Killian Sheriff

Ph.D. candidate @ MIT DMSE

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About me: I am a Ph.D. candidate in the Department of Materials Science and Engineering at MIT, advised by Prof. Rodrigo Freitas. Prior to MIT, I graduated with an BSc. in Mathematics and Physics from McGill University in 2021. I am originally from Cannes, a beautiful city nestled in the South of France.

Research interests: My research interests lie at the intersection of materials science, machine learning and mathematics. Broadly, I am interested in combining data science techniques with cross-scale atomistic simulations to unravel physical phenomenon at an unprecedented resolution. I also enjoy designing computational workflows facilitating the characterization and discovery of materials.

selected publications

  1. dissimilarity_space_rotating.gif
    Quantifying chemical short-range order in metallic alloys
    Killian Sheriff, Yifan Cao, Tess Smidt, and 1 more author
    Proceedings of the National Academy of Sciences, 2024
  2. DFT_size_2500.png
    Capturing short-range order in high-entropy alloys with machine learning potentials
    Yifan Cao, Killian Sheriff, and Rodrigo Freitas
    2024
  3. motifs.png
    Chemical-motif characterization of short-range order with E(3)-equivariant graph neural networks
    Killian Sheriff, Yifan Cao, and Rodrigo Freitas
    2024

news

Jun 13, 2024 News: Our work got featured in MIT News, NSF Access, and 10+ news outlet.
Jun 13, 2024 Paper alert: Our work on Quantifying chemical short-range order in metallic alloys has been published in the Proceedings of the National Academy of Sciences (PNAS)!
May 28, 2024 Thrilled to be joining Toyota Research Insitute as a Machine Learning for Molecular Dynamics Resarch Intern over the summer to work on the prediction of solid-state materials synthesis.
May 15, 2024 Preprint alert: Our work on Chemical-motif characterization of short-range order with E(3)-equivariant graph neural networks is out on arXiv!
Jan 14, 2024 Preprint alert: Our work on Capturing short-range order in high-entropy alloys with machine learning potentials is out on arXiv!
Nov 2, 2023 Conference alert: I will be presenting our latest work at HEA 2023, MRS Fall 2023 and TMS 2024. Would love to chat if anyone is around!
Nov 1, 2023 Preprint alert: Our work on Quantifying chemical short-range order in metallic alloys is out on arXiv!
Oct 1, 2023 Code release: We released AtomisticReverseMonteCarlo, an Ovito python modifier that enables the generation of atomic systems matching a set of target Warren-Cowley parameters.
Sep 25, 2023 Code release: We released WarrenCowleyParameters, an Ovito python modifier that enables the computation of Warren-Cowley parameters in atomistic simulations.
Feb 16, 2023 I officially passed my Ph.D. qualifying exam!
Dec 1, 2022 Our blog post on Demistifying E(3)-equivariant neural networks is out!
May 2, 2022 Code release: I created LovelyPlots, a collection of matplotlib style sheets to nicely format figures for scientific papers, thesis and presentations while keeping them fully editable in Adobe Illustrator.
Sep 1, 2021 I started my Ph.D. at the Massachusetts Institute of Technology.