About Me

Salut! I’m Nand Chandravadia. I’m a neuromorph, musician, and 1st year CSE PhD student @ Georgia Tech (advised by Nabil Imam).

I work on topics in neuromorphic computing & machine learning. I am fortunate to be supported by the President’s Fellowship.

Previously, I received a Masters in Computer Science (Machine Learning Track) at Columbia University, where was a DREAM Computing Fellow. I also spent some time as a quantitative researcher @ Hilldale Research Capital, where I developed statistical machine learning algorithms.

Before that, I studied neuroscience at UCLA, where I worked on brain-computer interfaces with William Speier and Nader Pouratian. I won the UCLA Library Prize for Undergraduate Research, and was nominated for the Dean’s Prize for Excellence in Research in Science, Engineering, & Math.

Outside of academia, I enjoy composing algorithmic music, playing my guitar, playing poker, and tennis. Feel free to contact me, if we have mutual interests!

Education

• Ph.D., Computational Science and Engineering, Georgia Institute of Technology (2023-Present)
• M.Sc., Mathematics, Georgia Institute of Technology (2023-Present) (en route to Ph.D)
• M.Sc., Computer Science (Machine Learning Track), Columbia Univesity (2020-2023)
• B.S., Neuroscience, University of California, Los Angeles (2013-2017)
  • Thesis: Comparing System Performance of a P300 Speller Brain-Computer Interface using Different Stimulus Paradigms

Research Interests

I am deeply interested in the intersection of math, computer science, and neuroscience. More specifically, I am interested in utilizing the “algorithmic lens” (as referred by theoretical computer scientists) to study the brain (among many other topics). Ultimately, my goal is to discover neural algorithms, and implement them in neuromorphic hardware, realizing a computer that works like a brain.

I also like to think deeply about theoretical neuroscience, theoretical machine learning, and computational/applied math.