Education

• B.M. in Peking University Health Science Center, 1998
• M.S. in Molecular Pathology, University of Pittsburgh, 2000
• M.S. in Biostatistics, University of Minnesota, 2002
• Ph.D in Biostatistics, University of Washington, 2007

Work experience

• Faculty member in Biostatistics Program, Fred Hutchinson Cancer Center, Seattle, WA [2007 - 2022]
  • Assistant professor 2007-2012, Vaccine and Infectious Disease Division
    • Lead statistician for phase 1-3 HIV prevention trials (Statistical Center for HIV & AIDS Research, SCHARP): PK & PD, randomization, sample size calculation, statistical analysis plan, interim analysis and early stopping rules
  • Associate professor 2013-2019, Public Health Science Division
    • Principal Investigator of NIH R01 project “Statistical methods for high-dimensional genetic association and sequencing studies”: lead and conduct methodology research in high-dimensional genetic analyses, gene-treatment interaction, mediation, regularized regression and ensemble methods
    • Principal Investigator of NIH R21 project “Genomic studies for understanding etiology of esophageal adenocarcinoma”: lead and conduct comparative genomics between US and Chinese cancers, next-generation sequencing, mutations and copy-number alterations
  • Full professor 2019-2022, Public Health Science Division
    • Multiple Principal Investigator for NCI, Cancer Early Detection Research Network, Data and Management Coordinate Center: Lead and conduct cancer biomarker trials, omics and high-throughput biomarker discovery and validation
    • Principal Investigator of NIH R01 project “Statistical genetics and genomics for epidemiologic research”: Lead and conduct methodology research in pharmacogenetics, cancer omics biomarker discovery, cancer DNA methylation, machine learning and high-dimensional cancer genomics analysis
• Biostatistics Senior Director, GRAIL LLC, Menlo Park, CA [2022 - present]
  • design and analysis of clinical studies for liquid biopsy and cfDNA-based MCED tests
  • cancer screening methodologies (statistics and math modeling)
  • Clinical evidence and data package for premarket approval (PMA) application of GRAIL’s MCED test

Expertise and skills

• biostatistics and epidemiologic analysis
  • randomized clinical trials (RCT), biomarker in RCT, subgroup analysis
  • cancer epidemiology
  • causal inference, confounding and mediation, instrumental variables
• cancer genetics and genomics
  • machine learning and classifiers for prediction
  • feature selection and high-dimensional inference