Hi there! Nice to meet you.
About Me
I am a statistics/data science researcher and educator. I have been at Marquette University since fall 2020. During 2018-2020, I was doing my postdoctoral research at Rice University with Dr. Marina Vannucci, Dr. Meng Li and Dr. Simon Fischer-Baum on derivative Gaussian processes with applications in Event-Related Potentials (ERPs). I also worked with Shell as a data scientist doing spatial-temporal modeling on oil drilling such as switching dynamical systems. I was a PhD student in Statistics and Applied Mathematics (currently Statistical Science) at University of California, Santa Cruz, advised by Dr. Raquel Prado. Before enjoying California’s sunshine, I studied Economics and Statistics at Indiana University Bloomington (IUB).
I received my bachelor degree in Public Economics at National Chengchi University in my hometown Taipei, Taiwan.
Statistics/Data Science Degree Programs at Marquette
Our Statistics/Data Science programs include
- Statistical Science Major
- Data Science Major/Minor
- Applied Statistics Master
- Data Science Master
- Computational and Statistical Sciences Master/PhD
More information can be found in undergraduate and graduate pages. Welcome to send an email to cheng-han.yu@marquette.edu if you would like to discuss the programs with me.
Talks that Last
Scalable Spatially Varying Coefficient Models with Global-Deviation Spike-and-Slab Group Lasso
This paper proposes an SSGL method that decomposes spatially varying coefficients into global effects and selectable spatial deviations, accurately identifies which predictors require spatial variation, and improves estimation efficiency and computation relative to Bayesian spatial competitors, while simultaneous uncertainty calibration for highly localized effects remains challenging.
Read moreTeaching
MSSC 6975 - Practicum for Statistical Consulting
MSSC 6975 - Practicum for Statistical Consulting at Marquette University
Fall 2021
