Research Interests by Faculty Member



Researcher: Eric Bachmann

  • Project: Eric Bachmann’s research interests include human factors and training in virtual environments (VE), enabling immersed VE users to explore virtual worlds of unlimited size, and locomotion interfaces for virtual environments. He has conducted extensive research in human posture tracking and gait measurement for navigation using inertial/magnetic sensor modules.
  • Project: The HIVE (huge immersive virtual environment) is a state-of-the-art virtual environment facility on the Oxford campus of Miami University. Funded by a grants from the U.S. Army Research Office (ARO) and the National Science Foundation(NSF), the HIVE offers completely untethered full-body tracking of multiple users in a physical space larger than 1000 square meters. Its size and functionality make the HIVE a unique facility in the research community and one of the premier facilities in the world for conducting research and demonstrating the effectiveness of immersive virtual environments.

Researcher: William (Bo) Brinkman

  • Project: Dr. Brinkman is interested in algorithms for geometric problems and the social and ethical implications of computing. In algorithms he is most interested in approximation algorithms and hardness results for metric space embedding problems, such as dimension reduction, and Euclidean and rectilinear embeddings of graph metrics. In computing ethics he is interested in a wide array of topics, but his current focus is on the implications of the (hypothetical) wide-spread adoption of augmented reality.

Researcher: Janet Burge

  • Project: Janet Burge’s research studies to utilize expert knowledge captured in the form of rationale: the reasons behind decisions made when planning, designing, and implementing. The rationale provides intent of the decision-maker and can be used to evaluate the decisions, avoid repeating past mistakes, and learn from past experience. Applications of rationale use currently being studied include software engineering and engineering design.

Researcher: Valerie Cross

  • Project: She has a broad research agenda on the role of ontologies in the development of the Semantic Web and narrower research projects on: 1) assessing semantic agreement within and across ontologies, 2) consumer metrics for evaluation of ontologies, 3) adapting techniques for finding and visualizing semantic pathways through the WordNet ontology, 4) modifying and extending existing ontologies through learning techniques to enable ontology re-use, and 5) adapting scientific visualization techniques for exploring information contents and structure of ontologies.
  • Project: She has expertise in the management of uncertainty in knowledge bases with fuzzy set theory and approximate reasoning. She is investigating the role of uncertainty management in the Semantic Web.
  • Project: Multi-FCA is a system being developed that combines ontological terminologies and annotation databases through the use of formal concept analysis (FCA) to analyze the similarity or discover the relationships among the annotated objects. It is a user friendly and generic tool that focuses on FCA for annotated objects whose annotations come from an ontological terminology. An already existing system QUOTA (QUerying Ontological Terminologies and their Annotations) permits the user to assess the similarity of annotated objects and to summarize a set of annotated objects using the most descriptive ontology terms for the input set.

Researcher: Keith Frikken

  • Project: Keith Frikken’s research interests are in the areas of information security and applied cryptography. His specific interests include: privacy-preserving protocols for computing collaborative outcomes without revealing information, key mechanisms for access control (including hierarchical, temporal, and geo-spatial), secure (privacy and integrity) aggregation in sensor networks, authenticated and confidential outsourcing, security in social networks, and private data publishing.

Researcher: Gerald Gannod

  • Project: Semantic Web Services. Dr. Gannod has been developing approaches for facilitating the adoption of semantic web services through the use of model-driven architecture and model-driven development. The benefits of this research for software developers are three-fold. First, the work is intended to increase productivity by focusing developer attention on modeling rather than programming. Second, the work is intended to facilitate migration of software and people towards the ontology-based paradigm whereby knowledge about various domains can be embedded in software in order support development activities. Finally, the work is meant to address common development problems such as those related to composition and integration of systems. In addition, it is the intent of the work to eventually support the use of automated reasoning and automated agents to realize implementations of distributed applications.
  • Project: Autonomic Computing. Dr. Gannod has been developing an autonomic approach for the survivability of application-based web servers. Current web application-level Quality of Service (QoS) frameworks resort to refusing requests when met with overload. The self-healing adaptive content framework (SHAC) we are proposing allows dynamic web-based applications to adapt their output in order to minimize the effects of flash crowds and server overload without refusing requests. We present a methodology to create a SHAC system for existing web applications. An analytical Queuing Network model is created to predict the performance impact of the framework on existing systems. A PID controller-based autonomic manager is implemented to maintain response times below that of a preset service level agreement. Evaluation of the framework is shown through implementations in web services, a portal, an AJAX-driven systems and a blog server along with significant performance testing and QoS analysis.
  • Project: Reverse Engineering using Machine Learning. The complexity of the systems that software engineers build has continuously grown since the inception of the field. What has not changed is the engineers’ mental capacity to operate on about seven distinct pieces of information at a time. Improvements like the widespread use of UML have led to more abstract software design activities, however the same cannot be said for reverse engineering activities. The well-known concept assignment problem is still being solved at the line-by-line level of analyzing source code. The introduction of abstraction to the problem will allow the engineer to move farther away from the details of the system, increasing his ability to see the role that domain level concepts play in the system. In this work we have developed a technique that facilitates filtering of classes from existing systems at the source level based on their relationship to the core concepts in the domain. This approach can simplify the process of reverse engineering and design recovery, as well as other activities that require a mapping to domain level concepts.

Researcher: John Karro

  • Project: Computational Biology / Bioinformatics. Since the completion of the human genome project (as well as the mouse genome project, the dog genome project, the rice genome project, and many other genome projects), biologists have had unprecedented amounts of biological data to work with – far to more than can be dealt with by a human hand. Automated techniques for the analysis of biological data have become invaluable tools for the modern biologists, and have posed new computational challenges of interest to computer scientists. The development of new analysis tools constitute a contribution to biological research that can only be made by researchers with an understanding of computational science, but are leading biologists to a new understanding of human health, biological history, and the ability to identify genetic disorders and other diseases.

Researcher: James Kiper

  • Project: Software engineering, software risk assessment, design rationale. Advances in support for the early phases of software development, that is requirements engineering and design, can have great leverage in reducing problems in subsequent phases of a development process. Techniques and tools that can help in achieving requirements, reducing risk, and capturing and analyzing design rationale give engineers and managers important leverage in system development.

Researcher: Lukasz Opyrchal

  • Project: Lukasz Opyrchal's research interests include computer and network security, privacy, and distributed systems. His current projects include secure content-based publish subscribe systems, fine-grained access control in large databases, distributed on-line matching with private inputs, and phishing detection.

Researcher: Mufit Ozden

  • Interests: Optimization and simulation models and their applications to complex problems.

Researcher: Alton Sanders

  • Alton Sanders has long had a research interest in natural language processing, software engineering, computer-assisted instruction, and intelligent tutoring systems.

Researcher: Ann Sobel

  • Ann Sobel is interested in formal methods of software specification, software engineering, software specification methodology, and software engineering education.

Researcher: Doug Troy

  • Project: Doug Troy’s current research is in using technology to assist the people of the Miami Tribe with language and culture revitalization and preservation. Dr. Troy and his students develop and evaluate mobile computing applications, computer games, and interactive web applications that provide learning tools to tribal families that are dispersed around the county. We work closely with the Myaamia Project located on the Miami University campus.

Researcher: Yuksel Uckan

  • Yuksel Uckan's research interests include relational databases, deductive databases, object-oriented databases and languages.

Researcher: Mike Zmuda

  • Project: Mike Zmuda’s research interests centers on the use of artificial intelligence and machine learning for the design of intelligent systems. Techniques such as evolutionary computation, particle filters, supervised learning, search, and image processing are techniques he has applied to problems. Application areas of current interest are pattern recognition in high-dimensional data, robot localization, and sensor fusion.