BIOGRAPHY

Peter Haas received an M.S. in Statistics and Ph.D. in Operations Research from Stanford University in 1984 and 1986, respectively, and joined IBM Almaden Research Center in 1987, where he remained until 2017, rising to the level of Principal Research Staff Member. During 1992-93 he spent a sabbatical year at the University of Wisconsin-Madison, where he was an Honorary Fellow at the Center for the Mathematical Sciences. He was also a Consulting Professor in the Department of Management Science and Engineering at Stanford University from 1998 to 2017, where he conducted joint research and taught a graduate course on computer simulation.

At IBM, his ideas were incorporated into products including IBM's DB2 database system and Apache SystemML. He received an IBM Outstanding Technical Achievement Award in 2003 for his work on sampling and mining in databases, a Research Division Award in 2005 for his work on learning optimizers, and an Outstanding Innovation Award in 2015 for his work on algorithms for massive scale matrix factorization. Peter is a six-time winner of the IBM Research Division's Pat Goldberg Memorial Best Paper Award in Computer Science, Electrical Engineering and Mathematics. In 2012 he was designated an IBM Master Inventor, and has received a number of IBM Invention Achievement Awards for patents filed and granted, including a Supplemental Patent Award (for distinguished patents).

He has been active professionally in the Computer Science community, and has been an ACM Fellow since 2013. He serves on the editorial board of ACM Transactions on Database Systems and was an Associate Editor for The VLDB Journal from 2007 to 2013. He also served as a Guest Editor for a special issue of the VLDB Journal on Uncertain and Probabilistic Databases. He has served on the program committees for ACM SIGMOD, VLDB, PODS, ICDE, and KDD, among others, and is currently serving on the VLDB Awards Committee. In 1999, his paper on interactive query processing earned him runner up for Best Paper at ACM SIGMOD, and he was a keynote speaker at the 11th International Conference on Scientific and Statistical Database Management (SSDBM 1999). His paper on maximum-entropy methods (VLDB 2005) and on incremental sample maintenance (VLDB 2006) were both selected as among the top VLDB papers for their respective years, with extended versions appearing in VLDB Journal. In 2007, Peter received the ACM SIGMOD Test of Time Award for his 1997 paper, Online Aggregation, coauthored with Joe Hellerstein and Helen Wang. In 2009, his work on distinct-value estimation under multiset operations was selected to appear in the "Research Highlights" section of Communications of the ACM. In 2011 he won a Best Paper Honorable Mention for his "Data is Dead" paper in the Challenges and Visions Track at VLDB 2011, as well as a Best Paper Award at the 2011 NIPS Big Learning Workshop for his work on matrix factorization over massive data. More recently, he won Best Paper awards at VLDB 2016, for his work on matrix compression for scalable machine learning, and at EDBT 2018, for his work on time-biased sampling for managing machine learning models. He received SIGMOD Research Highlights awards in 2016 and 2018 for both of these papers. His work on stochastic package queries for in-database optimization under uncertainty and on the SuDocu prototype for automatic document summarization by example won the Best Demo Award and Best Demo Runner-Up Award, respectively, at VLDB 2020.

He has also been active in the Operations Research community, and has been an INFORMS Fellow since 2016. He served as President of the INFORMS Simulation Society (I-Sim) from 2010 to 2012, and was Co-Chair of the 2011 INFORMS Simulation Society Research Workshop. He was also Co-Chair of the 2017 INFORMS Simulation Society Research Workshop and was Program Chair for the 2019 Winter Simulation Conference. He has served on the editorial board of ACM Transactions on Modeling and Computer Simulation (TOMACS) since 2004. He has served as Guest Editor of two TOMACS special issues, one on Simulation in Complex Service Systems and one in honor of Donald Iglehart, and is currently serving as Guest Editor for a third ACM TOMACS special issue on model-data ecosystems. He also served on the editorial board of Operations Research (Simulation Area) from 1995--2018. He received the 2003 Outstanding Publication Award from the INFORMS College on Simulation (now the INFORMS Simulation Society) for his book on stochastic Petri nets, and his work on generative neural networks for simulation input modeling received a Best Paper Runner-Up Award at WSC 2020. He has served on program committees for PNPM, WSC, and other conferences, and organized tracks and sessions at the INFORMS Annual Meeting.

He is the author of over 140 conference publications, journal articles, and books, and has been awarded over 30 patents.

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