Image & Acoustic Signals Analysis (IASA) uses state-of-the-art equipment and techniques to analyze digitized signals, for example, for facial and speech recognition. The research carried out by first-year students in the IASA research stream at Binghamton University addresses a variety of problems ranging from autism classification through gaze, automatic sign language recognition through gesture recognition, and facial expression recognition through state of the art techniques.
Image & Acoustic Signals Analysis is cross-disciplinary in nature
Image and Acoustic Signals Analysis
Artificial Intelligence
Computer Vision
Robotics
Machine Learning
Mathematics
Signal Processing
IASA research intersects the traditional disciplines of Computer Science, Computer Engineering and Electrical Engineering. FRI IASA students tackle state of the art questions related to biometrics, human-computer interaction and robotics. The questions answered here will help give people a better quality of life, increase communication and make the world a safer place to live.
IASA Research Educators
Umur Aybars Ciftci is one of the Research Educators for Image and Acoustic Signals Analysis research stream since Spring 2019. He received the MSc degree in computer science from Binghamton University in 2014. He is currently a Ph.D. candidate in the Computer Science department of Binghamton University where he is part of the Graphics and Image Computing Laboratory. His research interests are in computer vision, human-computer interaction and affective computing.
