
About
Jason Xu is an Associate Professor of Biostatistics at the University of California Los Angeles (UCLA), with a courtesy appointment in Duke University's Statistical Science department. He holds a Ph.D. in Statistics from the University of Washington (2016) and a BS in Mathematics from the University of Arizona (2012). His research focuses on statistical methodologies for stochastic processes, with applications in epidemiology, cancer biology, and machine learning. Xu has led NSF-funded projects investigating epidemic dynamics on adaptive networks and cancer latency modeling through semi-Markov processes. He teaches advanced courses in Bayesian inference, time series analysis, and statistical computing. Notable recognitions include the NSF Postdoctoral Fellowship and NDSEG Fellowship.
Research Interests:
- Stochastic modeling of biological systems
- Bayesian computational methods
- Epidemiological network analysis
- Cancer stem cell dynamics
- Optimization algorithms for statistical inference
Grants & Awards:
- RAISE: IHBEM Grant (NSF, $2M, 2022-2026)
- NSF Postdoctoral Research Fellowship (2018-2021)
- NDSEG Fellowship (2013-2016)
Labs/Teams: Core member of UCLA's Biostatistics Computational Biology Group, collaborating with Duke's Statistical Science group on multi-institutional projects.
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