SciML Scientific Machine Learning Showcase

The purpose of this page is to demonstrate the various applications where the SciML tools have been employed. If you would like your own work added to this list, please open a pull request.

External Applications Libraries and Large Projects using SciML

There are many external libraries which connect and utilize SciML utilities under the hood. The following an incomplete list of software organizations providing domain modeling tools that are built upon SciML. If you would like your institution's tools added to the list, please open a pull request.

Press Coverage Featuring SciML

Books

Practical Julia
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications
Nonlinear Dynamics: A Concise Introduction Interlaced with Code
Numerical Methods for Scientific Computing: The Definitive Manual for Math Geeks
Fundamentals of Numerical Computation
Statistics with Julia
Statistical Rethinking with Julia
The Koopman Operator in Systems and Control
- "All simulations have been performed in Julia, with additional Julia packages: LinearAlgebra.jl, Random.jl, Plots.jl, Lasso.jl, DifferentialEquations.jl"

Media

Awards Associated with SciML Software

2024: PumasAI Named Best Clinical Pharmacology Technology Development Firm in Biotechnology Awards
- Press Release
2023: IEEE HPEC Best Student Paper Award, for Continuous Deep Equilibrium Models: Training Neural ODEs Faster by Integrating Them to Infinity, Avik Pal, Alan Edelman, Christopher Rackauckas
2023: International Society of Pharmacometrics (ISoP) QSP Student Symposium Best Oral Presentation, for Uncertainty Quantified Discovery of Chemical Reaction Networks via Bayesian Scientific Machine Learning, Emily Helen Nieves
2023: MIT Center for Computational Science & Engineering MathWorks Prize for Outstanding Master's Research in Computational Science & Engineering. For Songchen Tan (MIT Julia Lab) for his work on TaylorDiff.jl for use NeuralPDE.jl physics-informed neural networks (PINNs)
2022: MIT Portugal Program Poster Award, Vinicius Santana, University of Porto
2021: NeurIPS 2021 Differentiable Programming Workshop Best Poster, AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia, by Frank Schaefer (University of Basel), Mohamed Tarek (Pumas-AI, UNSW), Lyndon White (Invenia Labs), and Christopher Rackauckas (MIT, Julia Computing, Pumas-AI)
2021: International Society of Pharmacology (ISoP) Mathematics and Computing Special Interest Group Poster Award. Niklas Korsbo (Pumas-AI, University of Cambridge), Chris Elrod (Julia Computing), Francesco Brizzi (Roche), Antoine Soubret (Roche), Andreas Noack (Julia Computing), Vijay Ivaturi (Pumas-AI, University of Maryland School of Pharmacy) and Christopher Rackauckas (Julia Computing, MIT): For "Automatic identification of non-obvious prognostic factors in big data with DeepNLME". DeepNLME is built using the SciML tooling.
2021: United States Department of the Air Force Artificial Intelligence Accelerator Scientific Excellence Award (Chris Rackauckas): For "For developing innovative computational processes to accelerate the simulation of nonlinear systems using neural networks".
2021: Mediterranean Machine Learning School Outstanding Poster Award (Simone Azeglio, Valerio Pagliarino, Francesco Calisto, Luca Bottero, Martina S., Sara Tiengo, Giovanni Graziano): For "Physics-Informed Machine Learning Simulator for Wildfire Propagation" with NeuralPDE.jl.
2020: International Society of Pharmacology (ISoP) Emerging Scientist Award (Chris Rackauckas): For development of SciML and Pumas.
2020: American Conference on Pharmacometrics (ACoP) Quality Award (Chris Rackauckas and Vijay Ivaturi): For DiffEqGPU accelerating QSP models by 175x.
2020: IEEE High-Performance Extreme Computing (HPEC) Outstanding Paper Award (Chris Rackauckas and Qing Nie): For the high-performance adaptive SDE solvers in StochasticDiffEq.jl.
2019: International Society of Pharmacology (ISoP) Mathematics and Computing Special Interest Group Poster Award (Chris Rackauckas and Vijay Ivaturi): Koopman operator tooling of DiffEqUncertainty.jl accelerating uncertainty quantification in PK/PD modeling by 100x.
2018 Julia Community Award (Chris Rackauckas): For development of SciML (at the time, named JuliaDiffEq).
DSWeb 2018 Dynamical Systems Software Contest: Runner up is DifferentialEquations.jl and a winner is DynamicalSystems.jl which utilizes DifferentialEquations.jl.
2017: Best Speaker Award, Tsukuba Global Science Week (Chris Rackauckas): Presentation on StochasticDiffEq.jl for systems biology.