Alastair J. A. Price

Postdoctoral Research Fellow

University of Toronto / Acceleration Consortium

Supervised by Prof. O. Anatole von Lilienfeld

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720+

Citations

Publications

h-index

Invited Talks

$10M+

Grant Funding

Research Interests

Density functional theory — Exchange-hole dipole moment (XDM) dispersion corrections, adaptive hybrid functionals (aPBE0), local hybrid density functionals, and method development within the FHI-aims and Psi4 packages. Named developer for FHI-aims.

Machine learning for molecular science — MACE neural network potentials, physics-informed adaptive parameter learning for interatomic potentials, and ML-accelerated molecular property prediction.

AI-driven research — Agentic AI systems for drug discovery, autonomous computational workflows, and AI-powered materials design.

Computational infrastructure — Scalable DFT pipelines on HPC, ML training workflows, and self-hosted tools for experiment tracking and collaboration.

Education

Postdoctoral Fellow — University of Toronto / Acceleration Consortium (2023–present)
Supervisor: Prof. O. Anatole von Lilienfeld

Ph.D. Chemistry — Dalhousie University (2019–2023)
Supervisor: Prof. Erin R. Johnson
Dissertation: New implementation of the exchange-hole dipole moment (XDM) dispersion method for large-scale materials simulations

B.Sc. Honours (First Class) — Dalhousie University (2016–2019)

Research Grants

$10,000,000 — Data Factory for ML Design of Complex Materials. NRF Singapore–UofT. Lead PIs: Sir K. Novoselov FRS & A. Aspuru-Guzik. Collaborator. 2026.
$60,000 — AI for Modeling Defects and Functional Intelligent Materials. NUS–UofT Seed Grant. Co-PI. 2024–2026.

Publications

720+ citations • h-index 14 • i10-index 17 (Google Scholar, March 2026)

2025 S. G. Dale, N. Kazeev, A. J. A. Price et al. AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit. arXiv 2511.20976.

2025 Abbott, J. W. et al. (incl. A. J. A. Price). Roadmap on Advancements of the FHI-aims Software Package. arXiv 2505.00125.

2025 D. Khan, A. J. A. Price, M. L. Ach, O. A. von Lilienfeld. Adaptive hybrid density functionals. Sci. Adv. 11(5), eadt7769.

2025 I. Poltavsky et al. (incl. A. J. A. Price). Crash Testing ML Force Fields: Molecular Dynamics in the TEA Challenge 2023. Chem. Sci. 16, 3738–3754.

2025 I. Poltavsky et al. (incl. A. J. A. Price). Crash Testing ML Force Fields: Model Analysis in the TEA Challenge 2023. Chem. Sci. 16, 3720–3737.

2024 L. M. Hunnisett et al. (incl. A. J. A. Price). Seventh blind test of crystal structure prediction: structure ranking methods. Acta Crystallogr. B 80(6), 548–574.

2024 L. M. Hunnisett et al. (incl. A. J. A. Price). Seventh blind test of crystal structure prediction: structure generation methods. Acta Crystallogr. B 80(6), 517–547.

2024 R. A. Mayo, A. J. A. Price, A. Otero de la Roza, E. R. Johnson. Assessment of XDM for the seventh CSP blind test. Acta Crystallogr. B 80(6), 595–605.

2024 S. Heinen, D. Khan, ..., A. J. A. Price et al. Reducing Training Data Needs with Minimal Multilevel Machine Learning (M3L). Mach. Learn.: Sci. Technol. 5(2), 025058.

2023 C. J. Nickerson, K. R. Bryenton, A. J. A. Price, E. R. Johnson. Comparison of DFT Dispersion Corrections for the DES15K Database. J. Phys. Chem. A 127(41), 8712–8722.

2023 A. J. A. Price, R. A. Mayo, A. Otero de la Roza, E. R. Johnson. Accurate and efficient polymorph energy ranking with XDM-corrected hybrid DFT. CrystEngComm 25(6), 953–960.

2023 A. J. A. Price, A. Otero de la Roza, E. R. Johnson. XDM-corrected hybrid DFT with numerical atomic orbitals predicts molecular crystal energetics with unprecedented accuracy. Chem. Sci. 14, 1252–1262.

2022 M. DeJong, A. J. A. Price et al. Small molecule binding to surface-supported single-site transition-metal reaction centres. Nat. Commun. 13, 1–10.

2022 J. A. Weatherby, A. F. Rumson, A. J. A. Price et al. Vibrational free-energy corrections for molecular crystal polymorphism. J. Chem. Phys. 156, 114108.

2021 A. J. A. Price, K. R. Bryenton, E. R. Johnson. Requirements for an accurate dispersion-corrected density functional. J. Chem. Phys. 154, 230902. Top 10% Altmetric

2020 A. J. A. Price, E. R. Johnson. Amino-acid adsorption on hydroxylated quartz surfaces: dispersion can determine enantioselectivity. Phys. Chem. Chem. Phys. 22, 16571. 2020 PCCP Hot Article

2013 J. J. McDowell, I. Schick, A. J. A. Price et al. Pure blue emitting poly(silafluorenes) via nickel-catalyzed cross-coupling. Macromolecules 46(17), 6794–6805.

2012 D. O. Faulkner*, J. J. McDowell*, A. J. A. Price* et al. Measurement of absolute photoluminescence quantum yields using integrating spheres. Laser Photonics Rev. 6(6), 802–806. * Joint First Author

Selected Invited Talks

2025 — Toward Trustworthy Hybrid DFT in Autonomous Materials Research. Seoul National University, South Korea.
2025 — Adaptive Density Functional Methods. Fritz-Haber-Institut, Max Planck, Berlin.
2025 — Adaptive System-Specific Dispersion Corrections. I-FIM, National University of Singapore.
2025 — Implementation of Adaptive DFT within FHI-aims. University of Oviedo, Spain.
2024 — Adaptive Density Functional Theory. University of Cambridge, UK.
2023 — XDM for Local Orbitals. Physical, Theoretical and Computational Chemistry Virtual Seminar.
2022 — XDM for Local Orbitals. NRC & University of Ottawa.
2022 — Perspective on DFA Selection. Grey Group, University of Cambridge.

Selected Awards

2023 Dalhousie Openthink Scholar • 2022 Douglas E. Ryan Prize for Excellence in Graduate Studies • 2022 Best Graduate Student Poster, CSTCC • 2020 Mitacs Globalink Research Award (Max Planck Hamburg) • 2019 Faculty of Science Undergraduate Research Prize • 2019 Hypercube Scholar Award (top honours student, theoretical/computational chemistry)

Teaching

CHM328H1 S: Modern Physical Chemistry — University of Toronto, Winter 2026
Guest lecturer for Prof. O. Anatole von Lilienfeld. Two lectures on Density Functional Theory covering electronic structure foundations, thermodynamic properties from first principles, transition state theory, reaction mechanisms, and computational selectivity prediction.

Lecture slides, companion notes, and LaTeX source

CHM328H1 S: Modern Physical Chemistry — University of Toronto, Winter 2025
Guest lecturer. DFT foundations for physical chemistry students.

Teaching Assistant — Dalhousie University, 2017–2023
Senior TA for CHEM 1011/1012/1021/1022 (500+ students per course). General and engineering chemistry.

Software & Tools

Developer: Named developer for FHI-aims. Contributor to Psi4/XDM.

Computational: Psi4, FHI-aims, ORCA, ASE, critic2, PyTorch, MACE, scikit-learn, MLflow

AI/ML: LangChain/LangGraph, agentic AI systems, RAG, Intel IPEX/XPU

Infrastructure: Docker, Proxmox, Prometheus/Grafana, ZFS, CI/CD, GPU computing

Languages: Python, Fortran, Bash, LaTeX