SAMSI Introduces NEW 2017-2018 Postdoctoral Fellows

Institute: SAMSI     October 2017

SAMSI welcomes the 2017-2018 Program Postdoctoral Fellows. These eight young professionals will spend the next two years working in their assigned programs: Program on Mathematical and Statistical Methods for Climate and the Earth System (CLIM) or the Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics (QMC). This year’s postdoctoral fellows will bring their own unique talents to work for SAMSI’s programs. SAMSI is proud to present this year’s group!

Cheng Cheng

Cheng Cheng
Cheng is in the SAMSI QMC Program. She earned her Ph.D. in Mathematics from the University of Central Florida in 2017. Her research interests include applied and computational harmonic analysis, emphasis on sampling theory in signal processing, and high dimensional data analysis.

Yawen Guan

Yawen Guan
Yawen is in the SAMSI CLIM Program. She received her Ph.D. in statistics from Pennsylvania State University. During her graduate studies, she was fortunate to work with top scientists in the study of the Antarctic Ice Sheet. She was intrigued by the ice sheet physics and developed a statistical method to combine physics and multiple data sets to study ice streams on West Antarctica. Her research interests are spatial statistics, Bayesian modeling and computational methods for large data.

Huang Huang

Huang Huang
Huang is in the SAMSI CLIM Program. He received his Ph.D. in Statistics from King Abdullah University of Science & Technology (KAUST). His research experiences include computational methods for spatio-temporal statistics and functional data analysis. He enjoys using these statistical tools to collaborate with other scientists who have expertise in climate, oceanography, geophysics, etc., in order to explore interesting environmental problems.

Whitney Huang

Whitney Huang
Whitney is in the SAMSI CLIM Program. His research focuses on statistics of extremes and spatial, spatio-temporal data analysis with applications in climate. Ultimately, his research goal, as a statistician, is to bridge the gap between statistics and atmospheric/oceanic sciences. In his spare time he enjoys hiking, travel, and watching sports (basketball, tennis).

Maggie Johnson

Maggie Johnson
Maggie is in the SAMSI CLIM Program. She received her Ph.D. in Statistics from Iowa State University in 2017. Her broad research interests are in developing statistical methods for solving environmental problems. Some of her particular statistical research interests are in temporal and spatiotemporal statistics, Bayesian statistics, hierarchical modeling, and mixture models. She is originally from Minnesota where her family owns a Highland cattle farm, and in her spare time she enjoys cooking, fly-fishing, and woodcarving.

Mikael Kuusela

Mikael Kuusela
Mikael is in the SAMSI CLIM Program. He is a statistician working on data analysis methods for physical science applications. He is currently working on developing spatio-temporal interpolation techniques for analysis of oceanographic data from Argo profiling floats. In his free time, he enjoys traveling to far-away places, hiking in the summer and skiing in the winter.

Matthias Sachs

Matthias Sachs
Matthias is in the SAMSI QMC Program. During his Ph.D. he has have been working on numerical methods for ergodic stochastic differential equations. He has focused his efforts towards working on discretization methods for variants of the Langevin equation with applications in canonical sampling and molecular modelling. He is currently exploring the application of these models in sampling problems in Bayesian statistics and machine learning.

Christian Sampson

Christian Sampson
Christian is in the SAMSI CLIM Program. He just received his Ph.D. in mathematics from the University of Utah this year. His research interests lie at the interface between geophysics and mathematics. He is interested in sea ice and its role in the Earth’s climate system. While at SAMSI, he will be working with Professor Chris Jones at UNC Chapel Hill.