ECE Seminar: From Plumes to Produce: Leveraging Atmospheric Modeling and Smart Sensing for Food Safety
Presenter: Derek Hollenbeck, postdoctoral research scholar, University of California, Merced
Description: Advances in drone-based environmental sensing, atmospheric modeling, and intelligent monitoring systems are creating new opportunities for addressing emerging challenges in food safety and agricultural resilience. This talk explores how methodologies originally developed for methane emission detection and quantification could be translated toward agricultural and food safety applications. The presentation begins with an overview of research experiences in autonomous sensing and environmental monitoring, including work associated with the inaugural CITRIS Aviation Prize before outlining some key potential areas for food safety with drones. Then, the talk overviews previous research on the topics related to drone-based environmental monitoring, Digital Twins, and Smart Sensing – with a focus on methane emission source quantification, atmospheric transport modeling of a point source, and inverse problem methodologies for real-time parameter estimation. Finally, the talk examines how these concepts may be adapted to food safety research questions, as well as highlight opportunities for interdisciplinary collaboration alongside emerging priorities from organizations and certification frameworks.
Bio: Derek Hollenbeck is a postdoctoral research scholar at the University of California, Merced (UCM), where he serves as the manager of the Center for Methane Emissions Research and Innovation (CMERI) under the supervision of Dr. YangQuan Chen. He earned his B.Sc. (2016) and Ph.D. (2023) in Mechanical Engineering from UCM, where he conducted research in the Mechatronics Embedded Systems and Automation (MESA) Lab.
His work sits at the intersection of fluid mechanics, controls, dynamics, and inverse problems, with a focus on developing intelligent environmental monitoring systems using small unmanned aerial systems (sUAS). His research integrates machine learning and physics-based modeling to detect, localize, and quantify methane emissions in complex environments.
Dr. Hollenbeck is the author of Smart Sensing with Digital Twins: Methane Emission Source Determination with sUAS, which presents a framework for combining digital twins, inverse modeling, and autonomous sensing to improve environmental observability. His work emphasizes how data-driven and physics-informed approaches can be fused to optimize sensor placement, enhance estimation accuracy, and enable real-time decision-making in single/distributed mobile sensing systems.
Hosted by: Professor Marco Rolandi, ECE Department
Zoom Link: https://ucsc.zoom.us/j/96727838511?pwd=1Qzl9HTV3G2BxaSEG8GeKOPZVu2NWj.1