Adrian Barb, Ph.D.
Adrian S. Barb, associate professor of Information Science, received his B.S. in Industrial Engineering from the University of Bucharest. He earned his Ph.D. in Computer Science and MBA from the University of Missouri, where he also worked as a database programmer-analyst and web system coordinator. Dr. Barb teaches database management and information retrieval. His research interests include database management systems, knowledge discovery in databases, database indexing, knowledge representation and exchange in content-based retrieval systems, semantic modeling and retrieval, conceptual change in knowledge-based systems, ontology integration, and expert-in-the-loop knowledge exchange. His research interests include data mining, software estimation, database management systems, knowledge discovery in databases, database indexing, knowledge representation and exchange in content-based retrieval systems, semantic modeling and retrieval, conceptual change in knowledge-base systems, ontology integration, and expert-in-the-loop knowledge exchange.
Nathan Bastian, Ph.D.
Nathan Bastian, instructor of Supply Chain and Information Systems holds a Ph.D. in Industrial Engineering and Operations Research from the Pennsylvania State University, M.Eng. in Industrial Engineering from Penn State, M.S. in Econometrics and Operations Research from Maastricht University, and B.S. in Engineering Management (electrical engineering) with honors from the U.S. Military Academy at West Point. He is an experienced operations researcher, data scientist, decision analyst and industrial engineer who discovers and translates 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.
Mosuk Chow, Ph.D.
Dr. Mosuk Chow's areas of research interest include biostatistics, statistical decision theory, Bayesian inference, and sampling methods. An important question in statistical decision theory is to characterize the set of all optimal procedures. An admissible procedure is optimal in the weak sense that it cannot be outperformed by another procedure completely in all circumstances. It is thus desirable to find necessary conditions for admissible procedures. Her work in decision theory involves finding such necessary conditions, investigating the admissibility properties of various estimators for problems arising from biology, genetics, and fishery.
Since for most cases a necessary condition for admissibility is that the procedure corresponds to a generalized Bayes rule, Dr. Chow's research also covers Bayesian inference. With recent advances in Bayesian computation methods, she has used Markov chain Monte Carlo methods in some of her work. Currently she is interested in Bayesian inference for aggregated distributions under various sampling schemes and Bayesian approach to problems related to biostatistics.
Mohamad Darayi, Ph.D.
Mohamad Darayi, assistant professor of Systems Engineering, earned his Ph.D. in Industrial and Systems Engineering from the University of Oklahoma, M.S. in Industrial Engineering from Tarbiat Modares University, and B.S. in Industrial Engineering from University of Tabriz. His principal research interests and key publications lie in infrastructure network resilience and system simulation modeling and analysis applications in healthcare, manufacturing, supply chain, and logistics management. As a member of the Institute for Operations Research and the Management Sciences (INFORMS) and the Institute of Industrial and Systems Engineers (IISE), he has showcased his work at multiple international conferences.
Terry Harrison, Ph.D.
Terry Harrison, professor of Supply Chain and Information Systems and Earl P. Strong Executive Education Professor in Business, teaches Prescriptive Analytics for Business (BAN 550) as part of the certificate program. He is a Fellow and past president of the Institute for Operations Research and the Management Sciences (INFORMS) and is a former 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. Dr. Harrison earned his doctorate in Management Science from the University of Tennessee.
John I. McCool, Ph.D.
John I. McCool, distinguished professor of Systems Engineering, received his doctorate in Statistics from Temple University, and his bachelor and master of science in Mechanical Engineering from Drexel University. He teaches courses in statistics, experiment design, reliability, statistical process control, applied data mining, probability models, and optimization. His research includes statistical inference for the Weibull distribution and industrial statistics. He is a Fellow of the American Society for Quality and received the Irwin S. Hoffer Award from the ASQ’s Philadelphia Section for the promotion of statistical thinking.
Ashkan Negahban, Ph.D.
Ashkan Negahban, assistant professor in Engineering Management, earned his Ph.D. and M.E. from Auburn University and a B.S. from University of Tehran (all in Industrial and Systems Engineering). Prior to joining Penn State, he was an instructor at Auburn University where he taught courses in simulation modeling and analysis and probability and statistics. His research interests include the application of different types of simulation (discrete event, agent-based, and Monte Carlo) in manufacturing system design and operation and marketing-operations management interface. He has also developed several video-based e-learning series which have received world-wide publicity and are used by faculty from leading institutions around the world.
Colin J. Neill, Ph.D
Colin Neill, associate professor of Software Engineering and Systems Engineering and director of engineering programs, earned his doctorate in Software and Systems Engineering, M.Sc. in Communication Systems, and BEng in Electrical Engineering from the University of Wales, Swansea, United Kingdom. He teaches many courses in software and systems engineering, project management, and systems thinking. Prior to joining Penn State, Dr. Neill worked on time and mission-critical system modeling and design manufacturing systems and production management with the University of Wales, Swansea; Oxford University; the Rover Car Company; and British Aerospace. He is the author of over 80 articles on the development and evolution of complex software and systems and the management and governance thereof. 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. As Director of Engineering Programs, Dr. Neill oversees the Division’s portfolio of graduate degree programs delivered both in residence and online.
Chun-Kit Ngan, Ph.D.
Ben C.K. Ngan, assistant professor of Information Science, earned his Ph.D. in Information Technology and a graduate certificate in Database Management from George Mason University, his MBA in Management Information Systems from California State University, and his B.Eng. in Electronic Engineering from Hong Kong University of Science and Technology. While at George Mason University, Dr. Ngan spent years as an adjunct professor in the department of applied information technology, a bridge peer learning scholar at the Center for International Student Access, a graduate teaching assistant for the department of computer science. He is a member of IEEE Communications Society, IEEE Computer Society, EWG-DSS Euro Working Group on Decision Support Systems, IFIP WG8.3 on Decision Support Systems; a guest speaker at the Center for International Student Access at GMU; and a guest lecturer at the Dept. of Applied Information Technology at GMU, and the Dept. of Computer Science at GMU. Dr. Ngan has received numerous honors and awards and has published several articles, books, chapters, and workshop papers.
Guanghua Qiu, Ph.D.
Robin G. Qiu, professor of Information Science, earned his Ph.D. in Industrial Engineering from Penn State and his M.S. and B.S. from Beijing Institute of Technology, China. He teaches courses on data analytics, information science, software engineering, computer security, and enterprise service computing. Dr. Qiu’s research includes Service Science, Smart Service Systems, Big Data, Data/Business Analytics, Service Operations and Management, Information Systems and Integration, Supply Chain Management, and Control and Management of Manufacturing Systems. Dr. Qiu 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, PhD
Arvind Rangaswamy, Anchel Professor of Marketing, teaches Marketing Analytics (BAN 540) as part of the certificate program. He is actively engaged in research to develop concepts, methods, and models to improve the efficiency and effectiveness of marketing using information technologies, an area in which he is internationally recognized. Dr. Rangaswamy has consulted widely with companies and is a co-founder of DecisionPro, Inc. He is co-author of Marketing Engineering, a widely used textbook on marketing analytics. Previously, he was a member of the faculties at the Wharton School of the University of Pennsylvania and the Kellogg School of Management of Northwestern University. Dr. Rangaswamy earned his Ph.D. from Northwestern University.
Raghvinder Sangwan, Ph.D
Raghvinder S. Sangwan, associate professor of Software Engineering, holds a doctorate in Computer and Information Sciences from Temple University. He joined Penn State in 2003 after more than seven years in industry, where he worked mostly with large software-intensive systems in the domains of health care, automation, transportation, and mining. His teaching and research involve analysis, design, and development of software systems, their architecture, and automatic and semi-automatic approaches to assessment of their design and code quality, and he has several peer-reviewed publications in these areas. Dr. Sangwan actively consults for Siemens Corporate Research in Princeton, New Jersey, and also holds a visiting scientist appointment at the Software Engineering Institute at Carnegie Mellon University in Pittsburgh, Pennsylvania. He is also a senior member of the IEEE and the Association for Computing Machinery (ACM).
Durland L. Shumway, Ph.D
Dr. Durland Shumway's academic background is in the environmental sciences. He earned a M.S. in Ecology from Rutgers and a doctorate in Forest Science at Penn State in 1990. Dr. Shumway taught at Frostburg State University in Maryland as an associate professor of Forest Ecology where his research expertise was in tree architecture. In 2005, he returned to Penn State as a faculty consultant and research associate in the Department of Statistics. From 2007 to 2012 he served as the director of the department's Statistical Consulting Center. Today he teaches both online and resident courses in ANOVA, regression, and design of experiments, and is also currently working on developing case studies.
Aleksandra B. Slavkovic, Ph.D.
Dr. Aleksandra Slavković's past and current research interests include usability evaluation methods, human performance in virtual environments, statistical data mining, application of statistics to social sciences, algebraic statistics, and statistical approaches to confidentiality and data disclosure. Her Ph.D. dissertation work focuses on statistical methodologies for disclosure limitation and data confidentiality, and presents new theoretical links between disclosure limitation, statistical theory, and computational algebraic geometry. It is a unique and interesting integration of diverse results from conditional specification of joint distribution, graphical models, disclosure limitation, and algebraic statistics.
Dr. Slavković served as a consultant to the National Academy of Sciences/National Research Council Committee to Review the Scientific Evidence on the Polygraph in 2001 and part of 2002. In 2003 she received an honorable mention for the best student paper from the Committee on Statisticians in Defense and National Security of the American Statistical Association.
Christopher Solo, Ph.D.
Dr. Solo teaches a variety of courses in Supply Chain Management and Management Information Systems at Penn State. Prior to joining the Smeal faculty, Dr. Solo served over 21 years on active duty 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, Dr. Solo also served on the faculty at the U.S. Air Force Academy, where he taught undergraduate courses covering probability and statistics, optimization, decision analysis, queueing theory, and simulation. Dr. Solo retired from the Air Force in the rank of lieutenant colonel and is a member of the Institute for Operations Research and the Management Sciences (INFORMS).
Satish M. Srinivasan, Ph.D.
Satish M. Srinivasan, assistant professor of Information Science, received his B.E. in Information Technology from Bharathidasan University, India and M.S. in Industrial Engineering and Management from the Indian Institute of Technology Kharagpur, India. He earned his Ph.D. in Information Technology from the University of Nebraska at Omaha. Prior to joining Penn State Great Valley, he worked as a postdoctoral research associate at University of Nebraska Medical Center, Omaha. Dr. Srinivasan teaches courses related to database design, data mining, data collection and cleaning, computer, network and web securities, and business process management. His research interests include data aggregation in partially connected networks, fault- tolerance, software engineering, social network analysis, data mining, machine learning, Big Data and predictive analytics and bioinformatics.
Xi Zhang, Ph.D.
Xi Zhang, assistant professor of Data Analytics, received her B.S. and M.S. in Electrical Engineering from Shandong University. She earned her Ph.D. in Physics from Stevens Institute and Technology. Following her doctorate, Dr. Zhang worked as a post-doctoral researcher in quantitative finances on a project funded by the Chicago Mercantile Exchange examining analytic approaches to portfolio optimization, risk minimization, and corporate credit rating classification. Dr. Zhang teaches data mining and foundations of predictive analytics.