Biosketch: Charles Nicholson

Nicholson CV (May 2020)

Professional Preparation

  • Bachelor of Science, Physics, University of North Texas, May 1999
  • Bachelor of Science, Mathematics, University of North Texas, May 1999
  • Master of Science, Decision Technologies, University of North Texas, May 2001
  • Doctor of Philosophy, Operations Research, Southern Methodist University, December 2010

Relevant Professional Appointments

  • 7.2019 – present Associate Professor, Industrial and Systems Engineering, Univ of Oklahoma
  • 3.2017 – present: Co-appointment in Data Science and Analytics, Gallogly College of Engineering, Univ of Oklahoma
  • 8.2013 – 7.2019 Assistant Professor, Industrial and Systems Engineering, Univ of Oklahoma
  • 10.2008 – 8.2013 Director and Founder, CN Analytics LLC, North Richland Hills, TX
  • 8.2007 – 8.2013  Teaching Professor, Engineering and Information Science, DeVry, Dallas, TX
  • 5.2002 – 8.2007   Director of Consumer Analysis, Blockbuster, Dallas, TX
  • 2.2000 – 5.2002   Statistical Analyst, UICI (Health Markets), North Richland Hills, TX
  • 9.1997 – 9.1999   Research/Academic Assistant, Univ of North Texas

Current Funding

Total: $21,640,344;  OU portion:  $2,651,344;  Nicholson: $765,032

NSF PIPP PHASE I: Next Generation Surveillance Incorporating Public Health, One Health, And Data Science to Detect Emerging Pathogens of Pandemic Potential
National Science Foundation
Co-Principal Investigator: 08.15.2022 to 8.14.2023
Total/OU portion: $999,977;

UNSA/OU: Public Health Monitoring and Decision Making 
Universidad Nacional de San Agustin
Co-Principal Investigator: 01.01.2021 to 12.31.203
Total/OU portion: $1,636,344; Nicholson: $207,982

RENEWAL: Center for Risk-Based Community Resilience Planning
National Institute of Standards and Technology
Co-Principal Investigator: 02.01.2020 to 01.31.2025
Total: $20,000,000; OU portion: $1,011,000; Nicholson: $556,050

Past Funding

Total: $22,532,410;  OU portion:  $2,232,319;  Nicholson: $827,075

Blending Data Streams to Create Reliable Ecological Forecasts
OU Data Institute for Societal Challenges Seed Grant Award Co-Principal Investigator: 01.15.2021 to 9.15.2021
Total/OU portion: $4,000; Nicholson: $1,000

Center for Risk-Based Community Resilience Planning
National Institute of Standards and Technology
Co-Principal Investigator: 02.01.2015 to 01.31.2020
Total: $20,000,000; OU portion: $1,374,998; Nicholson: $458,332

Machine learning enhanced COVID-19 propagation models for rural, semi-rural, and small urban regions
OU COVID-19 Rapid Response Seed Grant 
Principal Investigator: 05.15.2020 to 10.31.2020
Total/OU portion: $38,000; Nicholson: $12,667

HYDRA: Implementation of multi-threaded software for reconnaissance
Boeing Defense and Space Group
Co-Principal Investigator: 09.04.2020 to 12.19.2020
Total/OU portion: $161,705; Nicholson: $32, 341

SKYNET: Artificial intelligence and machine learning improvements for reconnaissance
Boeing Defense and Space Group
Co-Principal Investigator: 09.04.2020 to 12.19.2020
Total/OU portion: $83,576; Nicholson: $16,715

Collaborative Research: Resilience Analytics: A Data-Driven Approach for Enhanced Interdependent Network Resilience
National Science Foundation
Co-Principal Investigator: 10.15.2015 to 10.14.2020
Total: $2,209,129; OU portion: $534,040; Nicholson: $267,020

Data mining applications for gaming data
Nerd Kingdom
Principal Investigator: 01.15.2016 to 5.15.2017
Total/OU portion: $40,000; Nicholson: $40,000

Research

*denotes student authors

  1. Gupta, H.*, O. Nofal, A. Gonzalez, C. Nicholson, J. van de Lindt. 2022. Optimal selection of short- and long-term mitigation strategies for buildings within communities under flooding hazard, Sustainability, Accepted.
  2. Nicholson, C., L. Beattie, M. Beattie, T. Razzaghi, S. Chen. 2022. A machine learning and clustering-based approach for county-level COVID-19 analysis, PLOS ONE 17(4):e0267558. https://doi.org/10.1371/journal.pone.0267558
  3. Bosco, V.* , C. Nicholson. 2022.Modeling the economic impact of incoming tropical cyclones using machine learning.  Natural Hazards 110, 487–518. https://doi.org/10.1007/s11069-021-04955-8
  4. Beattie, M.* & C. Nicholson. 2021. Feature Extraction for Heroin-Use Classification Using Imbalanced Random Forest Methods, Substance Use & Misuse 56:1, 123-130, DOI: 10.1080/10826084.2020.1843058
  5. Reinert, A.,  L. Snyder, J. Zhao, A. Fox, D. Hougen, C. Nicholson, D. Ebert. 2020. Visual Analytics for Decision-Making During Pandemic. Computing in Science and Engineering 22(6):48-59 DOI: 10.1109/MCSE.2020.3023288
  6. Pires de Lima, R.*, D. Duarte, C. Nicholson, R. Slatt, K. Marfurt. 2020. Petrographic microfacies classification with deep convolutional neural networks.  Computers and Geosciences 142:104481 DOI: 10.1016/j.cageo.2020.104481 (download)
  7. Tao, W, N. Wang, B. R. Ellingwood, C. Nicholson. 2020. Enhancing the performance of highway bridges following earthquakes using Markov decision processes.  Structure and Infrastructure Engineering, DOI: 10.1080/15732479.2020.1730410 (download)
  8. Zhang, W.* and C. Nicholson. 2019. Objective scaling ensemble approach for mixed integer programming.  Journal of Heuristics. DOI:10.1007/s10732-019-09418-9. [LINK] (download)
  9. Beyney, C.*, S. Bhavaraju*, C. Nicholson. 2019. Quantitative analysis of social media sensitivity to natural disasters.  International Journal of Disaster Reduction. 39 (2212-4209): 101251. DOI: 10.1016/j.ijdrr.2019.101251 [LINK] [bibTex] (download)
  10. Bosco, W.* and C. Nicholson. 2019. Port disruption impact on the maritime supply chain: A literature review. Sustainable and Resilient Infrastructure, DOI: 10.1080/23789689.2019.1600961 [LINK] [bibTex] (download)
  11. Darayi, M.*, K. Barker, C. Nicholson. 2019. A multi-industry economic impact perspective on adaptive capacity planning in a freight transportation network. International Journal of Production Economics. 208: 356-268 [LINK] [bibTex] (download)
  12. Pires de Lima, R.*, A. Bonar, D. D. Coronado, K. Marfurt, C. Nicholson. 2019. Deep convolutional neural networks as a geological image classification tool. The Sedimentary Record, June 2019. LINK (download)
  13. Morshedlou, N.*, K. Barker, G. Sansavini, C. Nicholson. 2018. Adaptive capacity planning formulation for infrastructure networks. Journal of Infrastructure Systems. 24(4): 04018022. [LINK] [bibTex] (download)
  14. Zhang, W.*, P. Lin*, N. Wang, C. Nicholson, X. Xue. 2018. Probabilistic prediction of post-disaster functionality loss of community building portfolios considering utility disruptions. ASCE Journal of Structural Engineering, Special Issue on Structural Design and Robustness for Community Resilience to Natural Hazards. 144(4), 04018015. LINK [bibTex] (download)
  15. Zhang, W.*, N. Wang, C. Nicholson. 2017. Resilience-based post-disaster recovery strategies for road-bridge networks.  Structure and Infrastructure Engineering, 13(11):1404-1413 DOI:10.1080/15732479.2016.1271813  LINK [bibTex] (download)
  16. Almoghathawi, Y.*, K. Barker, C.M. Rocco, and C. Nicholson. 2017. A multi-criteria decision analysis approach for importance ranking of network components. Reliability Engineering and System Safety, 158: 142-151 LINK [bibTex](download)
  17. Nicholson, C., L. Goodwin*,  and C. Clark. 2017. Variable neighborhood search for reverse engineering of gene regulatory networks. Journal of Biomedical Informatics, 65:120-131 LINK [bibTex](download)
  18. Barker, K., J. Lambert, C. Zobel, A. Tapia, J. Ramirez-Marquez, L. McLay, C. Caragea, C. Nicholson. 2017. Defining resilience analytics for interdependent cyber-physical-social networks. Sustainable and Resilient Infrastructure, 2(2):59-67 [LINK] [bibTex](download)
  19. Nicholson, C., K. Barker, and J.E. Ramirez-Marquez. 2016. Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning. Reliability Engineering and System Safety, 145: 62-73 LINK [bibTex](download)
  20. Zhang, W.* and C. Nicholson. 2016. Prediction-based relaxation solution approach for the fixed-charge network flow problem. Computers & Industrial Engineering, 99:106-11 LINK [bibTex](download)
  21. Nicholson, C. and W. Zhang*. 2016. Optimal network flow: A predictive analytics perspective on the fixed-charge network flow problem. Computers & Industrial Engineering, 99:260-268 LINK [bibTex] (download)
  22. Zhang, W.* and C. Nicholson. 2016. A multi-objective optimization model for retrofit strategies to mitigate direct economic loss and population dislocation. Sustainable and Resilient Infrastructure, 1 (3-4):123-136 LINK [bibTex](download)
  23. Kennington, J. and C. Nicholson. 2010. The uncapacitated time-space fixed-charge network flow problem: An empirical investigation of procedures for arc capacity assignment. INFORMS Journal on Computing, 22: 326-337. LINK [bibTex]
  24. Lin, P.*, N.Wang, W. Zhang*, F. Hu, C. Nicholson, X. Xue. Modeling Post-disaster Functionality Recovery of Building Portfolios: The Impact of Lifeline Networks. In review in Reliability Engineering and System Saftey.

Conference Papers and Presentations

  1. Unterbrink, J., C. Nicholson, T. Razzaghi, A. González, Y. Velazco-Paredes, B. Lipe.  Monitoring and Forecasting the COVID-19 Pandemic in Peru.  IISE Annual Conference & Expo, May 20-23, 2023, New Orleans, LA. (download)
  2. Duarte, J.*,  H. Vergara, J. J. Gourley, P.E. Kirkstetter, C. Nicholson. ML-based guidance for impact-based flash flood warnings. American Meteorology Society, 30th Conference on Severe Local Storms. Santa Fe, NM, October 24-28, 2022. 
  3. Nicholson, C. Covid-19 propagation modeling for sub-populations. Invited presentation at 2022 INFORMS Annual Meeting, Indianapolis, IN. October 16-19, 2022.
  4. Sen Gupta, H.*, O. Nofal, A. D. Gonzalez, C. Nicholson, J. van de Lindt. Optimal Selection of pre-event building- and community-level mitigation strategies for flood risk. Invited presentation at 2022 INFORMS Annual Meeting, Indianapolis, IN. October 16-19, 2022.
  5. Nicholson, C. Machine learning and clustering-based approach for county-level Covid-19 analysis. Invited presentation at 2021 INFORMS Annual Meeting, Anaheim, CA. October 24-27, 2021.
  6. Duarte, J.*,  P. E. Kirstetter, M. Saharia, J. J. Gourley, H. Vergara, C. Nicholson. Predicting flood responses from spatial rainfall variability and basin morphology through machine learning.  European Geosciences Union 2020 — Data Science and Machine Learning Application in Natural Hazards. Vienna, Austria, May 3-8, 2020.
  7. Nicholson, C. Big Data and Intelligent Data Analytics.  Invited speaker at the 3rd Annual OU-OUHSC Biomedical Engineering Symposium: Collaborate to Cure,  Oklahoma City, OK, March 29, 2019.
  8. Nicholson, C., W. Zhang*, N. Wang, P. Lin, X. Xue. 2018.  Interdependent Network Functionality And Recovery For Community Resilience.  Invited presentation at 2018 INFORMS Annual Meeting, November 4-7, 2018.
  9. Nicholson, C. A. Rodriguez*. 2018. A Hybrid Machine Learning Approach To The Stochastic Network Design Problem For Mitigation Strategies. Invited presentation at 2018 INFORMS Annual Meeting, November 4-7, 2018.
  10. Bosco, V.*, C. Nicholson. 2018. Dynamic Decision Models for Port Shutdown and Ship Rerouting.  Conference paper accepted 2018 IISE Annual Conference, Orlando, FL, May 2018
  11. Rodriguez, A.*, C. Nicholson. 2018. IISE Data-based Methodology for Mitigation Decision-making in Critical Infrastructure. Conference paper accepted at 2018 IISE 2018 Annual Conference, Orlando, FL, May 2018.
  12. Zhang, W.*., C. Nicholson 2018. Interdependent Network Recovery Problem. 2018 IISE Annual Conference, Orlando, FL, May 2018.
  13. Nicholson, C. 2018. A hybrid machine learning and optimization modeling application for economic analysis. Conference paper accepted at Learning and Intelligent Optimization Conference, Kalamata, Greece, June 10-15, 2018.
  14. Zhang W.*, N. Wang, C. Nicholson, M. Tehrani*. 2017. Stage-wised Resilience Planning for Transportation Networks.  Proceedings of the 12th International Conference on Structural Safety and Reliability, Vienna, Austria.
  15. Nicholson C., Intelligent Data Analytics.  Invited speaker at the October 2017 OKC Innovates Big Data Symposium, Oklahoma City, OK, USA. (download)
  16. Cutler, H., C. Nicholson, N. Wang, S. Zahran. 2016. Merging Economic and Civil Engineering Models to Estimate the Impact of Earthquakes.  Paper accepted and presented at 55th Annual Meeting of the Southern Regional Science Association, Washington, D.C.
  17. Zhang, W.*, N. Wang, C. Nicholson. 2016. Resilience-Based Risk Mitigation and Recovery for Highway Transportation Network. Presented at the Probabilistic Mechanics & Reliability Conference 2016, Nashville, TN.
  18. Zhang, W.*, N. Wang, C. Nicholson. 2016. Resilience-Based Post-disaster Recovery Strategies for Community Road-bridge Networks. Presented at INFORMS Annual Meeting, Nashville, TN.
  19. Zhang, W.*, C. Nicholson. 2016. A Multi-objective Optimization Model for Mitigating Community Economic Loss and Population Dislocation. Presented at INFORMS Annual Meeting, Nashville, TN.
  20. Zhang, W.*, C. Nicholson. 2016. Objective Scaling Ensemble Approach for Integer Linear Programming. Presented at INFORMS Annual Meeting, Nashville, TN.
  21. Nicholson, C. and W. Zhang*. 2015. Optimal Flow Analysis. Presented at INFORMS Annual Meeting, Philadelphia, PA.
  22. Zhang, W.* and C. Nicholson. 2015. Regression-Based Relaxation. Presented at INFORMS Annual Meeting, Philadelphia, PA.
  23. Barker, K. C. Nicholson, J. Ramirez. 2015. Vulnerability Importance Measures Toward Resilience-Based Network Design. Conference paper and presentation at 12th International Conference on Applications of Statistics and Probability in Civil Engineering, Vancouver, Canada, July 12-15, 2015.
  24. Barker, K., C. Nicholson, and J.E. Ramirez-Marquez. 2014. Resilience-based importance measures for network design optimization. Presented at Industrial and Systems Engineering Research Conference, Montreal, QC.
  25. Clark, C. and C. Nicholson. 2013. Distributed parallel process particle swarm optimization on fixed charge network flow problems. Presented at INFORMS Annual Meeting, Minneapolis, MN.
  26. Nicholson, C. 2010. Generalized time-space fixed-charge network flows. Presented at INFORMS Annual Meeting. Austin, TX.

Works in progress

  1. Tehrani, M.H.*, A. D. Rodriguez*,  N. Wang, C. Nicholson. A data-driven framework for hazard-sensitive infrastructure component importance ranking. Work in progress.
  2. Rodriguez, A.*, C. Nicholson.  Probabilistic perspective on network component importance measures for mitigation decision-making.
  3. Nicholson, C.  Parameterized Dynamic Slope Scaling for the Fixed-Charge Network Flow Problem.
  4. Zhang, W.*, N. Wang, C. Nicholson, and M. Tehrani*. A Stage-wise Decision Framework for Transportation Network Resilience Planning and Recovery.
  5. Wen, Y*., C. Nicholson, A.D.Gonzalez.  Mitigation analysis: Joplin.  Work in progress.
  6. Nicholson, C., H. Cutler. Engineering and economic modeling for community mitigation decision-making. Work in progress.

Synergistic Activities

  • Developed proprietary data analytics solutions for eight corporations across the nation and internationally over 12 years. Projects included a wide variety of predictive and prescriptive analytics for diverse companies representing multi-billion dollar retail, finance, and restaurant industries. An excerpt of successful data-intensive solutions included customer-level behavior prediction, fraudulent activity detection, geographic information systems (GIS) strategic and competitive targeting, and product allocation optimization.
  • Developing new core curriculum a new interdisciplinary program: Masters in Data Science and Analytics.
  • Serves on the Editorial board of the Taylor and Francis journal Sustainable and Resilient Infrastructure (2015-2020)
  • Collaborating with multiple universities and NIST as member and PI for OU of the “Community Resilience Center of Excellence” team to develop NIST-Community Resilience Modeling Environment (IN-CORE).
    • Colorado State University, Rice University, Oregon State University,University of Illinois at Urbana-Champaign, Texas A&M University, University of Washington, University of Kansas, University of Colorado Boulder
  • Collaborating with multiple universities and the NSF regarding “Resilience Analytics” on a newly funded NSF-CRISP multi-year interdisciplinary project
    • Penn State,University of Wisconsin, University of Virginia,Virginia Tech, Stephens Institute of Technology, University of North Texas
  • Serves on the Editorial board of Sustainable and Resilient Infrastructure

Collaborators and Other Affiliations

  • University of Oklahoma: Kash Barker (OU ISE), Andres Gonzalez (OU ISE), Naiyu Wang (OU Civil Engineering)
  • Colorado State University: Bruce Ellingwood (Civil Engineering), John van de Lindt (Civil Engineering), Sammy Zahran (Economics), Harvey Cutler (Economics)
  • Texas A&M: Walt Peacock, Nathaniel Rosenheim (Hazard Reduction & Recovery Center, Department of Landscape Architecture & Urban Planning)
  • Rice University: Leonardo Duenas-Osorio (Civil Engineering)
  • University of Illinois, Urbana-Champaign:  Paolo Gardoni (Civil and Environmental Engineering), Jong Lee (National Center for Supercomputing Applications)
  • Kansas State University: Doina Caragea (Computer Science)

Graduate Students

Current (6)

ISE PhD candidates/students:  Yunjie Wen, Jay McKinley, Jorge Duarte

ENGR PhD students: Matthew Beattie

DSA MS students: Will Keely, Rafia Bushra

Former PhD Students (3)

2020: Vera Bosco (PhD ISE), Sai Theja Bhavaraju (PhD ISE)

2017: Weili Zhang (PhD ISE) — Machine Learning Engineer at Google

Former Master Students (20)

2019: Paúl Calle (MS DSA), Rafael de Lima Peres (MS DSA)

2018: Alexander Rodríguez Castillo (MS DSA), Yanbin Chang (MS ISE), Alex Beene (MS DSA), Genwei Zhang (MS DSA)

2017: Megan Snelling (MS ISE), Alexandra Amidon (MS DSA), Emily Grimes (MS DSA), Samineh Nayeri (MS ISE), Pauline Ribeyre (MS ISE), Yunjie Wen (MS DSA), Gowtham Talluru (MS DSA)

2016: Olivia Perret (MS ISE), Param Tripathi (MS ISE)

2015: Leslie Goodwin (MS ISE), Oluwafemi Oseni (MS ISE), Diana Wang (MS ISE), Cyril Beyney (MS ISE), Weili Zhang (MS DSA)

Teaching

  • 2017 Gallogly College of Engineering Teaching Scholar Award winner

Classes taught:

  • ISE 5103 Intelligent Data Analytics (Spring ’14, Fall ’14, Fall ’15, Fall ’16, Fall ’17, Fall ’18, Fall ’19, Fall ’20)
    • Campus and online offerings
  • ISE 5113 Advanced Analytics and Metaheuristics (Spring ’15, Spring ’16, Spring ’17, Spring ’18, Spring ’19, Spring ’20, Spring ’21)
    • Campus and online offerings
  • ISE 3293/5013 Applied Engineering Statistics (Summer ’14, Fall ’14, Summer ’15, Fall ’15, Summer ’19, Summer ’20)
  • ISE 4113 Spreadsheet-based Decision Support Systems (Fall ’16, Fall ’17, Fall ’18, Fall ’19, Fall ’20)

Other

  • Brazilian Jiu-jitsu at Titan Martial arts 
  • Enjoy backpacking and mountaineering — I usually attempt a 14’er or two each year.
  • Fluent in English and Spanish
  • Beginner+ level rock climber at Summit Climbing Gym
  • Volunteer at Victory Family Iglesia: photography and musician (2017-2019)
  • Crossfit member at Koda Crossfit Norman (2016-2019)
  • Served 1 year term on board of directors for the non-profit Luggage With Love (2016)
  • Proud soccer dad and kid’s coach (Go Power Ponies! Go Punishers!) and (former) player (Total Chaos!)