Postdoctoral researcher at the University of Pennsylvania. I received my PhD (summa cum laude) from the Technical University of Munich, where I worked on deep learning approaches to population genetics. My research focuses on integrating biology and computation — leveraging the stochastic nature of evolution to train deep learning models, with work spanning coalescent theory, ancestral recombination graphs, and simulation-based inference. Previously at the University of Oregon and TU Munich, with research stays at Queen Mary University of London and Imperial College London.
Projects with full ReadTheDocs documentation
Sequencing technology reference. Educational materials covering modern sequencing methods and their applications.
Fast coalescent translation toolkit. Efficient implementations for coalescence x translation operations.
A Python rewrite of SINGER for sampling and inference of genealogies with recombination (ARG sampling).
Coalescence x Translation. Framework and documentation for the coalescent translation paradigm.
A polarization package for population genetics. Provides tools for ancestral allele polarization and related analyses.
A Friendly Likelihood-based Inference Guide. Educational resource for understanding likelihood methods in population genetics.
The Watchmaker's Guide to Population Genetics. A comprehensive guide connecting watchmaking analogies to population genetic concepts.
A fork catalog for stdpopsim providing additional population genetic simulation models and demographic histories.
A fork catalog for stdpopsim with alternative population genetic models and simulation configurations.
A fork catalog for stdpopsim with standard population genetic models for additional species.
Software accompanying published research
Graph neural networks for demographic inference from genealogical trees under the coalescent model.
C++ forward-in-time simulator for selective sweeps under the weak seed bank (dormancy) model.
Simulator for the paper "Determinants of rapid adaptation in species with large variance in offspring production".
Paper and analysis: Three fork catalogs for stdpopsim (stdferdowsim, stdgrimmsim, stdvoidsim).
Coalescence and Translation: A language model approach to population genetics. Framework for the coalescent translation paradigm.
Fast coalescent translation toolkit for efficient coalescence x translation operations.
Ensemble ResNet method for detecting balancing selection using temporal genomic data.
Genetic map of Littrell et al. 2018 for the rn6 rat genome assembly.