With over $15 million in active research projects supported by organizations such as NSF, AFOSR, DOE, DHS, DARPA, and NIH, our highly qualified faculty enjoy teaching and research in a broad range of research specialization areas. Below is a list of our research areas with the faculty participating in each area. At the bottom of the page you will find a list of links to specific research groups and projects.
ARTIFICIAL INTELLIGENCE: Genetic and evolutionary algorithms, reinforcement learning, neural networks, planning and evaluation, machine learning, robotics.
SOFTWARE ENGINEERING: Requirements analysis, software architecture and design, process evaluation, software testing and reliability, software maintenance and evolution, program comprehension, object-oriented techniques, modeling all aspects of software development.
COMPUTER NETWORKS: Trusted/secure computing and network modeling, distributed systems and protocols, network security and measurements, immersive systems, fault tolerance, High-performance packet processing.
HIGH PERFORMANCE COMPUTING: Parallel computing, optimizing compilers, distributed systems, static and dynamic program analysis, polyhedral model/compilation, domain-specific languages, platform-specific code optimization for current and next-generation target platforms: accelerators, GPUs, FPGAs, heterogeneous SoCs, multi-core CPUs, supercomputers.
DATA SECURITY AND PRIVACY: Data privacy and anonymity, secure data streams, secure clouds, access control, trust models and trust management, information flow models, security protocols, security analysis, human factors in security, attack modeling, security risk management, vulnerabilities, quantitative methods, Web security, malware analysis.
BIOINFORMATICS: Protein bioinformatics: prediction of protein function and interactions, alternative splicing, applications of kernel methods in bioinformatics. Algorithms for computational problems in genomics and transcriptomics, genome sequencing and resequencing, detection of transcription regulatory elements.
COMPUTER VISION AND GRAPHICS: Semantic object recognition, modeling the human expert recognition pathway, embedded real-time computer vision, 3D model-based object recognition and adaptive object recognition.
DISTRIBUTED SYSTEMS: Cloud computing, real-time stream processing, virtualization, content dissemination systems, MapReduce, large-scale topologies, and scalable storage systems.
BIG DATA: Analytics, high-throughput storage and retrieval, time-series data, metadata, provenance, and visualization.
Participating Faculty: Sangmi Pallickara
ALGORITHMS: Graph-theoretic algorithms, combinatorial algorithms, text algorithms, certificates of correctness, combinatorial optimization.