Jungsik Noh

Jungsik Noh is an Assistant Professor in the Lyda Hill Department of Bioinformatics at UT Southwestern Medical Center. He holds a Ph.D. in Statistics from Seoul National University (2000–2010) and has specialized in statistical methods for analyzing biomedical big data since 2014. His research focuses on integrating statistical modeling with bioinformatics to address complex biological problems, including cell migration dynamics, telomere biology, and pandemic modeling. Notably, his 2021 machine-learning pipeline for estimating hidden SARS-CoV-2 infections gained international attention across 20+ news outlets.

Research interests include:

• Statistical analysis of time-series and biomedical data
• Machine learning applications in epidemiology
• Actin cytoskeleton regulation and cell motility
• Quantitative approaches to cellular aging

Key contributions involve developing novel methodologies like the DynamicNeuronTracker for single-neuron analysis (2024) and advancing light-sheet microscopy techniques (2024). His work bridges computational statistics with experimental biology, addressing both fundamental and applied scientific challenges.

Lab activities center around the Noh Lab, focusing on systems-level analysis of cellular processes. While no specific grants or awards are listed, his work demonstrates significant societal impact through pandemic-related research and methodological innovations.