Ted Zadouri

I'm a third-year PhD student in Computer Science at Princeton University, advised by Tri Dao, and a research intern at Together AI. Previously, I was a researcher at Cohere, working with Ahmet Üstün and Sara Hooker on MoEs. Prior to that, I completed my M.S. in Computer Science at UCLA in 2022, where I was advised by Baharan Mirzasoleiman.

Research Interests

Automatic Differentiation
Efficient Inference
Hardware-Efficient Algorithms

Publications

FlashAttention-4: Algorithm and Kernel Pipelining Co-Design for Asymmetric Hardware Scaling Ted Zadouri^*, Markus Hoehnerbach^*, Jay Shah^*, Timmy Liu, Vijay Thakkar, Tri Dao MLSys 2026
Hardware-Efficient Attention for Fast Decoding Ted Zadouri, Hubert Strauss, Tri Dao COLM 2025
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning Ted Zadouri, Ahmet Ustun, Arash Ahmadian, Beyza Ermis, Acyr Locatelli, Sara Hooker ICLR 2024
High Probability Bounds for Stochastic Continuous Submodular Maximization Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman AISTATS 2023