The SyFI Lab at the University of Washington builds efficient and resilient infrastructure for the future of AI. As applications grow more complex, we bridge the gap between next-gen models and heterogeneous hardware through cross-stack innovation, delivering scalable, open-source systems validated by industrial partners.
Our research targets three key areas:
Keisuke Kamahori, Shihang Li, Simon Peter, Baris Kasikci — (2026)
Keisuke Kamahori, Wei-Tzu Lee, Atindra Jha, Rohan Kadekodi, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci — (2026)
Aditya K Kamath, Arvind Krishnamurthy, Marco Canini, Simon Peter — European Conference on Computer Systems (EuroSys) (2026)
May 12, 2026
We present VibeServe, a multi-agent system that synthesizes a complete LLM serving runtime end-to-end, specialized to a user-specified model, hardware, and workload.January 31, 2026
January 2026 was a milestone month for the SyFI Lab, with six papers published across MLSys and ICLR—spanning inference, training, scheduling, retrieval, and model architecture.October 03, 2025
We present LLMc, an open-source tool to compress natural language using LLMs as the world's most reference-packed dictionary.May 15, 2026 Dimitrios Skarlatos — Carnegie Mellon University
May 8, 2026 Jialin Li — National University of Singapore
May 8, 2026 Jeff Mogul — Google