Manuel Huth
Manuel develops statistical methods and software in Julia, R, and Python focusing on nonlinear mixed-effects models, longitudinal data, and federated learning. He began using Julia in 2023 and now builds research software leveraging its composability and automatic differentiation ecosystem. He is the author of Coconots.jl and NoLimits.jl. Manuel is a PhD student in Mathematics in the group of Jan Hasenauer at the University of Bonn.
Session
NoLimits.jl is a flexible open-source Julia framework for nonlinear modeling and parameter estimation with random effects. It supports ODE-based mechanistic models, hidden Markov models, hybrid mechanistic-machine learning components, normalizing flows, and nested random-effect structures within a unified interface. By leveraging Julia’s composability, it enables scalable frequentist and Bayesian inference beyond the constraints of traditional open-source mixed-effects software.