The Pownall Lecture in Chemistry brings experts to Wilkes to discuss exciting topics in research, chemistry and more.
Using Machine Learning to Improve Quantum Chemistry and to Advance Student Learning
Learn more about how data science impacts two distinct research areas that address long-standing challenges in chemistry: quantum chemistry and student learning. Tools of deep machine learning can help develop low-cost quantum chemistry models that are both computationally fast and accurate. In student learning, open learning initiatives gather millions of records on how students learn chemistry, critical in helping to improve teaching and learning.
About David Yaron, PhD
David Yaron is a professor in the Department of Chemistry at Carnegie Mellon University. He received a BS in chemistry from Wilkes College in 1983, a Ph.D. from Harvard in 1990 and completed postdoctoral work at MIT before joining Carnegie Mellon in 1992. He develops quantum chemical methods for large systems, including especially organic materials for electronic and photophysical applications. Most recently, he 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. He also develops and studies educational materials through his ChemCollective project and Open Learning Initiative (OLI) courseware.
About the Lecture Series
The Pownall Lecture in Chemistry was established thanks to Henry J. and Linda C. Pownall. Dr. Henry Pownall graduated from Wilkes College in 1967 with a master’s degree in chemistry. He earned his doctorate from Northeastern University in physical chemistry with postdoctoral fellowships in molecular spectroscopy at the University of Houston, and biochemistry at Baylor College of Medicine with an emphasis on lipid metabolism.
- David Yaron, PhD
- Using Machine Learning to Improve Quantum Chemistry and to Advance Student Learning