Moises Goldszmidt
PRINCIPAL RESEARCHER
Microsoft Research Silicon Valley
e-mail: moises "at" microsoft.com
phone: (650) 693-3398
mail: 1065 La Avenida, Mountain View, CA, 94043
I am fascinated with automatically building actionable models from data. I use methods and algorithms from machine learning, graphical models, Bayesian networks, statistics, decision analysis, pattern recognition, and artificial intelligence. Besides making contributions to Bayesian Networks learning and classifiers, I have applied these extensively to the automated diagnosis, forecasting, and control of performance problems, faults, and power in large networked computer systems. I have recently shifted some of my attention to modeling certain aspects of social networks.
I joined the MSR Silicon Valley Lab in early 2006. Prior to Microsoft, I was at Hewlett-Packard Labs, SRI International, and Rockwell Science Center, and I was a principal scientist with Peakstone Corporation (start-up). I earned my PhD degree in Computer Science from the University of California in Los Angeles (1992).
Full publication list (pre-Microsoft)
Publications
- John D. Davis, Suzanne Rivoire, Moises Goldszmidt, and Ehsan K. Ardestani, CHAOS: Composable Highly Accurate OS-based Power Models, in International Symposium on Workload Characterization, IEEE, November 2012
- John D. Davis, Suzanne Rivoire, and Moises Goldszmidt, Star-Cap: Cluster Power Management Using Software-Only Models, no. MSR-TR-2012-107, October 2012
- John D. Davis, Suzanne Rivoire, Moises Goldszmidt, and Ehsan K. Ardestani, Including Variability in Large-Scale Cluster Power Models, in Computer Architecture Letters, IEEE Computer Society, November 2011
- John D. Davis, Suzanne Rivoire, Moises Goldszmidt, and Ehsan K. Ardestani, No Hardware Required: Building and Validating Composable Highly Accurate OS-based Power Models, no. MSR-TR-2011-89, July 2011
- Dawn B. Woodard and Moises Goldszmidt, Online Model-Based Clustering for Crisis Identification in Distributed Computing, in Journal of the American Statistical Association, American Statistical Association, March 2011
- John D. Davis, Suzanne Rivoire, Moise Goldszmidt, and Ehsan K. Ardestani, Accounting for Variability in Large-Scale Cluster Power Models, in 2nd Workshop on Exascale Evaluation and Research Techniques, Held in Conjunction with ASPLOS 2011, Association for Computing Machinery, Inc., March 2011
- Mark Gabel, Junfeng Yang, Yuan Yu, Moises Goldszmidt, and Zhendong Su, Scalable and Systematic Detection of Buggy Inconsistencies, in ACM International Conference on Systems, Programming, Languages, and Applications: Software for Humanity, OOPSLA Research Papers Track (SPLASH/OOPSLA), October 2010
- Peter Bodik, Moises Goldszmidt, Armando Fox, Dawn B. Woodard, and Hans Andersen, Fingerprinting the datacenter: automated classification of performance crises, in EuroSys, 2010
- Moises Goldszmidt, Mihai Budiu, Yue Zhang, and Michael Pechuk, Toward Automatic Policy Refinement in Repair Services for Large Distributed Systems, in The 3rd ACM SIGOPS International Workshop on Large Scale Distributed Systems and Middleware, 17 September 2009
- Dawn B. Woodard and Moises Goldszmidt, Model-Based Clustering for Online Crisis Identification in Distributed Computing, no. MSR-TR-2009-131, September 2009
- Peter Bodik, Moises Goldszmidt, Armando Fox, and Hans Andersen, Fingerprinting the datacenter: Automated classification of performance crises, no. MSR-TR-2009-122, 5 July 2009
- Gabriela Cretu, Mihai Budiu, and Moises Goldszmidt, Hunting for problems with Artemis, in USENIX Workshop on the Analysis of System Logs (WASL), USENIX, December 2008
- Peter Bodik, Moises Goldszmidt, and Armando Fox, HiLighter: Automatically Building Robust Signatures of Performance Behavior for Small- and Large-Scale Systems, in Usenix Workshop on Tackling Computer Systems Problems with Machine Learning Techniques, USENIX, December 2008
- Aleksander Simma, Moises Goldszmidt, John MacCormick, Paul Barham, Richard Black, Rebecca Isaacs, and Richard Mortier, CT-NOR: Representing and reasoning about events in continuous time, in International Conference on Uncertainty in Artificial Intelligence (UAI), Helsinki, Finland, July 2008
- Paul Barham, Richard Black, Moises Goldszmidt, Rebecca Isaacs, John MacCormick, Richard Mortier, and Aleksandr Simma, Constellation: automated discovery of service and host dependencies in networked systems, no. MSR-TR-2008-67, April 2008
- Yinglian Xie, Fang Yu, Kannan Achan, Eliot Gillum, Moisés Goldszmidt, and Ted Wobber, How Dynamic are IP Addresses, in Proceedings of the ACM SIGCOMM Conference, Association for Computing Machinery, Inc., Kyoto, Japan, August 2007
- Moises Goldszmidt, Making Life Better One Large System at a Time: Challenges for UAI Research, in Conference on Uncertainty in Artificial Intelligence (UAI 2007), Vancouver, BC, Canada, July 2007
- Paramvir Bahl, Paul Barham, Richard Black, Ranveer Chandra, Moises Goldszmidt, Rebecca Isaacs, Srikanth Kandula, Lun Li, John MacCormick, David A. Maltz, Richard Mortier, Mike Wawrzoniak, and Ming Zhang, Discovering Dependencies for Network Management, in Workshop on Hot Topics in Networks (HotNets-V), Association for Computing Machinery, Inc., Irvine, California, November 2006
- Emre Kıcıman, Dave Maltz, John Platt, and Moises Goldszmidt, Mining Web Logs to Debug Distant Connectivity Problems, in ACM SIGCOMM Workshop on Mining Network Data (MineNet-06), Association for Computing Machinery, Inc., 15 September 2006
- Emre Kıcıman, Dave Maltz, Moises Goldszmidt, and John Platt, Mining Web Logs to Debug Distant Connectivity Problems, in ACM SIGCOMM Workshop on Mining Network Data (MineNet-06), Association for Computing Machinery, Inc., Pisa, Italy, September 2006
