PhD Candidate Profile: Vladimir Kobzar

Who are our PhD students? Where do they come from, what are they studying now, and where do they hope to go in the future? Find out more about one of our PhD candidates, Vladimir Kobzar!

Vladimir Kobzar

I am a Ph.D. candidate at the NYU Center for Data Science (CDS), where I am a member of the Math and Data Group. I earned my MS in Mathematics at the Courant Institute under the advisement of Professor Afonso Bandeira, as well as my JD and LLM from the NYU School of Law.

Before joining the CDS, I worked as a researcher at Argonne National Laboratory operated by he University of Chicago on the development of machine learning models for analysis of time-resolved X-ray scattering data. Before that, I served for several years as Executive Director at Goldman Sachs, where I advised on legal and regulatory aspects of transactions and other initiatives involving data and technology in growth markets.

In my current research, I use methods of optimization and probability to establish that recovering the position and orientation of an object from noisy observations can be done in a robust and efficient manner. This problem is central to various areas of science and technology, including cryo-electron microscopy, robotics, and computer and human vision.

At the CDS, I plan to continue working on the development of provably robust and computationally efficient algorithms at the intersection of mathematics and data science. I am also interested in designing a framework and methods for interpreting deep learning and other “black box” algorithms. These frameworks and methods can then be used to analyze, among other things, the legal and regulatory ramifications of such algorithms.