Longbo Huang
Scholar

Longbo Huang

Google Scholar ID: g9d_K0sAAAAJ
Professor, IIIS, Tsinghua University, ACM Distinguished Scientist
Reinforcement Learning (RL)Deep RLMachine LearningStochastic NetworksPerformance Evaluation
Citations & Impact
All-time
Citations
4,651
 
H-index
34
 
i10-index
72
 
Publications
20
 
Co-authors
36
list available
Resume (English only)
Academic Achievements
  • ACM Distinguished Member, CCF Distinguished Member, IEEE Senior Member, IEEE ComSoc Distinguished Lecturer, and ACM Distinguished Speaker. Received the Tsinghua University Distinguished Teaching Award (良师益友) in 2014, and the ACM SIGMETRICS Rising Star Research Award in 2018. Paper “Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks” received the best paper award from ACM Sigmetrics 2025.
Research Experience
  • Was a visiting professor at Bell-labs France, Microsoft Research Asia, and CUHK, and a visiting scholar at the Laboratory for Information and Decision Systems (LIDS) @ MIT. Also, a long-term visiting scientist at the Simons Institute for the Theory of Computing at Berkeley in Fall 2016.
Education
  • Ph.D. from the EE department @ University of Southern California; Postdoctoral researcher in the EECS department @ UC Berkeley; B.E. from Sun Yat-sen University, Guangzhou, China; M.S. from Columbia University, New York City, both in EE.
Background
  • Research Interests: AI for Decisions, aiming to develop efficient, robust, and safe AI theory and algorithms for decision making and optimization. Professional field: Information Sciences.
Miscellany
  • Personal interests not mentioned