Abstract

Modern data from images, videos, scientific instruments, and social systems is high dimensional yet highly structured. My research focuses on developing computational methods to discover and exploit this structure. I will present work spanning geometric vision, temporal modeling of human motion, robust visual tracking, and applications of machine learning to scientific and environmental data. Together, these efforts illustrate how combining geometry, learning, and data-driven modeling can enable new forms of perception and discovery across diverse domains.

About the Speaker

Eraldo Ribeiro is an Associate Professor of Computer Sciences at Florida Institute of Technology. He has a Ph.D. degree in Computer Vision from the Department of Computer Science at the University of York, in the United Kingdom. Dr. Ribeiro’s main research interests are in the areas of computer vision and pattern recognition. Ongoing research topics include human-motion recognition, activity recognition, and object recognition.