Research Associate
I've recently completed my PhD at The University of Manchester, where I worked on force field design for molecular simulations. I was involved with the use of machine learning techniques as a means to impart conformational dependence to various atomic properties, as obtained through a Bader decomposition. I'm now working on porting Quantum Monte Carlo algorithms to reconfigurable hardware devices (FPGAs), as a part of the EXTRA initiative (https://www.extrahpc.eu/).
In my spare time, I'm a competitive ballroom and latin dancer, and enjoy reading about various esoteric topics in stochastic mathematics.
Publications
Field-programmable gate arrays and quantum Monte Carlo: Power efficient coprocessing for scalable high-performance computing
– International Journal of Quantum Chemistry
(2019)
119,
e25853
(doi: 10.1002/qua.25853)
Modeling Electron Transfers Using Quasidiabatic Hartree-Fock States.
– J Chem Theory Comput
(2018)
14,
4629
(doi: 10.1021/acs.jctc.8b00379)
Geometry Optimization with Machine Trained Topological Atoms.
– Scientific Reports
(2017)
7,
12817
(doi: 10.1038/s41598-017-12600-3)
The prediction of topologically partitioned intra-atomic and inter-atomic energies by the machine learning method kriging
– Theoretical Chemistry Accounts
(2016)
135,
195
(doi: 10.1007/s00214-016-1951-4)
The computational prediction of Raman and ROA spectra of charged histidine tautomers in aqueous solution
– Physical Chemistry Chemical Physics
(2016)
18,
27377
(doi: 10.1039/c6cp05744f)
Prediction of conformationally dependent atomic multipole moments in carbohydrates.
– J Comput Chem
(2015)
36,
2361
(doi: 10.1002/jcc.24215)
Realistic sampling of amino acid geometries for a multipolar polarizable force field.
– J Comput Chem
(2015)
36,
1844
(doi: 10.1002/jcc.24006)
Multipolar electrostatics.
– Physical chemistry chemical physics : PCCP
(2014)
16,
10367
(doi: 10.1039/c3cp54829e)