At the Department of Computer Science at Colorado State University, research is a team effort. Our faculty and students participate in an exciting interdisciplinary research community and propel the national and international reputation of our laboratories and centers. Partnering with domestic and international universities, industry, and government, we find cures for diseases, build robots, secure networks, create adaptive technologies, protect your information and privacy, prepare for natural disasters, develop cyber and defense tools, design smart cities, and much more. Come help us conquer these important global challenges.
ARTIFICIAL INTELLIGENCE: Genetic and evolutionary algorithms, reinforcement learning, neural networks, machine learning, multimodal data, deep learning, planning and evaluation, robotics.
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.
SOFTWARE ENGINEERING: Formal methods, verification, synthesis and control, cyber-physical systems, 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.
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.
COMPUTER INTERACTION/VISION: Semantic object recognition, modeling the human expert recognition pathway, embedded real-time computer vision, 3D model-based object recognition, and adaptive object recognition.
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.