Hello! I'm Connor (Zishi) Ding

I am currently a second-year MS student in electrical engineering at Stanford University. Previously, I was at the University of California, Santa Barbara, where I earned my B.S. in Psychological & Brain Sciences and Mathematics. 

I am working on research projects related to data compression and diffusion models with Professor Tsachy Weissman after finding his course on information theory unexpectedly fascinating. Thus, my current research focuses on information theory, exploring both its theoretical foundations and diverse applications, including:

• Generative modeling of discrete data using information-theoretic approaches.

• Image compression leveraging implicit neural representations.

• Algebraic techniques in coding theory for efficient communication and storage.

• Statistical estimation for enhanced sampling and inference efficiency.

Before becoming an engineer, I was a neuroscientist (I still am to be fair). I am always grateful for my experience as an undergraduate researcher in Dr. Regina Lapate's LEAP Neuro Lab and Dr. Thomas Sprague's PCA Lab, where I became fascinated by the variety of ways that we study cognition and behavior. 

And yes, I am still interested in the mathematical basis behind the methods of neuroscience and better techniques for neural data acquisition, processing, and analysis, to which I hope one day I can apply my research in information theory and machine learning. Wouldn't it be cool to have a powerful ML model in an MRI scanner? 

Contact me at czsding@stanford.edu!