Research Interests

With recent advances in DNA computation, scientists are on the verge of developing smart molecules that can communicate, perform tasks, and control matter at the nano level. To reach this initiative, as computer scientists, we should provide the theoretical foundation needed through the abstract models of molecular computing. My work is focused on a better understanding of distributed systems that model these physical systems and capture their dynamics to help biological computation scientists achieve their goals. I am working on population protocols, an appropriate model for electronic computing scenarios such as sensor networks, and ''fast-mixing'' physical systems such as chemical reactions, gene regulatory networks, and animal populations. I've researched problems like leader election, majority and consensus, exact and approximate counting, and counting in dynamic networks in population protocols. In our papers, we use probabilistic and combinatorics techniques to design and analyze our distributed (randomized) algorithms.

Population protocols are a complete network of agents with no control over whom they will interact with; in particular, the agents communicate via a sequence of pairwise interactions among randomly chosen pairs of agents.