Bringing 13 years of research and business consulting experience in business data analysis and system design, this information systems and decision sciences expert specializes in predictive analytics, business intelligence, data mining, and quantitative decision support. Technical expertise includes data warehousing, ETL integration of heterogeneous data sources, multidimensional analysis, advanced reporting, custom KPI development, structured and unstructured data mining, clickstream analysis, predictive modeling, Monte Carlo simulation, and interpretation of analytical outputs for decision-risk assessment. The supplied materials do not document prior expert witness, deposition, or courtroom testimony experience.

Applied work has included the design and implementation of executive reporting and automated forecasting systems, healthcare text-mining applications, survey research automation, valuation modeling, contract-management platforms, automotive warranty classification, e-commerce navigation analysis, and large-scale electricity-market forecasting. Additional technical experience encompasses logical data modeling, software and database design, numerical simulation, model development and comparison, and integration of structured and unstructured information within data warehouses. His consulting and research background combines software development, statistical and analytical modeling, database environments, and business-oriented interpretation of complex data.

Educational attainment includes a doctoral degree, with an academic background bridging business and computer science. Professional leadership includes service as a professor of information systems and decision sciences and as founder and managing partner of an analytics consulting practice. His scholarly record includes more than 40 peer-reviewed publications, research in electronic commerce, business research, information processing, operations research, scheduling, and data warehousing, and co-authorship of a monograph addressing web-based information filtering and data-warehouse integration. This combination of predictive analytics, system design, quantitative modeling, and applied business consulting supports evaluation of analytical methodology, data quality, forecasting models, reporting systems, and decision-support processes.