My research is interdisciplinary. I like to branch out, learn new things, and jump on new problems.

I have written two independent Ph.D. dissertations and published papers being affiliated with departments of mathematics, physics, computer science, and civil engineering. According to Dyson's “birds-and-frogs” classification, I am a bird. I have done research in differential geometry, applied probability, and computational statistics with applications to integrable systems, rare event estimation, reliability engineering, quantitative finance, and network science while living in Moscow, Hong Kong, Los Angeles, Liverpool, Boston, and Pasadena.

Doing research is thinking about something that you don't understand. This is a very difficult and “unhappy business.” Why do I like it? There are three main reasons. The first is an immense satisfaction from those very rare eureka moments, when, after many failed attempts, you understand “how to put the two sticks together to reach the banana.” Second, I enjoy collaboration with my students and colleagues. The most important thing in collaboration – especially interdisciplinary collaboration – is to find a common language, which is often a nontrivial task. Finally, I like writing and explaining my thoughts. Doing this clearly and logically is a challenge, but I am trying my best and enjoying the process.

My current main research interest is network science. I am interested in network data analysis, network models, network dynamics, percolation and network resilience, dynamical processes on complex networks. As a special type of complex networks, I am particularly interested in course-prerequisite networks.

Network science is a fascinating interdisciplinary field, where discrete mathematics meets continuous, probability meets statistics, statistical physics meets computer science, and models meet data. For a great inspiring introduction to network science, watch the following three talks by Mark Newman, one of the fathers of the field, given at the Santa Fe Institute in 2010: Talk 1, Talk 2, and Talk 3.

To learn about my work in this field, check my papers on Planar Maximally Filtered Graphs [10], Network Reliability Problem [11], Geometric Preferential Attachment [12], Exponential Random Simplicial Complexes [13], Hamiltonian Dynamics of Complex Networks [14], Causality Networks [17], Navigability of Random Geometric Graphs [18], Visibility Graphs [20], Financial Networks [22], Critical Infrastructure Networks [C4], Random Hyperbolic Graphs [27], and Course-Prerequisite Networks [25].