Keiran Thompson

Stanford University

Palo Alto, California, United States of America

Research Expertise

Physical and Theoretical Chemistry
Colloid and Surface Chemistry
Biochemistry
Catalysis
Computer Science Applications
Library and Information Sciences

About

Keiran Thompson is a machine learning and quantum chemistry researcher. Originally from Australia, he currently works as an AI research scientist at Stanford University where he transfers machine learning knowledge from the private sector to academic research which can then be reconverted back to private sector usage. He is experienced with large scale numerical computing and has led several startups as Chief Scientist.

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Publications

Polyatomic molecular potential energy surfaces by interpolation in local internal coordinates
The Journal of Chemical Physics
1998
Convergence of molecular potential energy surfaces by interpolation: Application to the OH+H2→H2O+H reaction
The Journal of Chemical Physics
1995
Semiclassical influence functionals for quantum systems in anharmonic environments1Presented at the American Physical Society Meeting in Los Angeles, California, USA, March 19, 1998.1
Chemical Physics Letters
1998
Influence functionals with semiclassical propagators in combined forward–backward time
The Journal of Chemical Physics
1999
Molecular potential-energy surfaces by interpolation: Further refinements
Journal of the Chemical Society, Faraday Transactions
1997
Rigorous forward-backward semiclassical formulation of many-body dynamics
Physical Review E
1999
The utility of higher order derivatives in constructing molecular potential energy surfaces by interpolation
The Journal of Chemical Physics
1995
Molecular potential energy surfaces by interpolation in Cartesian coordinates
The Journal of Chemical Physics
1998
Supercollision events in weak collisional energy transfer of highly excited species
Chemical Physics Letters
1991
CH5+:  Chemistry's Chameleon Unmasked
Journal of the American Chemical Society
2005
On the Extent of Intramolecular Hydrogen Bonding in Gas-Phase and Hydrated 1,2-Ethanediol
The Journal of Physical Chemistry A
2005
Ab initio/interpolated quantum dynamics on coupled electronic states with full configuration interaction wave functions
The Journal of Chemical Physics
1999
A classical trajectory study of the photodissociation of T1 acetaldehyde: The transition from impulsive to statistical dynamics
The Journal of Chemical Physics
2006
Large-Scale Functional Group Symmetry-Adapted Perturbation Theory on Graphical Processing Units
Journal of Chemical Theory and Computation
2018
The non-adiabatic nanoreactor: towards the automated discovery of photochemistry
Chemical Science
2021
ChemPix: Automated Recognition of Hand-drawn Hydrocarbon Structures Using Deep Learning
Unknown Venue
2021
Efficiency considerations in the construction of interpolated potential energy surfaces for the calculation of quantum observables by diffusion Monte Carlo
The Journal of Chemical Physics
2004
The response of a molecule to an external electric field: predicting structural and spectroscopic change
Chemical Physics Letters
2003
The Unusual Intensity Behavior of the 281-cm-1 Resonance Raman Band of C60:  A Complex Tale of Vibronic Coupling, Symmetry Reduction, Solvatochromism, and Jahn−Teller Activity
The Journal of Physical Chemistry A
2004
The Physical Principles of Group Theory
Group Theory: An Intuitive Approach
1995
Quantum Effects in Loosely Bound Complexes
ACS Symposium Series
2006
Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model
Unknown Venue
Combined Ab Initio, Kinetic Modeling, and Shock Tube Study of the Thermal Decomposition of Ethyl Formate
Unknown Venue
TeraChem: Accelerating electronic structure and ab initio molecular dynamics with graphical processing units
The Journal of Chemical Physics
2020
D-term scattering in the resonance Raman spectrum of C60
Journal of the American Chemical Society
1994
Crackanthorpe, Montague Hughes, (1832–16 Nov. 1913), JP, DL; KC
Who Was Who
2007
ChemPix: automated recognition of hand-drawn hydrocarbon structures using deep learning
Chemical Science
2021
TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations
Journal of Chemical Information and Modeling
2020
Geodesic interpolation for reaction pathways
The Journal of Chemical Physics
2019

Education

Australian National University

PhD, Physical Chemistry / 1999

Canberra, Australian Capital Territory, Australia

University of Illinois Urbana-Champaign

Postdoc / 1999

Urbana, Illinois, United States of America

Experience

Stanford University

Research Fellow / 2016Present

Snowball Trading

Head of Research / 20142016

Robo-Advisor startup applying machine learning and the latest finance research to produce dramatically more profitable portfolios for ordinary investors.

Datagmi

Chief Scientist / 20132016

Datagami is a machine learning startup, bringing insights about your data to you, in terms you already understand. Under the hood it's cutting edge algorithms and cloud services. At the front end, a disarmingly simple interface you likely already use.

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