Phillip B. Gibbons Curriculum Vitae
[email protected] http://cs.cmu.edu/~gibbons/ July 2020 Research Interests Research areas include big data, parallel computing, databases, cloud computing, sensor networks, distributed systems, and computer architecture. My publications span theory and systems, across a broad range of computer science and engineering (e.g., conference papers in APoCS, ATC, ESA, EuroSys, HPCA, ICML, IPDPS, ISCA, MICRO, NeurIPS, NSDI, OSDI, PACT, SoCC, SODA, SOSP, SPAA and VLDB since 2015). Education • University of California at Berkeley, Berkeley, California, 1984{1989. Ph.D. in Computer Science. Dissertation advisor: Richard M. Karp. • Dartmouth College, Hanover, New Hampshire, 1979{1983. B.A. in Mathematics. Graduated summa cum laude and Phi Beta Kappa. Professional Experience • Carnegie Mellon University, Pittsburgh, Pennsylvania. Professor, Computer Science Department, 2015{present. Professor, Electrical and Computer Engineering Department, 2015{present. Principal Investigator (PI or co-PI) for the following research projects: { Prescriptive Memory: Razing the semantic wall between applications and computer systems with heterogeneous compute and memories. { Asymmetric Memory: Write-efficient algorithms and systems, for settings (such as emerging non- volatile memories) where writes are significantly more costly than reads. { Big Learning Systems: Mapping out and exploring the space of large-scale machine learning from a systems' perspective. Recent focus on geo-distributed learning over non-IID data. Adjunct Professor, Computer Science Department, 2003{2015. Adjunct Associate Professor, Computer Science Department, 2000{2003. Visiting Professor, Computer Science Department, 2000. • Intel Labs Pittsburgh, Pittsburgh, Pennsylvania. Principal Research Scientist, 2001{2015. Principal Investigator for the Intel Science and Technology Center for Cloud Computing { A $11.5M research partnership with Carnegie Mellon, Georgia Tech, Princeton, UC Berkeley, and U.