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Bob Price

Bob Price works on inference, tracking, learning, and planning applications for government and industry clients. He has developed technologies for inferring the strategic intent of military forces from low-level reports of individual military units in the field for the DARPA Deep Green Program. Bob developed algorithms for PARC client Dai Nippon Printing to learn behavior patterns of cell phone users from logs of their GPS traces and use these patterns together with background databases of local vendors to infer user preferences for activities. He has also worked in the area of model-based control on a system for improving the diagnostic information generated from automatically constructed plans; machine learning of rules to diagnose problems in printing engines from fault code sequences; and optimization of power loads to minimize power and cost and maximize utility.

Previously, Bob held a post-doctoral fellowship at the University of Alberta where he modeled the online purchasing behavior of consumers, worked on predictive models of web searching behavior and constructing recommendation sets with optimal diversity. At the University of Toronto, Bob worked on symbolic/relational approaches to planning under uncertainty. His thesis work developed methods to exploit observations of other agents to guide learning of an agent and exchange knowledge between heterogeneous representations. Bob continues to pursue a variety of projects involving extraction of structure from noisy data, computer support of human learning and decision making, and automatic planning under uncertainty. Bob earned his MSc in Computer Science at the University of Saskatchewan and Ph.D. in Computer Science from the University of British Columbia.


PARC publications

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Multi-source anomaly detection: using across-domain and across-time peer-group consistency checks

Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications(JoWUA)

6 June 2014


Continuous state estimation for heterogeneous Hadoop clusters

To be presented at the International Workshop on Principles of Diagnosis: DX-2013

19 August 2013

ThroughputScheduler: learning to schedule on heterogeneous Hadoop clusters

International Conference on Autonomic Computing (ICAC '13)

27 June 2013

Multi-domain information fusion for insider threat detection

2013 IEEE Workshop on Research for Insider Threat (WRIT)

24 May 2013


Reference image-independent fault detection in transportation camera systems for nighttime scenes

IEEE Conference on Intelligent Transportation Systems 2012

16 September 2012

Detection of scene obstructions and persistent view changes in transportation camera systems

IEEE Conference on Intelligent Transportation Systems 2012

16 September 2012

Modeling destructive group dynamics in on-line gaming communities

International Conference on Weblogs and Social Media (ICWSM)

5 June 2012

Proactive insider threat detection through graph learning and psychological context

IEEE Workshop on Research for Insider Threat (WRIT)

25 May 2012


Pervasive diagnosis

IEEE Transactions on Systems, Man and Cybernetics - A

September 2010



A unified information criterion for evaluating probe and test selection

International Conference on Prognostics and Health Management

6 October 2008

Heuristic search for target-value path problem

AAAI 2008 Search Workshop

13 July 2008

Scalable architecture for context-aware activity-detecting mobile recommendation systems

Winner - Best demo at ADAMUS Workshop at WoWMoM 2008

23 June 2008