COMPUTER SCIENCE AND ENGINEERING Graduate Programs
AREAS OF SPECIALIZATION The Division of Computer Science and Engineering offers both a Master of Science and PhD in Computer Science. Our graduate program is designed to be flexible in order to provide our students with opportunities to take courses and do research in both core and applied/interdisciplinary areas. There are currently about 100 students, roughly evenly split between the MS and PhD programs. Additionally, our graduate program is in the top 30 nationwide, according to the latest National Research Council ranking.
DEGREES OFFERED MS in Computer Science PhD in Computer Science The MS in Computer Science program is an innovative and versatile The PhD in Computer Science program offers talented students curriculum, offering a wide range of opportunities to students. the opportunity to prepare for research careers in universities or Combined with various concentrations and options, it aims to give industrial laboratories. There is a strong and continuing demand students the education, training, and research skills and experiences for computer scientists to work at the frontiers of knowledge in they need to be successful in the many computer-oriented jobs both theoretical and applied specialties. Our curriculum covers that exist today. It can also serve as a stepping stone toward several areas related to theoretical foundations, systems and pursuing a doctoral degree in computer science. The curriculum architecture, cyber security, databases and data analytics, software, covers core topics, such as theory of computation, algorithms, computational science, and digital media. operating systems, programming languages, networks, cyber GRADUATE ADVISOR GRADUATE COORDINATOR security, computer graphics, databases and analytics, and software Gerald Baumgartner Symone Johnson development. In addition, the student may choose a systems- [email protected] [email protected] related specialization area and application of the techniques from 225-578-2191 225-578-1497 these core areas.
LEARN SO MUCH MORE LSU.EDU/ENG /LSUEngineering FACULTY RESEARCH AREAS
Gerald Baumgartner Supratik Mukhopadhyay [email protected] — design and implementation of domain- [email protected] — software engineering, program analysis, specific languages, compiler optimization, desktop grids, video analytics, applications object-oriented languages, software engineering tools, embedded systems programming tools Seung-Jong Park [email protected] — big data and deep learning, Konstantin Busch cyberinfrastructure, high-performance computing, high-speed [email protected] — distributed algorithms and data network, data center network, software-defined network structures, communication algorithms, algorithmic game theory Golden Richard III Doris Carver [email protected] — cybersecurity, memory forensics, digital [email protected] — requirement traceability, model-driven forensics, reverse engineering, malware analysis software development, reverse engineering, testing Rahul Shah Feng Chen [email protected] — algorithms, data structures, databases [email protected] — operating systems, storage systems (flash SSDs, persistent memory, cloud storage), data management in Mingxuan Sun cloud and large-scale distributed storage systems [email protected] — machine learning, data science and visualization Jianhua Chen [email protected] — machine learning and data mining, Evangelos Triantaphyllou data clustering, applications of machine learning for security, [email protected] — data mining, decision making web mining and ontology construction, fuzzy logic and fuzzy systems, intelligent information retrieval and interactive systems, Chen Wang knowledge representation, logics in AI, non-monotonic reasoning [email protected] — cyber security and privacy, mobile sensing and computing, smart health care, internet of things, Bijaya Karki machine learning, wireless communications [email protected] — scientific visualization and applications, computational materials, large-scale simulations Qingyang Wang [email protected] — distributed systems and cloud Sukhamay Kundu computing (performance and scalability analysis of large-scale [email protected] — software modeling and analysis, networking, web applications) graph algorithms, data mining, clustering, machine learning Jinwe Ye Kisung Lee [email protected] — computer vision, computational [email protected] — scaling big data analytics, cloud computing, photography, computer graphics distributed computing systems, mobile computing and spatial data management, distributed data intensive systems, social Jian Zhang network analytics [email protected] — machine learning and applications
Anas Mahmoud [email protected] — software engineering, requirements engineering, program comprehension, code analysis