Focuses on fundamental developments in statistical machine learning and data modeling aimed at delivering novel methodologies and algorithms specifically tailored to address the challenges of industrial data. Industrial settings often involve complex systems monitored by multiple different sensors. Unlike conventional predictive models, this area focuses on systems exhibiting multiple fault/failure modes, systems comprised of multiple components with interactive degradation processes, and systems with high levels of data censoring and significant data quality issues. Research in this area involves fundamental statistical developments that can then be packaged into next-generation ML tools used by practitioners.

Video: Industrial Analytics & Machine Learning

Service Logistics & Intelligent MRO

Integrating analytics and optimization for service logistics and intelligent maintenance, repair and operations (MRO).

Cyber-Security & Data Privacy in IoT Systems

Developing modeling frameworks and architecture to enhance industrial ICS cyber-security and IoT data privacy.

The NASA HOME Space Institute

Developing autonomous predictive analytic for enabling self-awareness and self-sufficiency in deep space Smart Habitats.