Chang (April) Shu
Principal Investigator
Dr. Chang Shu, also known as April Shu, is an Assistant Professor in the Center for Genetic Epidemiology and the Department of Population and Public Health Sciences as well as Department of Pediatrics at Keck School of Medicine of USC. April specializes in psychiatric genetics and epidemiology. Her work focuses on autism genetics, substance use epigenetics, and single-cell transcriptomics. She utilizes advanced statistical and machine learning tools to uncover novel genetic factors in mental and behavioral disorders.
April earned her Ph.D. in Mental Health focusing on psychiatric genetics and epigenetics in 2018 from Johns Hopkins Bloomberg School of Public Health under the mentorship of Drs. Brion Maher and Dani Fallin. During her time there, she also trained in statistical genetics and machine learning with Dr. Hongkai Ji and completed a concurrent master's degree in Biostatistics. Her postdoctoral training was conducted at Yale University with Dr. Ke Xu, followed by a position as an Associate Research Scientist in labs led by Drs. Wendy Chung and Yufeng Shen. She holds an additional master's degree in Epidemiology from Harvard School of Public Health, mentored by Drs. Edward Giovannucci and Benjamin Le Cook. April completed her undergraduate degree in Chemistry and Biochemistry at Tsinghua University in Beijing.
April's interdisciplinary training positions her uniquely at the intersection of genetics, epidemiology, and biostatistics, offering a comprehensive lens to explore complex mental health issues.
Qing Tan
Postdoctoral Associate
Qing is a Postdoctoral Associate in the Center for Genetic Epidemiology at USC. He completed his Ph.D. in Computational Mathematics at Wuhan University, China. As a researcher in mathematical methods and bioinformatics, he specializes in using mathematical models to design machine learning algorithms for integrative analysis of multi-dimensional data, particularly in single-cell RNA-seq , spatial transcriptomics, and, imaging, and clinical data. During his Ph.D., he primarily conducted integrative analyses of imaging and clinical data of endometrial cancer patients from the perspective of evolutionary network models. Additionally, he designed early warning models for acute kidney injury based on machine learning algorithms.
Wanyi Tang
PhD Student in Epidemiology
Wanyi is a PhD student in Epidemiology in the Department of Population and Public Health Sciences at USC. She currently focuses on examining the underlying epigenetic mechanisms beyond Organophosphorus Flame Retardants (OPFR) and maternal depression. She earned her Master of Public Health in Applied Biostatistics and Epidemiology from the joint degree program between Yale University and Tsinghua University.
Boyang Li
PhD Student in PIBBS
Boyang Li is a fourth year PhD student in the Biomedical and Biological Sciences (PIBBS) program co-mentored by Dr. Hussein Yassine at the USC. He currently focuses on the role of lipid dysregulation and cellular senescence in Alzheimer's Disease pathologies from single cell RNA-seq data. He earned his bachelor degree from the University of California, Irvine.
Qi Zhang
M.S. in Biostatistics
Qi recently obtained her M.S. in Biostatistics at USC. Her research focus is utilizing machine learning models to investigate the severity and subtypes of autism. Recently, she completed her master's thesis titled "Predicting autism severity classification by machine learning models", which won a thesis excellence award. Qi completed her undergraduate degree in Statistics at the University of Waterloo.
James Lee
Master's Student in Biostatistics
James is a first year master’s student in Biostatistics at USC with a background in Biotechnology. His research interests include the application of AI and computational biology to address public health challenges. In his previous work, he developed a Python-based pipeline for ChIP-Seq data analysis. He is passionate about leveraging biostatistics and AI to explore health disparities and enhance preventive healthcare strategies.
Nithin Aditya Pradeepkumar
Master's Student in Computer Science
Nithin is a first-year M.S. student in Computer Science at USC. His research focuses on applying machine learning to healthcare. His previous research involved developing a resource-efficient pipeline for blood pressure estimation using PPG signals, leveraging EdgeML techniques. He is passionate about exploring the intersection of machine learning and healthcare.
Emily Lu
Research Assistant
Emily completed her undergraduate from University of California, Irvine majoring in Biomedical Engineering. As a genomics and bioinformatics researcher, she specializes in using computational techniques to analyze single cell RNA data, applicable to mental health personalized medicine. During her undergraduate, she worked on Drosophila melanogaster gene expression and development of gene expression simulation apps to manage large-scale genetic studies.
Preethi Prakash
Undergraduate Student in Computer Science
Preethi is a senior at Columbia University majoring in Computer Science on the Intelligent Systems track. She is currently working on perform and evaluate missing data imputation methods on parent-reported data and standardized surveys for children with autism. She simulates several data missingness patterns to investigate the imputation performance of various machine learning models including random forest, autoencoder, and more. Preethi is also co-mentored by Dr. Yufeng Shen.