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ACM Youngstown

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About us

ACM Youngstown is a non-profit professional group that meets regularly to discuss diverse topics in computer science such as virtual reality, game development, predictive analytics, applied machine learning, statistical modeling, open data, data visualization, user experience, user research, and artificial neural networks. Meeting topics are varied and range from tutorials on basic concepts and their applications, to success stories from local practitioners and academic students, to discussions of tools, new technologies, and best practices. All are welcome to attend, to meet others, and to present their work.
ACM Youngstown is powered by the NEO ACM Professional chapter (http://www.neoacm.org) and ACM Local (http://local.acm.org) at Association for Computing Machinery, Inc.

Featured event

NEOACM REMOTE TECH TALK: Towards Interpretable & Sustainable AI 09/19/26

Sat, Sept 19 · 14:00 EDT

Online

"The Nexus: AI, Computing and Our Future" is an annual event featuring speakers who will discuss the advancements and concerns of the current state of AI and computing, and their impact on practitioners, researchers, students, the general public, and the quality of our lives and society.

For our inaugural event, we are honored to welcome Dr. C.-C Jay Kuo, Distinguished Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California (USC), who will present his lecture entilted:

# Toward Interpretable and Sustainable AI

Dr. Kuo holds an M.S. and a Ph.D. from the Massachusetts Institute of Technology, Cambridge, and is a Fellow of AAAS, ACM, IEEE, NAI, and SPIE. His presentation will cover his pioneering research in green computing. This event will be a remote presentation and will take place on September 19, 2026 at 2:00 – 3:30 EDT PM.

Given that data centers and large Deep Learning networks have a high carbon footprint that threatens our environment, it is imperative to find alternative AI technologies that are interpretable and sustainable. Dr. Kuo has researched Green AI/ML models characterized by low carbon footprints, small model sizes, low computational complexity, and mathematical transparency. Green AI/ML has been successfully applied to various applications and he discusses several examples during his presentation to demonstrate their effectiveness and efficiency.