Computer Science Department supports three designated research centers
Within the MU College of Engineering, 12 areas of collaborative research have been designated as research centers. Directed by engineering faculty members, each center is dedicated to a research specialty, a distinction that adds stature to interdisciplinary work being done in the specialty area by a group of MU researchers, especially when research groups seek funding. Faculty members in the Computer Science Department direct three of the college’s centers.
Center for Urban Safety
Associate Professor Ye Duan leads the Center for Urban Safety. Several additional engineering faculty members are affiliated with the center, which concerns itself with the development of systems that will predict, monitor and mitigate the impact on urban systems caused by natural and man-made disasters, including terrorist attacks.
A current highway project uses an underground robot to assess roadway quality and detect potential problems.
Members of the research group are in the process of applying for funding to build a digitally navigable 3-D model of downtown St. Louis that could be used to discern the best routes for emergency response.
Center for High Assurance Computing
Associate Professor Bill Harrison leads the Center for High Assurance Computing. Work conducted through the center takes aim at making certain computer systems are secure and data remains confidential. Harrison’s efforts contributed to MU’s designation as a Center for Academic Excellence in Information Assurance Education by the National Security Agency.
One of the center’s collaborative research projects is directed at providing secure ballot transmission for American citizens who are overseas when state and national elections occur. Harrison is working with others in engineering and the Boone County clerk’s office on the project. The Department of Defense Federal Voting Assistance Program provided funding for the project. Additional funded research projects include malware analysis for the Department of Defense, and an investigation into the security of imported hardware.
The ability of game theory to predict economic models and insider threats is area of interest and Harrison has applied for funding to further investigative the possibilities.
Center for Computational Biology and Medicine
Professor Chi-Ren Shyu leads the Center for Computational Biology and Medicine. The center’s collaborators include faculty and students from engineering, education, biology, plant sciences, psychology, the MU Sinclair School of Nursing and the MU School of Medicine.
A recent National Science Foundation-funded collaborative project with a number of other universities made use of computational methodologies to understand the characteristics of shapes, which often dictate biological function. In nature, shapes change over time, so, for instance, looking at shapes can help predict the date of sediment layers based on the shapes of organisms within them.
Projects include an ongoing NIH-funded collaboration with MU nursing Professor Jane Armer, which is collecting spatial and temporal data from breast cancer surgery patients from around the world who have suffered from lymphedema associated with the surgery. The researchers are building a common dataset and data analytic tools to better inform physicians and therapists.
Toni Kazic, an MU associate professor of computer science working under the center’s umbrella, is conducting research on maize phenotypes. Funded by NSF, Kazic is extracting phenotypic information from images of diseased maize and building a database in order to have the ability predict pathology from images.
Under the auspices of the center, funded by NSF, another MU computer science colleague, Assistant Professor Dmitry Korkin, is investigating mimicry in host-pathogen interactions. Pathogens can alter cellular functions by mimicking a host protein’s structure or its function. Korkin is working to develop computational methods to detect mimicry.
An additional recent NSF-funded project with MU faculty collaborations used web cameras to track eye movement — called gaze tracking — in “reasoning for training” procedures. Doctors, from novices to experts, were asked to look at and assess images like X-rays for specific diagnostics, while the camera measures “fixations” and “saccades.” The research is aimed at proving that visual reasoning and knowledge representation for clinicians can be computationally modeled. The applications of such researches include medical error detection, security authentication and image analyst training.