Date: Monday November 6, 2023
Time: 5:30pm MDT
Room: Zoom zoom.us, Meeting ID 942 3255 5926, passcode 171681
The talk will be held in Cramer Hall Room 203.
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Abstract: Advanced metering infrastructure (AMI), as an essential component of the modern smart grid, collects a massive amount of high-frequency power consumption data from customers through smart meters. Smart meter data analytics utilizes data-driven approaches to extract actionable knowledge from smart meter data, aiming to improve the efficiency and sustainability of smart grid applications. In this talk, I will introduce novel machine learning and deep learning approaches developed by my research group for smart meter data analytics applications, including building occupancy detection, electricity theft detection, and non-intrusive load monitoring (NILM).
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Jun Zheng is currently a full professor in the Department of Computer Science and Engineering at New Mexico Institute of Mining and Technology (New Mexico Tech). He earned his Ph.D. degree in computer engineering from the University of Nevada, Las Vegas. He leads the Human-Centered Computing and Security Lab at New Mexico Tech. His current research interests include cybersecurity, machine learning, deep learning, and their applications. His research has been supported by NSF, DOE, DHS, and ARL.