PhD students in the program are mentored by the following approved faculty members. Students must have either a primary mentor or a co-mentor who is a computational mentor. View our curriculum and research opportunities to learn more about training in our program.
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Aakrosh Ratan *
Aakrosh Ratan specializes in developing computational methods for analyzing genomic data, with particular emphasis on variant discovery, genome assembly, and comparative genomics.
Aidong Zhang *
Aidong Zhang develops machine learning and data mining methods for biomedical applications, focusing on interpretable and fair learning, federated learning, and using large language models for scientific discovery.
Ani Manichaikul *
Ani Manichaikul develops and applies statistical genetics methods to understand the genetic basis of complex diseases.
Bon Q. Trinh
Bon Trinh investigates how proteins and RNAs regulate gene activity at the chromatin level in myeloid cell development and disease.
Charles R. Farber *
Charles Farber uses systems genetics approaches to investigate complex bone phenotypes related to physiology and disease.
Chongzhi Zang *
Chongzhi Zang develops computational methods for analyzing epigenomic and transcriptomic data to understand gene regulation mechanisms.
Clint Miller
Clint Miller investigates genetic and environmental risk factors for coronary artery disease and complex cardiovascular diseases using large-scale multi-omics profiling, single-cell genomics, and computational systems biology.
Gloria M. Sheynkman *
Gloria Sheynkman develops integrative proteogenomics methods to understand proteoform diversity and its role in human disease.
Gustavo K. Rohde *
Gustavo Rohde develops mathematical and computational methods for biomedical imaging and data analysis, particularly transport-based morphometry techniques.
Jason A. Papin *
Jason Papin develops computational models of cellular networks and metabolic systems to understand biological processes relevant to human disease.
Jeffrey Saucerman *
Jeffrey Saucerman combines computational modeling and high-throughput experiments to discover molecular networks and drugs against heart diseases.
John Platig *
John Platig develops computational methods to understand how gene regulatory networks change in response to stimuli and disease states.
Nathan C. Sheffield *
Nathan Sheffield develops computational methods for analyzing large-scale genomic data, particularly focusing on epigenomics, chromatin accessibility, and regulatory genomics.
Nicholas Landry *
Nicholas Landry investigates how networks and higher-order interactions influence the spread of diseases, information, and opinions across populations.
Nikolay V. Dokholyan *
Nikolay Dokholyan investigates the molecular etiology of neurodegenerative diseases, focusing on protein misfolding mechanisms in ALS, Alzheimer's, Huntington's, and Parkinson's diseases.
Philip E. Bourne *
Phil Bourne is a pioneer in structural bioinformatics and data science, focusing on drug discovery, systems pharmacology, and understanding biomolecular structure-function relationships.
Stefan Bekiranov *
Stefan Bekiranov applies computational and statistical methods to analyze genomic and epigenomic data, focusing on understanding gene regulation, chromatin dynamics, and the molecular mechanisms underlying cancer.
Stephen S. Rich *
Stephen Rich conducts large-scale genetic epidemiology studies to understand the genetic basis of diabetes and cardiovascular diseases.
Timothy W. Clark *
Tim Clark specializes in biomedical informatics and FAIR data principles, developing computational frameworks for reproducible research and data integration.
Wei-Min Chen *
Wei-Min Chen develops statistical methods and software tools for genetic association studies and genomic data analysis.
Yanjun Qi *
Yanjun Qi develops machine learning and deep learning methods with applications in bioinformatics and trustworthy AI.
* Computational Mentor