P2 Science Adds Professor Alàn Aspuru-Guzik to Scientific Advisory Board

P2 Science Inc. welcomed Professor Alan Aspuru-Guzik to the company’s scientific advisory board (SAB). Aspuru-Guzik is 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.
 
Aspuru-Guzik also holds a Google Industrial Research Chair in Quantum Computing. He 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. In addition to these roles, Professor Aspuru-Guzik is editor in chief of the journal Digital Discovery and co-founder of both Zapata Computing and Kebotix.
 
“Alan’s cutting- edge expertise in artificial intelligence, machine learning and quantum chemistry is sure to inspire us in areas that we have barely explored but which have enormous potential for our green chemistry platforms” said P2 CEO Neil Burns. “He is a leading thinker in many areas of chemistry and we are happy to have him as part of our team”
 
“P2 Science is an exciting company that produces functional chemicals for a variety of applications” said professor Aspuru-Guzik. “I am very interested in the intersection of this unique platform and data science approaches. I am looking forward to the exciting SAB discussions that will ensue.”
 
At the University of Toronto, Aspuru-Guzik 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, Professor Aspurs-Guzik is interested in automation and autonomous chemical laboratories for accelerating scientific discovery.