Riley J. Hickman

University of Toronto — Canada

Materials Science · Physical Sciences

17h-index1.5kcitations53works22.52yr avg
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Research Topics

Machine Learning in Materials Science(21), Computational Drug Discovery Methods(17), Innovative Microfluidic and Catalytic Techniques Innovation(17), Drug Solubulity and Delivery Systems(4), Process Optimization and Integration(4)

Publications53 total

Machine learning-assisted exploration of multidrug-drug administration regimens for organoid arrays
Science Advances·2025· 5 citedOpen Access
Author response for "Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation"
2025
Author response for "Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation"
2025
Author response for "Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation"
2025
Self-driving lab for the photochemical synthesis of plasmonic nanoparticles with targeted structural and optical properties
Nature Communications·2025· 37 citedOpen Access
Atlas: a brain for self-driving laboratories
Digital Discovery·2025· 18 citedOpen Access
Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation
Digital Discovery·2025· 8 citedOpen Access
The Dawn of a New Pharmaceutical Epoch: Can AI and Robotics Reshape Drug Formulation?
Advanced Healthcare Materials·2024· 12 citedOpen Access
Delocalized, asynchronous, closed-loop discovery of organic laser emitters
Science·2024· 113 citedOpen Access
ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories
Matter·2024· 55 citedOpen Access
Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters
Zenodo (CERN European Organization for Nuclear Research)·2024Open Access
Data-driven development of an oral lipid-based nanoparticle formulation of a hydrophobic drug
Drug Delivery and Translational Research·2023· 21 cited
Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation
2023· 10 citedOpen Access
Revolutionizing drug formulation development: The increasing impact of machine learning
Advanced Drug Delivery Reviews·2023· 93 cited
Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters
2023· 16 citedOpen Access
Data-driven development of an oral lipid-based nanoparticle formulation of a hydrophobic drug
Research Square (Research Square)·2023· 1 citedOpen Access
Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters
2023Open Access
Data-driven development of an oral lipid-based nanoparticle formulation of a hydrophobic drug
2023· 1 citedOpen Access
Atlas: A Brain for Self-driving Laboratories
2023· 24 citedOpen Access
ChemOS 2.0: an orchestration architecture for chemical self-driving laboratories
2023· 27 citedOpen Access
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Frequent Co-authors

Alán Aspuru‐Guzik(40), Matteo Aldeghi(17), Pauric Bannigan(13), Christine Allen(13), Zeqing Bao(12), Tony Wu(11), Cyrille Lavigne(10), Martin Seifrid(9), Jenya Vestfrid(9), Andrés Aguilar‐Granda(9), Florian Häse(8), Han Hao(7), Leroy Cronin(7), Benjamín Sánchez-Lengeling(6), Emily J. Hopkins(6), Felix Strieth‐Kalthoff(5), Théophile Gaudin(5), Robert Pollice(4), Théophile Gaudin(4), Alán Aspuru-Guzik(4)