I'm Nick Feng, a PhD candidate at Department of Electrical and Computer Engineering in New York University, where my advisors are Professor Ivan Selesnick and Debra Laefer.

Broad-speaking, my research evolves around signal processing, optimization and convex analysis. Specific research problem I'm currently working on are:

1. Tight norm design for simultaneously structured models,

2. Non-convex sparse regularized linear inverse problem with a benign global optimization landscape.

However, I find myself more and more interested in statistical perspectives in signal processing. Classical convex relaxation techniques' inferior performance comes from mismatch between the regularization and underlying signal distribution. Resorting to non-convex formulation can partially solve the problem, but much has to be done. Another pathway is inferring the distribution on the flying, i.e. message passing. I'm also actively looking for collaborations! 

Outside academia, I volunteer as union steward at Graduate Student Organizing Committee. As we are preparing to negotiate and renew our union contract, we need more engagement and solidarity!

New York University, 2016
M.S., Electrical Engineering

Binghamton University, 2014
M.B.A., Finance

Binghamton University, 2013
B.S., Electrical Engineering

Research Centers, Labs, and Groups