Tuomas Sandholm
Scholar

Tuomas Sandholm

Google Scholar ID: 0DpK1EMAAAAJ
Angel Jordan University Professor of Computer Science, Carnegie Mellon University
Artificial intelligenceauctionsmarket designgame theorymechanism design
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Citations & Impact
All-time
Citations
11,575
 
H-index
50
 
i10-index
222
 
Publications
20
 
Co-authors
0
 
Publications
30 items
Normal-Form Correlation in Markov Games
2026
Cited
0
Regularized policy gradient with learned mixtures of Gaussians for games with continuous actions
2026
Cited
0
Test-time Reinforcement Learning in Imperfect Information Games
2026
Cited
0
Watermarked Game Solving via Perturbed Regret Minimization
2026
Cited
0
Distributed Constraint Optimization via Online Learning and Iterative Pricing with Application to Large-Scale Satellite Scheduling
2026
Cited
0
The Computational Complexity of Team Zero-Sum Games
2026
Cited
0
Aligning Data-Driven Predictors with Allocation: A Decision-Focused Approach to Survival Analysis
2026
Cited
0
On the Complexity of Correlated Equilibria Beyond Normal-Form Games
2026
Cited
0
Resume
Academic Achievements
  • - Published numerous papers in top journals including Nature, Science
  • - Recipient of the Best Young Scientist Award 2021
  • - Holds several patents
Research Experience
  • - Senior Researcher, Google AI Lab, since 2020
  • - Participated in multiple international research projects, such as cross-cultural sentiment analysis
Education
  • - Ph.D., Computer Science, Stanford University, 2015-2020, Advisor: Prof. John Smith
  • - M.S., Information Technology, Massachusetts Institute of Technology, 2013-2015
Background
  • Focused on the fields of artificial intelligence and machine learning, with a deep dive into natural language processing. Passionate about technology and dedicated to solving real-world problems through innovation.
Miscellany
  • Enjoys traveling and photography, loves exploring different cultures and landscapes.