Richard Povinelli

Richard Povinelli is Professor and Director of Computer Engineering Laboratories at Marquette University's Opus College of Engineering. His research develops machine learning methods for time series analysis with applications in energy forecasting, biomedical signal processing, and industrial systems. Award-winning contributions include PhysioNet Challenge solutions for cardiac arrhythmia detection.

Research pillars:

• Deep neural networks for natural gas demand forecasting
• Anomaly detection in smart meter data
• Nonlinear signal processing for ECG classification
• Computer vision for industrial defect detection

Recent publications demonstrate innovation in hierarchical forecast reconciliation for energy systems, dynamical modeling of medical prognostics, and image-based quality control. Collaborative projects with Apache Corporation have developed pipeline alarm prediction systems using extremal quantile regression.