Biography of Alán Aspuru-Guzik
IEEE is hosting the first-ever IEEE International Conference on Quantum Computing and Engineering (QCE20) 12-16 October 2020. The fully virtual IEEE Quantum Week will feature more than 270 hours of content covering a wide range of quantum technology topics. The panel sessions and keynote speakers will provide insight on many aspects of quantum computing and its practical applications.
This biography of Alán Aspuru-Guzik serves as an introduction to one of IEEE Quantum Week’s keynote speakers. Dr. Aspuru-Guzik has a deep background in chemistry and computer science. And his recent work revolves around developing machine learning algorithms to automate experimentation in chemical laboratories, accelerating the discovery and development of new chemical materials.
Alán Aspuru-Guzik’s background in machine learning, quantum computing, chemistry
For the last fourteen years, Dr. Aspuru-Guzik has conducted groundbreaking research in the fields of quantum computing, quantum chemistry, and machine learning. His work in automation has the potential to reduce the amount of busywork in the laboratory, freeing scientists to focus their attention on high-value tasks, such as conceptualizing new research projects.
Dr. Aspuru-Guzik earned his bachelor of science in chemistry at the Universidad Nacional Autónoma de México. He went on to earn his PhD in chemistry at the University of California, Berkeley.
Upon earning his PhD in 2004, Dr. Aspuru-Guzik spent two years as a postdoctoral researcher at UC Berkeley’s chemistry department. He began his independent career at Harvard University’s Department of Chemistry and Chemical Biology. There, he led research into the interface of quantum information and chemistry, focusing on applications for materials related to renewable energy. He has studied quantum coherence, excitonic energy, organic semiconductors, organic photovoltaic energy, and organic light-emitting diodes.
Dr. Aspuru-Guzik now conducts research at the University of Toronto, where his current focus is on the intersection of quantum computing and chemistry. His work in machine learning aims to streamline research in the lab by developing algorithms that can direct machines to quickly carry out the repetitive tasks of experimental chemistry. Moreover, scientists could apply these algorithms to estimate the molecular properties of new chemical compounds with an accuracy and speed that the human mind isn’t capable of unaided.
Publications by Alán Aspuru-Guzik
Anyone interested in the applications of quantum computing and quantum chemistry should look into Dr. Aspuru-Guzik’s body of published work. He has contributed to several US patent applications and participated in dozens of studies related to artificial intelligence, renewable energy, and theoretical chemistry.
Where to find Dr. Aspuru-Guzik’s published work
Dr. Aspuru-Guzik’s work is available to read in science journals exploring key issues and breakthroughs in chemistry, physics, and artificial intelligence. Such journals include Advanced Energy Materials, Machine Learning: Science and Technology, and ChemRxiv. In addition, the IEEE Xplore digital library has published two of his papers: “Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units” and “Observation of Topologically Protected Bound States in Photonic Quantum Walks.”
Aspuru-Guzik’s most recent published work
As of September 2020, Dr. Aspuru-Guzik’s most recent research publication is “Interface Chemistry of an Amide Electrolyte for Highly Reversible Lithium Metal Batteries.” This publication appeared in Nature Communications in August of 2020 and explores a method of increasing the energy density of rechargeable lithium batteries.
Alán Aspuru-Guzik’s top accomplishments
Dr. Aspuru-Guzik’s career is full of notable accomplishments in chemistry and quantum computing. By increasing the rate at which chemists reach breakthroughs in material discovery and development, his work has the potential to impact global industries. Case in point, automation in the chemical lab is already expediting drug discovery in the pharmaceuticals industry.
His achievements in chemistry go as far back as junior high, when Dr. Aspuru-Guzik represented Mexico in the International Chemistry Olympiad in Norway. And as a scholar, he founded the Harvard Clean Energy Project (CEP). The goal of the CEP is to search for the next generation of organic solar cell materials.
Awards and fellowships
Dr. Aspuru-Guzik’s career in academia has earned him a number of prestigious awards and fellowships. In 2010, he was named one of MIT Technology Review’s thirty-five innovators under thirty-five. He has also received the Early Career Award in Theoretical Chemistry from the American Chemical Society and the Google Focus Research Award in Quantum Computing. His fellowships include Alfred P. Sloan, the American Association for the Advancement of Science, and the American Physical Society.
Alán Aspuru-Guzik’s current position
Alán left Harvard in 2018 to teach at the University of Toronto, where he now teaches chemistry and computer science. Dr. Aspuru-Guzik also has a foot in the private sector, having cofounded two companies that develop algorithms and software for quantum computing.
Dr. Aspuru-Guzik is a cofounder of Zapata Computing, a firm whose mission is “to accelerate the quantum revolution.” This company develops quantum software and algorithms for applications in business. Alan also cofounded Kebotix, a self-driving lab that combines data and AI with robotics to discover and create advanced chemicals and materials at a much faster rate using machine learning.
Dr. Aspuru-Guzik is the Canada 150 research chair in theoretical chemistry and a Canada CIFAR AI chair at the Vector Institute. He is also a CIFAR Lebovic Fellow in the Biologically Inspired Solar Energy program.
Driving discovery in theoretical chemistry
When it comes to the interface of theoretical chemistry and quantum computing, Alán Aspuru-Guzik is a rising figure. Dr. Aspuru-Guzik’s continued work on high-throughput quantum chemistry and artificial intelligence to create self-driving laboratories has significant implications for experimentation involving huge data sets.
To learn all about Dr. Aspuru-Guzik’s work developing algorithms for simulating chemicals in near-quantum computers, attend his 15 October virtual talk during IEEE Quantum Week. Register for the event to hear other keynote speakers, sit in on panel discussions, and participate in workshops exploring the wide world of quantum computing.
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