Ifeoma Nwogu Headshot

Ifeoma Nwogu

Assistant Professor
Department of Computer Science
Golisano College of Computing and Information Sciences

585-475-4937
Office Location

Ifeoma Nwogu

Assistant Professor
Department of Computer Science
Golisano College of Computing and Information Sciences

Education

BS in Electrical Engineering, University of Lagos (Nigeria); MS in Computer and Information Science, University of Pennsylvania; Ph.D. in Computer Science and Engineering, University at Buffalo, SUNY

585-475-4937

Areas of Expertise
Machine Learning
Computer Vision
Computational Social Psychology

Currently Teaching

CSCI-631
3 Credits
An introduction to the underlying concepts of computer vision and image understanding. The course will consider fundamental topics, including image formation, edge detection, texture analysis, color, segmentation, shape analysis, detection of objects in images and high level image representation. Depending on the interest of the class, more advanced topics will be covered, such as image database retrieval or robotic vision. Programming assignments are an integral part of the course. Note: students who complete CSCI-431 may not take CSCI-631 for credit.
CSCI-431
3 Credits
An introduction to the underlying concepts of computer vision. The course will consider fundamental topics, including image formation, edge detection, texture analysis, color, segmentation, shape analysis, detection of objects in images and high level image representation. Depending on the interest of the class, more advanced topics will be covered, such as image database retrieval or robotic vision. Programming homework assignments that implement the concepts discussed in class are an integral part of the course.
CSCI-739
3 Credits
This course examines current topics in Intelligent Systems. This is intended to allow faculty to pilot potential new graduate offerings. Specific course details (such as prerequisites, course topics, format, learning outcomes, assessment methods, and resource needs) will be determined by the faculty member(s) who propose a specific topics course in this area. Specific course instances will be identified as belonging to the Intelligent Systems cluster, the Computational Vision and Acoustics cluster, the Security cluster, or some combination of these three clusters. Course offered every other year.