Mental Health Data Science Staff
Melanie Wall, PhD
Research Area Leader
Dr. Wall has worked extensively with modeling complex multilevel and multimodal data on a wide array of psychosocial public health and psychiatric research questions in both clinical studies and large epidemiologic studies. She is an expert in longitudinal data analysis and latent variable modeling, including structural equation modeling focused on mediating and moderating (interaction) effects where she has made many methodological contributions. She has a long track record as a biostatistical mentor for Ph.D. students and NIH K awardees and regularly teaches graduate level courses in the Department of Biostatistics in the Mailman School of Public Health attended by clinical Masters students, Ph.D. students, post-docs, and psychiatry fellows. Her current research mission is improving the accessibility and application of state-of-the-art and reproducible statistical methods across different areas psychiatric research.
Yuanjia Wang, PhD
Dr. Wang's primary research interest is in statistical genetics with a focus on high-dimensional data analysis. With recent advance of technology in the fields of genetics and genomics, high throughput data are routinely generated and pose various challenges to their analyses. Dr. Wang's work involves developing efficient statistical methods and data mining tools to cope with large scale data. Her other research interests include semi-parametric inference and functional data analysis.
Hanga Galfalvy, PhD
Dr. Hanga Galfalvy graduated in 2000 with a PhD in Statistics from the University of Illinois at Urbana-Champaign. After one year postdoctoral experience in the area of machine learning research, she worked as a Postdoctoral Research Fellow and then an Assistant Professor of Clinical Neurobiology in the Department of Psychiatry at Columbia University and New York State Psychiatric Institute. From June 2013 she is an Assistant Professor of Clinical Biostatistics (in Psychiatry). She was the recipient of an NIMH K25 award for the study of statistical methodology for predicting suicide attempts, and has worked as a co-investigator or statistician on many observational and treatment studies of suicidal behavior. Her methodological interests include censored regression models, longitudinal data analysis, methodology for the analysis of high-dimensional genetic data, and building predictive models for suicide and suicide attempts.
Seonjoo Lee, PhD
Dr. Seonjoo Lee received her B.S. and M.S. degrees in Statistics from the Seoul National University, South Korea. She completed her Ph.D. in Statistics and Operations Research from the University of North Carolina at Chapel Hill in 2011. Her thesis focused on the development of independent component analysis with biomedical applications. After completion of her degree she joined the Center for Neuroscience and Regenerative Medicine at National Institution of Health and Uniform Service University and is currently working on the development of statistical methodology for high-dimensional longitudinal data. She also interested in multimodal data analysis and latent variable modeling.
Jean Choi, MS
Jean Choi earned her master’s degree in biostatistics at the University of Pittsburgh, Graduate School of Public Health and her BS in psychology and statistics at Carnegie Mellon University. She has collaborated as the primary data analyst with Richard Sloan in Behavioral Medicine working on several clinical trials examining the effects on cardiovascular responses due to aerobic conditioning as well as varying emotions and participated in one paper being published in Psychophysiology. Jean has been involved in ongoing development of new statistical methods for relating the high dimensional cardiac monitoring data to the momentary assessment of emotions.
Jennifer Scodes, MS
Jennifer Scodes received her MS in Biostatistics from Columbia University's Mailman School of Public Health and earned her BA in Computational Biology and Statistics from Cornell University. She has been working as a Biostatistician in the Division of Biostatistics in Psychiatry since May 2015. Her current collaborations include clinical trial research in Behavior Medicine with Dr. Richard Sloan and Substance Abuse research with Dr. Deborah Hasin.
Tianshu Feng, MS
Tianshu Feng joined Division of Biostatistics in Psychiatry in October 2012. Her primary collaboration is with Dr. Monk in behavioral medicine working on several studies looking at stress markers and birth outcomes in teen pregnancy. She also works with Dr. Wall on the project in impact of state level medical marijuana law passage on adolescent marijuana use. Her other collaborations include anxiety disorder and cognitive regulation of addictive behaviors.
Tse Choo, MPH
Tse Choo has a MPH in Biostatistics from Columbia's Mailman School of Public Health, and is currently a Biostatistician in the division of Biostatistics in Psychiatry at Columbia. His research interests include mediation, spatial data analysis, latent variables, and resampling techniques.
Chen Chen, MPH
Chen Chen graduated from Columbia University's Mailman School of Public Health with a MPH in Enviromental Health Sciences and Applied Biostatistics. She joined the Division of Biostatistics in June 2016. Her current collaborations include eating disorders, weight teasing, biological aging and Diagnostic Interview Schedule for Children (DISC).
Tom Corbeil holds a BA from UC Davis, an MCS from Regent College, and an MPH in biostatistics from Columbia University’s Mailman School of Public Health. He currently provides data analysis collaboration on projects including the study of psychological development in Puerto Rican youth, mental health and hazardous drinking in sexual minority women, the promotion and acceptance of HIV testing among high school students in the Bronx, and predictors of successful transitional care after psychiatric hospitalization.
Chris Adams joined the Division of Biostatistics in June 2017. He has a BA in Psychology from Cornell University, and a MPH in Biostatistics from Columbia University’s Mailman School of Public Health. His current collaboration topics include suicidality and aging, and sexual risk behaviors, HIV testing, and psychological development among Puerto Rican youth.
Cale Basaraba received his MPH in Epidemiology and Applied Biostatistics from Columbia University’s Mailman School of Public Health in 2016 and holds a BA and BS from Stanford University. As part of the Mental Health Data Science Group, he collaborates as a data analyst on projects concerning the treatment of first episode psychosis in young adults, substance abuse research, and also provides statistical support for the HIV Center for Behavioral and Clinical Studies.