Kaiyan Zhang (张开颜)

I’m currently serving as the CTO of Frontis.AI, where I work on agent self-evolution, recursive self-improvement, and AI for AI. I earned my Ph.D. (2026) from the Department of Electronic Engineering, Tsinghua University, under the guidance of Professor Bowen Zhou. Before that, I earned B.S. (2020) and M.S. (2022) degrees in Computer Science and Technology from the Harbin Institute of Technology (HIT), where I was supervised by Weinan Zhang and Ting Liu in the HIT-SCIR lab.

We are hiring interns! If you are passionate about agent self-evolution, recursive self-improvement, and AI for AI, feel free to reach out. We publish papers and release open-source work.

My mission is to build AI that improves itself — shifting from human-supervised training toward agents that learn from their own experience and recursively bootstrap stronger successors (the ExpertAGI vision). This pursuit runs along two intertwined threads.

The first is the learning machinery for self-improvement: scalable and test-time reinforcement learning, multi-agent training, and reward modeling that let models supervise and improve other models — work like TTRL, SSRL, and MARTI, surveyed in our overview of RL for large reasoning models. The second is putting self-improving agents to work in high-value settings such as AI for AI — charted in our survey on self- to meta-evolution — alongside rigorous benchmarks like NatureBench and EnterpriseClawBench that keep our claims of capability honest.