(T) I was kindly invited to attend the first “ACM-IMS Interdisciplinary Summit on the Foundations of Data Science” yesterday at the Palace Hotel in San Francisco. The summit organized by the Association for Computing Machinery (ACM) and the Institute of Mathematical Statistics (IMS) focused on what could be next for data science.
Following is the program:
Computing and statistics underpin the rapid emergence of data science as a pivotal academic discipline.
- Jeffrey Dean, Google, “Deep Learning for Tackling Real-World Problems”
- Emmanuel Candès, Stanford University, “Making the Black Box Effective: What Statistics Can Offer”
- Daphne Koller, insitro, Stanford University, “Machine Learning: A New Approach to Drug Discovery”
Panel 1: Deep Learning, Reinforcement Learning, and Role of Methods in Data Science
- Shirley Ho, Flatiron Institute
- Sham Kakade, University of Washington
- Manuela Veloso, J. P. Morgan, Carnegie Mellon University
Panel 2: Robustness and Stability in Data Science
- Aleksander Madry, Massachusetts Institute of Technology
- Xiao-Li Meng, Harvard University
- Richard J. Samworth, University of Cambridge, Alan Turing Institute
- Bin Yu, University of California, Berkeley
Panel 3: Fairness and Ethics in Data Science
- Alexandra Chouldechova, Carnegie Mellon University
- Kristian Lum, HRDAG (Human Rights Data Analysis Group)
Final Session: Future of Data Science
- Michael I. Jordan, University of California, Berkeley
- Adrian Smith, Alan Turing Institute
Following is the live stream
Note: The picture above is Tulips at Filoli in Woodside.
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