Uncertainty is ubiquitous in modeling complex systems in various scientific and engineering problems that involve stochastic processes, random parameters, unknown physics, noise, etc. Uncertainty quantification (UQ) is the science of quantitative characterization and reduction of uncertainties in real world problems. The behaviors of these problems are widely predicted using mathematical modeling and computer simulations. UQ methods aim to predict system responses against uncertain inputs, quantify confidence of the predictions, obtain optimized solutions that are stable across a wide range of inputs, reduce computational or experiment cost in engineering design of complex systems.
The Lehigh Uncertainty Quantification (LUQ) Group consists of researchers from engineering, mathematics and public health, and aims to promote multidisciplinary collaborations across different areas. Please explore our page to find out more about the people affiliated with our group, the research areas of our affiliated faculty members, our seminar series, and our events.