Faculty Recruiting Support CICS

Peter Haas

Peter Haas Photo
Doctoral Program Director & Professor
204 CS Building
(413) 545-3140


Information management; mining, analytics, and exploration of massive data; probabilistic database systems; machine learning; modeling and computer simulation of complex stochastic systems.


Professor Haas' research centers on the application of techniques from applied probability and statistics to the design, performance analysis, and control of systems for information management, mining, integration, exploration, learning, and optimization. Other projects focus on techniques for modeling, simulation, design, and control of complex systems, especially discrete-event stochastic systems, as well as on the interface of simulation and information management. 


Ph.D., Operations Research, Stanford University (1986), M.S., Statistics, Stanford University (1984), M.S., Environmental Engineering, Stanford University (1979), S.B. Magna cum Laude, Engineering and Applied Physics, Harvard University (1978). Prior to joining UMass, Professor Haas spent 30 years at IBM Research, most recently in the role of Principal Research Staff Member. For the past 20 years he has also been a Consulting Professor in the Department of Management Science and Engineering at Stanford University, teaching and pursuing research on simulation of discrete-event stochastic systems. During 1992-93, he was an Honorary Fellow at the Center for the Mathematical Sciences at the University of Wisconsin, Madison, and has also been an Assistant Professor of Decision and Information Sciences at Santa Clara University (1985-87) and a Staff Scientist at Radian Corporation (1979-81).

Activities & Awards

Professor Haas is a Fellow of both ACM and INFORMS and a member of Sigma Xi. He served as Vice President and then President of the INFORMS Simulation Society (I-Sim) from 2008-2012, and he joined the Winter SImulation Conference Board in 2020. He serves on the editorial boards of ACM Transactions on Modeling and Computer Simulation (where he has co-edited three special issues), and ACM Transactions on Databases. He served on the editorial board of Operations Research from 1995 to 2018, and from 2007 to 2013 he was an Associate Editor for the VLDB Journal, where he co-edited a special issue on Uncertain and Probabilistic Databases. He was Program Chair for the 2019 Winter Simulation Conference, and has been co-chair of the 2011 and 2017 I-Sim Research Workshops. He has served on numerous program committees for conferences including SIGMOD, VLDB, PODS, SSDBM, and KDD. Within IBM, he has been granted over 30 patents and was designated a Master Inventor in 2012, as well as earning an Outstanding Technical Achievement Award, Outstanding Innovation Award, and Research Division Award for his contributions to IBM products including the IBM DB2 Database System. He is a six-time winner of the IBM Research Division Pat Goldberg Memorial Paper Award, an IBM record. Other awards include a 2019 and a 2016 SIGMOD Research Highlights Award, 2018 EDBT Best Paper Award, 2016 VLDB Best Paper Award, 2011 NIPS Big Learning Workshop Best Paper Award, 2007 SIGMOD Test-of-Time Award, and the I-Sim 2003 Outstanding Publication Award for his monograph on stochastic Petri nets. His work has twice been recognized in the Research Highlights section of Communications of the ACM.