"When it came to real-world complexities, the elegant equations and the fancy mathematics he’d spent so much time on in school were no more than tools – and limited tools at that" -- The Emerging Science at the Edge of Order and Chaos (by M. Mitchell Waldrop)
"I knew that if I failed I wouldn't regret that, but I knew the one thing I might regret is not ever having tried" -- Jeff Bezos' version of "regret minimization"
"一把青秧插野田, 低头便见水中天, 六根清净方为道, 退步原来是向前"
(*Ph.D and Graduate Research Assistant positions are available)
Professional Experiences:
2023 ~ present: David M. McKenney Family Associate professor, ISyE, Georgia Tech.
2023 ~ 2023: John L. Imhoff Endowed Chair and Assistant Professor, Department of Industrial Engineering, University of Arkansas.
2017 ~ 2023: Assistant Professor, Department of Industrial Engineering, University of Arkansas.
2015 ~ 2017: Research Staff Member (RSM), IBM Thomas J. Watson Research Center, Yorktown Heights, New York.
2012 ~ 2015: Research Staff Member (RSM), IBM Smarter Cities Research Collaboratory, Singapore.
2013 ~ 2016: Adjunct Assistant Professor, Department of Industrial and Systems Engineering, National University of Singapore.
Domain-Aware Statistical Learning
--- The Integration of Scientific and Engineering Knowledge into Data-Driven Solutions
1️⃣ Statistical Learning for Physical/Engineering Processes:
physics-informed statistical learning and prediction for nonlinear dynamics (e.g., advection-diffusion, collision, etc.).
machine learning for adaptive reduced-order modeling.
inverse modeling and optimal sampling.
2️⃣ Resilience & Environment
wildfires and power grid resilience.
remote-sensing data modeling and environmental processes (e.g., propagation of smoke and aerosols).
stochastic degradation and maintenance, reliability, and survival analysis.
3️⃣ Data Science & Applied Statistics
ensemble trees for recurrence data, gradient boosted trees for Gaussian process, structural boosting trees for edge detection, etc.