Students & collaborators
People whose work connects with the questions, methods, and communities around evolutionary dynamics.
Earlham College
Studies how mutation rates evolve and how harmful mutations constrain adaptation. His work combines population-genetic theory with microbial experiments, including studies of the fitness costs of elevated mutation rates in yeast and the evolutionary roles of recombination.
Michigan State University
Uses experimental evolution to investigate adaptation, genome change, and the repeatability of evolution. He founded the long-term E. coli evolution experiment in 1988; its independently evolving populations allow direct comparisons of fitness gains, historical contingency, and the emergence of new functions.
University of Strathclyde
Develops mathematical models of population dynamics, with particular attention to variation among individuals. Her research examines how differences in susceptibility and exposure interact with selection to shape infectious-disease dynamics, and how accounting for this variation changes models and intervention planning.
Los Alamos National Laboratory
Works on statistical methodology and the mathematical foundations of learning from data. His research includes nonparametric regression: developing nearest-neighbor estimators and establishing when they recover underlying relationships reliably, how quickly their errors decrease, and how to adapt them to unknown data distributions.
Université Grenoble Alpes
Studies probability and statistical inference for stochastic population models. His work on Luria–Delbrück fluctuation experiments develops methods for estimating mutation frequencies and relative fitness from mutant counts, including robust approaches to the unusually large counts generated by early-arising mutations.
Autonomous University of the State of Hidalgo (UAEH)
Applies computational and mathematical methods to physiology and neuroscience. Her research includes nonlinear analysis of physiological time series, fractal representations of signals associated with cognitive impairment, and Markov-chain approaches to respiratory sinus arrhythmia and cardiovascular regulation.
IIMAS, National Autonomous University of Mexico (UNAM)
Works on nonlinear differential equations, dynamical systems, and optimization. His applied research connects mathematical and physical models with biology, finance, and archaeology, while another strand explores music and acoustics, including the use of mathematical methods in algorithmic composition.
Institute of Mathematics, UNAM
Develops mathematical models of infectious-disease transmission and control. His work connects population dynamics with public-health questions, including vaccination strategies, environmental transmission, and the effects of ecological and evolutionary processes on epidemic spread.
Institute of Ecology, UNAM
Investigates microbial diversity, speciation, and coexistence through evolutionary ecology and molecular evolution. Much of her work centers on the nutrient-poor oasis of Cuatro Ciénegas, Mexico, asking how ancient microbial lineages persist and how cooperation and interaction networks structure their communities.
Complutense University of Madrid
Develops and analyzes infectious-disease models to evaluate vaccination and other public-health interventions. His work combines dynamical systems, optimal control, and numerical simulation, with applications to human papillomavirus, COVID-19, and vector-borne infections.
Centers for Disease Control and Prevention (CDC)
Investigates HIV prevention and antiretroviral resistance. His research uses preclinical macaque models to assess preventive drug regimens, including pre-exposure prophylaxis, and examines how drug-resistance mutations affect viral fitness and the evolution of HIV under treatment pressure.
São Paulo State University (UNESP), Botucatu
Uses mathematical and computational models to study biological populations. Her work includes age-structured models of mosquito behavior and phenotypic plasticity, alongside differential-equation and cellular-automaton approaches to population dynamics and the control of vector-borne disease.
Formerly Max Planck Institute for Mathematics in the Sciences
Studies RNA structure and evolution using computational mathematics. His work includes evolutionary algorithms for RNA folding and inverse folding, probabilistic models of three-dimensional RNA structure, and genotype–phenotype maps that connect sequence changes with structural and evolutionary properties.
CNRS · Institute of Evolutionary Science of Montpellier (ISEM)
Combines mathematical theory and experimental evolution to study adaptation and evolutionary rescue under environmental stress. His work uses fitness-landscape models and real-time tracking of E. coli populations to examine responses to antibiotics, predators, and other changing selective pressures.
Western University
Builds mathematical models of microbial evolution, focusing on the fate of new mutations during adaptation. Her research asks how changes in the mutation spectrum influence bacterial evolution, and how mutations contribute to antibiotic resistance, host shifts, and adaptation to environmental change.
Institute of Ecology, UNAM
Combines population genetics, genomics, and evolutionary ecology to study biological diversity. His research includes the evolution and domestication of Mexican plants, with particular attention to agaves, and connects genetic variation and phylogenetic history with conservation and plant–pollinator relationships.
City of Hope & TGen · Université Paris-Est Créteil
Develops stochastic models of populations, with a focus on branching processes, extinction, and lineage dynamics. Her work spans epidemic risk and mutation–selection balance, and applies mathematical and statistical methods to cancer evolution, cancer risk, and early detection.
Aarhus University
Combines evolutionary genetics and bioinformatics to study how mutations affect fitness and fuel adaptation. His research develops statistical models of mutational effects and fitness landscapes, bringing together experimental measurements and population-genomic data to understand the genetic basis of evolutionary change.
Federal University of São Carlos (UFSCar)
Uses mathematical models and computer simulations to study ecological population dynamics. His work includes age-structured predator–prey systems and network models of aphids and their predators, examining how life stages, predation, and spatial interactions affect population stability.
University of Pennsylvania
Studies microbial adaptation and the evolution of mutation rates. His work has quantified the fitness costs of harmful mutations in yeast; more recent research in the de la Fuente lab investigates the genetic basis of bacterial adaptation to antimicrobial peptides.
Autonomous University of the State of Hidalgo (UAEH)
Works in dynamical systems, operator algebras, and applied mathematics. His publications include spectral properties of tridiagonal operators, classification problems in symbolic dynamics, and stability analysis of delayed economic models, alongside collaborative studies of physiological time series and sleep transitions.
Bielefeld University
Develops mathematical population genetics linking mutation, selection, recombination, and random genetic drift. A central theme is the relationship between the evolution of populations and their ancestral histories, using stochastic processes and genealogical constructions to analyze how genetic variation is maintained and reshuffled.
BOKU University, Vienna
Studies stochastic processes arising in population genetics. His research connects forward-time changes in allele frequencies with backward-time genealogies, using duality methods to analyze mutation, selection, and random environments in models such as the Moran and Wright–Fisher processes.
Institute for Integrative Systems Biology (CSIC–University of Valencia)
Studies how RNA viruses evolve, adapt to hosts, and redirect host-cell resources. His research combines experimental evolution, molecular biology, omics, and mathematical modeling, including studies of how environmental stress can shift plant–virus interactions from harmful toward mutually beneficial.