IEEE WIE ROC Virtual Speaker Series: Trustworthy and Adaptive AI for Imaging Systems
IEEE WIE ROC Virtual Speaker Series
Trustworthy and Adaptive AI for Imaging Systems
Dr. Dimah Dera
Frederick and Anna B. Weidman II Professor
Rochester Institute of Technology
Abstract:
This work advances the development of trustworthy and adaptive artificial intelligence for imaging applications. Building on Bayesian uncertainty estimation and probabilistic learning, the proposed framework enables imaging systems to assess their confidence, adapt to changing environments, and maintain reliability under data drift. Applications span medical image segmentation, remote-sensing anomaly detection, and autonomous vision, where uncertainty-guided adaptation enhances safety, interpretability, and robustness. The approach integrates statistical signal processing with deep learning to create imaging-based AI systems that are self-aware, resilient, and transparent in real-world conditions.
Speaker Bio:
Dr. Dera holds a Ph.D. and M.S. in Electrical and Computer Engineering and an M.A. in Mathematics from Rowan University. Her research focuses on adaptive and uncertainty-aware AI systems grounded in Bayesian theory and statistical signal processing, with applications in healthcare, remote sensing, and autonomous imaging. She has received numerous accolades, including the NSF CISE CRII Award (2023), IEEE Best Paper Award (2019), and the NJ Tech Council STEM Innovator to Watch Award (2019).
Intended Audience:
Beginners, undergraduates, graduates. Those with interest in the topic.
Event Snapshot
When and Where
Who
This is an RIT Only Event
Interpreter Requested?
No