WILKES-BARRE — Wilkes University will kick off its Henry J. and Linda C. Pownall Lecture in Chemistry on October 19 with a presentation by a 1983 alumnus on the use of machine learning in quantum chemistry.
David Yaron, professor of chemistry at Carnegie Mellon University, will deliver the talk in Room 105 of the Stark Learning Center at 7 p.m. The full title is “Using Machine Learning to Improve Quantum Chemistry and Advance Student Learning”.
“Machine learning” refers to a type of artificial intelligence that results in software that essentially adjusts itself to better accomplish its goal without a person having to reprogram it. The software has algorithms that use historical data of its performance as input to predict new results.
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 nanoscale materials, and reactions and processes taking place in biological systems.” .
A press release about the conference explains that “data science” – amassing and manipulating 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 fast and computationally accurate. In student learning, open learning initiatives bring together millions of records of how students learn chemistry, which is essential to help improve teaching and learning.
Yaron earned his BS in Chemistry from Wilkes, his Ph.D. from Harvard in 1990, and completed post-doctoral 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 “worked on ways to incorporate machine learning into quantum chemical models and developed a neural network that performs quantum chemical calculations within the network.” Neural networks are computer programs designed to mimic the way the human brain works by recognizing underlying relationships in sets of data.
Yaron also develops and researches educational materials through its ChemCollective project and Open Learning Initiative (OLI) tutorials.
According to chemcollective.org, the goals of the project “are to support a community of instructors interested in improving chemistry education through interactive and engaging online activities.” According to Carnegie Mellon’s website (cmu.edu), Yaron’s open learning initiative “helps provide free resources for teachers in secondary and higher education.” 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 Chemistry Conference was created thanks to Henry J. and Linda C. Pownall. Henry Pownall graduated from Wilkes in 1967 with a master’s degree in chemistry and received his doctorate in physical chemistry from Northeastern University. He completed postdoctoral fellowships in molecular spectroscopy at the University of Houston and in biochemistry at Baylor College of Medicine.
The conference is free and open to the public. Advance registration is encouraged, but not required. More information is available at wilkes.edu/lectureseries.
Contact Mark Guydish at 570-991-6112 or on Twitter @TLMarkGuydish
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