Prior to joining the Heinz School faculty, Professor Roehrig was a research mathematician at the Coast Guard R&D Center in Groton, Conn., where he focused on analytical and simulation models of Coast Guard missions, and their integration in model management systems.
Professor Roehrig's current research interests include uncertainty management in artificial intelligence, the use of decision models in conjunction with those methods, and the use of numerical methods for logical inference. His recently completed dissertation "Probabilistic and Defeasible Reasoning Using Extended Path Analysis" shows how the statistical technique of path analysis can be reinterpreted as a means of organizing and propagating probabilistic belief in expert systems.
Professor Roehrig received a bachelor's degree in mathematics from Suffolk University, Boston, a master's degree in mathematics from the University of Rhode Island, and a PhD in information systems from the Wharton School, University of Pennsylvania.
"Disclosure Detection in Multivariate Categorical Databases" (with S. Dutta Chowdhury, G. Duncan, R. Krishnan, and S. Mukherjee); Management Science, forthcoming.
"The Relationship Between Advertising and Content Provision on the Internet" (with Y. Yuan and J. Caulkins); European Journal of Marketing, forthcoming.
"Disclosure Detection in Multiple Linked Categorical Datafiles; A Unified Network Approach" (with Rema Padman, George Duncan, and Ramayya Krishnan); Proceedings of Statistical Data Protection '98, Lisbon, Portugal, forthcoming.
"Modeling Management in Electronic Markets for Decision Technologies: A Software Agent Approach" (with H.K. Bhargava, R. Krishnan, M. Casey, D. Kaplan, and R. Muller); Proceedings of the 30th Hawaii International Conference on System Sciences, 1997.
"Cell Suppression to Limit Content-Based Disclosure" (with G. Duncan, R. Krishnan, R. Padman, P. Reuther); Proceedings of the 30th Hawaii International Conference on System Sciences, 1997.
"Incompletely Specified Probabilistic Networks," Journal of Management Information Systems, Vol. 12, pp. 81-96, 1995-96.
"On the Duration of Copyright Protection for Digital Information" (with Yuehong Yuan); The Internet and Telecommunications Policy: Selected Papers from the 1995 Telecommunications Policy Research Conference; Erlbaum, Hillsdale, New Jersey, 1996.
"Numerical Inference on Statistical Databases" (with Sumit Dutta Chowdhury, George Duncan, Ramayya Krishnan, and Sumitra Mukherjee); Proceedings of the 29th Hawaii International Conference on System Sciences, 1996.
"Path Analysis and Probabilistic Networks," Decision Support System, Winter 1995.
"A Genetic Programming Approach for Heuristic Selection in Constrained Project Scheduling" (with Rema Padman); Computer Science and Operations Research: Recent Advances in the Interface (R. Helgason, ed.), Kluwer, 1995.
"Service Models, Operational Decisions and Architecture of Digital Libraries" (with Yuehong Yan); Proceedings of Digital Libraries '95, (F. Shipman, R. Furata, and D. Levy, eds.), Austin, Texas, June 1995.
"Probabilistic Inference and Path Analysis," Decision Support Systems, Elsevier, 1995.
PhD, Information Systems, The Wharton School, University of Pennsylvania
Home-delivered meals (HDM) provision is a volunteer-staffed activity for which little strategic planning is currently performed. This paper presents and evaluates a Genetic Algorithm to solve the HDM location routing problem (LRP). This planning model addresses facility location, allocation of demand to facilities, and design of delivery routes, while balancing efficiency and effectiveness considerations. We provide computational results on benchmark LRP instances.
This paper defines a policy system to be a collection of hardware, software, communication technologies, persons, procedures, protocols, and standards driven by and for the purpose of advancing a public organization’s mission in regard to policy analysis, planning, and program evaluation decisions. While policy systems already exist in practice, they have not been identified and studied as a separate, distinguishable area of information systems. They have components and patterns of use that could benefit governments of all levels in carrying out policy making. This paper proposes principles for building policy systems, identify their components, discuss how they address the complexities of policy making, illustrate them with several examples including a policy system built for a local government agency, and distinguish them from related systems such as management information systems, decision support systems, and collaboratories.(Download)
Government agencies collect and disseminate data that bear on the most important issues of public interest. Advances in information technology, particularly the Internet, have multiplied the tension between demands for evermore comprehensive databases and demands for the shelter of privacy. In mediating between these two conflicting demands, agencies must address a host of difficult problems. These include providing access to information while protecting confidentiality, coping with health information databases, and ensuring consistency with international standards. The policies of agencies are determined by what is right for them to do, what works for them, and what they are required to do by law. They must interpret and respect the ethical imperatives of democratic accountability, constitutional empowerment, and individual autonomy. They must keep pace with technological developments by developing effective measures for making information available to a broad range of users. They must both abide by the mandates of legislation and participate in the process of developing new legislation that is responsive to changes that affect their domain. In managing confidentiality and data access functions, agencies have two basic tools: techniques for disclosure limitation through restricted data and administrative procedures through restricted access. The technical procedures for disclosure limitation involve a range of mathematical and statistical tools. The administrative procedures can be implemented through a variety of institutional mechanisms, ranging from privacy advocates, through internal privacy review boards, to a data and access protection commission.(Download)
This paper provides geographic information system (GIS) methods and empirical models to forecast point demand for home-delivered goods. A point forecast consists of stops on a street network, including demand at each stop. The purpose of the forecast is to support a network optimization model, based on the traveling salesman problem, to locate one or more new facilities in a region. This paper illustrate the approach with a case study of home-delivered meals (meals ons wheels) in Allegheny County, Pennsylvania.
This paper presents a GIS-based decision support system for the non-profit sector, designed to assist strategic and tactical decision making in the area of home-delivered services such as meals on wheels. Using data collected from existing programs, current and forecasted demographic data, and a series of algorithmic tools, this paper provides a system for evaluating current meals on wheels facilities, and for making facility location decisions that satisfy coverage and equity requirements.(Download)
Incompletely Specified Probabilistic Networks(Download)