Invited Speakers and Panelists
Peter Bajcsy received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign (UIUC). He is currently a computer scientist at the National Institute for Standards and Technology in USA. Peter’s area of research is large-scale image-based analyses and syntheses using mathematical, statistical and computational models while leveraging computer science fields such as image processing, machine learning, computer vision, and pattern recognition. He has authored more than 30 papers in peer reviewed journals, and co-authored 8 books or book chapters and 100+ conference papers.
Edward J. Delp was born in Cincinnati, Ohio. He received the B.S.E.E. (cum laude) and M.S. degrees from the University of Cincinnati, and the Ph.D. degree from Purdue University. In May 2002 he received an Honorary Doctor of Technology from the Tampere University of Technology in Tampere, Finland.
In 2008 he was named a Distinguished Professor and is currently The Charles William Harrison Distinguished Professor of Electrical and Computer Engineering and Professor of Biomedical Engineering and Professor of Psychological Sciences (Courtesy) at Purdue University.
His research interests include image and video processing, image analysis, computer vision, image and video compression, multimedia security, medical imaging, multimedia systems, communication and information theory.
Dr. Delp is a Fellow of the IEEE, a Fellow of the SPIE, a Fellow of the Society for Imaging Science and Technology (IS&T), and a Fellow of the American Institute of Medical and Biological Engineering. In 2004 Dr. Delp received the Technical Achievement Award from the IEEE Signal Processing Society for his work in image and video compression and multimedia security. In 2015 he was named Electronic Imaging Scientist of the Year by the IS&T and SPIE.
Danna Gurari is currently a Postdoctoral Fellow at University of Texas at Austin under the supervision of Dr. Kristen Grauman. She completed her PhD at Boston University in the Image and Video Computing Group under the supervision of Dr. Margrit Betke. Her research interests span computer vision, human computation/crowdsourcing, medical/biomedical image analysis, and applied machine learning. In 2007-2010, Danna worked at Boulder Imaging building custom, high performance, multi-camera recording and analysis systems for military, industrial, and academic applications. From 2005-2007, she worked at Raytheon developing software for satellite systems. Danna earned her BS in Biomedical Engineering and MS in Computer Science from Washington University in St. Louis in 2005, with her thesis on ultrasound imaging. Danna was awarded the 2015 Researcher Excellence Award from the Boston University computer science department, 2014 Best Paper Award for Innovative Idea at MICCAI IMIC, and 2013 Best Paper Award at WACV.
Dr. Daniel Hoeppner is an investigator at the Lieber Institute for Brain Development (LIBD), an interdisciplinary research organization founded to treat schizophrenia through understanding its developmental origins. Dr. Hoeppner applies quantitative cellular imaging and high-throughput sequencing of induced pluripotent cells as they transition from pluripotent stem cells through a series of self-organizing meta-stable developmental states, ultimately producing active neurons. At LIBD, Dr. Hoeppner has created a world-class light imaging environment that enables laser capture microdissection of post-mortem brain, multispectral confocal microscopy, medium-throughput high-content imaging and quantitative image analysis. Prior to LIBD, Dr. Hoeppner was a student at Cold Spring Harbor Laboratory, then a fellow and staff scientist at NIH.
Dr. Dimitris Metaxas is a Distinguished Professor in the Computer and Information Sciences Department at Rutgers University since 2007. He was a tenured faculty of Computer Science at the University of Pennsylvania from 1992 to 2002. He is currently the Chair of the department and is directing the Center for Computational Biomedicine, Imaging and Modeling (CBIM) and the NSF I/UCR Center on Dynamic Data Analytics between Rutgers and Stony Brook.
Prof. Metaxas received a Diploma in Electrical Engineering from the National Technical University of Athens Greece in 1986, an M.Sc. in Computer Science from the University of Maryland, College Park in 1988, and a Ph.D. in Computer Science from the University of Toronto, Ontario, Canada in 1992. Dr. Metaxas has been conducting research towards the development of formal methods upon which computer vision, computer graphics and medical imaging can advance synergistically.
In biomedical applications new methods have been developed for material modeling and shape estimation of internal body parts (e.g., lungs) from MRI, SPAMM and CT data, a pioneering framework for cardiac motion analysis and for linking the anatomical and physiological models of the human body. In the past 10 years he has been focusing on microscopic image analytics, histopathology-based tissue characterization, mouse behavior analytics for coupling phenotype and genotype and novel imaging methods such as 3D bioluminescence.
In computer vision, new methods have been developed for deformable models, 3D human motion analysis, behaviors, machine learning, sparse methods, surveillance, object recognition and biometrics in the wild. New methods based on coupling models and learning are currently being pursued.
In computer graphics, he introduced the Navier-Stokes methodology for Fluid animations in the mid 90s, based on which the water scenes in the movie “Antz” were created in 1998. Since then, he is working on new techniques for modeling fluid phenomena, and control theoretic techniques for automating and improving the animation of articulated (e.g., humans) objects.
Dr. Metaxas has published over 500 research articles in these areas and has graduated 42 PhD students. The above research has been funded by NSF, NIH, ONR, AFOSR, HSARPA and the ARO. Dr. Metaxas work has received many best paper awards and he has 7 patents. He was awarded a Fulbright Fellowship in 1986, is a recipient of an NSF Research Initiation and Career awards, an ONR YIP, is a Fellow of the American Institute of Medical and Biological Engineers, IEEE and a member of ACM. He has been general chair of IEEE CVPR 2014, Program Chair of ICCV 2007, General Chair of ICCV 2011, FIMH 20011 and MICCAI 2008 and the Senior Program Chair for SCA 2007.
Dr. Tolga Tasdizen is an Associate Professor of Electrical and Computer Engineering at the University of Utah. He received his PhD from Brown University in 2001 and was a postdoctoral associate with the Scientific Computing and Imaging Institute at the University of Utah 2001-4. He is a Senior Member of the IEEE, IEEE Signal Processing Society and IEEE Computer Society. Dr. Tasdizen’s research interests are in the general areas of image processing and pattern recognition with applications to bioimage and medical image analysis. Dr. Tasdizen is a recipient of the NSF Early Career Award. He has served as an Associate Editor for the IEEE Signal Processing Letters (2012-16) and BMC Bioinformatics (2012-14) and is currently a member of IEEE Signal Processing Society’s Bio Imaging and Signal Processing Technical Committee.