👋 Hello, I am a PhD student in Electrical Engineering and Computer Sciences at UC Berkeley. I study how data-driven AI and mechanistic models can advance our understanding of neural computation and enable safer bidirectional brain-computer interfaces. My work is supported by the NSF Graduate Research Fellowship Program (GRFP).

My research interests in brain-computer interfaces center on:

1. Data-driven AI models for learning neural representations and latent inference
2. Mechanistic modeling for interpretable neural population dynamics and computation
3. Closed-loop neurostimulation and control for targeted plasticity, network reorganization, and sensorimotor BCI

More broadly, I am interested in neural engineering for basic science and ideas at the intersection of neuroscience, AI, and the philosophy of mind. I write about these topics on my personal website.

• 1st year PhD student in EECS at UC Berkeley (Fall 2026)
• NSF Graduate Research Fellow
• B.S. in Electrical and Computer Engineering with a minor in Philosophy, The University of Texas at Austin (2026, Honors)
• Undergraduate research: Wang Lab and Fenno Lab
• Research interests: Brain-computer interfaces | Neural population dynamics | Closed-loop neurostimulation | Neural engineering for basic science | Neuro/AI ethics
• Selected Projects Can Be Found:

• Email: tonychae01@berkeley.edu