Lab Homepage: http://tsenglab.biostat.pitt.edu/. My research interests focus on statistical applications of genomics and bioinformatics. We mainly work on data mining of high-throughput genomic, transcriptomic and proteomic data (such as microarray, next-generation sequencing and mass spectrometry data) and develop methods in study design, candidate marker detection, supervised machine learning (classification), unsupervised machine learning (clustering), high-dimensional feature selection and other topics driven by biological problems. Related research also include statistical modelling, statistical computing, graphical visualization of data, omics data integration and neuroimaging. Collaboration with biology labs plays an important role where most of our projects and methodological ideas come from.
- 1997 | National Taiwan University, Taiwan | BS in Mathematics
- 1999 | National Taiwan University, Taiwan | MS in Mathematics (specialized in Statistics)
- 2003 | Harvard School of Public Health, Boston, MA | ScD in Biostatistics (specialized in Bioinformatics)
- Clinical Research Scholar (K12) Award, Clinical and Translational Science Institute (CTSI), NIH. 2007-2009.
- Elected Member, International Statistical Institute (ISI). 2012.
- Statistician of the Year, American Statistical Association (ASA) Pittsburgh Chapter. 2017.
- Elected Fellow, American Statistical Association (ASA). 2017.
- Provost's Award for Excellence in Mentoring. University of Pittsburgh. 2019.
- BIOST 2055 Introductory high-throughput genomic data analysis I: data mining and applications. (offered every other year in the fall)
- BIOST 2078 Statistical Learning in High-Dimensional Data with Omics Applications. (offered every other year in the spring)
See Lab Homepage: http://tsenglab.biostat.pitt.edu/.