Bienfait Isamura - Theoretical Chemistry & Machine Learning

About Me

I am a PhD candidate in Theoretical Chemistry at the University of Manchester, where I focus on the design, implementation, and application of machine learning algorithms in computational chemistry.

My current research involves the development of FFLUX, a physics-informed machine-learnt force field. This work represents a significant advancement in molecular simulation accuracy and efficiency.

I am a published and cited author with more than 30 publications in peer-reviewed journals. I hold a MSc in Computational Chemistry from Rhodes University (South Africa) and a BSc/Hons in Physical Chemistry and Computer Science from the University of Kinshasa (DRC).

In addition to my academic work, I am the recipient of several awards, including the S2A3 bronze medal for outstanding research at the masters level. You can find more information about my work on my Google Scholar and ResearchGate profiles.

Research Focus

FFLUX Force Field

My work is on the development of a physics-informed machine-learnt force field called FFLUX.

Machine Learning in Chemistry

My work involves the design, implementation, and application of machine learning algorithms in computational chemistry.

Computational Chemistry

I am a PhD candidate in Theoretical Chemistry, a field that uses computational methods to solve complex molecular problems.

Recent Publications

Unprecedented robustness of physics-informed atomic energy models at and beyond room temperature

Isamura, B., Aten, O., Nosratjoo, M. and Popelier, P., 2025

ChemRxiv Preprint

CHQuant: A Protocol for Quantifying Conformational Sampling with Convex Hulls

Chung, J., Isamura, B. and Popelier, P., 2025

ChemRxiv Preprint

Accurate prediction of electron correlation energies of topological atoms by delta learning from the Müller approximation

Bandyopadhyay, P., Isamura, B.K. and Popelier, P.L., 2025

The Journal of chemical physics, 162(7)

Regioselectivity and physical nature of the interactions between (methyl) guanine with HCl and CH3OH

Diyavanga, D., Isamura, B.K., Bilonda, M.K., Kahenga, F.K., Muzomwe, M. and Muya, J.T., 2024

Discover Chemistry, 1(1), p.10

Incorporating Noncovalent Interactions in Transfer Learning Gaussian Process Regression Models for Molecular Simulations

Brown, M.L., Isamura, B.K., Skelton, J.M. and Popelier, P.L., 2024

Journal of Chemical Theory and Computation, 20(14), pp.5994-6008

An unsupervised machine learning approach for the automatic construction of local chemical descriptors

Gallegos, M., Isamura, B.K., Popelier, P.L. and Martín Pendás, A., 2024

Journal of Chemical Information and Modeling, 64(8), pp.3059-3079

Transfer learning of hyperparameters for fast construction of anisotropic GPR models: design and application to the machine-learned force field FFLUX

Isamura, B.K. and Popelier, P.L., 2024

Physical Chemistry Chemical Physics, 26(36), pp.23677-23691

Metaheuristic optimisation of Gaussian process regression model hyperparameters: insights from FEREBUS

Isamura, B.K. and Popelier, P.L., 2023

Artificial Intelligence Chemistry, 1(2), p.100021

Awards & Recognition

S2A3 Bronze Medal

For outstanding research at masters level (April 2022)

BEBUC Masters Scholarship

Prestigious scholarship award (February 2020)

Prix d'Excellence Académique

Awarded by SENAREC/BEBUC (September 2022)

Science Discretionary Grant

Three-month research grant at Rhodes University (2022)

Supervisors

Paul Popelier

Google Scholar

Kevin Lobb

Google Scholar

Jules Muya

Google Scholar

Contact Me

Email (Work)

bienfait.isamura@postgrad.manchester.ac.uk

Email (Personal)

bki.stoicprogrammer@gmail.com

Phone

+44 7496 531670

Google Scholar

View Publications

ResearchGate

Research Profile