastercard)
Machine learning techniques are being deployed across almost every industry and sector. But this adoption comes with real, and oftentimes underestimated, privacy and security risks. Andrew Burt and Brenda Leong convene a panel of experts including David Florsek, Chris Wheeler, and Alex Beutel to detail real-life examples of when ML goes wrong, and the lessons they learned. Read more.

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