Computer Science Assistant
Resume:
Ole J. Mengshoel
Curriculum Vitae
Contact Carnegie Mellon University, Silicon Valley
NASA Ames Research Center
Mail Stop 269-3
Bldg. T35B. Rm. 107
Mo?ett Field, CA 94035-0001
Phone: 650-***-****
Email: ***.*********@**.***.***
URL: http://www.cmu.edu/silicon-valley/faculty-sta?/mengshoel-ole.html
Research Interests
Monitoring and diagnosis; Bayesian networks; Reasoning and learning
under uncertainty; Machine learning and discovery; Evolutionary com-
putation; Stochastic local search; Real-time and embedded systems; Re-
source allocation; Decision support.
Education Ph.D., Computer Science,May1999
University of Illinois at Urbana-Champaign
Urbana, IL
Thesis: E?cient Bayesian Network Inference: Genetic Algorithms,
Stochastic Local Search, and Abstraction
Advisers: Prof. David C. Wilkins and Prof. David E. Goldberg
B.S., Computer Science,April1989
Norwegian Institute of Technology
Tr o nd he i m, No r way
Employment
11/2008presentSenior Systems ScientistCarnegie Mellon University, Silicon Valley
Mo?ett Field, CA
5/200611/2008Senior Research Scientist, Research Area Lead
USRA/RIACSMo?ett Field, CA
5/19995/2006Research ScientistRockwell Scientific
Thousand Oaks, CA
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1/19955/1999Research AssistantBeckman Institute, University of Illinois at Urbana-Champaign
Urbana, IL
5/19988/1998 Summer InternFirst Quadrant
Pasadena, CA
8/19945/1996Research Assistant
General Engineering, University of Illinois at Urbana-Champaign
Urbana, IL
4/19898/1993Research Scientist
SINTEF DELAB
Tr o nd he i m, No r way
8/19854/1989Teaching AssistantDepartment of Computer Science, Norwegian Institute of Technology
Tr o nd he i m, No r way
Summers 1987 and 1988 SummerInternBasic Communication Group, Norsk Data AS
Oslo, Norway
Summer 1986SummerIntern
RegnskapsRevisjon AS
Hamar, Norway
Te a ch ing
Fal l 2010 Statistical Discovery and Learning (Instructor, with Dr. Joy Zhang),
Carnegie Mellon University, Silicon Valley, Mo?ett Field, CA.
Fal l 2009 Statistical Discovery and Learning (Instructor, with Dr. Joy Zhang),
Carnegie Mellon University, Silicon Valley, Mo?ett Field, CA.
Fal l 1985 Spri ng 1989Introductory Computer Science; Data Bases;and Symbolic Compu-
tation (Teaching Assistant), Department of Computer Science, Norwe-
gian Institute of Technology, Trondheim, Norway.
Advising Dongzhen Piao, Ph.D. Student, CMU, Fall 2010-present
Michele Cossalter, Ph.D. Student, CMU, Spring 2010-present
Priya Sundararajan, Ph.D. Student, CMU, Spring 2010-present
Lu Zheng, Ph.D. Student, CMU, Spring 2010-present
Xinyao Hu, Graduate Student, CMU, Fall 2009-Summer 2010
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Suresh Babu Rajasekaran, Graduate Student, CMU, Fall 2009-Summer
2010
Avinash Jha, Graduate Student, CMU, Fall 2009
Erik Reed, Undergraduate Student, University of Washington, Summer
2010
Craig Harrison, Undergraduate Student,
University of Maine, Summer
2010
Brian Ricks, Undergraduate Student, University of Texas at Dallas,
Spring 2009 and Summer 2010
Guowei Yang, Ph.D. Student, University of Texas at
Austin, Summer
2010
Guido Ciollaro, Undergraduate Student, Mataro School of Engineering,
Summer 2010
Brittney Bullis, Undergraduate Student, South Dakota State University,
Spring 2010
Stephanie Hunsche, Undergraduate Student, Indiana Institute of Tech
-
nology,
Fall 2009Godohaldo Perez, Undergraduate Student, University of Puerto Rico
at
Mayaguez, Summer 2009
Cyril Lan, Undergraduate Student, MIT, Summer 2009
Tr e vo r Te tzla?, Und ergra du ate St u de nt, S a n Fr a nc iscoStat
e Uni ve rsi ty,
Summer 2009
W. Bradley Knox, Ph.D. Student, University of Texas at Austin, Summer
2008
Robert Ni?enegger, Undergraduate Student, Purdue, Summer 2008
Zachary Green, Undergraduate Student, California Polytechnic State
University at San Luis Obispo, Summer 2008
Yu l i ya Za b i ya ka, Gr aduateStude nt, UCLA, S u mme r2007
Lois Desplat, Undergraduate Student, San Jose State University, Sum-
mer and Fall 2007
Long Term Visitors, Post-Docs, Research Sta?
Dr. Carla D. Cotwright-Williams, Assistant Professor, Department of
Mathematics, Norfolk State University, Summer 2010
.
Dr. Ehsan Sheybani, Assistant Professor, Department of Engineering
and Technology,
Virginia State University, Petersburg, VA, Summer
2009.
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Dr. Severino F. Galan, Associate Professor, Department of Artificial
Intelligence, UNED, Madrid, Spain, Spring 2008.
Reviewing Reviewer for Artificial Intelligence Journal
Reviewer for the Genetic and Evolutionary Computation Conference
(GECCO)
Reviewer for IEEE Transactions on Knowledge and Data Engineering
Reviewer for IEEE Transactions on Evolutionary Computation
Reviewer for IEEE Transactions on Systems, Man, and Cybernetics
(SMC), Part A
Reviewer for the International Workshop on the Principles of Diagnosis
(DX)
Reviewer for the International Joint Conference on Artificial Intelligence
(IJCAI)
Reviewer for International Conference on Prognostics and Health Man-
agement
Reviewer for International Journal of Prognostics and Health Manage-
ment
Reviewer for Journal of Machine Learning Research
Reviewer for Knowledge-Based Systems
Reviewer for NASA SBIR/STTR/NRA proposals
Reviewer for National Science Foundation (NSF)
Invited Talks
Carnegie Mellon University, Pittsburgh, PA, CyLab Corporate Partners
Meeting, September 2010. Towards Autonomous Trustworthy Comput-
ing: An Intelligent Systems Perspective.
Carnegie Mellon University, Silicon Valley, Mo?ett Field, CA, Talks on
Computing Systems (TOCS), June 2009. Recent Advances in Modeling
and Computation using Bayesian Networks.
Georgia Institute of Technology, Atlanta, GA, December 2009.Visual-
ization of Analytical Processes.
NASA Aviation Safety Program Technical Conference, Washington D.C.,
November 2009. Probabilistic Methods for Diagnosis of Aircraft Systems.
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Carnegie Mellon University, Pittsburgh, PA, ECE Department, Special
Seminar, February 2009. Recent Advances in Modeling and Computation
using Bayesian Networks.
NASA Ames Research Center, Mo?ett Field, CA, January 2008.Bayesian
Methods for Diagnosis.
NASA Ames Research Center, Mo?ett Field, CA, May 2008.Bayesian
Networks and Probabilistic Risk Analysis.
Stanford University, CA, Seminar on Computational Learning and Adap-
tation, March 2006. Evaluating Bayesian Network Inference and Learn-
ing Algorithms: Creating Problem Instances of Increasing Di?culty.
NASA Ames Research Center, Mo?ett Field, CA, February 2006.Eval-
uating Bayesian Network Inference and Learning Algorithms: Creating
Problem Instances of Increasing Di?culty.
IBM T. J. Watson Research Center, Yorktown Heights, NY, March 1999.
E?cient Inference in Bayesian Networks Using Stochastic Search Algo-
rithms.
Rockwell Science Center, Palo Alto, CA, March 1999.E?cient Inference
in Bayesian Networks Using Stochastic Search Algorithms.
Patents US Patent 7,081,834, Aviation Weather Awareness and Reporting En-
hancements (AWARE) System using a Temporal-Spatial Weather Data-
base and a Bayesian Network Model.Granted, July 25, 2006.
US Patent 6,856,680, Contact center autopilot algorithms.Granted,
Fe bruary 15, 2005.
US Patent 6,853,721, Contact center autopilot architecture.Granted,
Fe bruary 8, 2005.
US Patent 6,842,515, Multi-site responsibility-based routing.Granted,
January 11, 2005.
Research Grants
AComputingFrameworkforDistributedDecisionMakingtoEnsureRo-
bustness of Complex Man-Made Network Systems: The Case of Electric
Power Networks,NSF.Co-PIwithRohitNegi,2009 2012,$1,499,983.
Visualization of Analytical Processes,NSF.PI,2009 2011,$497,401.
Advanced Tools And Techniques for V&V of IVHM,NASA.Co-PIwith
Johann Schumann, 2009 2012, $486,000.
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ISWHM: Tools and Techniques for Software and System Health Manage-
ment,NASA.Co-PIwithJohannSchumann,2008 2011,$196,223.
Autonomous Trustworty Computing Platforms and Devices,CMUCy-
Lab. PI, 2009 2010, $20,000.
Book Chapters
A.
O. J. Mengshoel and D. C. Wilkins. Abstraction for belief revision:
Using a genetic algorithm to compute the most probable explanation.
In Satisficing Models: Papers from the 1998 AAAI Spring Symposium,
pages 46 53, Menlo Park, CA, 1998. AAAI Press. Techical Report SS-
98-05.
O. J. Mengshoel, D. C. Wilkins, and S. Uckun. Filtering and visualizing
uncertain battlefield data using Bayesian networks. InIn Proc. of the
2nd Annual Federated Laboratory Symposium, Advanced Displays and
Interactive Displays,CollegePark,MD,February1998.
O. J. Mengshoel and D. C. Wilkins. Abstraction and aggregation in belief
networks. In Abstractions, Decisions, and Uncertainty: Papers from the
AAAI Workshop,pages53 58,MenloPark,CA,July1997. AAAIPress.
Te chi cal Re port WS - 9 7 - 0 8 .
O. J. Mengshoel and D. C. Wilkins. Recognition and critiquing of erro-
neous agent actions. In Agent Modeling: Papers from the AAAI Work-
shop,pages61
Te ch nicalReports
O. J. Mengshoel, D. Roth, and, D. C Wilkins. Stochastic Greedy Search:
Computing the Most Probable Explanation in Bayesian Networks. Tech-
nical Report UIUCDCS-R-2000-2150, Department of Computer Science,
University of Illinois at Urbana-Champaign, February 2000, Urbana, IL.
O. J. Mengshoel, D. Roth, and, D. C Wilkins. Hard and Easy Bayesian
Networks for Computing the Most Probable Explanation. Technical Re-
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port UIUCDCS-R-2000-2147, Department of Computer Science, Univer-
sity of Illinois at Urbana-Champaign, January 2000, Urbana, IL.
Software ProDiagnose: Software for detection and diagnosis using probabilistic
techniques.
Honey-bee Optimization: Implemented using Java and discrete event
simulation engine.
Configuration and Scheduling of Real-Time Systems: Software imple-
mented using Java and Swing.
Scheduling Analysis and Visualization of Programmable Logic Con-
trollers: Software implemented using Java and Swing.
Insider Intrusion Detection using Machine Learning: Implemented us-
ing Java, Markov chains, discrete event simulation, feature construction,
naive Bayes.
Contact Center Autopilot: Software for real-time monitoring and control
of contact centers.
AWA REdecisionengine : P r e - fl ightbrie fi ngsoft wa r e,
forpilots, u sing
Bayesian networks to drive display of weather hazards.
Information Fusion Toolbox: Software implemented using Java, XML,
Servlet, and Bayesian networks; integrated with tracker software.
CoRaven: Collaborative intelligence analysis using sonification, visualiza-
tion, and probabilistic reasoning; implemented in Java and Swing using
Bayesian networks.
Raven: Stochastic Search for computing MPEs in Bayesian Networks;
Generation of hard and easy Bayesian networks; implementation in C++.
Genetic Algorithm for Multi-Objective Optimization: Implemented in
C++, SQL database, and linear regression software.
Visual Critiquer: A spatial reasoning tutor, used in introductory en-
gineering courses to improve spatial visualization abilities of students.
Implemented in C and rule-based language Clips.
Knowledge Reformulation Tool: A tool for translation and interchange of
knowledge during knowledge acquisition; implemented in Common Lisp,
Prolog, and PCE.
Knowledge Validation Tool: GUI-oriented tool for validating expert sys-
tems, implemented in PCE and Common Lisp.
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October 21, 2010
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