Scholar
Shengyi Huang
Google Scholar ID: kl9YcpEAAAAJ
Allen Institute for Artificial Intelligence
Artificial Intelligence
Reinforcement Learning
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Citations & Impact
All-time
Citations
3,778
H-index
18
i10-index
21
Publications
20
Co-authors
0
Contact
Email
costa.huang@outlook.com
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Publications
5 items
Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
2025
Cited
0
Generalizing Verifiable Instruction Following
2025
Cited
0
2 OLMo 2 Furious
2024
Cited
0
TÜLU 3: Pushing Frontiers in Open Language Model Post-Training
arXiv.org · 2024
Cited
5
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
arXiv.org · 2024
Cited
2
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)
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