Prof. De’s research interests lie in computational complexity theory, analysis of Boolean functions and the interplay of these two areas with theoretical computer science. In analysis of Boolean functions, his main interest lies in the interaction of probability theory and Fourier analysis towards structural understanding of specific classes of Boolean functions (like halfspaces) and how such structural information can be helpful in the design of algorithms. In complexity theory, his main interest is in the area of pseudorandomness which seeks to understand the power of randomness in computation.
Prof. Kao studies the design, analysis and implementation of algorithms. His work spans a broad range of applications including bioinformatics, computational finance, electronic commerce, and nanotechnology. Kao’s most recent research includes work on DNA self-assembly, variants of the traveling salesman problem, and graph labeling problems. Kao heads the EECS Computing, Algorithms & Applications Division and is the editor-in-chief of .
- Randall Berry, EECS
- Dongning Guo, EECS
- Ehud Kalai, MEDS, Kellogg School
- Dave Morton, IEMS
- Jorge Nocedal, IEMS
- Ermin Wei, EECS