I am an Assistant Professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University. I am also affiliated with these other divisions of the university:
Until the summer of 2024, I was a postdoctoral associate in the Department of Computer Science at Yale University, hosted by Dan Spielman. Before that, in the spring of 2021, I received my PhD in Mathematics from the Courant Institute of Mathematical Sciences at New York University, advised by Afonso Bandeira (now at ETH Zurich) and G‌érard Ben Arous.
In the fall of 2024, I will be teaching a new graduate course on Random Matrix Theory in Data Science and Statistics. Stop by if you are interested! I am also looking for motivated PhD students to work with me. If you are already in the department, attending the above course is a good way to see if we have similar interests. Otherwise, apply to our PhD program and mention my name in your application. Unfortunately, I will not be able to respond to inquiries from students who have not yet been admitted to Johns Hopkins.
Some of my current research interests include:
- computationally-hard regimes in optimization and statistical problems
- average-case analysis of convex relaxations of combinatorial optimization
- random and pseudorandom matrix theory
- the nascent theory of random tensors
- convex optimization in proof assistants and experimental mathematics
- discrepancy theory and its algorithmic applications
Some upcoming events I will be attending or speaking at include:
- Nov 18: Georgia Tech Algorithms and Randomness Center (ARC) Colloquium (Georgia Tech)
- Dec 9–Dec 13: American Institute of Mathematics Workshop on Low-Degree Polynomial Methods in Average-Case Complexity (Caltech)
- Jun 8–Jun 13: BIRS Workshop on Frontiers in Combinatorics and Theoretical Computer Science (Hangzhou, China)
- Jun 30–Jul 3: INFORMS Applied Probability Society Conference 2025 (Georgia Tech)
You can reach me at kunisky [at] jhu.edu, or in person in Office N438 in the Wyman Park Building.