معرفی
Michael D. Porter is an Associate Professor in the School of Data Science and the Department of Engineering Systems and Environment at the University of Virginia. His work bridges data science, systems engineering, and applied statistics, with a focus on real-world forecasting and pattern detection problems.
His research interests include event prediction, machine learning, computational statistics, data linkage, and reproducible research. These areas are applied to critical domains such as crime analysis, terrorism, social media dynamics, and traffic safety. His development of self-exciting point process models has led to impactful forecasting tools.
Porter holds a Ph.D. in Systems and Information Engineering from the University of Virginia, an M.S. in Systems Engineering from Vanderbilt University, and a B.S. in Industrial Engineering from Purdue University.
The available publications suggest a strong trend in statistical modeling for event forecasting, particularly using point processes and machine learning techniques applied to public safety and behavioral data.
- Winning performance in NIJ's Real-time Crime Forecasting Challenge
Dr. Porter has advised academic programs and taught courses across multiple institutions, including the Darden School of Business and the University of Alabama. He emphasizes data-driven decision-making and reproducible research in his pedagogy. While specific grants are not listed, his applied research suggests involvement in funded projects related to public safety analytics.
He is affiliated with the University of Virginia's data science and engineering faculties, contributing to interdisciplinary research and education. His work is supported through academic collaboration and application-driven modeling.
