Data Analytics
Data Analytics is a cornerstone of modern Industrial and Systems Engineering, integrating computation, statistics, optimization and machine learning to extract insight from complex data. The discipline provides the theoretical and methodological foundation for modeling uncertainty, identifying patterns and supporting informed decision-making across engineered and organizational systems.
ISE researchers in Data Analytics advance both fundamental methods and applied frameworks for analyzing data, building predictive models and designing algorithms that enhance the performance and resilience of systems.
The program’s work spans four core domains:
- Statistics and data analysis
- Predictive analytics
- Computing and computational methods
- Enterprise and business fundamentals
Research in this area develops statistical inference techniques, clustering and classification methods, graphical models and data-driven optimization approaches. Together, these tools enable the rigorous modeling, analysis, and control of complex systems that equip researchers and practitioners to translate data into actionable knowledge and design systems that learn and adapt over time.