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followers: 136.0 following: 62.0 repos: 86.0 gists: 4.0

Name: Matthew Evans

Type: User

Company: @modl-uclouvain / @matgenix / @datalab-industries

Bio: Postdoc in comp. matsci. (@modl-uclouvain @Matgenix @Materials-Consortia) and full-stack materials research data (@the-grey-group @datalab-org)

Twitter: funroll_loops

Location: Brussels, BE / Norfolk, UK

Blog: ml-evs.science

I'm Matthew, a BEWARE Postdoctoral Research Fellow at UCLouvain and Matgenix, broadly interested in accelerating materials discovery and design via machine learning, digital data management and open source scientific software.

Current projects

Active learning workflows for inorganic materials discovery and design @modl-uclouvain
Automated and ML-accelerated workflows @matgenix
Data management systems that capture context for experimental materials chemistry @datalab-org, @datalab-industries & @the-grey-group, e.g., the-grey-group/datalab
Designing collaborative infrastructure and standards for scientific ETL @marda-alliance, e.g., marda-alliance/metadata_extractors
Web APIs for crystal structure databases @Materials-Consortia, e.g., Materials-Consortia/OPTIMADE, Materials-Consortia/optimade-python-tools, materialscloud-org/optimade-maker
The MADICES workshops promoting machine-actionable data interoperability in the chemical sciences @MADICES

Please reach out to me via the email on my personal website if you are interested in:

Testing out or hosting a deployment of the datalab software for your research group or company
Joining the MaRDA metadata extractors working group
Deploying your crystal structure data, or ingesting community data, with an OPTIMADE API
Benchmarking machine learned interatomic potentials on specific systems of interest

Matthew Evans's Projects

.dotfiles

aiida-castep

Interface with AiiDA to automate CASTEP calculations and preserve their provenance.

airss-m3gnet-test

Using pre-trained M3GNet machine learning potential for random structure searching

alexandria-optimade

amptorch

AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch

api

New API client for the Materials Project

atomate2

atomate2 is a library of computational materials science workflows

best-of-atomistic-machine-learning

🏆 A ranked list of awesome atomistic machine learning libraries ⚛️🧬💎.

big-map-registry

Registry for BIG-MAP apps and codes.

bluesky

experiment orchestration and data acquisition

c2x2py

castepxbin

Reading binary files generated by CASTEP in Python

cck-volunteer-web-app

chem_wasserstein

A high performance mapping class to construct ElM2D plots from large datasets of inorganic compositions.

cheminventory_python

A python wrapper for programatically accessing ChemInventory

chemnlp

ChemNLP project

coc.nvim

Intellisense engine for vim8 & neovim, full language server protocol support as VSCode

codebox-api

📦 CodeBox is the simplest cloud infrastructure for your LLM Apps and Services.

cv

My TeX CV built with moderncv.

datalab

datalab is a place to store experimental data and the connections between them.

datalab-deployment-concat

discover-mc3d-react

Discover app of MC3D developed with react.js

dist-matrix

Fast Numba-enabled CPU and GPU computations of Earth Mover's (scipy.stats.wasserstein_distance) and Euclidean distances.

emmo-repo.github.io

GitHub Pages repository for EMMO releases and documentation

fastapi

FastAPI framework, high performance, easy to learn, fast to code, ready for production

galvani

Read proprietary file formats from electrochemical test stations

git-tutorial

An introduction to git and version control, initially written for the Part II Computational Physics course at the Cavendish Laboratory.

ilustrado

High-throughput crystal structure prediction with genetic algorithms.

impedance.py

A Python package for working with electrochemical impedance data

jobflow

jobflow is a library for writing computational workflows.

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