Sedat Ozer is a researcher, a machine learning scientist and a data analysis expert. He is currently a PI at CRCV, UCF and collaborating with Mubarak Shah. (See the ranking of CRCV at UCF here in the computer vision field.) Before CRCV, he was a postdoctoral associate at CSAIL, MIT and was working with Daniela Rus in Distributed Robotics Lab. Before MIT, he was a postdoctoral associate at the Virginia Image and Video Analysis (VIVA) Lab at UVa with Scott Acton. Dr. Ozer received his PhD in the ECE dept. at Rutgers. His advisor was Deborah Silver. His dissertation title was: Activity Detection in Scientific Visualization.

He is a scientist by nature and an (electrical and computer) engineer by education. He likes studying and discussing the theory behind our daily world applications, their validity and applicability in general (in other fields). We have the tendancy of believing any "theory" presented to us, if it is provided with "some" logical evidence. However, while mostly true theories, sometimes a theory is confused with an hypothesis and (possibly due to a misuse of the term theory) such an hypothesis is also presented to us as a theory. These type of "theories" usually work only under certain assumptions which limits their applicability in general. This is where he likes doing research at, by enhancing the generality of what is available. Specifically his research interests overlap the following fields:

• Data, Signal, Image, Video Processing & Analysis,

• Machine learning (including both "shallow" and "deep" learning techniques),

• Visual Object Recognition & Detector Design,

• 3D Object and Group Tracking & Scientific Visualization,

• Activity Detection.