Alan Aspuru-Guzik

Alan Aspuru-Guzik

University of Toronto

Billions upon billions of molecules


Billions upon billions of molecules
The chemical space of synthetically-accessible molecules and materials is larger than the number of atoms in the visible universe. The molecules and materials required for solving many of the world’s most challenging problems lurk in that space remaining to be discovered. My passion, shared with many current and former group members and colleagues worldwide, is developing tools for navigating the uncharted waters of this chemical space as efficiently as possible. We believe that self-driving laboratories, platforms that combine artificial intelligence with automated chemical synthesis and characterization tools, maybe a solution to accelerate such exploration.
In this talk, I will discuss the use of AI for chemical design and process optimization and the critical elements of self-driving laboratories. Employing examples from our research and that of our collaborators, I will discuss using these tools to discover top-performing organic lasing compounds and organic light-emitting diodes, but self-driving laboratories have broad implications for all areas of chemistry. Finally, I connect these ideas with my other long-time passion. When quantum computers are powerful enough, they will complement the tools mentioned above by simulating molecules and materials exactly and not approximately.


Alán Aspuru-Guzik is a professor of Chemistry and Computer Science at the University of Toronto and is also the Canada 150 Research Chair in Theoretical Chemistry and a Canada CIFAR AI Chair at the Vector Institute. He is a CIFAR Lebovic Fellow in the Biologically Inspired Solar Energy program. Alán also holds a Google Industrial Research Chair in Quantum Computing. Alán is the director of the Acceleration Consortium, a University of Toronto-based strategic initiative that aims to gather researchers from industry, government and academia around pre-competitive research topics related to the lab of the future.

Alán began his independent career at Harvard University in 2006 and was a Full Professor at Harvard University from 2013-2018. He received his B.Sc. from the National Autonomous University of Mexico (UNAM) in 1999 and obtained a PhD from the University of California, Berkeley in 2004, where he was also a postdoctoral fellow from 2005-2006.

Alán conducts research in the interfaces of quantum information, chemistry, machine learning and chemistry. He was a pioneer in the development of algorithms and experimental implementations of quantum computers and quantum simulators dedicated to chemical systems. He has studied the role of quantum coherence in the transfer of excitonic energy in photosynthetic complexes and has accelerated the discovery by calculating organic semiconductors, organic photovoltaic energy, organic batteries and organic light-emitting diodes. He has worked on molecular representations and generative models for the automatic learning of molecular properties. Currently, Alán is interested in automation and “autonomous” chemical laboratories for accelerating scientific discovery.

Among other recognitions, he received the Google Focused Award for Quantum Computing, the Sloan Research Fellowship, The Camille and Henry Dreyfus Teacher-Scholar award, and was selected as one of the best innovators under the age of 35 by the MIT Technology Review. He is a member of the American Physical Society and an elected member of the American Association for the Advancement of Science (AAAS) and received the Early Career Award in Theoretical Chemistry from the American Chemical Society.

Alán is editor-in-chief of the journal Digital Discovery as well as co-founder of Zapata Computing and Kebotix.

Plenary speakers

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