Keiran Thompson

Stanford University

Palo Alto, California, United States of America

Research Interests

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.

Publications

Polyatomic molecular potential energy surfaces by interpolation in local internal coordinates

The Journal of Chemical Physics / May 22, 1998

Thompson, K. C., Jordan, M. J. T., & Collins, M. A. (1998). Polyatomic molecular potential energy surfaces by interpolation in local internal coordinates. The Journal of Chemical Physics, 108(20), 8302–8316. https://doi.org/10.1063/1.476259

Convergence of molecular potential energy surfaces by interpolation: Application to the OH+H2→H2O+H reaction

The Journal of Chemical Physics / Apr 08, 1995

Jordan, M. J. T., Thompson, K. C., & Collins, M. A. (1995). Convergence of molecular potential energy surfaces by interpolation: Application to the OH+H2→H2O+H reaction. The Journal of Chemical Physics, 102(14), 5647–5657. https://doi.org/10.1063/1.469296

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 / Jul 01, 1998

Makri, N., & Thompson, K. (1998). 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, 291(1–2), 101–109. https://doi.org/10.1016/s0009-2614(98)00590-9

Influence functionals with semiclassical propagators in combined forward–backward time

The Journal of Chemical Physics / Jan 15, 1999

Thompson, K., & Makri, N. (1999). Influence functionals with semiclassical propagators in combined forward–backward time. The Journal of Chemical Physics, 110(3), 1343–1353. https://doi.org/10.1063/1.478011

Molecular potential-energy surfaces by interpolation: Further refinements

Journal of the Chemical Society, Faraday Transactions / Jan 01, 1997

Thompson, K. C., & Collins, M. A. (1997). Molecular potential-energy surfaces by interpolation: Further refinements. Journal of the Chemical Society, Faraday Transactions, 93(5), 871–878. https://doi.org/10.1039/a606038b

Rigorous forward-backward semiclassical formulation of many-body dynamics

Physical Review E / May 01, 1999

Thompson, K., & Makri, N. (1999). Rigorous forward-backward semiclassical formulation of many-body dynamics. Physical Review E, 59(5), R4729–R4732. https://doi.org/10.1103/physreve.59.r4729

The utility of higher order derivatives in constructing molecular potential energy surfaces by interpolation

The Journal of Chemical Physics / Dec 08, 1995

Jordan, M. J. T., Thompson, K. C., & Collins, M. A. (1995). The utility of higher order derivatives in constructing molecular potential energy surfaces by interpolation. The Journal of Chemical Physics, 103(22), 9669–9675. https://doi.org/10.1063/1.469982

Molecular potential energy surfaces by interpolation in Cartesian coordinates

The Journal of Chemical Physics / Jan 08, 1998

Thompson, K. C., Jordan, M. J. T., & Collins, M. A. (1998). Molecular potential energy surfaces by interpolation in Cartesian coordinates. The Journal of Chemical Physics, 108(2), 564–578. https://doi.org/10.1063/1.475419

Supercollision events in weak collisional energy transfer of highly excited species

Chemical Physics Letters / Aug 01, 1991

Clarke, D. L., Thompson, K. C., & Gilbert, R. G. (1991). Supercollision events in weak collisional energy transfer of highly excited species. Chemical Physics Letters, 182(3–4), 357–362. https://doi.org/10.1016/0009-2614(91)80229-q

CH5+:  Chemistry's Chameleon Unmasked

Journal of the American Chemical Society / Mar 12, 2005

Thompson, K. C., Crittenden, D. L., & Jordan, M. J. T. (2005). CH5+:  Chemistry’s Chameleon Unmasked. Journal of the American Chemical Society, 127(13), 4954–4958. https://doi.org/10.1021/ja0482280

On the Extent of Intramolecular Hydrogen Bonding in Gas-Phase and Hydrated 1,2-Ethanediol

The Journal of Physical Chemistry A / Mar 01, 2005

Crittenden, D. L., Thompson, K. C., & Jordan, M. J. T. (2005). On the Extent of Intramolecular Hydrogen Bonding in Gas-Phase and Hydrated 1,2-Ethanediol. The Journal of Physical Chemistry A, 109(12), 2971–2977. https://doi.org/10.1021/jp045233h

Ab initio/interpolated quantum dynamics on coupled electronic states with full configuration interaction wave functions

The Journal of Chemical Physics / Jan 15, 1999

Thompson, K., & Martı́nez, T. J. (1999). Ab initio/interpolated quantum dynamics on coupled electronic states with full configuration interaction wave functions. The Journal of Chemical Physics, 110(3), 1376–1382. https://doi.org/10.1063/1.478027

A classical trajectory study of the photodissociation of T1 acetaldehyde: The transition from impulsive to statistical dynamics

The Journal of Chemical Physics / Jan 28, 2006

Thompson, K. C., Crittenden, D. L., Kable, S. H., & Jordan, M. J. T. (2006). A classical trajectory study of the photodissociation of T1 acetaldehyde: The transition from impulsive to statistical dynamics. The Journal of Chemical Physics, 124(4), 044302. https://doi.org/10.1063/1.2139672

Large-Scale Functional Group Symmetry-Adapted Perturbation Theory on Graphical Processing Units

Journal of Chemical Theory and Computation / Jan 18, 2018

Parrish, R. M., Thompson, K. C., & Martínez, T. J. (2018). Large-Scale Functional Group Symmetry-Adapted Perturbation Theory on Graphical Processing Units. Journal of Chemical Theory and Computation, 14(3), 1737–1753. https://doi.org/10.1021/acs.jctc.7b01053

The non-adiabatic nanoreactor: towards the automated discovery of photochemistry

Chemical Science / Jan 01, 2021

Pieri, E., Lahana, D., Chang, A. M., Aldaz, C. R., Thompson, K. C., & Martínez, T. J. (2021). The non-adiabatic nanoreactor: towards the automated discovery of photochemistry. Chemical Science, 12(21), 7294–7307. https://doi.org/10.1039/d1sc00775k

ChemPix: Automated Recognition of Hand-drawn Hydrocarbon Structures Using Deep Learning

Mar 08, 2021

Weir, H., Thompson, K., Choi, B., Woodward, A., Braun, A., & Martínez, T. J. (2021). ChemPix: Automated Recognition of Hand-drawn Hydrocarbon Structures Using Deep Learning. https://doi.org/10.26434/chemrxiv.14156957

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 / Nov 22, 2004

Crittenden, D. L., Thompson, K. C., Chebib, M., & Jordan, M. J. T. (2004). 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, 121(20), 9844–9854. https://doi.org/10.1063/1.1756580

The response of a molecule to an external electric field: predicting structural and spectroscopic change

Chemical Physics Letters / Mar 01, 2003

Jordan, M. J. T., & Thompson, K. C. (2003). The response of a molecule to an external electric field: predicting structural and spectroscopic change. Chemical Physics Letters, 370(1–2), 14–20. https://doi.org/10.1016/s0009-2614(03)00045-9

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 / Jun 03, 2004

Gallagher, S. H., Thompson, K. C., Armstrong, R. S., & Lay, P. A. (2004). 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, 108(26), 5564–5572. https://doi.org/10.1021/jp036834w

The Physical Principles of Group Theory

Group Theory: An Intuitive Approach / Jun 01, 1995

The Physical Principles of Group Theory. (1995). Group Theory: An Intuitive Approach, 1–28. https://doi.org/10.1142/9789814261432_0001

Quantum Effects in Loosely Bound Complexes

ACS Symposium Series / Jul 23, 2006

Jordan, M. J. T., Crittenden, D. L., & Thompson, K. C. (2006). Quantum Effects in Loosely Bound Complexes. Advances in Quantum Monte Carlo, 101–140. https://doi.org/10.1021/bk-2007-0953.ch009

Quantum Effects in Loosely Bound Complexes

ACS Symposium Series / Jul 23, 2006

Jordan, M. J. T., Crittenden, D. L., & Thompson, K. C. (2006). Quantum Effects in Loosely Bound Complexes. Advances in Quantum Monte Carlo, 101–140. https://doi.org/10.1021/bk-2007-0953.ch009

Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model

Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model. (n.d.). https://doi.org/10.1021/acs.jpca.0c09168.s001

Combined Ab Initio, Kinetic Modeling, and Shock Tube Study of the Thermal Decomposition of Ethyl Formate

Combined Ab Initio, Kinetic Modeling, and Shock Tube Study of the Thermal Decomposition of Ethyl Formate. (n.d.). https://doi.org/10.1021/acs.jpca.7b05382.s001

TeraChem: Accelerating electronic structure and ab initio molecular dynamics with graphical processing units

The Journal of Chemical Physics / Jun 14, 2020

Seritan, S., Bannwarth, C., Fales, B. S., Hohenstein, E. G., Kokkila-Schumacher, S. I. L., Luehr, N., Snyder, J. W., Song, C., Titov, A. V., Ufimtsev, I. S., & Martínez, T. J. (2020). TeraChem: Accelerating electronic structure and ab initio molecular dynamics with graphical processing units. The Journal of Chemical Physics, 152(22), 224110. https://doi.org/10.1063/5.0007615

D-term scattering in the resonance Raman spectrum of C60

Journal of the American Chemical Society / Dec 01, 1994

Gallagher, S. H., Armstrong, R. S., Lay, P. A., & Reed, C. A. (1994). D-term scattering in the resonance Raman spectrum of C60. Journal of the American Chemical Society, 116(26), 12091–12092. https://doi.org/10.1021/ja00105a075

Crackanthorpe, Montague Hughes, (1832–16 Nov. 1913), JP, DL; KC

Who Was Who / Dec 01, 2007

Crackanthorpe, Montague Hughes, (1832–16 Nov. 1913), JP, DL; KC. (2007). Who Was Who. https://doi.org/10.1093/ww/9780199540884.013.u185016

ChemPix: automated recognition of hand-drawn hydrocarbon structures using deep learning

Chemical Science / Jan 01, 2021

Weir, H., Thompson, K., Woodward, A., Choi, B., Braun, A., & Martínez, T. J. (2021). ChemPix: automated recognition of hand-drawn hydrocarbon structures using deep learning. Chemical Science, 12(31), 10622–10633. https://doi.org/10.1039/d1sc02957f

TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations

Journal of Chemical Information and Modeling / Apr 08, 2020

Seritan, S., Thompson, K., & Martínez, T. J. (2020). TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations. Journal of Chemical Information and Modeling, 60(4), 2126–2137. https://doi.org/10.1021/acs.jcim.9b01152

Geodesic interpolation for reaction pathways

The Journal of Chemical Physics / Apr 28, 2019

Zhu, X., Thompson, K. C., & Martínez, T. J. (2019). Geodesic interpolation for reaction pathways. The Journal of Chemical Physics, 150(16), 164103. https://doi.org/10.1063/1.5090303

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.

Links & Social Media

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