About Me

I am a computer scientist with expertise in many areas of data science, including ML, deep learning, multi-modal learning, and network science. I've recently obtained a PhD in computer science from Purdue University, where I was advised by Prof. Ananth Grama. In my thesis, I developed and applied tools from ML/data science to analyze biomedical images -- in particular, functional MRIs of brains. I bring a computer scientist's perspective to interesting problems in connectomics. My solutions are rooted in computationally sound methods with good performance guarantees.

More broadly, I'm interested in solutions for challenging problems by using clever models, and leveraging insights from different sub-areas of data science. To this end, I actively develop new methods, while leveraging the power of relevant existing work. A key emphasis in my work is to find the right balance between interpretability and performance.

I also have experience in healthcare, single-cell transcriptomics, rehabilitation robotics (in DLR/German Aerospace Center), and wireless networks (in the Indian Institute of Science).


Starting Fall '22, I will be an Assistant Professor in the EECS department at the University of Cincinnati. Please contact me if you're interested in my work!

UPDATES:

  • Accepted an offer for a tenure-track position (assistant professor) at the University of Cincinnati (Mar' 2022)

  • Defended my thesis

  • Paper accepted in ICIP 2021

  • Paper accepted in SIGMOD 2021

  • Paper accepted in Frontiers in Neuroscience [2021]

  • Paper accepted in IJCAI 2020