Since December 2017, Jungsik Noh has been appointed as an Assistant Professor in the Lyda Hill Department of Bioinformatics. He received his Ph.D. in Statistics from Seoul National University in Korea (2000–2010), where he developed the expertise in time series analysis and general statistical principles. Since 2014, he has been working at UTSW developing statistical methods that can resolve the complexity of modern biomedical big data. In 2021, he developed and published a machine-learning based pipeline for COVID-19 data to estimate the numbers of currently infected populations worldwide that are hidden due to under-ascertainment of the COVID infections. This study was addressed in >20 news outlets worldwide.
- Causal inference for time series of microscopic images
- Statistical methods for genomic data
- Time series analysis
- Estimation of the fraction of COVID-19 infected people in U.S. states and countries worldwide.
- Noh J, Danuser G, PLoS One 2021 16 2 e0246772
- Spatiotemporal dynamics of GEF-H1 activation controlled by microtubule- and Src-mediated pathways.
- Azoitei ML, Noh J, Marston DJ, Roudot P, Marshall CB, Daugird TA, Lisanza SL, Sandí MJ, Ikura M, Sondek J, Rottapel R, Hahn KM, Danuser G, J Cell Biol 2019 09 218 9 3077-3097
- Quantile regression estimator for GARCH models
- Lee, S. and Noh, J. Scandinavian Journal of Statistics 2013 40 1 2-20
Honors & Awards
- National Institute of Biomedical Imaging and Bioengineering (NIBIB/NIH) K25 Award