Biomedical Informatics and Data Science

Program affiliation
Immunology
Molecular Genetics and Genomics
Biomedical Informatics and Data Science

Research summary
Our research focuses on employing multi-omics strategies to elucidate mechanisms of immune tolerance, identify novel targets for immunosuppression and develop precision approaches to immunosuppression management in advanced lung disease and lung transplantation.

Key words
immunology, genetics, T cell, neutrophil, transplant, pharmacogenetics, pharmacogenomics, immunogenetics, immunogenomics, clonal hematopoiesis, senescence, immune aging

Program affiliation
Neurosciences
Computational and Systems Biology
Biochemistry Biophysics and Structural Biology
Biomedical Informatics and Data Science

Research summary
Applying concepts and methods from statistical physics and mathematics to the study of the brain

Key words
theoretical and computational neuroscience, statistical physics

Program affiliation
Plant and Microbial Biosciences
Computational and Systems Biology
Ecology and Evolutionary Biology
Biomedical Informatics and Data Science

Research summary
Understanding the genetic basis of root growth and environmental plasticity using phenomics

Key words
imaging; plant; genetics; computation; phenotyping; roots; plant x environment

Program affiliation
Neurosciences
Computational and Systems Biology
Biomedical Informatics and Data Science

Research summary
Elucidating the biological pathways underlying cognition, emotion, and behavior, determining developmental deviations and degenerative processes in these pathways

Key words

Program affiliation
Molecular Genetics and Genomics
Computational and Systems Biology
Molecular Cell Biology
Biomedical Informatics and Data Science
Biochemistry Biophysics and Structural Biology

Research summary
My lab seeks to understand how DNA sequence determines its regulatory function. We combine functional genomic technologies with deep learning models to answer this question.

Key words
computational biology, gene regulation, genomics, deep learning, technology development

Program affiliation
Biomedical Informatics and Data Science

Research summary

Key words

Program affiliation
Biomedical Informatics and Data Science

Research summary
Our lab develops and applies informatics methods to support clinical research and learning health systems across a range of neurological and chronic disease domains. Core research areas include **computational phenotyping**, where we focus on developing, evaluating, and critically appraising algorithms that identify patient populations from large-scale EHR data; **real-world evidence generation**, where we build automated pipelines and predictive models that translate clinical data into actionable insights for care and research; and **research infrastructure for learning health systems**, where we design and evaluate the data harmonization pipelines, classification tools, and integration methods that make large-scale clinical research possible. Across all of these areas, we maintain a strong emphasis on algorithmic equity, examining how methods perform across demographic subgroups and surfacing structural disparities in access and care. These methods are applied to a broad set of clinically significant conditions—including diabetes, stroke, Alzheimer's disease, ALS, movement disorders, and epilepsy—that share common informatics challenges such as diagnostic uncertainty, heterogeneous data, and underrepresented populations. Trainees gain hands-on experience in EHR-based cohort construction, multimodal data integration, algorithm development and validation, and the translation of informatics tools into practice, with opportunities to collaborate with clinical experts across these domains.

Key words
precision medicine, ehr, data science, phenotyping, informatics

Program affiliation
Biomedical Informatics and Data Science
Human and Statistical Genetics

Research summary
My research is focused on investigating the genetic determinants of under-studied musculoskeletal phenotypes, determining the impact of occupational burdens on musculoskeletal disease, and understanding interactions between genetic and non-genetic risk factors for musculoskeletal disease.

Key words

Program affiliation
Biomedical Informatics and Data Science

Research summary
Focused on applied clinical informatics research to support clinicians adapting to health information technology

Key words

Program affiliation
Computational and Systems Biology
Biomedical Informatics and Data Science
Developmental Regenerative and Stem Cell Biology

Research summary

Key words
Bioinformatics, epigenetics