Nathaniel Bastian
Ph.D., Industrial Engineering and Operations Research, Penn State
M.Eng., Industrial Engineering, Penn State
M.S., Econometrics and Operations Research, Maastricht University
B.S., Engineering Management (Electrical Engineering) with Honors, U.S. Military Academy at West Point
Dr. Nathan Bastian is an instructor of supply chain and information systems. His expertise lies in the discovery and translation of data-driven, actionable insights into effective decisions using mathematics, statistics, engineering, economics, and computational science to develop decision-support models for descriptive, predictive, and prescriptive analytics. His teaching interests lie in the areas of decision analytics, data science, and applied econometrics. His research interests lie in the areas of multiple objective optimization and sequential decision-making under uncertainty.
Mohamad Darayi
Ph.D., Industrial and Systems Engineering, University of Oklahoma
M.S., Industrial Engineering, Tarbiat Modares University
B.S., Industrial Engineering, University of Tabriz
Dr. Mohamad Darayi, assistant professor of systems engineering, focuses his principal research and key publications on infrastructure network resilience and simulation modeling applications in health care, manufacturing, and supply chain management. He teaches courses in system simulation, risk analysis, network modeling, and data analytics.
Terry P. Harrison
Ph.D., Management Science, University of Tennessee
M.S., Management Science, University of Tennessee
B.S., Forest Science/Forest Products, Penn State
Dr. Terry Harrison, professor of supply chain and information systems and Earl P. Strong Executive Education Professor in Business, teaches Prescriptive Analytics for Business. He is a Fellow and past president of the Institute for Operations Research and the Management Sciences (INFORMS) and has served as a member of the INFORMS Analytics Certification Board. He has teaching and research interests in the areas of supply chain management and modeling, large-scale production and distribution systems, decision support systems, applied optimization, and the management of renewable natural resources.
Ashkan Negahban
Ph.D., Industrial and Systems Engineering, Auburn University
M.E., Industrial and Systems Engineering, Auburn University
B.S., Industrial and Systems Engineering, University of Tehran
Dr. Ashkan Negahban is an assistant professor of engineering management. Prior to joining Penn State, he was an instructor at Auburn University where he taught courses in simulation, probability theory, and statistics. His research interests include the application of different types of simulation (discrete event, agent-based, and Monte Carlo) in design and operation of complex systems. He has developed several e-learning modules that have received worldwide publicity and are used by faculty from leading institutions around the world.
Colin Neill
Ph.D., Software and Systems Engineering, University of Wales Swansea
M.Sc., Communications Systems, University of Wales Swansea
B.Eng., Electrical Engineering, University of Wales Swansea
Dr. Colin Neill is an associate professor of software engineering and systems engineering. He teaches many courses in software and systems engineering and project management. He is the author of more than 80 articles on the development and evolution of complex software and systems and their management and governance. Dr. Neill is a senior member of the IEEE, a member of INCOSE, and serves as associate editor-in-chief of Innovations in Systems and Software Engineering.
Robin G. Qiu
Ph.D., Industrial Engineering, Penn State
Ph.D., (Minor), Computer Science, Penn State
M.S., Numerical Control, Beijing Institute of Technology, China
B.S., Mechanical Engineering, Beijing Institute of Technology, China
Dr. Robin G. Qiu is professor of information science at Penn State. He teaches courses on data analytics, information science, software engineering, and cyber security. Dr. Qiu's research includes smart service systems, IoT, big data, data/business analytics, information systems and integration, supply chain and industrial systems, and analytics. He served as the editor-in-chief of INFORMS Service Science. He is an associate editor of IEEE Transactions on Systems, Man, and Cybernetics, and IEEE Transactions on Industrial Informatics, and has more than 160 publications.
Arvind Rangaswamy
Ph.D., Marketing, Northwestern University
MBA, Indian Institute of Management, Calcutta
B.Tech, Indian Institute of Technology, Madras
Dr. Arvind Rangaswamy is Anchel Professor of Marketing at the Smeal College of Business. His research is focused on methods and models to improve the efficiency and effectiveness of marketing using information technologies. He has published numerous professional articles on marketing analytics and online marketing in top academic journals. He has consulted for many companies, and is a principal and co-founder of DecisionPro, Inc.
Raghvinder S. Sangwan
Ph.D., Computer and Information Sciences, Temple University
M.S., Computer Science, West Chester University
B.S., Genetics and Plant Breeding, Haryana Agricultural University
Dr. Raghvinder S. Sangwan is an associate professor of software engineering. His teaching and research involves analysis, design and development of software-intensive systems, their architecture, and automatic/semi-automatic approaches to assessment of their design and code complexity. He actively consults for Siemens Corporate Technology in Princeton, New Jersey, and holds a visiting scientist appointment at the Software Engineering Institute at Carnegie Mellon University in Pittsburgh, Pennsylvania. He is a senior member of the IEEE and ACM.
Rashmi Sharma
Ph.D., Supply Chain and Information Systems, Penn State
MBA, Supply Chain Management, Penn State
Master of Computer Applications, Indira Gandhi National Open University
B.S., Mathematics, Statistics, Computer Applications, University of Rajasthan
Dr. Rashmi Sharma, assistant clinical professor of supply chain and information systems and managing director of the Laboratory for Economics, Management, and Auctions, will teach Predictive Analytics (BAN 840). Before coming to Penn State, she worked in the software industry and managed the development of business intelligence solutions for manufacturing. She has teaching and research interests in the areas of supply chain management, management science, business analytics, incentive design, and workforce management.
Chris Solo
Ph.D., Industrial Engineering and Operations Research, Penn State
M.S., Operations Research, Air Force Institute of Technology
B.S., Mathematics, Penn State
Dr. Chris Solo, clinical assistant professor of supply chain and analytics, teaches Business Strategies for Data Analytics (BAN 530). Dr. Solo previously served more than 21 years in the U.S. Air Force, where he held leadership positions in the intelligence, acquisition program management, and operations research analyst career fields. During this time, he also served on the faculty at the U.S. Air Force Academy, where he taught a variety of quantitative analysis courses. He is an active member of the Institute for Operations Research and the Management Sciences (INFORMS).
Satish Srinivasan
Ph.D., Information Technology, University of Nebraska at Omaha
M.S., Industrial Engineering and Management, Indian Institute of Technology, Kharagpur
B.S., Information Technology, Bharathidasan University
Dr. Satish Srinivasan is an assistant professor of information science in the Engineering division at Penn State Great Valley. Dr. Srinivasan teaches courses related to database design, data mining, data collection and cleaning, design and implementation of predictive analytics system, network and web securities, and business process management. His research interests include social network analysis, data mining, machine learning, Big Data and predictive analytics and bioinformatics.
Xi Zhang
Ph.D., Physics, Stevens Institute of Technology
M.S., Electrical Engineering, Shandong University
B.S., Electrical Engineering, Shandong University
Dr. Xi Zhang, assistant professor of data analytics, teaches data mining and foundations of predictive analytics.