Janosh Riebesell - CV
From April 2024 to June 2025, I worked at Radical AI on vertically integrating MLIPs and robotic labs.
I worked for the Materials Project from Jul 2022 to Dec 2023 where I developed ML foundation models (CHGNet, MACE-MP) and high-throughput workflows for generating more diverse, higher-quality DFT datasets for future models.
I contribute to open source projects and help maintain matbench-discovery
, torch-sim
, pymatgen
, pymatviz
, matterviz
, atomate2
. See the full list.
Publications Sort by
TorchSim: An efficient atomistic simulation engine in PyTorch
O. Cohen, J. Riebesell, ..., A. Gangan — 10.48550/arXiv.2508.06628 — 2025-8Atomate2: modular workflows for materials science
A. Ganose, ..., J. Riebesell, ..., A. Jain — 10.1039/D5DD00019J — Digital Discovery — 2025-7 — 5 citationsAccelerated data-driven materials science with the Materials Project
M. Horton, ..., J. Riebesell, ..., K. Persson — 10.1038/s41563-025-02272-0 — Nature Materials — 2025-7Matbench Discovery - A framework to evaluate machine learning crystal stability predictions
J. Riebesell, R. Goodall, ..., K. Persson — 10.1038/s42256-025-01055-1 — Nature Machine Intelligence — 2025-6 — 5 citationsA Foundational Potential Energy Surface Dataset for Materials
A. Kaplan, ..., J. Riebesell, ..., S. Ong — 10.48550/arXiv.2503.04070 — 2025-3 — 6 citationsSystematic softening in universal machine learning interatomic potentials
B. Deng, ..., J. Riebesell, ..., G. Ceder — 10.1038/s41524-024-01500-6 — npj Computational Materials — 2025-1Discovery of high-performance dielectric materials with machine-learning-guided search
J. Riebesell, T. Surta, ..., A. Lee — 10.1016/j.xcrp.2024.102241 — Cell Reports Physical Science — 2024-10Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
M. Evans, ..., J. Riebesell, ..., R. Armiento — 10.1039/D4DD00039K — Digital Discovery — 2024-8 — 15 citationsLLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation
Y. Chiang, C. Chou, J. Riebesell — arxiv.org/abs/2401.17244 (preprint) — 2024-1 — 12 citationsJobflow: Computational Workflows Made Simple
A. Rosen, ..., J. Riebesell, ..., A. Ganose — 10.21105/joss.05995 — Journal of Open Source Software — 2024-1 — 18 citationsA foundation model for atomistic materials chemistry
I. Batatia, ..., J. Riebesell, ..., G. Csányi — arxiv.org/abs/2401.00096v1 (preprint) — 2023-12 — 171 citationsCHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling
B. Deng, ..., J. Riebesell, ..., G. Ceder — 10.1038/s42256-023-00716-3 — Nature Machine Intelligence — 2023-9 — 397 citationsCrystal Toolkit: A Web App Framework to Improve Usability and Accessibility of Materials Science Research Algorithms
M. Horton, ..., J. Riebesell, ..., K. Persson — 10.48550/arXiv.2302.06147 — 2023-2
Open Source Sort by
pymatgen 1706 ⭐ 1048 commits Python, Cython
One of the largest and most popular open source materials analysis codes that defines classes for structures, molecules, slabs, etc. and interfaces seamlessly with various other materials codes. It also powers the Materials Project.
Matbench Discovery 180 ⭐ 471 commits Python, TypeScript, Svelte
Benchmark for machine learning energy models simulating a real-world materials discovery campaign.
pymatviz 263 ⭐ 433 commits Python, TypeScript, Svelte
A toolkit for visualizations in materials informatics to complement pymatgen.
atomate2 238 ⭐ 379 commits Python, Jupyter Notebook, Shell
atomate2 is a library of computational materials science workflows used by the Materials Project and beyond.
MultiSelect 333 ⭐ 299 commits TypeScript, Svelte, CSS
Keyboard-friendly, accessible and customizable multi-select web component.
MatterViz 260 ⭐ 287 commits TypeScript, Svelte, CSS
A library of Svelte components for building interactive web apps with performant chemistry visualizations like periodic tables, Bohr atoms, nuclei, heatmaps, scatter plots.
Diagrams 354 ⭐ 254 commits Typst, TeX, Svelte
Typst and LaTeX diagrams of concepts in physics/chemistry/ML.
CHGNet 322 ⭐ 196 commits Python, C, Cython
Pretrained universal neural network potential for charge-informed atomistic modeling published on the Sep 2023 cover of NMI.
jobflow 106 ⭐ 136 commits Python, TeX
jobflow is a library for writing computational workflows. It provides the plumbing underlying atomate2 and was adopted by several other workflow libraries.
Tensorboard Reducer 74 ⭐ 86 commits Python, TeX
Reduce multiple PyTorch TensorBoard runs to new events/CSV/JSON. Good for model ensembles.
MatCalc 112 ⭐ 77 commits Python, Jupyter Notebook
A Python library for calculating materials properties from ML force field potential energy surfaces.
Normalizing Flows 1562 ⭐ 74 commits Python
Curated list of resources for learning and using normalizing flows, a powerful tool in ML for modeling probability distributions.
MLIP PES softening 23 ⭐ 61 commits Python, CSS, Svelte
Overcoming systematic softening in universal machine learning interatomic potentials by fine-tuning
TorchSim 274 ⭐ 30 commits Python
Torch-native, batchable, atomistic simulations.
Dielectrics 10 ⭐ 28 commits HTML, Python, TeX
Pushing the Pareto front of band gap and permittivity with ML-guided dielectrics discovery incl. experimental synthesis.
MACE Foundation Models 22 commits message, documentation_url, status
Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
MatPES 39 ⭐ Jupyter Notebook, Python, CSS
A foundational DFT potential energy dataset for materials covering 89 elements and emphasizing data diversity and quality (at PBE and r2SCAN level).
Materials Project message, documentation_url, status
Widely used database, website, API and OSS ecosystem built for computing properties of inorganic materials.
Education
PhD Student - University of Cambridge
Thesis title: Towards Machine Learning Foundation Models for Materials ChemistryMPhil in Scientific Computing - University of Cambridge
Thesis title: Probabilistic Data-Driven Discovery of Thermoelectric MaterialsMSc in Physics - ITP Heidelberg
Thesis title: Functional Renormalization Group Analytically Continued to Finite TemperaturesBSc in Physics - Hamburg University
Thesis title: van der Waals Corrections for Density Functional Theory - DFT+D2 applied to Graphene-hBN-Heterostructures
Languages
- English
- German
- French
- Spanish
Nationality
- Canadian
- German
Programming Languages and Tools
(emphasis ≈ proficiency)- Python (10)
- TypeScript (10)
- Svelte (10)
- Node.js (9)
- Deno (9)
- vitest (9)
- MongoDB (8)
- PyTorch (8)
- Dash (8)
- React (8)
- Puppeteer (8)
- PlayWright (8)
- Git (7)
- REST (7)
- TensorFlow (6)
- GraphQL (5)
- Mathematica (4)
- JAX (4)
- C (3)
- Rust (3)
Community
Associate Editor IOP AI for Science 2025 - present
Nature Computational Science frequent reviewer 2025 - present
Digital Discovery frequent reviewer 2024 - present
NPJ Computational Materials frequent reviewer 2024 - present
Cambridge Physical Society 2020 - present
Materials Research Society 2023 - present
Materials Project Software Foundation 2023 - present
Hobbies
- photography
- hiking
- cycling
- climbing