I'm a Quantitative Researcher at Nebula Research. I obtained my Ph.D. in Biostatistics from Columbia University Mailman School of Public Health. My research interests focus on deep learning models, natural language processing (NLP), quantitative models for Alpha discovery, and statitical genetics. More about me.
Selected Publications
- Guo, J., Kiryluk, K., & Wang, S. (2024). PheW2P2V: a phenome-wide prediction framework with weighted patient representations using electronic health records. JAMIA Open, 7(3), ooae084.
- Guo, J., Riley, K. W., Durham, T., Margolis A. E., Wang, S., Perera, F., & Herbstman, J. B. (2022). Association studies of environmental exposures, DNA methylation and children’s cognitive, behavioral, and mental health problems. Frontiers in genetics, 13, 871820.
- Guo, J., Lin, W. H. W., Zucker, J. E., Nandakumar, R., Uhlemann, A. C., Wang, S., & Shivakoti, R. (2022). Inflammation and mortality in COVID-19 hospitalized patients with and without type 2 diabetes. The Journal of Clinical Endocrinology & Metabolism, 107(5), e1961-e1968.
- Guo, J., Yuan, C., Shang, N., Zheng, T., Bello, N. A., Kiryluk, K., Weng, C., & Wang, S. (2021). Similarity-based health risk prediction using domain fusion and electronic health records data. Journal of biomedical informatics, 116, 103711.