Modeling and Simulation of Complex Systems
My research primarily involves stochastic simulation (discrete-event, agent-based, and Monte Carlo), statistical data analysis, and optimization approaches in design and operation of complex systems. My methodological and applied research aim to develop innovative algorithms that contribute to the science of decision-making in a wide range of areas from queueing systems, supply chains, bike sharing, energy, and infrastructure resilience to infectious disease modeling and intersection of production and marketing strategies for innovations.
A. Negahban (PI), O. N. Bjornstad, M. Darayi, G. Qiu. “Optimizing COVID-19 Control Strategies in Public Transportation Enabled by Individual-Level Data Analytics and Simulations,” The Institute for Computational and Data Sciences, The Pennsylvania State University, April 2020 – October 2020, $15,105.
S. M. Srinivasan, R. Sangwan, A. Negahban (co-PI). “Impact of Social Distancing Measures on Social, Economic, and Emotional Well-Being When Managing Response to Pandemics,” Funded jointly by the Social Science Research Institute, the Institute for Computational and Data Sciences, and the Huck Institutes of the Life Sciences, The Pennsylvania State University, April 2020 – October 2020, $33,778.
A. Negahban (PI), G. Qiu, M. Stutman, S. W. Wagner. “Energy Efficient Buildings: Using Data Analytics to Incorporate Occupancy in Scheduling and Load Profiling,” Institutes for Energy and the Environment, The Pennsylvania State University. April 2018 – June 2019, $33,050.
M. Darayi, A. Negahban (co-PI), Q. Qiang, S. M. Srinivasan. “Leveraging Big Data for Holistic Analysis of PA’s Freight Transportation Infrastructure Resilience Subject to Natural and Man-Made Disasters,” The Center for Security Research and Education (CSRE), The Pennsylvania State University. January 2019 – December 2019, $71,437.
Immersive Simulation-Based Learning
The project involves designing, developing, and assessing the effectiveness of problem-based learning (PBL) via immersive simulations. An immersive simulation PBL module is a learning environment specified by: (a) A virtual setting (immersive simulation model) that resembles a real system/environment and enables contextually enriched, technology-enhanced active learning and can be explored on a 2D display or via a virtual reality (VR) headset (if available); (b) processes in the virtual environment that include multiple stations, and comprise technical as well as organizational aspects; (c) A set of products or entities that flow throughout the environment and are processed (e.g., manufactured, assembled, stored, transported); and, (d) a didactical concept that comprises formal and informal learning, enabled by own actions of the learners during and after virtual site visits/field trips based on remote active learning instead of on-site learning. These represent problems/projects inspired by real-world situations and tied to the emerging and growing STEM workforce needs. More information and open online immersive simulation PBL modules can be found in the project’s website: https://sites.psu.edu/immersivesimulationpbl/
A. Negahban (PI), O. Onipede, S. Ozden, O. Ashour, C. Millet. “Transforming Online and On-Campus Education through Simulated Real-World Inspired Industry Projects,” University Strategic Initiative Seed Grants, The Pennsylvania State University. January 2019 – December 2020, $59,348.
A. Negahban (PI). “Virtual Reality-Enabled Simulation Modules for Teaching and Learning of Modeling Concepts,” Teaching & Learning Innovation Grant, The Pennsylvania State University, February 2019 – May 2020, $8,200.