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 *

Genome Sciences, School of Medicine

Aakrosh Ratan specializes in developing computational methods for analyzing genomic data, with particular emphasis on variant discovery, genome assembly, and comparative genomics.

๐Ÿงฌ Genomics & Sequencing ๐ŸŒณ Evolutionary Genomics โš™๏ธ Algorithm Development

Aidong Zhang *

Computer Science, School of Engineering and Applied Sciences

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.

๐Ÿค– AI/ML for Biology ๐Ÿฅ Clinical Informatics โš™๏ธ Algorithm Development

Ani Manichaikul *

Genome Sciences, School of Medicine

Ani Manichaikul develops and applies statistical genetics methods to understand the genetic basis of complex diseases.

๐Ÿ“Š Statistical Genetics ๐ŸŽฏ Precision Medicine ๐Ÿฅ Clinical Informatics

Chongzhi Zang *

Genome Sciences, School of Medicine

Chongzhi Zang develops computational methods for analyzing epigenomic and transcriptomic data to understand gene regulation mechanisms.

๐Ÿ”„ Epigenetics & Regulation ๐Ÿฅ Cancer Computational Biology ๐Ÿค– AI/ML for Biology ๐Ÿงฌ Multi-Omics Integration

Gloria M. Sheynkman *

Molecular Physiology and Biological Physics, School of Medicine

Gloria Sheynkman develops integrative proteogenomics methods to understand proteoform diversity and its role in human disease.

๐Ÿงช Protein Structure & Function ๐Ÿงฌ Multi-Omics Integration ๐Ÿงฌ Genomics & Sequencing ๐Ÿ”ฌ Structural Bioinformatics

Gustavo K. Rohde *

Biomedical Engineering, School of Engineering and Applied Sciences

Gustavo Rohde develops mathematical and computational methods for biomedical imaging and data analysis, particularly transport-based morphometry techniques.

๐Ÿ–ผ๏ธ Biomedical Imaging ๐Ÿค– AI/ML for Biology โš™๏ธ Algorithm Development

Jason A. Papin *

Biomedical Engineering, School of Engineering and Applied Sciences

Jason Papin develops computational models of cellular networks and metabolic systems to understand biological processes relevant to human disease.

๐Ÿ”— Systems & Network Biology ๐Ÿ”„ Metabolic Modeling ๐Ÿฅ Cancer Computational Biology

Nathan C. Sheffield *

Genome Sciences, School of Medicine

Nathan Sheffield develops computational methods for analyzing large-scale genomic data, particularly focusing on epigenomics, chromatin accessibility, and regulatory genomics.

๐Ÿค– AI/ML for Biology ๐Ÿ”„ Epigenetics & Regulation โš™๏ธ Algorithm Development ๐Ÿ’พ Data Science & Infrastructure

Philip E. Bourne *

Data Science, School of Data Science

Phil Bourne is a pioneer in structural bioinformatics and data science, focusing on drug discovery, systems pharmacology, and understanding biomolecular structure-function relationships.

๐Ÿ”ฌ Structural Bioinformatics ๐Ÿ’พ Data Science & Infrastructure ๐Ÿงช Protein Structure & Function

Stefan Bekiranov *

Biochemistry and Molecular Genetics, School of Medicine

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.

๐Ÿฅ Cancer Computational Biology ๐Ÿ”„ Epigenetics & Regulation ๐Ÿ”— Systems & Network Biology ๐Ÿ“Š Statistical Genetics

Stephen S. Rich *

Genome Sciences, School of Medicine

Stephen Rich conducts large-scale genetic epidemiology studies to understand the genetic basis of diabetes and cardiovascular diseases.

๐Ÿ“Š Statistical Genetics ๐ŸŽฏ Precision Medicine ๐Ÿฅ Clinical Informatics

Timothy W. Clark *

Public Health Sciences, School of Medicine

Tim Clark specializes in biomedical informatics and FAIR data principles, developing computational frameworks for reproducible research and data integration.

๐Ÿ’พ Data Science & Infrastructure ๐Ÿฅ Clinical Informatics โš™๏ธ Algorithm Development

Wei-Min Chen *

Genome Sciences, School of Medicine

Wei-Min Chen develops statistical methods and software tools for genetic association studies and genomic data analysis.

๐Ÿ“Š Statistical Genetics โš™๏ธ Algorithm Development ๐Ÿงฌ Genomics & Sequencing

Yanjun Qi *

Computer Science, School of Engineering and Applied Sciences

Yanjun Qi develops machine learning and deep learning methods with applications in bioinformatics and trustworthy AI.

๐Ÿค– AI/ML for Biology โš™๏ธ Algorithm Development

* Computational Mentor