The Materials for Tomorrow, Today

Recorded On: 02/18/2020

For materials discovery, one needs to go beyond simple computational screening approaches followed by traditional experimentation. I have worked on the design and implementation of what I call “materials acceleration platforms” (MAPs), which are enabled by the confluence of three disparate fields, namely artificial intelligence (AI), high-throughput quantum chemistry (HTQC), and robotics. I will describe our efforts under the Mission Innovation umbrella platform around this topic.

Alán Aspuru-Guzik, Ph.D.

Alán Aspuru-Guzik, Ph.D.

University of Toronto

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 “self-driving laboratories”, which promise to accelerate the rate of scientific discovery. Alán also develops quantum computer algorithms for quantum machine learning and has pioneered quantum algorithms for the simulation of matter. Jointly appointed Professor of Chemistry and Computer Science at the University of Toronto. Previously, full professor at Harvard University. Co-founder of Zapata Computing and Kebotix, two early-stage ventures in quantum computing and self-driving laboratories respectively.

Key:

Complete
Failed
Available
Locked
The Materials for Tomorrow, Today
Open to view video.
Open to view video.