Andre Wibisono is an Assistant Professor at Yale Universitys Department of Computer Science, with a secondary appointment in Statistics & Data Science. His research focuses on designing and analyzing algorithms for machine learning, specifically in optimization, sampling, and game theory. He earned his Ph. D. from UC Berkeley and his M. Eng. from MIT.
There is no publicly available information about Andres personal life, hobbies, or non-work-related activities. The available data focuses entirely on his academic and professional achievements in the field of computer science and machine learning.
He received an NSF CAREER Award to develop a new framework for algorithm design, a significant early-career achievement.
Andre Wibisono
Assistant Professor at Yale University
United States
Overview
Topics They Care About
Machine Learning Algorithms
His primary research interest is the design and analysis of algorithms for machine learning, with numerous publications on the topic.
Mathematical Optimization
A core part of his work involves creating novel optimization methods, highlighted in his highly cited paper, "A variational perspective on accelerated methods in optimization. "
Game Theory Dynamics
He explores problems in game theory and game dynamics as part of his academic research at Yale University.
Media Appearances
Andre has no verified media appearances
Work History
1-2021
Assistant Professor at Yale University
7-2018 - 1-2021
Postdoctoral Researcher at Georgia Institute of Technology
7-2016 - 6-2018
Postdoctoral Researcher at University of Wisconsin-Madison
5-2012 - 8-2012
Software Engineering Intern at Google
6-2008 - 8-2008
Summer Research Analyst at Bain Capital
Education
2010 - 2016
Doctor of Philosophy (Ph.D.) from University of California, Berkeley
2009 - 2010
MEng from Massachusetts Institute of Technology
More Information
Social Presence :
Prographics :
Exp : 9
Location : United States
Job Level : Junior
Designation : Assistant Professor at Yale University
