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I am an assistant professor of Human Genetics in the University of Pittsburgh’s School of Public Health. As a computational biologist, I seek to identify novel therapeutic targets for human diseases from a comprehensive understanding of biology. To achieve this goal, I am using quantitative techniques designed to overcome various challenges in the efforts. To comprehensively decode dynamics in each biological layer, I apply big data analysis techniques (e.g., signaling processing or information-theoretic measures) on NGS data, such as WES, WGS, RNA-Seq, miRNA-Seq, ChIP-Seq, methyl-Seq, and single-cell RNA-Seq. To understand extensive interactions across different biological layers, I develop computational models that can incorporate thousands of variables (e.g., network models or Markov Chain). To identify therapeutic targets from a comprehensive understanding of the interactions, I develop computational/statistical models (e.g. deep-learning or machine-learning) that can learn the relationship by extensive computational optimization. During 15 years of my research, I have a solid track record in the development of quantitative methods and big-data-driven biological studies.
In the collaboration network from 24 hospitals across the nation, we develop 'precision medicine' strategies to treat sepsis by developing machine-learning and causal inference methods.
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Monday, April 18, 2022
7:00 AM – 8:00 AM US CST
Monday, April 18, 2022
7:00 AM – 8:00 AM US CST
Monday, April 18, 2022
7:00 AM – 8:00 AM US CST