Drs. Ravi Chilukuri, Edgar Lobaton and Sevgi Gurbuz of the NC State Department of Electrical and Computer Engineering organized a workshop entitled “From Sensors to Decision Making: Delivering Precision Biomarker Insights with Resource-Constrained AI” at the IEEE Biomedical and Health Informatics Conference held in Atlanta, GA on October 29, 2025. See below for more details.
From Sensors to Decision Making: Delivering Precision Biomarker Insights with Resource-Constrained AI
Organizer:Sevgi Zubeyde Gurbuz, Edgar Lobaton, and Ravi Chilukuri
Presenters:Dr. Edgar Lobaton, NC State University, Dr. Omer Inan, Georgia Tech and Biozen, Dr. Brinnae Bent, Duke University, Dr. Chenhan Xu, NC State University, Dr. Sevgi Z. Gurbuz, NC State University, Bill Kutsche, Murata, Bharath Rajagopalan, ST
Precision health monitoring requires an integration of sensing and computation with biomechanics and bioengineering; however, oftentimes these domains are treated independently. A complete system integrating these domains faces critical challenges involving real-time computation, sensor signal processing, and multi-modal sensing for precision biomarker estimation. This workshop brings together experts along this entire processing chain and includes both academic and industry perspectives relating to performance, price and real-world deployment constraints. The workshop will feature talks from seven experts:
Dr. Edgar Lobaton, NC State University, Acoustic Wearable Monitoring with Embedded AI
Dr. Omer Inan, Georgia Tech and Biozen, Designing CardioTag
Dr. Brinnae Bent, Duke University, Designing Intelligence Under Constraints
Dr. Chenhan Xu, NC State University, Precision Sensing in Human-centric IoT
Dr. Sevgi Z. Gurbuz, NC State University, Real-time AI/ML with RF Sensors
Bill Kutsche, Murata, RF Modules for Medical Devices
Bharath Rajagopalan, ST, AI-enabled Sensors for Healthcare
The workshop will also feature two panel discussions related to the inter-disciplinary aspects of the workshop theme, spanning 1) sensing for precision health, 2) real-time edge computing, and 3) AI for sensing.