John Lehoczky received his Ph.D. in statistics from Stanford University in 1969. His main teaching and research interests involve the theory and application of stochastic processes to model the behavior of real applications. He has been published extensively in a variety of journals including Annals of Applied Probability, Management Science, and Real-Time Systems and he has served on the editorial staff of Management Science, IEEE Transactions on Computers, and Real Time Systems.
Over the last five years, Dr. Lehoczky has focused on two broad application areas: financial markets and real-time computer systems. In finance, he has been involved in the development of new simulation methodologies to price and hedge complex securities. More recently, he has been focusing on the estimation of parameters of stochastic differential equations and its application to term structure or asset price process models. His research in real-time computer systems involves collaboration with researchers at the CMU School of Computer Science, Software Engineering Institute, Electrical and Computer Engineering Department and the Department of Mathematical Sciences. Dr. Lehoczky is developing, jointly with Professor Steve Shreve, a new analytic methodology called real-time queuing theory, which predicts the ability of a queuing system to satisfy the timing requirements of the tasks, which use it. The theory is being implemented and tested on several pilot systems at CMU.