His first project focuses on the study of the theory and algorithms for solving nonlinear constrained optimization problems in discrete, continuous, or mixed spaces. Based on a new necessary and sufficient condition for characterizing constrained local optima and by exploiting the localities of constraints in these problems, his team has developed new algorithms for solving large-scale application problems in temporal planning, satisfiability, and nonlinear programming that are too large for other solvers.

His second project aims at developing new protocols and coding methods for concealing losses that occur during real-time transmissions of multimedia data (voice, speech, images, and video) over unreliable IP networks, such as the Internet and wireless networks. Since video and audio transmissions may tolerate some degrees of loss, his team focuses on studying trade-offs among the design of codecs for compressing data, protocols for scheduling transmissions and feedbacks, and reconstruction schemes for recovering lost data.