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Mohammed Yeasin

Mohammed Yeasin

Mohammed Yeasin

Associate Professor
Electrical and Computer Engineering
901.678.4078(office)
901.678.5469(fax)
myeasin@memphis.edu
lab website
curriculum vitae


Dr. Yeasin leads the Computer Vision, Perception and Image Analysis (CVPIA) laboratory. Main thrust of research in the CVPIA lab is in the general areas of computer vision, data mining, bio-informatics/computational biology, pattern recognition and human computer interfaces (HCI). The common underlying theme is (i) semantic integration and mining of large heterogeneous data, (ii) robust analysis and modeling of all possible types of signals (text, speech, images, video, time series and gene expressions etc.), and (iii) use service oriented architecture in providing services, and sharing databases and results. Major topics of research include (but are not limited to):

  1. Co-analysis of signal and sense and the interplay between the complementary modalities and the prosodic manifestations of their synchronization to develop novel algorithms for the recognition of gestures, facial expressions, emotions, dialog acts (DAs), behavior-based biometrics, and their applications in developing Meta-Tutor agents.

  2. Co-design and Integration of hardware and software for perceptual human-machine interfaces and mobility assistance for people who are blind or visually impaired. Towards this end a Reconfigured Mobile Android Phone (R-MAP) was developed to provide reading out-loud service to the visually impaired.

  3. Developing efficient and scalable algorithms for distributed data and graph mining, and their application to knowledge discovery from heterogeneous data. Also of interest, is to develop service oriented architecture to provide Web services in emerging areas like epigenetic and genome wide study.

  4. Sensor networks for monitoring large areas such as trails of drug smugglers.

  5. Image analysis and computer vision solutions for biomedical applications (medical informatics and modeling and evaluation of surgical skill) and robust analysis of human motion for creating articulated models of human body parts.

  6. Music therapy! Just like to do scale-space analysis of brain signals as a hobby.