"If you can't explain it simply, then you don't understand it well enough" - Albert Einstein
I am a PhD candidate in Electrical and Computer Engineering at Carnegie Mellon University. I am advised by Prof. Pulkit Grover. Prior to joining CMU, I graduated from IIT Kharagpur with a B.Tech. in Electronics and Electrical Communication. My undergraduate thesis was advised by Prof. Arijit De. During my undergraduate studies, I received the Best Undergraduate Thesis Award and the HONDA Young Engineer and Scientist Award.
I have also been a summer research intern at the IBM TJ Watson Research Center, where I was mentored by Gauri Joshi, Parijat Dube, Priya Nagpurkar and Soumyadip Ghosh.
The goal of my research is to design strategies for reliable computation using unreliable components prone to errors, faults, straggling delays etc. and derive fundamental limits to compare their performance. In my research, I have advanced upon ideas in information and coding theory, probability theory, performance analysis and optimization that provide insights into improving Distributed Machine Learning, Cloud Computing and High Performance Computing.
- Information Theory, Coding theory
- Machine Learning, Optimization
- Fault Tolerance for Large-Scale Parallel Computing
- Distributed Systems
- Performance Modeling
- Fair Machine Learning