For at least two thousand years, voting has been used as one of the most effective ways to aggregate people’s ordinal preferences. In the last 50 years, the rapid development of Computer Science has revolutionize every aspect of the world, including social choice (voting). This motivates us to study (1) conceptually, how computational thinking changes the traditional theory of voting, and (2) methodologically, how to better use voting for preference/information aggregation with the help of Computer Science.

In this talk, I will briefly discuss two research directions, one for each question asked above. The first focuses on investigating how computational thinking affects the game-theoretic aspects of voting. I will discuss the rationale and possibility of using computational complexity to protect voting from a type of strategic behavior of the voters, called manipulation. The second studies a voting setting called Combinatorial Voting, where the set of alternatives is exponentially large and has a combinatorial structure. I will focus on the design and evaluation of novel mechanisms for combinatorial voting that balance computational efficiency and the expressivity of the voting language, in light of some recent developments in Artificial Intelligence.

Short bio: Lirong Xia is a postdoctoral fellow at the Center for Research on Computation and Society at Harvard University. He got a Ph.D. in Computer Science in 2011 and an M.A. in Economics in 2010, both from Duke University. His research focuses on the intersection of computer science and microeconomics, in particular computational social choice, game theory, mechanism design, and prediction markets.