Laura L Pullum
Laura L Pullum
Sr. Research Scientist
Dr. Laura Pullum is a senior research scientist in the Computational Data Analytics Group at the Oak Ridge National Laboratory, with over 30 years experience. Her research is in software-based system dependability and intelligent systems. She currently conducts research in the evaluation, verification and validation of predictive analytics and machine learning systems, and the use of novel machine learning algorithms for dependable disease dynamics examination. Prior to joining ORNL, she worked in industry, at a non-profit research institute, as a visiting professor, and as a small business owner.
Dr. Pullum has authored numerous publications including books, book chapters, and peer-reviewed papers; holds one patent, serves on technical advisory boards and NSF review panels, and serves on the standards working group for IEEE P1012-201X Standard for System Verification and Validation. She is a senior member of the IEEE Computer Society.
Dr. Pullum holds a BS in Math; Masters degrees in Operations Research, Business Administration, and Geology; and a doctorate in Systems Engineering and Operations Research.
* Employee of the Quarter, Computational Sciences and Engineering Division, ORNL, 2014
* Distinguished Employee, Computing & Computational Sciences Directorate, ORNL, 2012
* Business development awards, Institute for Scientific Research, 2003-2006
* P.K. McElroy Award for Best Paper, 1996 Reliability and Maintainability Symposium for “Fault Tree Models for the Analysis of Complex Computer-Based Systems”
* SRS Technologies employee of the Month, Nov. 1989, June 1991
* Presidential Award for Outstanding Master’s Project, Southeastern Inst. of Technology, 1990
• Verification, Validation and Uncertainty Quantification of Machine Learning Systems (PI)
• ORCA (Oak Ridge Cyber-Analytics) – V&V Lead
• Oak Ridge Biosurveillance Toolkit (ORBiT) (co-I)
• PRIMUS Photogrammetric System – V&V Lead
• NIMBioS working group on Modeling Antimicrobial Resistance Intervention (Systems Lead)
• NEET (Nuclear Energy Enabling Technologies) – safety and fault tolerance of next generation nuclear plants
• Demonstrating a Novel Bio-defense Capability using Public Health Data Informatics (PI)
• Biosurveillance Ecosystem GovCloud Framework (PI)
• Verification and Validation of Agent-Based Disease Spread Models (PI)
• Digital Technology Qualification - Mitigation of Digital Common-Cause Failure Vulnerabilities for Nuclear Qualified Applications
• Biosurveillance Data Analysis and Decision Support (LDRD) – intelligent crawlers, information confidence measures, data fusion
• CMS – Data Analytics and Dependability for Medicare and Medicaid
• DAMSEL – dependability of a multi-modal learning system for radiologist assistant system
Peer-reviewed Papers Published since 2009 (full list and reports provided in CV):
Margevicius, K J, N. Generous, E Abeyta, L. Pullum, A. Ramanathan, A. Deshpande, et al. (2016). “The Biosurveillance Analytics Resource Directory (BARD): Facilitating the Use of Epidemiological Models for Infectious Disease Surveillance.” PLoS ONE 11(1):e0146600, January 2016, DOI: 10.1371/journal.pone.0146600.
Ozmen, Ozgur, Laura Pullum, et al. “Augmenting Epidemiological Models with Point-of-Care Diagnostics Data.” PLoS ONE 11(4), 1-13, (2016).
Ozmen, Ozgur, Laura Pullum, et al. “Analyzing the Impact of Modeling Choices and Assumptions in Compartmental Epidemiological Models.” SIMULATION: Transactions of The Society for Modeling and Simulation International 92, no. 5, 1-13, (2016).
Ramanathan, A., L. Pullum, et al. “Sequential Pattern Mining of Electronic Healthcare Reimbursement Claims: Experiences and Challenges in Uncovering How Patients are Treated by Physicians.” IEEE International Conference on Big Data (IEEE Big Data), 2016.
Ramanathan, A., L. Pullum, et al. “Constructing Patient Specific Clinical Trajectories from Electronic Healthcare Reimbursement Claims using Sequential Pattern Mining.” HI-POCT15, the NIH-IEEE Strategic Conference on Point of Care Technologies for Precision Medicine, 2016
Quinn, S., Ramanathan, A., L. Pullum, et al. “Dr. Twitter: The Logistics of Practical Disease Surveillance using Social Media.” IEEE International Conference on Biomedical and Health Informatics, 2016.
Quinn, S., Ramanathan, A., l. Pullum, et al. “Tracking Alcohol and Marijuana Usage and Behaviors from Social Media Using Oak Ridge Bio-Surveillance Toolkit.” IEEE International Conference on Biomedical and Health Informatics, 2016.
Ramanathan, A., Pullum, L., S. Jha, et al. “Integrating Symbolic and Statistical Methods for Testing Intelligent Systems: Applications to Machine Learning and Computer Vision.” IEEE Design, Automation & Test in Europe (DATE), 2016.
Ramanathan, A., Laura Pullum, et al. “Discovering Multi-scale Co-occurrence Patterns of Asthma and Influenza with the Oak Ridge Bio-surveillance Toolkit.” Frontiers in Public Health 3, no. 1, 1-12, (2015).
Ramanathan, Arvind, Laura Pullum, et al. “ORBiT: Oak Ridge Bio-surveillance Toolkit for Public Health Dynamics.” BMC Bioinformatics 16, (2015).
Ramanathan, Arvind, Laura Pullum, et al. “Discovery of Disease Co-occurrence Patterns from Electronic Healthcare Reimbursement Claims Data.” In Knowledge Discovery and Data Mining Big Data in Health Informatics (KDD-BHI), 2014.
Corley, Courtney D, Pullum, Laura L, Hartley, David M, Benedum, Corey, Noonan, Christine, Rabinowitz, Peter M, & Lancaster, Mary J. (2014). Disease Prediction Models and Operational Readiness. PloS one, 9(3), e91989.
Pullum, Laura, & McKinney, Michael L. (2014). “Abrasion from dam release does not affect mortality in a freshwater mussel,” North American Paleontological Convention (NAPC), Gainesville, FL. February 16, 2014.
Pullum, Laura L., & Michael L. McKinney. “Hierarchical Agglomerative Clustering for Delimiting Veneridae Species” Geological Society of America Annual Meeting, Denver, CO, Oct. 2013, In Geological Society of America Abstracts with Programs.
Ramanathan, Arvind, Pullum, Laura L, Steed, Chad A, Parker, Tara L, Quinn, Shannon P, & Chennubhotla, Chakra S. (2013). Oak Ridge Bio-surveillance Toolkit (ORBiT): Integrating Big-Data Analytics with Visual Analysis for Public Health Dynamics. In Public Health's Wicked Problems: Can InfoVis Save Lives? 2013.
Steed, Chad A, Potok, Thomas E, Pullum, Laura L, Ramanathan, Arvind, Shipman, Galen, & Thornton, Peter E. (2013). Extreme Scale Visual Analytics. In 4th SC Workshop on Petascale (Big) Data Analytics, 2013.
Pullum, Laura, & Ramanathan, Arvind. ORBiT–The Oak Ridge Biosurveillance Toolkit. IDIS 2013.
Ramanathan, Arvind, Pullum, Laura L, Steed, Chad A, Quinn, Shannon S, Chennubhotla, Chakra S, & Parker, Tara. (2013). Integrating heterogeneous healthcare datasets and visual analytics for disease bio-surveillance and dynamics. IEEE Workshop on Interactive Visual Text Analytics (Atlanta, GA).
Corley, Courtney D, & Pullum, Laura. (2013). Disease models for event prediction. Online Journal of Public Health Informatics, 5(1).
Pullum, Laura L., and Ozgur Ozmen. “Early Results from Metamorphic Testing of Epidemiological Models.” In Workshop on Verification and Validation of Epidemiological Models (VVEM-2012), ASE International Conference on BioMedical Computing, 62-67, December 2012.
Corley, Courtney and Laura L. Pullum. “Disease Models for Event Prediction.” 2012 International Society for Disease Surveillance (ISDS) Annual Conference, San Diego, California, USA, December 04-05, 2012.
Ramanathan, Arvind, Chad A. Steed and Laura L. Pullum. “Verification of Compartmental Epidemiological Models using Metamorphic Testing, Model Checking and Visual Analytics.” In 2012 Workshop on Verification and Validation of Epidemiological Models As part of 2012 ASE/IEEE International Conference on Biomedical Computing, 68-73, 2012.
Pullum, Laura L. and Xiaohui Cui. “A Hybrid Sensitivity Analysis Approach for Agent-based Disease Spread Models.” In DSN (Dependable Systems and Networks), June 2012.
Pullum, Laura L., and Xiaohui Cui. “Techniques and Issues in Agent-Based Modeling Validation.” In DSN (Dependable Systems and Networks), June 2012.
Rouff, Christopher, L. Pullum, et al., “The AdaptiV Approach to Verification of Adaptive Systems.” In Fifth International C* Conference on Computer Science & Software Engineering (C3S2E’12), April 2012.
Pullum, Laura L., C. Rouff, R. Buskens, X. Cui, E. Vassiv, and M. Hinchey, “Verification of Adaptive Systems,” AIAA Infotech@Aerospace 2012, April 2012.
Pullum, Laura L., and Michael L. McKinney, “Biological Homogenization of Freshwater Mussels from Human Activities,” Geological Society of America Southeastern Section - 61st Annual Meeting, Ashville, NC, April 2012, In Geological Society of America Abstracts with Programs, Vol. 44, No. 4, p. 16.
Pullum, L., and C. Symons, “Failure Analysis of a Complex Learning Framework Incorporating Multi-Modal and Semi-Supervised Learning,” In IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2011), 308-313, 2011.
Brettin, Thomas S., X. Cui, L. Pullum, et al., “A Novel Architecture for Biothreat Situation Awareness.” Supercomputing, Seattle, WA, Nov. 14-18, 2011.
Brettin, Thomas S., Laura Pullum, et al., “Enhanced Data Analytics and Decision Support for Biothreat Situation Awareness.” DTRA CBD S&T Conference, Las Vegas, Nevada, Nov., 2011.
Pullum, L.L., C. Symons, et al., “Architecture-Level Dependability Analysis of a Medical Decision Support System.” International Conference on Software Engineering (ICSE) Workshop on Software Engineering in Health Care. SEHC’10. Cape Town, South Africa. May 2010.
Haglich, P., C. Rouff, and L. Pullum, “Detecting Emergent Behaviors with Semi-Boolean Algebra,” Proceedings of AIAA Infotech @ Aerospace, 2010.
Darrah, Margie, Laura Pullum, et al., “Using Genetic Algorithms for Robust Tasking of Multiple UAVs with Diverse Sensors,” Proceedings of AIAA Infotech @ Aerospace, 2009.
Cui, Xiaohui, Laura Pullum, et al., “A Stigmergy Approach for Open Source Software Developer Community Simulation.” In Symposium on Social Computing Applications (SCA09), 2009.
Cui, Xiaohui, Laura Pullum, et al. “A Stigmergy Collaboration Approach in the Open Source Software Developer Community.” In Human Behavior-Computational Intelligence Modeling Conference, 2009.
U.S. Patent # 6,212,649 B1, “System and Method for Providing Highly-Reliable Coordination of Intelligent Agents in a Distributed Computing Environment,” (co-inventor), 2001.