Faculty and Staff Profiles

Dr. Yeasin is an Associate Professor and a Data Scientist. He is the recipient of National Science Foundation (NSF) Career Grant, Senior Member of the IEEE and Associate Editor of two peer reviewed Journals (BMC Bioinformatics and PRML). He is practicing machine learning for 15 years in the field of Bioinformatics, Biomedical Engineering, Computer Vision, Cognitive Engineering, Human Computer Interaction and Assistive Technology. He is leading a group of enthusiastic students to conduct cutting edge research in collaboration with partners from the academia, industry, and community at large. He is the leader of Blind Ambition – an interdisciplinary research and outreach effort pioneering assistive solutions for people who are blind. He introduced the notion of assistive thinking – a seamless blend of participatory design, system thinking and design thinking to develop technology solutions. He has 23 years of academic experience and authored/co-authored over 125 peer reviewed technical papers. He is committed to provide quality educational experiences while gaining perspective through research, and engaged scholarship. He has proven record of academic excellence and established a successful research program to: (i) publish original works in peer reviewed journals and conferences, (ii) recruit, train and retain graduate students and also minority students, (iii) identify and advance cutting edge research, (iv) integrate research with the classroom teaching to increase his effectiveness as an educator, and (v) create a culture of research. He has been involved with many technological innovations (for example, ARIANA, Emo-Assist, Expression, i-FEPS, O-MAP, i-TOBI/i-CBE etc.). He pioneered the concept of co-analysis of signals and sense for modeling emotions, behavioral expressions, epistemic state of mind, gestures and consumer demographics. He strives to find intuitive explanation of complex concepts to further innovation. He is an expert and also an enthusiast of asking relevant questions, connecting ideas and is a lifelong learner. He has extensive knowledge in video analysis and big data analytics.

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.  Assistive Technology Solutions,b> The main goal is to develop adaptive, affordable, effective, portable and usable assistive technology solutions for the people who are blind or visual impaired. The key idea is to keep the design simple so that the user can interact with the system effectively with minimal cognitive effort.

2. Big Data Analytics Develop algorithms and tools for text analytics, data stratification/growing data size, finding networks of semantic associations among different concepts, effective and flexible visualization of information at various levels of granularity and interactive Web services for diverse users through both cloud and mobile platform.

3. Cognitive Engineering Study temporal dynamics in human working memory network to better understand individual difference in quantification of performance or understand disorders. Our hypothesis is individuality and variation in cognitive capacity can be predicted from the functional connectivity of cerebral networks.  

4.          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.