Kelly Bakulsky
Associate professor of epidemiology, School of Public Health
Bakulski’s research in molecular epidemiology focuses on the interaction between environmental factors and genetics in neurological diseases.
Her work, especially relevant in conditions like autism spectrum disorder and Alzheimer’s disease, is pivotal in understanding how environmental chemicals influence these disorders. Her team develops innovative biomarker and cell-specific tools for population-based studies, contributing significantly to the field.
Her commitment to mentoring is reflected in her receipt of the School of Public Health Excellence in Teaching Award, underscoring her role in developing future scientists.
Santhi Ganesh
David J. Pinsky M.D. Professor in Cardiovascular Medicine, professor of internal medicine and of human genetics, Medical School
Ganesh is distinguished in her field as a physician-scientist, particularly known for her pioneering work in the genetics of vascular diseases.
Awarded the National Institutes of Health MIRA R35 award, Ganesh’s research is defining new frontiers in understanding critical genetic influences on diseases like hypertension, fibromuscular dysplasia, and spontaneous coronary artery dissections.
Her work is crucial in addressing unmet clinical needs in cardiovascular health, especially among women, and integrates computational and functional approaches to unearth the underlying mechanisms of these diseases.
Ganesh’s laboratory focuses on the genetics of vascular remodeling and arterial dysplasia, key processes in various cardiovascular diseases. Using gene-discovery methods such as genome sequencing and statistical genetic analysis, along with model systems of the discovered genetic effects, her team aims to elucidate the genetic basis of these conditions and their translational potential. This research is vital in developing novel treatment strategies for vascular diseases.
Kristin Koutmou
Dow Early Career Professor of Chemistry and associate professor of chemistry, LSA
Koutmou’s expertise in biochemistry centers on the intricate processes of protein synthesis in cells.
Her innovative research uncovers how RNA chemical modifications affect protein production, a crucial factor in both understanding and treating various diseases. This area of study is fundamental for advancements in mRNA-based therapies and vaccines.
Her lab’s approach is multidisciplinary, blending mechanistic enzymology, biophysical chemistry and genome-wide techniques.
Koutmou’s work is pivotal in decoding the “RNA epigenetic code,” revealing the connections between mRNA modifications and diseases like cancer and diabetes, and potentially guiding new treatment methodologies.
Joshua Welch
Associate professor of computational medicine and bioinformatics, Medical School; associate professor of electrical engineering and computer science, College of Engineering
Welch is a computational biologist specializing in machine learning and AI for single-cell genomic and spatial transcriptomic datasets. His work in developing software tools like LIGER and MultiVelo has been transformative in the field.
Welch’s contributions are significant in national and international efforts to map human body cell types, such as the NIH BRAIN Initiative and the Human Cell Atlas network.
His areas of interest include the development of tools for high-throughput sequencing technologies, understanding cell differentiation and gene dysregulation in diseases. Welch’s lab focuses on open-source software for single-cell sequencing data analysis, contributing to stem cell differentiation and brain studies.
Xiang Zhou
Professor of biostatistics, School of Public Health
Zhou, a leading biostatistician, excels in developing statistical and computational methods for genetic and genomic studies.
His innovative research tackles large-scale, high-dimensional data from genomewide association and functional genomic sequencing studies. His aim is to uncover the genetic underpinnings of phenotypic variations in human diseases.
Zhou’s areas of expertise include Bayesian methods, machine learning and analysis of complex genomic data. His projects span GWAS, TWAS, single-cell, and spatial multi-omics, advancing our understanding of genetics and genomics in health and disease.
His contributions are integral to the field of genomic data science and the Precision Health initiative at the university.
