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IEEE Rochester Section ExCom Meeting – July 2024
IEEE Rochester Section ExCom Meeting – July 2024
The monthly Rochester IEEE Executive Committee meeting brings together all of the leaders of the Section, Chapters, and Groups. At this meeting, we review plans for upcoming Rochester meetings within our Section, Chapters, and groups. If you are looking to become more engaged in IEEE in the Rochester Section, please plan on attending an Excom meeting! The July ExCom meeting is cancelled. The next regular Rochester Section ExCom meeting will occur on (https://events.vtools.ieee.org/m/422864). ***CANCELED*** Agenda: No meeting will be held for July. Bldg: Tandoor of India, 376 Jefferson Rd, Rochester, New York, United States, 14623, Virtual: https://events.vtools.ieee.org/m/420483
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Edge Computing in Cellular Systems: Implementation, Standardization and Applications
Edge Computing in Cellular Systems: Implementation, Standardization and Applications
This will be an interactive session. Prof. Huzur Saran, IIT New Delhi, India, will provide brief motivation of Edge Computing. He will then discuss the ETSI MEC architecture and its evolution in the 3GPP standards, followed by how it has been implemented in their 5G test-bed at Bharti School, IIT New Delhi, India. Prof. Saran, will present some of the applications related to edge intelligence to enable split control in haptics applications. He will also discuss the notion of "edgefiability" that looks at when having an edge intelligence is feasible. The discussion will end with some natural "next-step" identification. Room: 1400 Lecture hall, Bldg: 070, 1, Lomb memorial drive, Rochester, New York, United States, 14623
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Webinar: Neuromorphic Computing for Future AI Systems
Neuromorphic Computing for Future AI Systems Cory Merkel, Ph.D. Director, Brain Lab Assistant Professor, Department of Computer Engineering, RIT Abstract: Artificial intelligence (AI) has become the linchpin in a growing number of products, services, and research programs which are aimed at automating and enhancing the human decision-making process. There is no doubt that AI will play a central role in the future of healthcare, transportation, manufacturing, and defense, among others. However, the rapidly growing size, weight, and power (SWaP) cost of AI algorithms limits their deployment on devices with practical computing and energy constraints (satellites, wearables, wireless sensors). In this talk, I will discuss our lab’s efforts to bridge this gap by closely emulating the structure and function of biological brains, with the ultimate goal of enabling AI in the most SWaP-constrained environments. This research takes a holistic approach, examining the entire AI stack, from devices and circuits to algorithms and applications. At the lowest level, I will present our research on memristor-based circuits for implementing weighted communication pathways in artificial neural networks (ANNs) and spiking neural networks (SNNs). Memristors reduce the power and latency associated with running ANNs/SNNs on traditional computer architectures by directly emulating both the memory and computation of biological synapses. In addition, memristor plasticity enables on-chip learning and allows ANNs/SNNs to function in the presence of hardware defects and process variations. Moving up the design hierarchy, the talk will highlight ideas for biologically-inspired energy management in neuromorphic systems and efficient ANN/SNN topologies. Finally, the talk will provide an overview of our research related to the trustworthiness and potential security vulnerabilities of AI hardware with ties to human perception and psychology. Bio: Cory Merkel is an assistant professor with the Department of Computer Engineering, Rochester Institute of Technology. He earned his BS and MS degrees in computer engineering (2011) and a Ph.D. in microsystems engineering (2015) from RIT. From 2016 to 2018, Dr. Merkel was a research electronics engineer with the Information Directorate, Air Force Research Lab. He is currently the director of the Brain Lab, a multidisciplinary research lab aimed at fundamental research to enable the next generation of ultra-efficient and trustworthy AI systems. His current research focuses on mapping of AI algorithms, primarily artificial and spiking neural networks, to mixed-signal hardware, design of brain-inspired computing systems using emerging technologies, and trustworthy AI hardware. Dr. Merkel’s research has been published in a number of peer-reviewed conferences, journals, and books. Co-sponsored by: IEEE, Rochester Section, Region 1 Speaker(s): , , Agenda: Wednesday, July 31st, 7:30 PM: Introduction of Dr. Cory Merkel, tonight's speaker. 7:35 PM: Presentation: Neuromorphic Computing for AI Systems 8:20 PM: Questions and Answers 8:30 PM: Webinar end Virtual: https://events.vtools.ieee.org/m/426383