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 interest centers around information theory, both in its theoretical development and its applications, which include and are not limited to:

• Neural network compression for more efficient storage and/or faster inference.

• Learned image compression for lower bit rates and higher perceptual quality.

• Generative models as compressors through information-theoretic techniques. 

• Algebraic methods in coding theory for data communication and storage.

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!