Pinyuan Feng


Hi! I am currently a PhD student at the Zuckerman Mind Brain Behavior Institute at Columbia University, working with Prof. Niko Kriegeskorte. My research aims to translate insights from cognitive science and neuroscience into advances in AI, and to use AI as a tool for deepening our understanding of human intelligence.


Previously, I completed my Master of Science in Computer Science at Brown University and my Bachelor of Science in Artificial Intelligence at the University of Nottingham. I also spent a wonderful year as a Machine Learning Engineer Intern at NIO Inc.


I had the privilege of working with Prof. Thomas Serre and Prof. Drew Linsley at Brown, Prof. Steve Benford and Prof. Eugene Ch'ng at Nottingham, as well as Prof. Ching-Yao Chan and Dr. Yu-Ke Li at Berkeley DeepDrive.


Columbia Brown Nottingham Berkeley NIO

2026

Paper Interpretable Visual Decoding was accepted by ICLR 2026.

2025

Paper Better AI ≠ Better Bio Model was accepted by Trends in Cognitive Sciences.

Presented Interpretable Visual Decoding at NeurIPS 2025 BrainBodyFM Workshop.

Paper Adversarial Alignment was accepted by ICLR 2025 Re-Align Workshop.

My new academic website is live!

2024

Started my PhD at Columbia University.

2022

Started my MS at Brown University.

2021

Started my internship at NIO Inc.

Completed my Bachelor's degree at the University of Nottingham.

Graduated with First Class Honours and received the High Achievers Award.

. . .

My current research spans three main directions:

  • multimodal brain encoding and decoding
  • human-inspired self-supervised representation learning
  • representational similarity analysis between humans and machines

For a more up-to-date list of my work, please visit my Google Scholar.

I am a member of GrowAI community with a shared interest in growing AI to learn like a child.


I am a member of Neurotech X Columbia to advancing neurotechnology and AI.