Ashkan Negahban earned his Ph.D. and M.E. from Auburn University and a B.S. from University of Tehran (all in Industrial and Systems Engineering). His research involves stochastic simulation, statistical data analysis, and optimization techniques that aim to advance the science of decision-making in a wide range of applications. Dr. Negahban also conducts research related to novel learning environments in STEM education enabled by immersive simulations. His research has been supported by the National Science Foundation, Google, Microsoft, and several research institutes.
Dr. Negahban’s teaching primarily involves simulation and mathematical modeling courses. His video labs and simulation-based learning modules have received world-wide publicity and are used by faculty at various leading institutions.
VISTA Millennial Superstar Award, Chester County, Pennsylvania (2020)
Early Career Award for Research and Scholarship, Penn State Great Valley (2018)
ACM Special Interest Group on Simulation and Modeling (SIGSIM) Award (2014)
Outstanding Doctoral Fellow Award, Auburn University (2014)
- Discrete-event simulation
- Agent-based simulation
- Simulation-based optimization
- Statistical data analysis
- Immersive simulation-based learning in STEM education
Pallikere, Avinash, Robin Qiu, Parhum Delgoshaei, and Ashkan Negahban. “Incorporating occupancy data in scheduling building equipment: A simulation optimization framework.” Energy and Buildings, (2020). https://doi.org/10.1016/j.enbuild.2019.109655.
Sangwan, Raghvinder, Ashkan Negahban, Robert L. Nord, and Ipek Ozkaya. “Optimization of software release planning considering architectural dependencies, cost, and value.” IEEE Transactions on Software Engineering, (2020). https://doi.org/10.1109/tse.2020.3020013.
Negahban, Ashkan. “Simulation-based estimation of the real demand in bike-sharing systems in the presence of censoring.” European Journal of Operational Research 277, no. 1 (2019): 317-332.
Negahban, Ashkan, and Jeffrey S. Smith. "Optimal production-sales policies and entry time for successive generations of new products." International Journal of Production Economics 199, (2018): 220-232.
Negahban, Ashkan. “Optimizing consistency improvement of positive reciprocal matrices with implications for Monte Carlo Analytic Hierarchy Process.” Computers & Industrial Engineering 124, (2018): 113-124.
Negahban, Ashkan, and Jeffrey S. Smith. "A joint analysis of production and seeding strategies for new products: An agent-based simulation approach." Annals of Operations Research 268, (2018): 41-62.
Negahban, Ashkan, and Jeffrey S. Smith. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products." International Journal of Production Research 54, no. 13 (2016): 3852-3869.
Negahban, Ashkan, and Jeffrey S. Smith. "Simulation for manufacturing system design and operation: Literature review and analysis." Journal of Manufacturing Systems 33, no. 2 (2014): 241-261.
Negahban, Ashkan, and Levent Yilmaz. "Agent-based simulation applications in marketing research: An integrated review." Journal of Simulation 8, no. 2 (2014): 129-142.
Negahban, Ashkan, Levent Yilmaz, and Trenton Nall. "Managing production level in new product diffusion: An agent-based simulation approach." International Journal of Production Research 52, no. 17 (2014): 4950-4966.
B.S., Industrial and Systems Engineering, University of Tehran
M.E., Industrial and Systems Engineering, Auburn University
Ph.D., Industrial and Systems Engineering, Auburn University