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Stanford Data Science Initiative Fall 2018 Retreat

Event Details:

Tuesday, November 13, 2018


Paul Brest Hall
555 Salvatierra Walk
Stanford, CA 94305
United States

Emerging Topics in Data Science for Business and Society

The Stanford Data Science Initiative (SDSI) 2018 Fall Retreat explores emerging topics in data science for business and Society. As the state of the art and practice of data science continues to advance at a rapid pace, today’s agenda presents a wide array of innovative technologies such as advanced analytics, security, understanding and preventing bias, and their application to fields ranging from healthcare to how people communicate. Stanford’s talented researchers work at the forefront of data intensive methodologies with a strong interdisciplinary nature. Stanford’s strong presence in many domains encourages the development of new approaches in a number of fields that benefit both academia and industry.


8:00 amBreakfast and Registration
9:00 amWelcome and Introductions
9:05 am

Vision for Data Science

Jure Leskovec
Associate Professor of Computer ScienceSDSI Affiliates Program Co-Director

9:15 am

Consumer Choice in Longitudinal Data: New Methods and Applications

Susan Athey
The Economics of Technology Professor, Stanford Graduate School of Business

9:45 am

Uncovering Security Weaknesses through Internet-Wide Scanning

Zakir Durumeric
Assistant Professor of Computer Science

10:15 am

Understanding Deep Learning

Tengyu Ma
Assistant Professor of Computer Science

10:45 amBreak
11:15 am

Finding and Reducing Human Biases in AI

James Zou
Assistant Professor of Biomedical Data Science

11:45 am

Using Past Technologies to Predict Future Communication

Elaine Treharne
Roberta Bowman Denning Professor of Humanities

12:15 pmLunch
1:15 pmWelcome back
1:20 pm

Data Science for Humans and Populations

Euan Ashley
Professor of Medicine

1:30 pm

Hardware Architectures for Software 2.0

Kunle Olukotun
Cadence Design Systems Professor Electrical Engineering and Computer Science

2:00 pm

The Artful Design of Technology

Ge Wang
Associate Professor of Music

2:45 pmBreak
3:00 pm

Almond: An Open User-Programmable Virtual Assistant

Monica Lam
Professor of Computer Science

3:30 pm

Mostly Exploration-Free Algorithms in Personalized Decision-Making

Mohsen Bayati
Associate Professor of Operations, Information and Technology

4:00 pm

The Good, the Bad, and the Challenging of Machine Learning for Networked Systems

Keith Winstein
Assistant Professor of Computer Science

4:30 pmPoster Preview Presentations
4:50 pmClosing Comments
4:55 pmPoster Viewing and reception
6:30 pmAdjourn

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