Please tell me if you are interested in talking with him, since I have a few slots in the afternoon left. I also am looking for people to lunch with him as well (first come first served) (8th April)Hi all.Professor Todd Martinez from Stanford will be visiting the Boston area to
give a talk as part of the shared Harvard/MIT/BU theoretical chemistry
seminar series.The title of his presentation is Leveraging Machine Learning and
Stream Processors for Theoretical Chemistry(please find his abstract below).
The seminar is scheduled on the next day, April 9th, at 4:00 PM in room 4-163 (MIT).Ed Pyzer-Knapp*************************************************************************************
Leveraging Machine Learning and Stream Processors for Theoretical Chemistry
Todd J. Martínez
Department of Chemistry, Stanford University, Stanford, CA 94305
Abstract: Novel computational architectures and methodologies are revolutionizing
diverse areas ranging from video gaming to advertising and espionage. In this talk, I
will discuss how these tools and ideas can be exploited in the context of theoretical and
computational chemistry. I will discuss how insights gleaned from recommendation
systems (such as those used by Netflix and Amazon) can lead to reduced scaling methods
for electronic structure, how the algorithms in electronic structure can be adapted for
commodity stream processing architectures such as graphical processing units, and how
nonlinear dimensionality reduction methods can be used to extract chemical knowledge
from the resulting data. I will discuss some of the details regarding the structure and
implementation of these methods. I will also show how these advances can be harnessed to
progress from traditional “hypothesis-driven” methods for using electronic structure and
first principles molecular dynamics to a “discovery-driven” mode where the computer is
tasked with discovering chemical reaction networks. Finally, I will show how these can be
combined with force-feedback (haptic) input devices and three-dimensional visualization
to create molecular model kits that carry complete information about the underlying
electrons. This interactive first principles molecular dynamics method (molecular
computer-aided design or mol-CAD) opens the door to novel ways of teaching chemistry
and may also be of use in applied chemical research.