Παρασκευή 04 Μαρτίου 2011
What's New & Exciting @ University of Houston
Ioannis A. Kakadiaris
Depts. of Computer Science and ECE, U. of Houston
The goal of the talk is to present an overview of state-of-the-art research themes at the University of
Houston (UH). The first part of the talk will provide an overview of the research activities of the UH Depts. of CS and ECE.
The second part will outline selected research projects of the UH Computational Biomedicine Laboratory (CBL). Our passion for research is fueled by fundamental open problems in the broad and challenging areas of data analytics and machine learning, and their applications on computer vision and pattern recognition with an emphasis on human-centered computing such as face recognition, non-verbal human behavior understanding, cardiovascular informatics, neuro-informatics, and cancer informatics. Our mission in the pursuit of scientific excellence and innovative engineering, enabling pragmatic solutions to problems of societal impact. For example, our effort to understand non-verbal human behavior focuses on facial expression analysis and activity recognition. In the domain of cardiovascular informatics, we seek to develop a new scoring algorithm capable of identifying individuals who are at risk of suffering a heart attack in the next 12 months. Finally, in the area of neuroinformatics, we are focused on reconstructing the morphology of single neurons towards increasing our knowledge of brain function. Recent advances in each of these exciting research areas and challenging open problems will be highlighted.
UH, one of the largest universities in the U.S.A. with over 36,000 students, is located in one of the most vibrant metropolitan areas. Houston, the 4th largest U.S. city, is the epicenter of the energy industry, features the largest medical center in the world, and hosts the Johnson Space Center. The Department’s research laboratories have joint programs with laboratories from the local medical schools and hospitals, NASA, and the high-tech industry. Recently, UH has also launched two strategic initiatives in the areas of Health and Energy capitalizing on its location. CBL's work in vasa vasorum (neovascularization) imaging pioneered a new very active research area in cardiovascular screening, our 3D-3D face recognition software ranked first in the 3Dshape section of the 2007 Face Recognition Vendor Test (FRVT) organized by NIST, while our 3D-2D system outperforms the state of the art 2D-face recognition methods. During the visit, I will be delighted to meet with anyone who is excited about the research opportunities at the University of Houston whether they are students (internships, graduate scholarships, postdoctoral positions) or faculty (collaborations, short term visits, sabbaticals). Please email me directly or contact my host.
Ioannis A. Kakadiaris is an Eckhard Pfeiffer Professor of Computer Science, Electrical & Computer Engineering, and Biomedical Engineering at the University of Houston (UH). He joined UH in August 1997 after a postdoctoral fellowship at the University of Pennsylvania. Ioannis earned his B.Sc. in physics at the University of Athens in Greece, his M.Sc. in computer science from Northeastern University, and his Ph.D. at the University of Pennsylvania. He is the founder of the Computational Biomedicine Lab (http://www.cbl.uh.edu) and in 2008 he directed the Methodist-University of Houston-Weill Cornell Medical College Institute for Biomedical Imaging Sciences (IBIS) (ibis.uh.edu). His research interests include biometrics, computer vision, pattern recognition, biomedical image analysis, and cardiovascular informatics. Dr. Kakadiaris is the recipient of a number of awards, including the NSF Early Career Development Award, Schlumberger Technical Foundation Award, UH Computer Science Research Excellence Award, UH Enron Teaching Excellence Award, and the James Muller Vulnerable Plaque Young Investigator Prize. His research has been featured on The Discovery Channel, National Public Radio, KPRC NBC News, KTRH ABC News, and KHOU CBS News.