Alfred University has introduced a new short course focused on battery machine learning. The course is part of a project funded by the National Science Foundation (NSF) and is designed to help engineering students gain the skills needed to succeed in the growing battery and energy storage industry. The project also explores how machine learning can be used to predict battery life.
The course is supported by a $160,644 grant from the NSF. It operates under the Upstate New York Energy Storage Engine: Creating Regional Workforce Opportunities (GROW) project. This initiative provides short-term training not only to Alfred University students but also to students from other schools and employees from private companies in New York State that work with battery technology.
The Upstate New York Energy Storage Engine is led by Binghamton University. It is one of the first regional innovation engine programs supported by the NSF. The goal is to build a strong battery and energy storage network in Upstate New York. It aims to support U.S. leadership in these areas by encouraging innovation, advancing technology, training the workforce, and promoting inclusive collaboration. The grant awarded to Alfred University is a sub-award through Syracuse University as part of the broader GROW initiative.
This week, the course included three employees from Raymond Corporation, an electric forklift manufacturer based in Greene, New York. The company is developing new battery systems at its Kirkwood facility near Binghamton. One of the participants was Ben Miller, an Alfred University graduate who earned both his bachelor’s degree (2002) and master’s degree (2003) in electrical engineering. He now works at Raymond as a development engineer.
Miller attended the course with two colleagues: Michael Dunham, an energy systems engineer, and Akshay Khairnar, a mechanical systems product engineer. They joined the program to learn how machine learning can predict battery performance and identify battery degradation patterns. Their goal is to apply these methods to Raymond’s battery development work.
Faculty members from Alfred University led several sessions. Zachary Knepp, assistant professor of chemistry, gave a talk on electrochemistry. Dan Lu, associate professor of renewable energy engineering, discussed machine learning techniques. Kun Wang, assistant professor of materials science and engineering, and Naimul Haque, a graduate student and teaching assistant in the Battery Machine Learning Lab, presented on battery machine learning applications developed by Microsoft.
Kun Wang is the lead researcher on the NSF project. Gabrielle Gaustad, dean of the Inamori School of Engineering and a 2004 Alfred graduate, and Scott Misture, a professor and former Alfred doctoral student, are serving as co-investigators.
The course also included three Alfred University students who recently completed their first year. Abby Atnafe is studying computer science, Elijah Kahl is majoring in glass science and engineering, and Song Jeonghyun is focusing on ceramic engineering. Two other students from the Alfred area, who are studying elsewhere, also participated. Liam Carstens, a student at Binghamton University, and Jack Byrnes, a student at Princeton University, joined the course. Carstens graduated from Alfred-Almond Central School and is the son of Shawn Carstens, an academic success coach at Alfred University’s Bernstein Counseling Center.
