Karl Sigman uses probability theory, random process theory, and simulation theory to model and analyze systems in which randomness is inherent, such as in telecommunications systems, queueing systems, inventory systems, and insurance risk businesses. This is known as “stochastic modeling”. He is also interested in the theory itself.
Sigman in particular is interested more recently in developing probabilistic simulation algorithms for producing random objects with exact precision, so that numerical estimates of quantities of interest can be obtained with very high accuracy. Blockchain technology and bitcoin is yet another recent interest.
Sigman received a BA in pure mathematics from the University of California, Santa Cruz in 1980, and then an MA (1983) in mathematics and an MS (1984) and PhD (1986) in industrial engineering and operations research, all from the University of California, Berkeley. He is a recipient of an NSF Presidential Young Investigator Award, and twice a recipient of The Distinguished Faculty Teaching Award from Columbia’s School of Engineering and Applied Sciences. He is the current Director of Columbia University’s Center for Applied Probability.
