Alex’s research interests include machine learning, time series, multi-agent systems, uncertainty quantification, and scientific modeling. His recent focus is on developing trustworthy AI systems that can offer insightful guidance for critical decisions, especially in applications involving complex spatiotemporal dynamics. His work is primarily motivated by real-world problems in public health, environmental health and community resilience.
COntact
WebsiteLocation
Ann Arbor
Methodologies
Artificial Intelligence / Data Mining / Graph-Based Methods / Machine Learning / Networks
Applications
Biological Sciences / Complex Systems / Engineering / Healthcare Research /