Areas of Research
Research Programs and Scholarly Activity
The CIS department is strong in spatial, temporal and graph data mining as well as big data analytics with applications to biomedical databases. The bioinformatics work focuses on understanding disordered proteins and their functions. Additional work in biomedical informatics focuses on developing data management and informatics tools for analyzing large repositories of clinical data and medical images and extracting patterns and associations between anatomical structures and normal or abnormal function. We also apply data mining and machine learning to video analysis and time series analysis. Our work in pattern recognition centers around object recognition, video analysis, shape similarity and perceptual grouping with applications to robot mapping.
CIS has a strong research program focused on networked computing, which includes wireless networks and mobile computing, security, resource and system management and parallel and distributed systems. The wireless network and mobile computing areas focus on innovative network architecture, delay tolerant network design, protocol design, and QoS support. The security research studies key management, anonymity design, and secure routing. In the areas of resource and system management, work is centered on applying reputation-based trust models to resource selection and mapping. Parallel and distributed systems work focuses on the principles of lossless high performance systems. Research in modeling of high performance computing (HPC) is enhanced through a very significant MRI grant from NSF for a hybrid HPC environment.
The department also has a core research component in complexity theory, fault diagnosis, mathematical theory of computation, algorithms and their applications to molecular computing and bioinformatics. Work in the area of artificial intelligence concentrates on learning and reasoning under conditions of uncertainty and insufficient knowledge and resources.
The majority of our research projects have being funded by the National Science Foundation (NSF), the Defense Advanced Research Projects Agency (DARPA), Department of Defense (DOD), the National Institutes of Health (NIH), the National Institute of Standards and Technologies (NIST) and the Office of Naval Research.
Much of the department’s research work is carried out by faculty and students of the Center for Data Analytics and Biomedical Informatics (DABI) and the Center for Networked Computing (CNC). The projects are interdisciplinary and involve faculty and students from departments as diverse as Engineering, Biology, Chemistry, Statistics, Mathematics, Operational Research, Radiology, Neurology, Pathology, Pharmacology, and Psychology.
Data Center Management
Work in this area is focused on a variety of issues concerning data center management including energy, robustness, security, and misconfigurations, storage systems, data center networks, and interaction of data centers with smart grid. This area involves professors Kant, and Wu. A new NSF industry university cooperative research center (IUCRC) directed by Professor Kant, and supported by industry members, has been created to address issues in this area.
Energy and Sustainability
Work in this area involves energy and sustainability issues in emerging data centers, management, security and robustness of smart grid, and use of information technology in water and food distribution systems. This area involves professors Kant, Mohrehkesh and Srinivasan.
Wireless Networks and Mobile Computing
The wireless networks and mobile computing faculty work on many aspects of wireless networks and systems. Current areas of interest include: WLANs, 4G WiMAX networks, sensor networks, mobile ad hoc networks, delay tolerant networks, network protocols, local and distributed algorithms. The wireless networks and mobile computing faculty includes professors Du, Ji, Kwatny, Mohrehkesh, Morris, Tan, Wu.
Information and Network Security and Forensics
The faculty in the security group conduct research on Internet and wireless security, including intrusion detection, botnet, security and privacy in cloud computing, security of implantable medical devices (IMD), trust in social networks, and security in wireless networks (such as key management, secure communication, broadcast authentication, secure time synchronization, and detection of compromised nodes). The faculty in the information and network security group are professors Ajaj, Du, Ji, Kant, Srinivasan, Tan, Wu, Zeng.
Cloud-Enabled Distributed and Parallel Processing
The faculty in the cloud-enabled distributed and parallel processing group study fundamental principles of cloud-enabled applications. Unlike traditional distributed and parallel processing research, this group studies the “failure models” of very large scale distributed and parallel processing applications. This work involves required structures of cloud enabled application architectures and API design and implementation. The research goals include the maximal application survivability and unlimited scalability in performance and availability. Currently, the group has focused on high performance scientific computing, large scale transaction processing and enterprise service bus (ESB) application in service oriented architectures (SOA). The faculty in this group are professors Ajaj, Ji, Kant, Shi, Srinivasan, Tan, Wu, Zeng.
CIS faculty are very active in the areas of visual computing, including computer vision, pattern recognition, and robotics. The group’s computer vision work has been focused on a number of research topics including shape and image recognition, image and category classification, object detection and perceptual organization, face recognition, video information analysis. The work in pattern recognition includes time series analysis, robust feature space measurement, and related topics. In robotics, the group has been working on robot mapping and related problems. The faculty in this group are professors Guo, Lakaemper, Latecki, Ling, Obradovic, and Vucetic.
Medical Informatics and Bioinformatics
CIS has a strong team in biomedical informatics and biomedical imaging. The bioinformatics work focuses on understanding disordered proteins and their function. Other work in biomedical informatics is concerned with developing data management and informatics tools for analyzing large repositories of medical images and other clinical data and extracting patterns and associations between anatomical structures and normal or abnormal function. The biomedical informatics group includes professors Guo, Ling, Obradovic, and Vucetic.
Data Mining & Machine Learning
The department has a strong research group in data mining and machine learning. The work of this group is focused on developing data mining techniques for spatial, temporal and graph data, as well as big data analytics. The machine learning work is concerned with memory constrained kernel learning, graphical model, and related problems. In addition, members of this group conduct research on data compression and explore the connection between data compression and data mining. Professors Guo, Lakaemper, Latecki, Obradovic, and Vucetic are the faculty in this group.
Web Data Management
The research activity in this area spans the following main topics: Web information extraction, information retrieval, Web data integration, quality of data on the Web and sentiment analysis. The research group investigates problems related to automatic construction and maintenance of metasearch engines, ranking, and record linkage and fusion. In sentiment analysis, our faculty has produced significant contributions in automatic sentiment lexicon acquisition and formal understanding of sentiment lexicons. Sentiment monitoring and analysis of social media streams (e.g., Twitter, Instagram) is another important research activity of this group. The faculty members in this group are professors Dragut, Guo, and Obradovic.
Research work in this area concentrates on topics such as retrieval, management, and inference on biomedical, image, audio, and video databases. The group’s research in video retrieval concentrates on modeling spatial and temporal context in human action analysis. In medical databases, the group focuses on management of large-scale medical image databases and high-dimensional biomedical data analysis for clinical usage. The faculty in this group are professors Dragut, Lakaemper, Latecki, and Ling.
The department also has a strong core in complexity theory (including circuit complexity and bounded queries), fault diagnosis, mathematical theory of computation, and algorithms. A highlight of the research in this group is the tight connection with other research areas in the department, namely bioinformatics, network security, etc. Faculty in this group include professors Beigel, Guo, Korsh, LaFollette, and Wu.
Work in the area of artificial intelligence concentrates on learning and reasoning under uncertainty and insufficient knowledge and resources, natural language processing, cognitive science, collaboration technology and computer supported collaborative activities. Faculty working in this area are professors Guo, Latecki, Nosek, Obradovic, and Wang.