| Michael Barker | Ecology & Evolutionary Biology | Develops computational genomic and transcriptomic approaches to study patterns of genome evolution, including whole-genome duplication and diversification across plant lineages. |
| Dean Billheimer | Epidemiology & Biostatistics | Develops Bayesian statistical frameworks and compositional data analysis methods for inference in complex biological and environmental health datasets. |
| Andrew Capaldi | Molecular & Cellular Biology | Uses quantitative genetics and systems biology approaches to dissect signaling network architecture controlling nutrient sensing and homeostasis via the TORC1 complex. |
| Darren Cusanovich | Cellular & Molecular Medicine | Develops single-cell genomics algorithms and computational tools to infer temporal dynamics of gene regulatory networks in respiratory development and disease. |
| Hongxu Ding | Pharmacy Practice & Science | Develops machine/deep learning and statistical approaches to interpret nanopore sequencing readouts. |
| David Enard | Ecology & Evolutionary Biology | Uses population genomic statistical frameworks to detect signatures of positive selection in human genomes driven by ancient viral pathogens. |
| Henk Granzier | Cellular & Molecular Medicine | Applies quantitative structural and mechanical assays alongside computational modeling to understand the contributions of giant sarcomeric proteins titin and nebulin to striated muscle function. |
| Ryan Gutenkunst | Molecular & Cellular Biology | Develops and applies diffusion approximation PDE models and machine learning to infer demographic history and natural selection from population genomic data. |
| John Kececioglu | Computer Science | Develops combinatorial and approximation algorithms for computational biology, including multiple sequence alignment and parameter advising, and for inferring metabolic pathways via optimal factories and hyperpaths in reaction networks. |
| Bonnie LaFleur | Epidemiology & Biostatistics | Applies statistical and machine learning methods for biomarker discovery, validation, and clinical translation in large-scale biomedical datasets. |
| Jingjing Liang | Pharmacy Practice & Science | Uses multi-omics and computational genomics approaches to identify genetic and epigenetic drivers of neurodegenerative diseases. |
| Kevin Lin | Mathematics | Develops machine learning methods to analyze neural population activity and decode latent brain states from electrophysiological time series, and constructs computational models of cortical circuitry to elucidate neurophysiology and dynamical mechanisms. |
| Joanna Masel | Ecology & Evolutionary Biology | Develops formal mathematical and simulation-based models of evolutionary theory, including protein evolution, evolvability, and the population genetics of deleterious mutation accumulation. |
| Claire McWhite | Molecular & Cellular Biology | Develops and applies protein language models and deep learning to predict protein function and interactions at proteome scale. |
| Laura Miller | Mathematics | Develops immersed boundary and other computational fluid dynamics methods to study the biomechanics of swimming, filtering, and pumping in biological systems. |
| Megha Padi | Molecular & Cellular Biology | Develops network-based algorithms and multi-omics integration methods to identify regulatory circuits driving cancer, with a focus on Merkel cell carcinoma. |
| Andrew Paek | Molecular & Cellular Biology | Combines live-cell imaging with computational image analysis and mathematical modeling to quantify single-cell signaling dynamics in response to cellular stress. |
| Ingmar Riedel-Kruse | Molecular & Cellular Biology | Uses quantitative computational modeling alongside synthetic biology to engineer and understand programmable living materials based on bacterial biofilms and synthetic adhesins. |
| Cristian Román-Palacios | Information Science | Develops biological data science and machine learning approaches for macroevolutionary inference and modeling of biodiversity and disease vector ecology. |
| Liliana Salvador | Animal & Comparative Biomedical Sciences | Develops computational and mathematical models of epidemiological and evolutionary dynamics to understand the ecology and spillover risk of zoonotic infectious diseases. |
| Timothy Secomb | Physiology | Develops theoretical and computational models of the circulatory system, including blood flow, mass transport, and cardiac function. |
| Patrick Shipman | Mathematics | Applies PDE and dynamical-systems theory to biological pattern formation, including tissue organization and phase-change patterning in biological materials. |
| Vignesh Subbian | Biomedical Engineering & Systems & Industrial Engineering | Develops and applies machine learning, electronic phenotyping, and explainability algorithms to address clinical decision-making and patient safety problems in learning health systems. |
| Xiaoxiao Sun | Epidemiology & Biostatistics | Develops novel statistical and machine learning methods for longitudinal epigenetic, spatial transcriptomics, and single-cell omics data. |
| George Sutphin | Molecular & Cellular Biology | Uses comparative genomics and systems genetics across model organisms, combined with high-content imaging and experimental validation, to identify genetic mechanisms of aging and stress response. |
| Koenraad M. Van Doorslaer | Immunobiology | Integrates genomics, bioinformatics, and evolutionary analysis to study how papillomaviruses remodel host cell biology and how evolutionary history predicts oncogenic potential. |
| Francesca Vitali | Center for Innovation in Brain Science | Develops network-based bioinformatics and matrix factorization methods for multi-omics data integration, drug repurposing, and single-subject precision medicine in Alzheimer's disease. |
| Joseph Watkins | Mathematics | Applies stochastic process theory and Bayesian statistical models to problems in population genetics, archaic admixture detection, genetic epilepsy classification, and epidemic dynamics. |
| Travis Wheeler | Pharmacy Practice & Science | Develops profile hidden Markov models, neural embedding architectures, and high-performance algorithms for biological sequence annotation, homology detection, and drug discovery. |
| Amanda Wilson | Environmental Health Sciences | Develops stochastic and agent-based mathematical models integrating behavioral and laboratory data to quantify microbial infection risks and evaluate intervention efficacies in healthcare environments. |
| Charles Wolgemuth | Physics | Develops continuum mechanics and reaction-diffusion PDE models to understand the biophysics of bacterial and eukaryotic cell motility, shape generation, and collective migration. |
| Guang Yao | Molecular & Cellular Biology | Combines ODE-based mathematical modeling and machine learning-based statistical modeling with single-cell experiments to dissect the control mechanisms underlying cellular quiescence depth, senescence, and cancer dormancy. |
| Hao (Helen) Zhang | Mathematics | Develops penalized regression, support vector machines, and nonparametric smoothing methods for high-dimensional statistical machine learning in genomics, medical imaging, and cancer research. |
