Computer Science

Mr. Todd Proebsting is Department Head and Professor of Computer Science at the University of Arizona. Mr. Proebsting worked for Microsoft for fifteen years, and is the Founder of Microsoft's efforts in using prediction markets to help forecast future events. He received his B.S. in Business Administration and Operations & Management from Lincoln University. Mr. Proebsting's research interests include cloud computing, programmer productivity and making resources even more accessible to developers. His knowledge on Cloud computing enables people to harness the power of networked resources productively and can overcome the inherent complexities of large-scale processing done on commodity hardware, allowing applications to scale elastically and reliably. This software knowledge allows Mr. Proebsting to focus on investigating how to get rid of all the clutter in most statically-checked computer programs without sacrificing the benefits of static analysis.

John Kececioglu is an Associate Professor in the Department of Computer Science, and the BIO5 Institute. His research is in applied algorithms, especially for areas of bioinformatics and computational biology such as: multiple alignment, inverse alignment, sequence assembly, and genome rearrangement. Software developed by his group includes Opal, a tool for multiple sequence alignment; Facet, a tool for alignment accuracy estimation; Ipa, a tool for inverse sequence alignment; AlignAlign, a tool for optimally aligning alignments, and Ninja, a tool for evolutionary tree construction. John is a recipient of a National Science Foundation CAREER Award, serves as an Associate Editor for IEEE/ACM Transactions on Computational Biology and Bioinformatics, and is on the Editorial Board of Algorithms for Molecular Biology. He was Conference Chair for RECOMB 2009, and Program Committee Co-Chair in the area of Sequence Analysis for ISMB 2011 and BCB 2012. John served as Associate Head of the Department of Computer Science during 2012.

Kobus Barnard, PhD, is an associate professor in the recently formed University of Arizona School of Information: Science, Technology, and Arts (SISTA), created to foster computational approaches across disciplines in both research and education. He also has University of Arizona appointments with Computer Science, ECE, Statistics, Cognitive Sciences, and BIO5. He leads the Interdisciplinary Visual Intelligence Lab (IVILAB) currently housed in SISTA. Research in the IVILAB revolves around building top-down statistical models that link theory and semantics to data. Such models support going from data to knowledge using Bayesian inference. Much of this work is in the context of inferring semantics and geometric form from image and video. For example, in collaboration with multiple researchers, the IVILAB has applied this approach to problems in computer vision (e.g., tracking people in 3D from video, understanding 3D scenes from images, and learning models of object structure) and biological image understanding (e.g., tracking pollen tubes growing in vitro, inferring the morphology of neurons grown in culture, extracting 3D structure of filamentous fungi from the genus Alternaria from brightfield microscopy image stacks, and extracting 3D structure of Arabidopsis plants). An additional IVILAB research project, Semantically Linked Instructional Content (SLIC) is on improving access to educational video through searching and browsing.Dr. Barnard holds an NSF CAREER grant, and has received support from three additional NSF grants, the DARPA Mind’s eye program, ONR, the Arizona Biomedical Research Commission (ABRC), and a BIO5 seed grant. He was supported by NSERC (Canada) during graduate and post-graduate studies (NSERC A, B and PDF). His work on computational color constancy was awarded the Governor General’s gold medal for the best dissertation across disciplines at SFU. He has published over 80 papers, including one awarded best paper on cognitive computer vision in 2002.