Joseph William Abbott
Researcher · Machine Learning
Swiss Federal Institute of Technology in LausanneAbout
Joseph William Abbott serves as a Doctoral Assistant at École Polytechnique Fédérale de Lausanne (EPFL) within the Laboratory of Computational Science and Modelling (COSMO) under the Institute of Materials in the School of Engineering. He joined EPFL in October 2022 and is concurrently enrolled in the Doctoral Program in Chemistry and Chemical Engineering.
Abbott earned his MSci Master's degree in Chemistry from the University of Bristol (2016-2020), including a study-abroad year at the University of Washington where he researched noble gas-doped nanodiamonds under Xiaosong Li. His undergraduate work also included a summer position at STFC neutron facilities near Oxford developing scientific software for neutron scattering data analysis, followed by a Master's thesis on quantum dynamics of photosynthetic energy transfer with Fred Manby at Bristol.
His research focuses on machine learning applications for electron density modeling using physics-inspired molecular representations, spanning quantum chemistry, electronic structure theory, molecular dynamics, and battery simulation. Abbott emphasizes open-source scientific software development, with industrial experience from a year-long algorithm development role at BIOVIA (Dassault Systèmes) in Cambridge focused on solid electrolyte interphase growth modeling for lithium-ion batteries.
As part of COSMO laboratory operations, Abbott contributes to computational science infrastructure while advancing his doctoral work at the intersection of quantum mechanics and machine learning. His technical profile includes active presence on GitHub, ORCID, and Google Scholar, with research outputs centered on atomistic modeling methodologies.
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