Faculty
Manisha Desai, PhD
Kim and Ping Li Professor of Medicine (Section of Biostatistics, Quantitative Sciences Unit) and of Biomedical Data Science, and, by courtesy, of Epidemiology and Population Health
Associate Dean of Research
Section Chief of Biostatistics
Director of the Quantitative Sciences Unit
Dr. Desai has been involved in several efforts to design studies that evaluate the utility of AI-based interventions. She led the Data Coordinating Center for the Apple Heart Study, a decentralized trial that enrolled over 400,000 participants to characterize performance of an app to identify atrial fibrillation in the general population. In addition, she collaborates on a study to evaluate a multi-faceted intervention that includes remote monitoring to improve diabetes management among children with type I diabetes. Her areas of interest include methods for establishing efficient and effective data science practices; the handling of missing data, translating trial findings to real-world target populations; and integrating real-world data into clinical trials.
Current Research Interests: Pediatrics; Diabetes; Artificial Intelligence
Summer Han, Ph.D.
Associate Professor of Neurosurgery, of Medicine (Section of Biostatistics, Quantitative Sciences Unit) and, by courtesy, of Epidemiology and Population Health
Dr. Han joined the QSU in 2015. Dr. Han's research focuses on understanding the genetic and environmental etiology of complex disease and developing and evaluating efficient screening strategies based on etiological understanding. She has developed various statistical methods to analyze high-dimensional data to identify genetic and environmental risk factors and their interactions for complex disease.
Current Research Interests: Statistical Genetics; Cancer Screening; Health Policy Modeling; Machine Learning Approaches
Zihuai He, Ph.D.
Assistant Professor of Neurology, of Medicine (Section of Biostatistics, Quantitative Sciences Unit), and, by courtesy, Biomedical Data Science
Dr. He joined the QSU in 2018. Dr. He’s research is concentrated in the area of biostatistics, statistical genetics, and integrative analysis of omics data. His current methodological work focuses on statistical inference in high-dimensional and large-scale testing problems, incorporating rigorous feature selection into machine learning methods, and translating data-driven discoveries into mechanistic insights and drug targets.
Current Research Interests: Statistical Genetics and Integrative Analysis of Omics Data; High Dimensional Data Analysis; Interpretable/Explainable Machine Learning; Neurological Disorders
Maya Mathur, Ph.D.
Associate Professor of Pediatrics, of Medicine (Section of Biostatistics, Quantitative Sciences Unit) and, by courtesy, of Epidemiology and Population Health
Dr. Mathur joined the QSU in 2020. She is a statistician whose methodological research focuses on meta-analysis and other forms of evidence synthesis, as well as causal inference. Outside of methodological research, she directs the Stanford Humane and Sustainable Food Lab and is the Associate Director of the Stanford Data Science’s Center for Open and Reproducible Science (CORES).
Current Research Interests:
Meta-Analysis; Causal Inference; Sustainable Food; Statistical Methods for Epidemiology
Vivek Charu, MD, Ph.D.
Assistant Professor of Pathology and of Medicine (Section of Biostatistics, Quantitative Sciences Unit)
Dr. Charu joined the QSU in 2021. Dr. Charu’s clinical expertise is in the diagnosis of non-neoplastic kidney and liver disease (including transplantation).
Current Research Interests: Clinical Trial Design; Causal Inference; Observational Data; Kidney and Liver Disease
Maria Montez Rath, Ph.D.
Assistant Professor (Research) of Medicine (Section of Biostatistics, Quantitative Sciences Unit and Nephrology)
Dr. Montez Rath is a data scientist with classical training in biostatistics focused on kidney health research. She leads the design and analysis of kidney-related clinical studies and bridges gaps in methodology to answer critical questions about kidney disease. She focuses on the novel design of complex studies, and innovative observational methods such as target trial emulation to draw causal inference, translate findings from randomized clinical trials to real-world target populations, and to handle missing data. Her work is data-driven in that she focuses efforts on methodological gaps that arise in the collaborative work. At the same time, her collaborative work is steeped in addressing important clinical questions that will directly improve patient’s lives and healthcare delivery.
Current Research Interests: Kidney Disease; Epidemiology; Observational and interventional studies