Notes/Class Projects

In compressive sensing, the measurement matrix is assumed to satisfy some conditions. These are usually stated using the notion of coherence or RIP. This brief note shows in detail how the two measures are related.

From June 1923, 2017, I participated in Mathematical Problems in Industry workshop held at New Jersey Institute of Technology. I was part of a team that worked on the mathematical modeling of the scheduling of advertisements during television shows. Under the excellent mentorship of Professor Peter Kramer, this was a very rewarding experience. The final report can be found here.

I was fortunate to take a graduate course “Introduction to Numerical Methods” from Prof. Steven Johnson at MIT. My final project for the class was Remez algorithm. Given a function \(f\), under certain condition, Remez algorithm gives a polynomial or rational function that “best” approximates it. The report here in detail discusses the Remez algorithm.
In Fall 2014, I took a graduate course in solid mechanics at Harvard where I learned a lot from very enjoyable lectures by Professor Vlassak. My final presentation was on HuWashizuDebeveque functional. This is a variational framework to derive the equations of linear elasticity. The presentation can be found here.
My first research experience was in the Nuclear Engineering Department at MIT. I learned a lot about research under my mentor Professor Michael Driscoll. The project was on assessing the effectiveness of a proposed fuel assembly for Sodium cooled fast reactors. The report can be found here.
Video
For the ESG X Program at MIT, I did an introductory lecture video, for a general audience, about the wave equation under Galilean transformation. The idea was to use ideas from multivariable class and motivate Lorentz transformation and special relativity. The video can be found here.