Faculty
Chandra Kambhamettu
Professor
ENB 339
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Biography
Chandra Kambhamettu is a professor in the ±«Óătv Bellini College of Artificial Intelligence, Cybersecurity and Computing. He joined the college in 2025 after more than two decades at the University of Delaware, where he directed the Video/Image Modeling and Synthesis Lab and held appointments in computer and information sciences, electrical engineering, and biomedical engineering. Before that, he served as a research scientist at NASA, where he contributed to visualization and modeling projects for weather and environmental systems.
Kambhamettu brings deep expertise in computer vision, artificial intelligence, deep learning, and biomedical image analysis. At ±«Óătv, he contributes to both graduate and undergraduate instruction in these areas.
Research Interests
His research spans a wide range of applications in vision and imaging, with an emphasis on developing algorithms that help computers understand and interpret complex visual data. His work has advanced fields such as optical flow estimation, 3D modeling, dynamic scene understanding, and biomedical image analysis.
Kambhamettu’s work is centered on computer vision and machine learning, with particular interest in non-rigid shape modeling, motion tracking, and spatiotemporal data analysis. His algorithms have been used in remote sensing, autonomous navigation, medical diagnostics, and augmented reality, among other domains. A key area of focus in recent years has been the development of physics-informed machine learning models and hybrid approaches that integrate deep learning with domain-specific constraints. At ±«Óătv, he aims to expand this work through new collaborations that combine foundational AI research with social and scientifically significant applications.
He has partnered with national laboratories, hospitals, and research centers on projects ranging from hurricane forecasting to retinal imaging and gastrointestinal diagnostics.
He has served as principal investigator or co-investigator on interdisciplinary teams supported by multi-million competitive grants from the National Science Foundation, the National Institutes of Health, NASA, and the U.S. Department of Defense, the U.S. Department of Agriculture, the National Oceanic and Atmospheric Administration, the U.S. Army, the Nemours Foundation, and the Miller Foundation, among others.
Honors and Awards
Kambhamettu received NASA’s Outstanding Scientist Award in 1996 for his contributions
to hurricane visualization. He is a senior member of IEEE and the recipient of the
NSF CAREER Award, recognizing early-career faculty who integrate research and education.
He has also been honored for research excellence and student mentoring by the University
of Delaware and has earned recognition in international competitions for innovations
in assistive technologies. Over his career, he has advised more than 30 graduate students
and collaborated with researchers across disciplines, including oceanography, atmospheric
science, radiology, and biomedical engineering.
In 2025, he and his collaborators received the “Test of Time” award from Winter Conference
on Applications of Computer Vision, recognizing lasting impact on the field of computer
vision and biometrics. That paper, "Deeply-Learned Feature for Age Estimation," introduced
a deep learning approach for estimating a person’s age from facial images, a task
traditionally hindered by variations in lighting, pose, and expression. Kambhamettu
and his collaborators demonstrated that features learned through a deep convolutional
neural network significantly outperformed hand-crafted features used in prior models.
The approach set a new standard for accuracy and its continued relevance.
Education
Kambhamettu earned both his master’s and doctoral degrees from the University of South Florida in Tampa, FL, both in computer science and engineering. He earned a bachelor’s degree in the same field from Osmania University in Hyderabad, India.