WILKES-BARRE — Wilkes University kicks off its Henry J. and Linda C. Pownall Lecture in Chemistry on Oct. 19 with a presentation from a 1983 graduate student on the use of machine learning in quantum chemistry.
David Yaron, Professor of Chemistry at Carnegie Mellon University, will deliver the 7 p.m. talk in Room 105 of the Stark Learning Center. The full title is “Using Machine Learning to Improve Quantum Chemistry and to Advance Student Learning”.
“Machine learning” refers to a type of artificial intelligence that causes software to essentially adapt itself to better serve its purpose without a person having to reprogram it. The software has algorithms that use historical data from its performance as input to predict new outcomes.
Quantum chemistry studies the properties of molecules and their reactions. According to sciencedirect.com, advances in computing have led chemists to “use quantum chemistry to understand, model, and predict molecular properties and their reactions, properties of nanometer materials, and reactions and processes that take place in biological systems.”
A media release about the lecture explains that “data science” – the collection and manipulation of large amounts of data – or can be applied to improve student learning. “Data science is impacting two distinct research areas that address long-standing challenges in chemistry: quantum chemistry and student learning. Deep machine learning tools can help develop low-cost quantum chemical models that are both computationally fast and accurate. As students learn, open learning initiatives collect millions of records of how students learn chemistry, which is critical to improving teaching and learning.”
Yaron received his bachelor’s degree in chemistry from Wilkes, his PhD from Harvard in 1990, and his postdoctoral work at MIT. He joined Carnegie Mellon in 1992 and developed quantum chemical methods “for large systems, including in particular organic materials for electronic and photophysical applications”.
Recently, Yaron “has been working on ways to integrate machine learning into quantum chemical models and has developed a neural network that performs quantum chemical calculations within the network.” Neural networks are computer programs designed to mimic how the human brain works when it detects underlying relationships in data sets.
Yaron also develops and researches educational materials through his ChemCollective project and the Open Learning Initiative (OLI) courseware.
According to chemcollective.org, the project’s goals are “to support a community of teachers interested in improving chemistry education through interactive and engaging online activities.” According to the Carnegie Mellon website (cmu.edu), Yaron’s Open Learning Initiative “helps provide free resources for college and college teachers.” Yaron developed the OLI in response to the shift to online learning during the COVID-19 pandemic to help teachers translate lab work into the virtual environment.
The Lecture in Chemistry was established thanks to Henry J. and Linda C. Pownall. Henry Pownall graduated from Wilkes with a master’s degree in chemistry in 1967 and earned his doctorate in physical chemistry from Northeastern University. He was a postdoctoral fellow in molecular spectroscopy at the University of Houston and in biochemistry at Baylor College of Medicine.
The lecture is free and public. Prior registration is recommended but not required. For more information, see wilkes.edu/lectureseries.
Reach Mark Guydish at 570-991-6112 or on Twitter @TLMarkGuydish
