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MAJ Nathaniel D. Bastian, Ph.D.

Senior Research Fellow | Adjunct Assistant Professor, Army Cyber Institute

Ph.D. Industrial Engineering and Operations Research, Pennsylvania State University, 2016
M.Eng. Industrial Engineering, Pennsylvania State University, 2014
M.S. Econometrics and Operations Research, Maastricht University, 2009
B.S. Engineering Management (Electrical Engineering) with Honors, U.S. Military Academy, 2008

MAJ Nathaniel D. Bastian, Ph.D. is an FA49 (Operations Research / Systems Analysis) Officer in the U.S. Army, where he serves as Senior Research Fellow and Adjunct Assistant Professor within the Intelligent Cyber-Systems and Analytics Research Laboratory (ICSARL) at the Army Cyber Institute. Nate is a leader, practitioner, researcher, and educator of mathematical, computational, analytical, data-driven, and decision-centric methods to support the improvement and enhancement of decision-making in cyber security, national defense, military operations, human resources and manpower, healthcare, logistics, energy and finance. As a decision analytics professional, Nate’s expertise lies in the scientific discovery and translation of actionable insights into effective decisions using algorithms, techniques, tools and technologies from operations research, data science, artificial intelligence, industrial engineering, and economics to design, develop, deploy and operationalize decision-support models for descriptive, predictive and prescriptive analytics.

  • Optimization, simulation, statistical computing, machine/deep learning, intelligent systems, big data analytics

  • Decision science, business analytics, applied econometrics, production economics, engineering management
Research Areas
  • Multiple objective optimization and decision-making under uncertainty for resource allocation problems

  • Predictive modeling and pattern recognition using machine/deep learning for artificial intelligence at scale

  • Productivity and cost-effectiveness analysis using econometrics for organizational performance improvement

  • Graph theoretic network science, graph mining and social network analysis in real-world, complex networks
Selected Publications

Bastian, N. (2020). Building the Army’s Artificial Intelligence Workforce: A Perspective. The Cyber Defense Review. In Press.

Bastian, N. & Hall, A. (2020). Military Workforce Planning and Manpower Modeling. In Natalie Scala & James Howard (Ed.), Handbook of Military and Defense Operations Research. Boca Raton, FL: CRC Press. In Press.

Bastian, N., Fisher, C., Hall, A. & Lunday, B. (2019). Solving the Army’s Cyber Workforce Planning Problem using Stochastic Optimization and Discrete-Event Simulation Modeling. Proceedings of the Winter Simulation Conference 2019, Military Applications Track (Ed. Mustafee et al.). In Press.

Shetty, S., Ray, I., Celik, N., Mesham, M., Bastian, N. & Zhu, Q. (2019). Simulation for Cyber Risk Management – Where are we, and where do we want to go. Proceedings of the Winter Simulation Conference 2019, Cyber Security Track (Ed. Mustafee et al.). In Press.

Bastian, N. (2019). Information Warfare and its 18th and 19th Century Roots. The Cyber Defense Review. In Press.

Robbins, M., Jenkins, P., Bastian, N. & Lunday, B. (2018). Approximate Dynamic Programming for the Aeromedical Evacuation Dispatching Problem: Value Function Approximation using Multiple Level Aggregation, Omega, Article in Press, 1-17.

Fulton, L. & Bastian, N.. (2018). Multi-Period Stochastic Programming Portfolio Optimization for Diversified Funds. International Journal of Finance and Economics, Online First, 1-15.

Bastian, N.., Swenson, E., Ma, L., Suk Na, H. & Griffin, P. (2017). Incentive Contract Design for Food Retailers to Reduce Food Deserts in the US. Socio-Economic Planning Sciences, 60: 87-98.

Paradarami, T., Bastian, N.. & Wightman, J. (2017). A Hybrid Recommender System Using Artificial Neural Networks. Expert Systems with Applications, 83: 300-313.

Bastian, N., Ekin, T., Kang, H., Griffin, P., Fulton, L. & Grannan, B. (2017). Stochastic Multi-Objective Auto-Optimization for Resource Allocation Decision-Making in Fixed-Input Health Systems. Health Care Management Science, 20(2): 246-264.

Ekin, T., Kocadagli, O., Bastian, N., Fulton, L. & Griffin, P. (2016). Fuzzy Decision-Making in Health Systems: A Resource Allocation Model. EURO Journal on Decision Processes, 4(3): 245-267.

Bastian, N. & Griffin, P. (2016). Multi-Criteria Network Design in Health and Humanitarian Logistics. In A. Ravi Ravindran (Ed.), Multiple Criteria Decision Making in Supply Chain Management (pp. 161 – 189). Boca Raton, FL: CRC Press.

Swenson, E., Bastian, N. & Nembhard, H. (2016). Data Analytics in Health Promotion: Health Market Segmentation and Classification of Total Joint Replacement Surgery Patients. Expert Systems with Applications, 60: 118-129.

Bastian, N., Griffin, P., Spero, E. & Fulton, L. (2016). Multi-Criteria Logistics Modeling for Military Humanitarian Assistance and Disaster Relief Aerial Delivery Operations. Optimization Letters, 10(5): 921-953.

Griffin, P., Nembhard, H., DeFlitch, C., Bastian, N., Kang, H. & Munoz, D. (2016). Healthcare Systems Engineering. Hoboken, NJ: John Wiley & Sons, Inc.

Bastian, N., McMurry, P., Fulton, L., Griffin, P., Cui, S., Hanson, T., & Srinivas, S. (2015). The AMEDD Uses Goal Programming to Optimize Workforce Planning Decisions. INFORMS Journal of Applied Analytics (formerly Interfaces), 45(4): 305-324.

Grannan, B., Bastian, N. & McLay, L. (2015). A Maximum Expected Covering Problem for Locating and Dispatching Two Classes of Military Medical Evacuation Air Assets. Optimization Letters, 9(8): 1511-1531.


For a full list of publications, please refer to Nathan’s Google Scholar page.