Postdoctoral researcher · UC San Diego Incoming faculty · School of Artificial Intelligence and Data Science, USTC · Fall 2026
I'm a physicist working at the crossroads of machine learning, dynamical systems, and autonomous research. My recent focus is building LLM agents that do science end-to-end — proposing hypotheses, running experiments, and writing up their findings.
Autonomous research. Physics for AI. AI for physics.
Agents publishing to agents. Failure as a first-class artifact. Experiments fully reproducible. Humans observe.
Research, today, is a human bottleneck. Ideas wait on attention; attention waits on careers; careers wait on venues that select for narrative over substance. We are squeezing 21st-century volumes of inquiry through a 20th-century pipe.
I think a second track is now possible — one operated end-to-end by autonomous LLM agents, in agent-native formats. Hypotheses framed as structured proposals. Experiments expressed as deterministic, containerized runs. Papers written in a form other agents can ingest and extend. A venue whose currency is provenance rather than prestige. My current work is laying the scientific and computational foundations for that track.
Treating discovery itself as a meta-optimization problem. Building agents that frame problems, run experiments, and write up their findings — with full provenance, full reproducibility, and a publication venue of their own.
Memcomputing, thermal neuristor networks, neuromorphic devices in novel materials. Harnessing collective dynamics in nonlinear systems to compute — faster, more energy-efficient, and biologically plausible.
Transformer quantum states for many-body problems. Graph neural networks for dynamical-systems modelling and control. Toward large quantum models: a substrate that lets us simulate, optimize, and characterize quantum matter at scale.
As I build my group at the School of Artificial Intelligence and Data Science (人工智能与数据科学学院), USTC, I want to hear from interested students broadly. The common thread: people who want to work at the intersection of physics, machine learning, and autonomous research systems.
Backgrounds in physics, applied math, computer science, or ML are all welcome — curiosity and strong programming matter more than a particular CV. More on the join page →