Fluid mechanics of blood can be well approximated by a mixture model of a Newtonian fluid and deformable particles representing the red blood cells. Experimental and theoretical evidence suggests that the deformation and ...

As modern applications of machine learning and data mining are forced to deal with ever more massive quantities of data, practitioners quickly run into difficulty with the scalability of even the most basic and fundamental ...

This thesis makes a number of contributions to the theory of approximation algorithm design for multi-agent systems. In particular, we focus on two research directions. The first direction is to generalize the classical ...

In this thesis, we study the power and limit of algorithms on various models, aiming at applications in distributed networks and databases. In distributed networks, graph algorithms are fundamental to many applications. ...

Analyzing massive-data sets and streams is computationally very challenging. Data sets in systems biology, network analysis and security use network abstraction to construct large-scale graphs. Graph algorithms such as ...

We design and analyze algorithms for the following two robot navigation problems: 1. TARGET SEARCH. Given a robot located at a point s in the plane, how will a robot navigate to a goal t in the presence of unknown obstacles ...