Curriculum vitae

Current

Postdoctoral Research Fellow, Harvard T.H. Chan School of Public Health

Education

• Ph.D. in Bioinformatics, UCLA, 2018
• B.S. in Computer Science, UCLA, 2013

Publication

• Shi H., Mancuso N., Spendlove S., Pasaniuc B. Local genetic correlation gives insights into the shared genetic architecture of complex traits

• Mancuso N., Shi H., Goddard P., Kichaev G., Gusev A., Pasaniuc B. Integrating gene expression with summary association statistics to identify susceptibility genes for 30 complex traits.

• Shi, H., Kichaev, G., Pasaniuc B. Contrasting the genetic architecture of 30 complex traits from summary association data. (American Journal of Human Genetics, 2016)

• Gusev A., Ko Arthur., Shi H., Bhatia G., Price A., Pajukanta P., Pasaniuc B., et al. Integrative approaches for large-scale transcriptome-wide association studies. (Nature Genetics, 2016)

• Gusev A., Shi H., Kichaev G., Price A., Pasaniuc B., et al. Genomic functional atlas of prostate cancer heritability in European and African Americans reveals extensive tissue-specific regulation. (Nature Communication, 2016)

• Shi, H., Pasaniuc, B., Lange, K. A multivariate Bernoulli model to predict DNaseI hypersensitivity status from haplotype data. (Bioinformatics, 2015)

• Pasaniuc B., Zaitlen N., Shi H., Bhatia G., Gusev A., Pickrell J., Hirschhorn J., Strachan D.P., Patterson N., Price A.L. Fast and accurate imputation of summary statistics enhances evidence of functional enrichment. (Bioinformatics, 2014)

• Orozco L.D., Morselli M., Rubbi L., Guo W., Go J., Shi H., Lopez D., Furlotte N.A., Bennett B.J., Farber C.R., Ghazalpour A., Zhang M.Q., Bahous R., Rozen R., Lusis A.J., Pellegrini M. Epigenome-wide association of liver methylation patterns and complex metabolic traits in mice. (Cell Metabolism, 2015)

Software

• HESS: Heritability Estimation from Summary Statistics
• ImpG-Summary: Gaussian imputation of summary statistics
• I am also involved in TWAS.

Skills

• C, C++, Java, CUDA, Matlab, Python, R, Unix shell script, Graphics Processing Unit, Computing Cluster

Courses

• Applied Probability, Bayesian Statistics, Theoretical Statistics, Statistical Methods in Computational Biology, Multivariate Analysis, Machine Learning and Pattern Recognition
• Linear Programming, Convex Optimization, Optimization Methods for Large-Scale Systems, Monte Carlo Methods for Optimization, Optimization Methods in Biology, Matrix Algebra and Optimization