His research centers on tackling fundamental algorithmic problems that are motivated by real-world optimization. Most of his work is concerned with developing new ideas and tools for algorithmic graph theory, with a particular focus on approaching central questions in that area with a mix of combinatorial and linear-algebraic techniques. He is also interested in understanding uncertainty in the context of optimization – how to model it, and how to cope with its presence.