Data-driven Risk and Decision Analysis
Research-paper seminar on data-driven risk analytics: Bayesian models, tree boosting, neural networks, time series and ensembles for risk-informed decisions.
Teaching
Courses in data analytics, predictive modeling and risk analysis.
University at Buffalo
Data Analytics and Predictive Modeling
Modern predictive modeling beyond linear regression: additive models, trees, boosting, bagging and model averaging, for graduate and undergraduate students.
Analytics and Computing for Industrial Engineers
Managing, analyzing and visualizing large data sets with R, using problems from manufacturing, service, healthcare and transportation.
Advanced Data Analytics and Predictive Modeling
Bayesian networks, multi-level models, neural nets, support vector machines and more, with data-driven labs and projects.
Earlier teaching
Graduate Seminar, Construction Engineering and Management
Orientation to the CEM specialty and M.S./Ph.D. requirements.
Life Cycle Engineering of Construction Facilities
Construction contracts, estimating, scheduling, cost, time, safety and quality. About 100 students.
General Chemistry
Stoichiometry, equilibrium, thermochemistry, bonding and more. About 120 students.