Shengyi Huang
Scholar

Shengyi Huang

Google Scholar ID: kl9YcpEAAAAJ
Allen Institute for Artificial Intelligence
Artificial IntelligenceReinforcement Learning
Citations & Impact
All-time
Citations
3,778
 
H-index
18
 
i10-index
21
 
Publications
20
 
Co-authors
0
 
Resume (English only)
Research Experience
  • Works as a Machine Learning Engineer at Hugging Face.
  • Uses Deep Reinforcement Learning to train bots to play games autonomously.
  • Recent work focuses on scaling Reinforcement Learning to Real-time Strategy (RTS) games.
  • Developed CleanRL, a library to train agents for various games.
  • Created Gym-MicroRTS, a simulated game environment to experiment with RL algorithms.
  • Contributed to StreetTraffic, a server package to collect traffic data and plan optimal travel time.
  • Trained StarCraft II agents to learn mineral collection.
Education
  • Ph.D. in Computer Science from Drexel University, under the supervision of Santiago Ontañón, specializing in Reinforcement Learning.
Background
  • Machine Learning Engineer with a focus on Reinforcement Learning. Enjoys conducting research and performing cool experiments.
Miscellany
  • Personal interests include training bots to play volleyball through self-play and safely landing a shuttle on the lunar surface.
Co-authors
0 total
Co-authors: 0 (list not available)