SCS Seminar Talk: Steven Wu

Event Details
  • Date/Time:
    • Thursday March 12, 2020
      11:00 am - 12:00 pm
  • Location: KACB 1116W
  • Phone:
  • URL:
  • Email:
  • Fee(s):
    N/A
  • Extras:
Contact

Tess Malone, Communications Officer

tess.malone@cc.gatech.edu

Summaries

Summary Sentence: Machine Learning Meets Societal Values

Full Summary: No summary paragraph submitted.

Media
  • Steven Wu Steven Wu
    (image/png)

TITLE: Machine Learning Meets Societal Values

ABSTRACT:

The vast collection of detailed personal data has enabled machine learning to have a tremendous impact on society. Algorithms now provide predictions and insights that are used to make or inform consequential decisions on people. Concerns have been raised that our heavy reliance on personal data and machine learning might compromise people’s privacy, produce new forms of discrimination, and violate other kinds of social norms. My research seeks to address this emerging tension between machine learning and society by focusing on two interconnected questions: 1) how to make machine learning better aligned with societal values, especially privacy and fairness, and 2) how to make machine learning methods more reliable and robust in social and economic dynamics. In this talk, I will provide an overview of my research and highlight some of my recent work on fairness in machine learning and differentially private synthetic data generation.

BIO:

Steven Wu is an assistant professor of computer science and engineering at the University of Minnesota. His research interests are in algorithms and machine learning, with a focus on privacy-preserving data analysis, algorithmic fairness, and algorithmic economics. From 2017 to 2018, he was a post-doc researcher at Microsoft Research-New York City in the machine learning and algorithmic economics groups. In 2017, he received his Ph.D. in computer science under the supervision of Michael Kearns and Aaron Roth at the University of Pennsylvania, where his doctoral dissertation received Penn’s Morris and Dorothy Rubinoff Award for best thesis. His research is supported by an Amazon Research Award, a Facebook Research Award, a Mozilla research grant, a Google Faculty Research Award, a J.P. Morgan Research Faculty Award, and the National Science Foundation.

Additional Information

In Campus Calendar
No
Groups

College of Computing, School of Computer Science

Invited Audience
Faculty/Staff, Postdoc, Public, Graduate students, Undergraduate students
Categories
Seminar/Lecture/Colloquium
Keywords
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Status
  • Created By: Tess Malone
  • Workflow Status: Published
  • Created On: Feb 26, 2020 - 11:50pm
  • Last Updated: Feb 27, 2020 - 3:54pm