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Sanjay Bapna > Sanjay Bapna

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    Sanjay Bapna

    Expertise

    Business Intelligence: BI Strategy, Datawarehouse Management and Schema Design, Security, Privacy, Performance Metrics, Alert design, OLAP, GIS, SAP BI and BusinessObjects

    Business Data Mining: Processes and Methodologies for Data mining, Classification Models, Clustering Models, Association Rule Models

    Modeling: Logit Models, Census, Household surveys, BLS, BEA, Demographics, Econometric Models, X-12-Arima, Time Series Models, Cost/Benefit Analysis and related Modeling

    Computer Security: Cyber-security, Cyber-terrorism, Risk Analysis

    Innovation: Drivers of Innovation, Metrics for Innovation

    Artificial Intelligence: Genetic algorithms, Neural Networks, Tabu Search, Simulated Annealing

    Industries: Unsecured Credit Industry, Commercial Vehicle Transportation, Intelligent Transportation Systems, Transportation Regulations

    Awards

    Best Application Paper Award, Nov. 2011, National Decision Sciences Institute, Boston.

    Best Interdisciplinary Paper Award, Nov. 2009, National Decision Sciences Institute, New Orleans.

    Outstanding Service Award, July 1994, International Business Schools Computing Association.

    Best Paper Award, Oct. 1994, International Association of Computer Information Systems.

    Recent Journal Publications

    Hua, J. & Bapna, S. “Who Can We Trust?: The Economic Impact of Insider Threats.” Journal of Global Information Technology Management

    Ramsey, G. & Bapna, S. “A Technique to Exploit Free-Form Notes to Predict Customer Churn.” International Journal of Computational Models and Algorithms in Medicine

    Hua, J. & Bapna, S. (2013).  Rethinking the Impact of Cyber Terrorism on Information Systems Security Investment, Journal of Strategic Information Systems, 22(2), 175-186.

    Hua, J. and S. Bapna (2012). “How Can We Deter Cyber Terrorism?” Information Security Journal: A Global Perspective 21(2): 102-114.

    Bapna, S. and S. C. Patel (2010). “Securing computerised models and data against integrity attacks.” International Journal of Electronic Finance 4(4): 343-354.

    Kumar, N., A. Gangopadhyay, S. Bapna, G. Karabatis and Z. Chen (2008). “Measuring interestingness of discovered skewed patterns in data cubes.” Decision Support Systems 46(1): 429-439.

    Bapna, S. and A. Gangopadhyay (2006). “A Wavelet‐Based Approach to Preserve Privacy for Classification Mining: Methodological Note.” Decision Sciences 37(4): 623-642.

    Kumar, N., A. Gangopadhyay, G. Karabatis, S. Bapna and Z. Chen (2006). “Navigation rules for exploring large multidimensional data cubes.” International Journal of Data Warehousing and Mining (IJDWM) 2(4): 27-48.

    Bapna, S. and A. Gangopadhyay (2005). “A web-based GIS for analyzing commercial motor vehicle crashes.” Information Resources Management Journal (IRMJ) 18(3): 1-12.

    Bapna, S. and J. N. D. Gupta (1997). “A Comparison between the Parthenogenetic Strategy and the Deterministic Threshold Accepting Strategy to Solve the Symmetric Traveling Salesman Problem.” International Journal of Management and Systems 13(2): 167-188.

    Bapna, S. and M. Chowdhury (1996). “An Application of Economic Forecasting Using Neural Networks.”  International Business Schools Computing Quarterly 8(1):1-10.

    Bapna, S. (1995). “The Role of Historically Black Colleges and Universities in preparing African-American Students for careers in Information Systems.” GATES: An international Journal 2(1): 47-56.

    Bapna, S. (1995). “Supporting Decisions for Multi-Project Software Engineering Projects.” Journal of Computer Information Systems 25(2): 16-19.

    Grants

    Shin, H., Bapna S., Farkas, A. “Measuring Economic Contribution of the Freight Industry to the Maryland Economy,” 2012-2013, Funded by State Highway Administration and National Transportation Center.

    Shin, H., and Bapna, S.  “Maryland Motor Carrier Program Performance Enhancement.,” 2010-2012 funded by State Highway Administration and National Transportation Center

    Bapna S. “Spatially Referenced Crash Data System for Application to Commercial Motor Vehicle Crashes,”  May 2003, Funded by Maryland Department of Transportation and The National Transportation Center

     The major objective of this project is to develop a Web-enabled prototype of an Accident Information System using GIS tools.  The system allows the user to drill down to perform detailed analysis.  Accident analysis is based on geographic region, accident severity, contributing circumstances, harmful event, weather condition, lighting condition, etc.  The prototype has subsequently been enhanced and is a starting guide for a production system in use for all crashes in Maryland.

    Bapna S., and J. Zaveri “Safety Profile of Commercial Motor Carriers Traveling in Maryland at the Perryville Scale House Under the Jurisdiction of the Maryland Transportation Authority Police (MdTAP),” January 2001, National Transportation Center, Baltimore.  102 pages. Funded by Maryland Department of Transportation and National Transportation Center

    Bapna S., and J. Zaveri “Safety Profile of Commercial Motor Carriers Traveling in Maryland at Two scale houses Under  the Jurisdiction of the Maryland State Police (MSP),”  November 2000, National Transportation Center, Baltimore.  216 pages.

    The major objective of this project is to collect, analyze, and document the safety profile of commercial motor vehicles traveling in Maryland.  Safety profile information includes ISS (Inspection Selection System) scores based on prior safety history of commercial motor carriers, average number of total violations and total out-of-service violations per inspection.  The distribution of safety ratings of commercial motor carriers traveling on three major routes inMarylandis provided.  The project also determines the effectiveness of using the ISS algorithm for the selection process of commercial vehicles for safety inspection.  This report based on the detailed analysis of the data collected will enable policymakers and commercial vehicle administrators to assess objectively the outcomes of the CVISN implementation.  This study may also help in evaluating the utility of safety algorithms like ISS and SafeStat and may promote fine tuning of these algorithms for improved performance and effectiveness.  This study will also assist the architects of the CVISN system to design and benchmark the system based on the needs of all the stakeholders.

    Bapna S., and J. Zaveri “Maryland Motor Carrier Program.  Safety Assurance Evaluation,” March 2000, National Transportation Center, Baltimore. 127 pages. Funded by Maryland Department of Transportation and National Transportation Center.

    The study evaluates the safety assurance activities ofMaryland’s Roadside Enforcement Program due to the current implementation of CVISN-related computer and communications systems used to collect and distribute safety-related data.  The following criteria are evaluated and compared for both electronic and manual inspections: efficiency and effectiveness of commercial vehicle and driver inspections in Maryland; availability of safety inspection data in a timely manner; driver and inspector satisfaction with the inspection processes; completeness and accuracy of inspection reports; and the efficiency of uploading inspection data.

    Bapna S., and J. Zaveri “Maryland Motor Carrier Program.  Safety Inspections of Commercial Vehicles at Maryland Weigh/Inspection Facilities,” March 2000, National Transportation Center, Baltimore.  35 pages.

    This paper documents the total number of safety inspections conducted at several fixed and roving weigh/inspection facilities in the state of Maryland.  This analysis is based on data collected from Maryland’s SAFETYNET.  Inspections are reported in terms of electronic (ASPEN) and manual inspections.

    Bapna, S., J. Zaveri, and Z.A. Farkas “Benefit-Cost Assessment of the Commercial Vehicle Information Systems Network (CVISN) in Maryland”, October 1998, National Transportation Center, Baltimore. 89 Pages. Funded by Maryland Department of Transportation and National Transportation Center.

    The objective of this study is to answer questions regarding the net benefits of Commercial Vehicle Information Systems and Networks (CVISN) deployment by the State ofMaryland.  The methodology consists of both quantitative and qualitative analyses of the benefits and costs of the CVISN project.  Costs and benefits are discounted to a present value over the economic life of the project.  The benefits and costs are assessed with regard to both agency and carrier interests, and the impact of CVISN on credential processing and safety enforcement is explored in detail.  The B/C ratios range from 3.28 to 4.68 for the worst and best case estimates for the benefits modeled.  The NPVs range from $76 million to $123 million.  For agencies and carriers, the worst B/C ratios are 1.45 and 6.67, respectively.

    Bapna, S., J. Zaveri, J., Z.A. and Farkas. “Benefit-Cost Assessment of the Commercial Vehicle Information Systems Network (CVISN) in Maryland: Executive Summary”, October 1998, National Transportation Center, Baltimore. 15 pages.

    Bapna, S., and J. Zaveri. “Commercial Vehicle Information Systems Network (CVISN) Baseline Study of Processes”, April 20, 1998, National Transportation Center, Baltimore. 186 pages. Funded by Maryland Department of Transportation and National Transportation Center.

    This document is a comprehensive study of all processes related to Commercial Vehicle Operations in the state ofMaryland.  Process descriptions using narratives, and data flow diagrams were documented along with operational statistics and other criteria of interest to evaluate the future implementation of CVISN. The following state agencies were studied:  Maryland Motor Vehicle Administration, Comptroller of the Treasury, State Highway Administration, Maryland Department of the Environment, Maryland State Police, Maryland Transportation Authority, Public Service Commission, and Maryland Port Administration.

    Bapna, S., and J. Zaveri. “Executive Summary of Commercial Vehicle Information Systems Network (CVISN) Baseline Study of Processes”, April, 1998, National Transportation Center, Baltimore. 30 pages.

    Conference Proceedings

    Mangle, A. and S. Bapna (2011). Progressing to Automated Strategic Actions: Traditional and Real-time Business Intelligence. Hawaii International Conference on Business.

    Hua, J. and S. Bapna (2011). Optimal IS Security Investment: Cyber Terrorism vs. Common Hacking. ICIS 2011, Shanghai, China.

    Hua, J. and S. Bapna (2011). Who Can We Trust?: The Influence of Insider Threats on IS Security. Proceedings of 42nd Annual Meeting of the Decision Sciences Institute, Atlanta, GA, Decision Sciences Institute.

    Hua, J. and S. Bapna (2010). How Can We Deter Cyber Terrorism? Proceedings of 41st Annual Meeting of the Decision Sciences Institute, Atlanta, GA, Decision Sciences Institute, 441-446.

    Hua, J. and S. Bapna (2009). The Impact of Cyber Terrorism on Investment for Information System Security Proceedings of 40th Annual Meeting of the Decision Sciences Institute, Atlanta, GA, Decision Sciences Institute pp:3151-3159.

    Bapna, S., A. Radhakrishnan, and A. Gangopadhyay (2008). AnonAggregate: Anonymizing Data Using Sequential Aggregation. Proceedings of 39th Annual Meeting of the National Decision Sciences Conference, Baltimore, MD, 1761-1765.

    Bapna, S., and S. Patel (2007). Securing Business Models and Data against Security Breaches. Proceedings of the 38th Annual Meeting of the National Decision Sciences Conference, Phoenix, AZ, 207, 4541-4546.

    Bapna, S. and J. Zaveri (2000). Perceived Benefits and Utilization of Technology: A Comprehensive Survey of the Maryland Motor Carrier Industry. ITS 2000, Boston, MA, Intelligent Transportation Society of America.

    Zaveri, J. and S. Bapna (2000). Comparison of Electronic (ASPEN) and Manual Inspections for Commercial Vehicles in Maryland. Proceedings of the 31st Annual Meeting of the National Decision Sciences Conference, Boston, 2000. pp. 671-673.

    Bapna, S., J. Zaveri and Z. A. Farkas (1999). Intelligent Transportation Systems: Benefit-Cost Assessment of CVISN in Maryland. ITS 99, Ninth Annual Meeting and Exposition Proceedings, Intelligent Transportation Society of America.

    Bapna. S., and J. Zaveri (1998) Maryland Commercial Vehicle Operations in the 21st Century, Proceedings of the 29th Annual Meeting of the Decision Sciences Institute, Las Vegas, NV

    Bapna, S. (1998). Virtual Reality for Abstract Data Applications. Proceedings of the 4th AMCIS 1998. Baltimore MD.

    Bapna S. (1998). Virtual Reality for Monitoring Stocks. Proceedings of the 2nd Annual Maryland Information Systems Workshop, 1998, BaltimoreMD.

    Bapna, S.. (1996). A comparison of the Aggressive with the Nonaggressive Parthenogenetic Search Strategy. Proceedings of the First INFORMS Conference on Information Systems and Technology, Pirkul, H., and Shaw, M.J., (editors), Washington D.C., 68-73.

    Bapna, S. (1995). Are Information Systems Professionals Averse to the Technical Career-Ladder?. Proceedings The Fourth Conference Urban Business Association, Amegbe,A.A., Windley, F.J., and Alford, H.L., (editors), 140-144.

    Bapna, S. (1994). Supporting Decisions for Multi-Project Software Engineering Projects. 1994 Proceedings of the Annual Conference of the International Association for Computer Information Systems 137-142.

    Bapna, S. and S. Gibson. (1994). Strategies for teaching the introductory Computer Information Systems Courses in Historically Black Colleges and Universities. Proceedings  of  the 22nd Annual Conference of International Business School Computing Association, Bapna, S., Emdad, A.F., and Zaveri, J., (editors), 318-325.

    Bapna, S. (1993) Candidate Lists based on the Regeneration of Solutions for the Symmetric Traveling Salesman Problem: Accelerating Global Optimization Strategies.  Proceedings of The Decision Sciences Institute, Perrewe, P.L., (editor), 1207-1209.

    Bapna, S. and J. Zaveri. (1993). Capturing  Structural Knowledge while Searching: An application to the Symmetric Traveling Salesman Problem. Proceedings of the 21st Annual Conference of the International Business Schools Computing Association, Elsea, J.E., and Cox, B.D., (editors), Denver, CO, 235-245.

    Zaveri, J. and S. Bapna. (1993). Discovering Scheduling Heuristics:  An AI-Based Approach. Proceedings of the 21st Annual Conference of the International Business Schools Computing Association, Elsea, J.E., and Cox, B.D., (editors), Denver, CO, 225-234.

    Bapna, S. and S. De (1993). Utilizing Captured Structural Knowledge to Solve the Symmetric Traveling Salesman Problem:  A Merge-Chain Tour Construction Heuristic. 1993 Proceedings Decision Sciences Institute, Rogers, D.F., and Raturi, A.S., (editors), Washington D.C., 1116-1118.

    Bapna, S. and S. De (1991). An Intelligent Search Strategy for Solving the Symmetric Traveling Salesman Problem, Proceedings of the 1991 IEEE International Conference on Systems, Man, and Cybernetics, Charlottesville, 579-583.