PARALLEL DATA LAB 

PDL People

Phillip B. Gibbons


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Office:
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Admin Phone:
GHC 7221
412-268-6354

412-268-5483
Mailing Address: School of Computer Science
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213-3891
Position: Professor
Projects: WEAD, Big Learning Systems, ISTC-CC, Hi-Spade


Bio:

Phil Gibbons is a Professor in the Computer Science Department and the Electrical & Computer Engineering Department at Carnegie Mellon University. He received his Ph.D. in Computer Science from the University of California at Berkeley in 1989. Gibbons was a researcher in the Mathematical Sciences Research Center at AT&T Bell Laboratories (1990-1996), the Information Sciences Research Center at Lucent Bell Laboratories (1996-2001), the Intel Research Pittsburgh Lablet (2001-2011), and the Intel Science and Technology Center for Cloud Computing (2011-2015). His research areas include big data, parallel computing, databases, cloud computing, sensor networks, distributed systems and computer architecture. Gibbons' publications span theory and systems, across a broad range of computer science and engineering (e.g., conference papers in ASPLOS, ATC, CCS, DSAA, EuroSys, HPCA, ICDM, ISCA, MICRO, NIPS, PACT, PODC, PPoPP, SoCC, SODA and SPAA since 2012).


Research Interests:

  • WEAD: Write-efficient algorithm design, 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.
  • Intel Science and Technology Center for Cloud Computing: A $15M+ research partnership among Intel, Carnegie Mellon, Georgia Tech, Princeton, UC Berkeley, and U. Washington.
  • Hi-Spade: A hierarchy-savvy approach to algorithm design and systems for emerging parallel hierarchies.