Alfred University’s Inamori School of Engineering recently hosted a short course on battery machine learning, which was attended by a group of students and representatives of a Binghamton-area company that manufactures battery-powered forklifts.
Alfred University’s Inamori School of Engineering recently hosted a short course on battery machine learning, which was attended by a group of students and representatives of a Binghamton-area company that manufactures battery-powered forklifts.
The Battery Machine Learning course was offered Wednesday, Thursday, and Friday, May 21-23, as part of a National Science Foundation-funded project aimed at helping prepare engineering students with the skills and knowledge needed to succeed in the battery and energy storage job market. The project studies how machine learning technology can be used to predict the useful life of batteries.
The project—supported by $160,644 in National Science Foundation (NSF) grant funding administered through the NSF Energy Storage Engine in Upstate New York: Generating Regional Opportunities in Workforce (GROW) program—offers short courses for students from Alfred University and other institutions, as well as private-sector employees of New York State businesses that utilize battery technology.
Led by Binghamton University, the Energy Storage Engine in Upstate New York is one of the inaugural NSF-supported Regional Innovation Engines across the country. It is dedicated to building a comprehensive battery and energy storage ecosystem in Upstate New York by fostering innovation, technology, translation, workforce development, and inclusive collaboration to support United States independence and leadership in these industries. Alfred University’s grant is a sub-award from GROW funding awarded to Syracuse University.
Among those talking the Battery Machine Learning course this week were three employees of Raymond Corporation, an electric forklift manufacturer in Greene, NY, which is developing new batteries at its facility in Kirkwood, NY, near Binghamton. They included Alfred University alumnus Ben Miller, who earned a bachelor’s degree in electrical engineering in 2002 and also a master’s degree in electrical engineering in 2003.
Miller, a development engineer at Raymond, said he and his colleagues—Michael Dunham, energy systems engineer, and Akshay Khairnar, mechanical systems product engineer—took the course to gain a better understanding of the technology used to predict the useful life of batteries and determine rates of battery degradation and how it can be applied to the battery development initiatives at Raymond.
Alfred University faculty gave presentations during the class. Zachary Knepp, assistant professor of chemistry, spoke on electrochemistry; Dan Lu, associate professor of renewable energy engineering, spoke on machine learning; and Kun Wang, assistant professor of materials science and engineering, and Naimul Haque, graduate student in electrical engineering and a teaching assistant in the Battery Machine Learning Lab, spoke on Microsoft applications for battery machine learning.
Kun Wang is principal investigator for the NSF project. Gabrielle Gaustad ’04, dean of the Inamori School of Engineering; Scott Misture ’90, ’94 PhD, Inamori Professor of materials science and engineering; and Xingwu Wang, professor of electrical engineering, serve as project co-investigators.
Three Alfred University students who just completed their first year of studies—Abby Atnafe, computer science major; Elijah Kahl, glass science engineering major; and Jeonghyun Song, ceramic engineering major—took the course. So, too, did two other undergraduate engineering students who graduated from Alfred-Almond Central High School and are enrolled in other institutions—Liam Carstens, Binghamton University, and Jack Byrnes, Princeton University. Liam Carstens is the son of Shawn Carstens, academic success coach in Alfred University’s Bernstein Center for Advising.