Welcome to My Personal Website!
I am a seasoned research scientist with a focus on health data science, computational analysis, and epidemiology. My work is centered around harnessing advanced analytical techniques to meet the dynamic demands of the health sector, driving innovation through data-centric strategies, and utilizing real-world evidence to make a significant impact in health research.
I have expertise in integrating diverse health data sources, designing computational pipelines for knowledge inference, and analyzing various risk factors and predictors that influence disease outcomes. I am particularly adept at managing large-scale datasets, identifying hidden patterns, and gaining a comprehensive understanding of complex health phenomena.
My passion for data-driven healthcare extends beyond my research, as I am dedicated to benefiting underserved populations, bridging healthcare disparities, and contributing to global health initiatives. I am committed to advancing scientific knowledge, addressing critical challenges in public health, and improving patient outcomes through innovative approaches. With my work, I aim to make a substantial impact on the advancement of healthcare and the betterment of society as a whole.
Department of Medicine
Section of Computational Biomedicine and Biomedical Data Science
Knapp Center for Biomedical Discovery, The University of Chicago
MPH (Epidemiology), Harvard T.H. Chan School of Public Health, USA
Ph.D. (Intelligent Data Analysis), University of Warwick, UK
Peri- & Post-natal Risk Factors Associated with Health of Newborns
Pre-print available at
Recreational Cannabis Legalization and the US Opioid Epidemic
Highlights of Recently Published Work
Risk of Preventable Injuries During Halloween Festivities
A Novel Quantitative Approach for Lumbar Spine
Air Pollution and Risk of Psychiatric Disorders in the US and Denmark
Machine Learning Approach for Predicting Past Occupational
Published in Journal of Occupational and Environmental Medicine
FIGS Package for Meta-Analysis of Cell-Specific Transcriptomic Data
Published in BMC Bioinformatics Download package from GitHub
Quantification of Age-Related Degenerative Changes Seen in Lumbar Spine
Published in IEEE Journal of Biomedical and Health Informatics
Incidence Measures for Schizophrenia in Medicaid and Commerical Enrollees
Pre-print available at
Recent Collaborative Efforts (Team Science)
Gene-Environment Interactions and Neuropsychiatric Disorders
Cell Reports Medicine
Genetic and Environmental Contributions to Schizophrenia Risk
Repurposed Drug for the Treatment of Glioblastoma Multiforme
Probing Seasonality of Psychiatric Disorders in US and Sweden
Effects of Daylight Saving Time (DST) Shifts on Human Health
Department of Defense Study on Occupational Exposure Biomarkers and Health Effects
Publsihed in Journal of Occupational and Environmental Medicine
Cell-Type Specific Pathogen
Response Network Explorer Tool
Automatied Analysis of Flow Cytometry Datasets with Mixture Models
Cytometry Part A
Featured Study: Environmental Pollution and Risk of Psychiatric Disorders
Thanks to my colleagues and collaborators (much obliged to my mentor Professor Andrey Rzhetsky, Edna K. Papazian Professor of Medicine at the University of Chicago), we recently published a trailblazing study on the association between environmental pollution and psychiatric disorders in the United States and Denmark. We did a computational investigation to study the complex interactions of environmental risk factors that are predictive of neuropsychiatric conditions.
This study is notable for its breadth, we analyzed over 150 million patients in the US and applied our model to Denmark to study the entire population of the country born between 1979 and 2002. The analyses showed that air and land pollution were significant predictors for the clinical frequency of several psychiatric disorders. An in-depth understanding of the environmental influence on mental health is needed to better characterize the health effects of exposure to pollutants. Evidence from most recent animal studies shows that air pollution causes neuroinflammation, which specifically supports our findings from massive clinical data mining.
The study was published in PLOS Biology on August 20, 2019.