I am a Quantitative Analytics Program Associate at Wells Fargo. I received my Ph.D. in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. I was fortunate enough to be advised by Professor Kaibo Liu.
Before coming to the U.S., I received a Bachelor of Business Administration and a Bachelor of Economics in Statistics from Korea University, Seoul, South Korea.
[Google Scholar] [LinkedIn] [CV] (Last updated: Aug, 2025)
Contact: yekwonhuh@gmail.com
About me
I work at the intersection of machine learning, statistical modeling, and engineering to develop predictive tools that support decision-making in complex environments. My goal is to create accurate, interpretable, and reliable models for real-world engineering applications such as manufacturing, healthcare, energy, and material science.
Research Interests
Prediction & data-driven decision making under uncertainty
Degradation modeling with multimodal data
Explainable & domain-aware ML/AI methods for prognostics
Education
Ph.D. Industrial and Systems Engineering, University of Wisconsin-Madison 2020 - 2025
Minor: Computer Science
M.S. Statistics, University of Wisconsin-Madison 2023 - 2024
B.B.A., Korea University 2014 - 2020
B.E. Statistics, Korea University 2014 - 2020
Leave of absence due to mandatory military service 2015 - 2016
Skills
Statistical Models: Bayesian statistics, Markov Chain Monte Carlo, Bayesian Neural Networks, Uncertainty Quantification, Hierarchical Bayesian Modeling, Gaussian Processes, Deep Survival Models
Programming: Python (Pytorch, TensorFlow, Scikit-learn, Huggingface, SciPy), R, SQL, Matlab, AWS Sagemaker, Stan
Updates
July '25: I have started a new position as a Quantitative Analytics Program Associate at Wells Fargo!
May '25: I have successfully defended my dissertation "Explainable Prognostics and Data-driven Modeling of Complex Data in Smart and Connected Systems"! A special thanks to my advisor, Professor Kaibo Liu, and my committee for their guidance and support.