Tyler Griggs

Tyler Griggs

I am a third year PhD student in Computer Science in the UC Berkeley Sky Computing Lab advised by Ion Stoica and Matei Zaharia. Previously, I worked in Network Infrastructure at Google Cloud. Before that, I graduated from Harvard with a BA in Computer Science advised by James Mickens.

My research interests are in designing and building efficient systems, primarily for machine learning workloads. My current research focuses on systems for post-training, especially reinforcement learning. Along with several wonderful collaborators, I am a co-lead of the NovaSky team. Our work has been featured in The New York Times, The Wall Street Journal, and The Information.

Current Projects

SkyRL
SkyRL: A Modular Full-stack RL Library for LLMs GitHub stars
SkyRL is a modular, performant RL framework built for multi-turn agentic training, using a simple and flexible design that allows both high-performance execution and adaptation to a wide variety of training scenarios.
Train your agent now with SkyRL, and don't hesitate to reach out!
[GitHub] [Blog]
SkyThought
SkyThought: A repository to reproduce NovaSky's research GitHub stars
The SkyThought repository holds all code needed to reproduce all prior work of the NovaSky team, such as efficient reasoning, reinforcement learning, test-time scaling, and more. See all our work on our website.
[GitHub]

Prior Projects

Reasoning models can be effective without thinking
Reasoning models can be effective without thinking
Wenjie Ma, Jingxuan He, Charlie Snell, Tyler Griggs, Sewon Min, Matei Zaharia
arXiv preprint [Paper]
Structure not Content
LLMs Can Easily Learn to Reason from Demonstrations: Structure, not content, is what matters!
Dacheng Li*, Shiyi Cao*, Tyler Griggs*, Shu Liu*, Xiangxi Mo, Eric Tang, Sumanth Hegde, Kourosh Hakhamaneshi, Shishir G Patil, Matei Zaharia, Joseph E Gonzalez, Ion Stoica
arXiv preprint [Paper]
MoE-Lightning
MoE-Lightning: High-Throughput MoE Inference on Memory-constrained GPUs
Shiyi Cao, Shu Liu, Tyler Griggs, Peter Schafhalter, Xiaoxuan Liu, Ying Sheng, Joseph E Gonzalez, Matei Zaharia, Ion Stoica
ASPLOS 2025 [Paper]
SkyServe
SkyServe: Serving AI Models across Regions and Clouds with Spot Instances
Ziming Mao, Tian Xia, Zhanghao Wu, Wei-Lin Chiang, Tyler Griggs, Romil Bhardwaj, Zongheng Yang, Scott Shenker, Ion Stoica
EuroSys 2025 [Paper] [Code]
Mélange
Mélange: Cost Efficient Large Language Model Serving by Exploiting GPU Heterogeneity
Tyler Griggs, Xiaoxuan Liu, Jiaxiang Yu, Doyoung Kim, Wei-Lin Chiang, Alvin Cheung, Ion Stoica
arXiv preprint [Paper] [Code]