Alán Aspuru-Guzik’s research lies at the interface of computer science with chemistry and physics. He works in the integration of robotics, machine learning and high-throughput quantum chemistry for the development of materials acceleration platforms. These “self-driving laboratories” promise to accelerate the rate of scientific discovery, with applications to clean energy and optoelectronic materials. Alán also develops quantum computer algorithms for quantum machine learning and has pioneered quantum algorithms for the simulation of matter. He is jointly appointed as a Professor of Chemistry and Computer Science at the University of Toronto, as well as cross-appointed in the departments of Materials Science and Chemical Engineering and Applied Science. Previously, he was a full professor at Harvard University. Alán is also a co-founder of Zapata Computing and Kebotix, two early-stage ventures in quantum computing and self-driving laboratories respectively.
Professor, Department of Chemistry, University of Toronto
Professor, Department of Computer Science, University of Toronto
Canada CIFAR Artificial Intelligence Chair
Director, Acceleration Consortium
Research Interests
- Machine Learning
- Robotics & Self-Driving Labs
- Quantum Computing
- Theoretical & Quantum Chemistry
Highlights
- Co-Director and Lebovic Fellow, CIFAR Accelerated Decarbonization Program
- Chemical Engineering Medal, ETH Zurich
- Canadian Society for Chemistry (CSC) John C. Polanyi Award
- The Plenary Robert J. Le Roy Lecturer. University of Waterloo
- Davidson Lecturer. University of North Texas. Denton, TX.
- Holds the Canada 150 Research Chair in Theoretical and Quantum Chemistry
- Google Focus Research Award in Quantum Computing
- CIFAR Senior Fellow, Biologically-Inspired Solar Energy Program
- MIT Technology Review 35 under 35
- Alfred P. Sloan Fellow
- Elected Fellow of the American Association for the Advancement of Science
- Fellow of the American Physical Society
Publications
Noisy intermediate-scale quantum algorithms
2022
Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package
2021
Machine-learned potentials for next-generation matter simulations
2021
Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery
2021
Nanoparticle synthesis assisted by machine learning
2021
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge
2021
Data-science driven autonomous process optimization
2021
Neural message passing on high order paths
2021
Olympus: a benchmarking framework for noisy optimization and experiment planning
2021
Quantum computing at the frontiers of biological sciences
2021
Meta-variational quantum eigensolver: Learning energy profiles of parameterized hamiltonians for quantum simulation
2021
Organic molecules with inverted gaps between first excited singlet and triplet states and appreciable fluorescence rates
2021
Assigning confidence to molecular property prediction
2021
Machine learning directed drug formulation development
2021
Conceptual understanding through efficient automated design of quantum optical experiments
2021
Mutual information-assisted adaptive variational quantum eigensolver
2021
Scientific intuition inspired by machine learning-generated hypotheses
2021
A comprehensive discovery platform for organophosphorus ligands for catalysis
2022
Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations
2021
Quantum computer-aided design: digital quantum simulation of quantum processors
2021
Self‐Driving Platform for Metal Nanoparticle Synthesis: Combining Microfluidics and Machine Learning
2021
Quantum computer-aided design of quantum optics hardware
2021
Natural evolutionary strategies for variational quantum computation
2021
Frank-van der Merwe growth in bilayer graphene
2021
An artificial spiking quantum neuron
2021
Experimental high-dimensional greenberger-horne-zeilinger entanglement with superconducting transmon qutrits
2022
Optimized low-depth quantum circuits for molecular electronic structure using a separable-pair approximation
2022
A molecular computing approach to solving optimization problems via programmable microdroplet arrays
2021
MPGVAE: improved generation of small organic molecules using message passing neural nets
2021
Noise robustness and experimental demonstration of a quantum generative adversarial network for continuous distributions
2021
Analog quantum simulation of non-Condon effects in molecular spectroscopy
2021
Routescore: Punching the ticket to more efficient materials development
2022
Machine Learning Predictions of Drug Release from Polymeric Long Acting Injectables
2021
Correction to “Generative Adversarial Networks for Crystal Structure Prediction”
2022
Updated Calibrated Model for the Prediction of Molecular Frontier Orbital Energies and Its Application to Boron Subphthalocyanines
2022
A Materials Acceleration Platform for Organic Laser Discovery
2022
Toward Quantum Computing with Molecular Electronics
2022
Funsies: A minimalist, distributed and dynamic workflow engine
2021
Fast Reverse Intersystem Crossing Over 107 s-1 in Organic Emitters with Inverted Singlet-Triplet Gap via Intramolecular Through Space Charge Transfer
2021
Correction to “Extending the Lifetime of Organic Flow Batteries via Redox State Management”
2021
Self-driving laboratories: A paradigm shift in nanomedicine development
2023
Large language models for chemistry robotics
2023
Revolutionizing drug formulation development: The increasing impact of machine learning
2023
Rational design of organic molecules with inverted gaps between the first excited singlet and triplet
2023
Recent advances in the self-referencing embedded strings (SELFIES) library
2023
Towards equilibrium molecular conformation generation with GFlowNets
2023
Data-driven development of an oral lipid-based nanoparticle formulation of a hydrophobic drug
2023
Boosting quantum amplitude exponentially in variational quantum algorithms
2023
Gauche: A library for Gaussian processes in chemistry
2024
Artificial design of organic emitters via a genetic algorithm enhanced by a deep neural network
2024
Ultrafast computational screening of molecules with inverted singlet-triplet energy gaps using the Pariser-Parr-Pople semi-empirical quantum chemistry method
2024
Accelerated chemical science with AI
2024
Unveiling the TADF Emitters with Apparent Negative Singlet‐Triplet Gaps: Implications for Exciton Harvesting and OLED Performance
2023
DELFI: A computer oracle for recommending density functionals for excited states calculations
2024
Determining 3D structure from molecular formula and isotopologue rotational spectra in natural abundance with reflection-equivariant diffusion
2024
Accelerating discovery in organic redox flow batteries
2024
Allosteric inhibition of tRNA synthetase Gln4 by N-pyrimidinyl-β-thiophenylacrylamides exerts highly selective antifungal activity
2024
Language models can generate molecules, materials, and protein binding sites directly in three dimensions as xyz, cif, and pdb files
2023
ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories
2023
Atlas: a brain for self-driving laboratories
2023
Fast quantum algorithm for differential equations
2023
Olympus, enhanced: benchmarking mixed-parameter and multi-objective optimization in chemistry and materials science
2023
A composite measurement scheme for efficient quantum observable estimation
2023
Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation
2023
Atom-by-atom protein generation and beyond with language models
2023
Drug Discovery in Low Data Regimes: Leveraging a Computational Pipeline for the Discovery of Novel SARS-CoV-2 Nsp14-MTase Inhibitors
2023
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
2024
Replan: Robotic replanning with perception and language models
2024
Self-Driving Laboratories for Chemistry and Materials Science
2024
ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization
2024
Towards the Prediction of Drug Solubility in Binary Solvent Mixtures at Various Temperatures Using Machine Learning
2024
Challenges and opportunities for applying quantum computers to drug design
2024
Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data
2024
From Eyes to Cameras: Computer Vision for High-Throughput Liquid-Liquid Separation
2024
Automating physical experiments via Large Language Models: an attempt on superconducting quantum processors
2024
Generative diffusion model for surface structure discovery
2024
Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS
2024
Chemically Motivated Simulation Problems are Efficiently Solvable by a Quantum Computer
2024
The generative quantum eigensolver (GQE) and its application for ground state search
2024
Artificial intelligence for science in quantum, atomistic, and continuum systems
2023