Research Centers and Facilities
Multi-agent systems, knowledge representation, computer vision, and intelligent tutoring systems are areas of research interest in the Department of Computer and Information Sciences at the University of Delaware. In addition, a Cognitive Science Program brings in well-known speakers from throughout North America and serves as a forum for joint research efforts with faculty from the departments of Educational Studies, Linguistics, and Psychology. Members of our AI group serve on the editorial boards of International Journal of Man-Machine Studies, Autonomous Agents and Multi-Agent Systems Journal, User Modeling and User-Adapted Interaction Journal, Machine-Mediated Learning, and Visible Language. In addition, they have served on the program committees for major conferences in artificial intelligence and multi-agent systems.
Multi-Agent Systems and Distributed Artificial Intelligence research deals with the issues that arise when groups or societies of autonomous agents (usually computer programs but sometimes people too) interact to solve problems. These agents may be self-interested, or cooperating to solve a shared problem. Important issues include reasoning about the knowledge and beliefs of other agents, communication and negotiation, and coordination and control. Furthermore, in many real-world problems, agents have limited computational resources available to them, and so must forgo optimal solutions for satisfying solutions.
Knowledge representation, planning, problem-solving, and plan recognition are important components of intelligent systems, especially systems that must react to their environment or interact with other agents, and several researchers are pursuing work in these areas. In addition, the video modeling and synthesis lab is studying a number of major problems in computer vision and image processing, with an emphasis on the modeling of non-rigid body motion.
- Rahmat Beheshti, Assistant Professor: Health Data Science; Applied Machine Learning.
- Austin Brockmeier, Assistant Professor: Algorithms and Statistical Models for Machine Learning and Data Science to process and extract relevant information from complex, high-dimensional data sets.
- Keith Decker, Associate Professor: Multi-agent systems; Distributed problem solving; Parallel and distributed planning and scheduling; Distributed information gathering; Bioinformatics; Computational organization design.
- Chandra Kambhamettu, Professor: Video Modeling and Image Analysis for biomedical, remote sensing, and multimedia applications.
- Kathleen McCoy, Professor (joint appointment with Linguistics & Cognitive Science): Artificial Intelligence, Computational Linguistics/Natural Language Generation, and Accessibility for People with Disabilities.
- Christopher Rasmussen, Associate Professor: Computer vision; Mobile robotics; Artificial intelligence.
- Ilya Safro, Associate Professor: Algorithms and Models for Quantum Computing; AI; Machine Learning; NLP; Network Science and Graphs; Large-scale Optimization.
- Vijay Shanker, Professor: Text mining; Information extraction; Machine learning.
- Hagit Shatkay, Professor: Computational Biology and Bioinformatics; Medical Information and Computational Biomedicine; Machine Learning; Artificial Intelligence.
- CISC481 Artificial Intelligence
- CISC484 Introduction to Machine Learning
- CISC489 Topics: Artificial Intelligence
- CISC684 Introduction to Machine Learning
- CISC849011 Advanced Topics in Computer Applications: Applied Game Theory
- CISC886 Multi-Agent Systems
- CISC889 Advanced Topics in Artificial Intelligence
Artificial Intelligence Laboratories
Healthy LAife Laboratory
429 Smith Hall, Professor Rahmat Beheshti.
The Healthy LAife lab leverages data science and AI techniques to understand how individuals can have healthier lifestyles. We use various modalities of data including brain imaging, electronic health records, and wearable sensor datasets, and we are specifically working on several projects in the area of obesity and diabetes research.
Computational Neural and Information Eng. Lab
309 Evans Hall, Professor Austin Brockmeier.
Multi Agent Systems Laboratory (MAS Lab)
447 Smith Hall, Professor Keith Decker.
An agent is a computer system capable of flexible, autonomous action in dynamic multi-agent environments. The success of the Internet has shown that computing is no longer only about fast numerical calculation, or isolated information processing. It is now also about interaction and coordination amongst machines, and between machines and people. The MAS laboratory focuses on the science of coordination in applications ranging from distributed energy management and emergency response support to scientific information gathering.
VIMS Vision Laboratory
212 Smith Hall, Professor Chandra Kambhamettu.
VIMS (Video/Image Modeling and Synthesis) Lab encompasses research in areas related to computer vision and graphics. Our current research topics include camera systems, structure and motion recovery, stereo vision, facial image analysis, medical image analysis, object recognition and scene understanding, scientific visualization. Work done at VIMS explores solutions to challenging real-world problems such as Arctic ice motion and thickness studies, medical diagnosis and assistive robotics.
Human Language Technologies Laboratory
100 Elkton Road, Professor Kathy McCoy.
The Human Language Technology Laboratory is an umbrella for two language-related laboratories: disabilities technology and discourse. The laboratory closely collaborates with the Statistical Information Retrieval Laboratory and the Text Mining Laboratory.
The Disabilities Technology Laboratory, directed by Kathy McCoy, develops intelligent interfaces for people with disabilities that affect their ability to communicate. The ICICLE System is an intelligent English grammar checker and tutor for people who are deaf. Other projects assist people who have special communication needs. We make “talking with” a computer faster and more natural. Another project is to help a person who has visual impairments “scan” a text to find the area relevant to answering a question.
The Discourse Laboratory, under the direction of Sandra Carberry, addresses problems related to discourse and dialogue. The Graphs project treats information graphics (bar charts, line graphs, etc.) as a form of discourse with a communicative goal. We are applying language understanding and generation techniques to index, store, and retrieve graphics from a digital library, to develop an interactive dialogue system that conveys the content of graphics via speech to individuals with sight impairments, and to develop an interactive graph design assistant that will critique graphs with the objective of improving them so that they achieve their communicative goal. Current collaborators include Dr. Stephanie Elzer (Millersville University), Dr. Dan Chester, and graduate students.
Dynamic Vision Lab
101 Smith Hall, Professor Christopher Rasmussen.
The Dynamic Vision Lab studies visual and 3-D perception for mobile robots, particularly methods for robust, real-time tracking, detection, and segmentation in semi-structured outdoor environments.
Safro Research Group
101 Smith Hall, Professor Ilya Safro.
Text Mining Laboratory
102 Smith Hall, Professor Vijay Shanker.
The Text Mining Laboratory, directed by Vijay Shanker, is concerned with the development of language technology algorithms to assist scientists to rapidly access relevant information from research literature. Projects include the extraction of targeted information, retrieval of relevant textual passages, and assistance in the knowledge discovery process. A related project involves rapid adaptation of language processing tools that were developed for a general domain to be used in a specific domain. A third project involves multi-disciplinary effort that integrates natural language cues found in large software programs and program analysis for multiple software development and maintenance tasks.