About

I currently work as a quantitative researcher for Voleon Group, where I develop machine learning models to predict stock movement and optimization framework for portfolio construction. I got my PhD in Biostatistics from Yale University in 2018 and my research focuses on building genetic risk prediction models leveraging diverse types of data. I enjoy working with data and making real-world impact using statistics and machine learning.

Experience & Education

2018 - present, Senior Member of Research Staff, Voleon Group, Berkeley CA
2013 - 2018, PhD in Biostatistics, Yale University, CT
2009 - 2013, B.Sc in Mathematics and Statistics, Peking University, China

Publication

google scholar

[14] Hu, Y., Zhao, Z., Lu, Q., Zhao, H. (2020+) A cross-trait genetic risk prediction framework leveraging biobank-scale GWAS summary statistics. In preparation

[13] Hu, Y., Li M. , Lu Q. , Wang J., Li B., Muchnik S., Shi Y., Kunkle B., Mukherjee S., Crane P., Zhao H. (2019) A statistical framework for cross-tissue transcriptome-wide association analysis. Nature Genetics, 51(3), 568-576. Winner of the ASA 2020 Outstanding Statistical Application Award

[12] Harvey P., Sun N., Bigdeli T., Fanous A., Aslan M., Malhotra A., Lu Q., Hu Y., Li B., Chen Q., Mane S.,Miller P., Rajeevan N., Sayward F., Cheung K., Li Y., Greenwood T., Gur R., Braff D., Consortium on the Genet- ics of Schizophrenia (COGS), Brophy M., Pyarajan S., Gleason T., Przygodszki R., O’Leary T., Muralidhar S., Gaziano M., Million Veteran Program (MVP), Huang G., Concato J., Zhao H., Siever L. (2019). Genome-wide association study of cognitive performance in US veterans with schizophrenia or bipolar disorder. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 183(3), 181-194.

[11] Gelernter J., Sun N., Polimanti R., Levey D., Pietrzak R., Bryois J., Lu Q., Hu Y., Li B., Radhakrishnan K., Aslan M., Cheung K., Li Y., Rajeevan N., Sayward F., Harrington K., Chen Q., Cho K., Pyarajan S., Sullivan P., Quaden R., Shi Y., Hunter-Zink H., Gaziano J., Concato J., Zhao H., Stein M., on behalf of the Department of Veterans Affairs Cooperative Studies Program (#575B) and Million Veteran Program. (2019). Genome-wide association study of posttraumatic stress disorder (PTSD) re-experiencing symptoms in >165,000 US veterans. Nature Neuroscience, in press.

[10] Gelernter J., Sun N., Polimanti R., Pietrzak R., Levey D., Lu Q., Hu Y., Li B., Radhakrishnan K., Aslan M., Cheung K., Li Y., Rajeevan N., Sayward F., Harrington K., Chen Q., Cho K., Honerlaw J., Pyarajan S., Lencz T., Quaden R., Shi Y., Hunter-Zink H., Gaziano J., Kranzler H., Concato J., Zhao H., Stein M., on behalf of the Department of Veterans Affairs Cooperative Studies Program (#575B) and Million Veteran Program. (2019). Genomewide association study of maximum habitual alcohol intake in >140,000 US European- and African- American veterans yields novel risk loci. Biological Psychiatry, in press.

[9] Hu, Y., Lu Q., Liu W., Zhang Y., Li M., Zhao H. (2017). Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction. PLOS Genetics, 13(6): e1006836.

[8] Hu, Y., Lu Q. , Powles R., Yao X., Yang C., Fang F., Xu X., Zhao H. (2017). Leveraging functional annotations in genetic risk prediction for human complex diseases. PLOS Computational Biology, 13(6): e1005589.

[7] Lu Q., Li B., Ou D., Erlendsdottir M., Powles R., Jiang T., Hu Y., Chang D., Jin C., Dai W., He Q., Liu Z., Mukherjee S., Crane P., Zhao H. (2017). A powerful approach to estimating annotation-stratified genetic covariance using GWAS summary statistics. American Journal of Human Genetics, 101(6), 939-964.

[6] Lu Q., Powles R., Abdallah S., Ou D., Wang Q., Hu Y., Lu Y., Liu W., Li B., Mukherjee S., Crane P., Zhao H. (2017). Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease. PLOS Genetics, 13(7): e1006933.

[5] Li M., Foli Y., Liu Z., Wang G., Hu, Y., Lu Q., Selvaraj S., Lam W., Paintsil E. (2017). High frequency of mitochondrial DNA mutations in HIV-infected treatment-experienced individuals. HIV Medicine, 18 (1), 45-55.

[4] Hu, Y., Zhao H. (2016). CCor: a whole genome network-based similarity measure between two genes. Biometrics, 72(4)-1225.

[3] Xi, R., Li, Y., Hu, Y. (2015). Bayesian quantile regression based on the empirical likelihood with spike and slab priors. Bayesian Analysis, Volume 11, 821-855.

[2] Lu Q., Hu, Y., Sun J., Cheng Y., Cheung K., Zhao H. (2015). A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data. Scientific Reports, 5, 10576.

[1] Lu, Q., Yao, X., Hu, Y., Zhao, H. (2015). GenoWAP: Post-GWAS Prioritization through integrated analysis of genomic functional annotation. Bioinformatics, 32(4), 542-548.

Conferences & Invited talks

02/2018 Invited talk, Department of Biostatistics and Bioinformatics, Duke University, NC

02/2018 Invited talk, Department of Statistical Science, University of Toronto, ON

01/2018 Invited talk, Department of Statistics, University of Illinois at Urbana-Champaign, IL

01/2018 Invited talk, Division of Human Genetics, Department of Psychiatry, Yale University, CT

10/2017 Platform presentation, American Society of Human Genetics Annual Meeting, Orlando, FL

08/2017 Oral presentation, Joint Statistical Meetings, Baltimore, MD

08/2016 Oral presentation, Joint Statistical Meetings, Chicago, IL

04/2016 Poster presentation, New England Statistical Symposium, New Haven, CT