Hi, I am Wenjie!

I’m a first-year Ph.D. student in Neural Computation at Carnegie Mellon University, where I’m fortunate to work with Jessica Cantlon, Leila Wehbe, and Yonatan Bisk.

My research explores how symbol-like behaviors emerge and are represented in both biological and artificial neural networks. I’m especially drawn to questions around compositionality, abstraction, and how we learn and represent complex concepts.

Before starting my Ph.D., I was an Assistant Research Scientist at NYU, collaborating with Brenden Lake and Moira Dillon. Before that, I worked with Guangyu Robert Yang at MIT. I earned my M.S. in Computer Science from NYU and my B.A. in Mathematics and Philosophy from Washington University in St. Louis.

Outside of research, I’m passionate about the philosophy of mind and language—and when I’m not thinking about brains or machines, you can probably find me dancing Tango.

Always happy to connect with curious minds—feel free to reach out!

Concept · Representation · Compositionality · Deep Learning · Cognitive Science

Publications

Li, Wenjie, Shannon C. Yasuda, Moira Rose Dillon, and Brenden Lake. “An Infant-Cognition Inspired Machine Benchmark for Identifying Agency, Affiliation, Belief, and Intention.” In Proceedings of the Annual Meeting of the Cognitive Science Society, vol. 46. 2024.

Yasuda, Shannon, Wenjie Li, Deisy Martinez, Brenden M. Lake, and Moira R. Dillon. “15‐Month‐Olds’ Understanding of Imitation in Social and Instrumental Contexts.” Infancy 30, no. 1 (2025): e70002.

Li, Wenjie, and Yao Li. “Entropy, mutual information, and systematic measures of structured spiking neural networks.” Journal of Theoretical Biology 501 (2020): 110310.