I am an independent AI researcher working on architectures for better reasoning, efficiency, memory, and continual learning. My background spans economics, computer science, and mathematics. I studied at Tsinghua University and Duke University. Outside research, I lift and play video games.
Research overview
At a high level, my current research areas are:
- New architectures for improved efficiency and inductive biases
- Memory, continual learning, and reinforcement learning
- Approaches inspired by symbolic methods
I approach research with:
- Ideation and experimentation as complements
- Simplicity as a prior in both research and engineering
- Ideas drawn across disciplines
I am currently building
Iter Labs (iter as in journey in latin and iter() in python), an early-stage independent research organization.
Selected works
Two intuitions for Graph Machine (2), one algorithmic and one biological.
Blog
GM-1: Whether giving Transformers explicit and dynamically updatable edges can improve relational reasoning on Sudoku.
Paper