About the Program
Students pursuing a graduate degree in Computer Science can further their knowledge of computer science and conduct critical research in the Department of Computer Science’s many varied areas of research. Faculty’s expertise spans across many areas of computer science. Research areas include: Artificial Intelligence, Machine Learning, and Natural Language Processing; Bioinformatics and Computational Biology; Computer Architecture; Computational Science and Engineering; Databases and Data Mining; Distributed Systems; Graphics, Visualization, and Geometric Modeling; Human-Computer Interaction; Information Security and Assurance; Networking and Operating Systems; Programming Languages and Compilers; Software Engineering; Robotics and Computer Vision; Theory of Computing, Algorithms, and Quantum Computing. Opportunities for graduate funding are abundant. The flurry of growth in computer science at Purdue means numerous fellowships, research assistantships, and teaching assistantships are available. Program Website Program Requirements
90 Credits RequiredRequired Courses (7 credits)
Research Orientation Course (1 credit)
Students must, in their first year, take CS 59100. This course introduces students to the research of CS faculty and includes lectures on how to conduct, present, and review research. Additionally, the University-mandated Field-Specific RCR Training requires PhD students to take two hours of ethics training. The first hour will be fulfilled by attending the CS Ethics lecture of CS 59100. The second hour can be fulfilled by one hour of participation in discussions with colleagues on RCR topics related to their specific research programs (e.g. through group meetings, coursework, orientations, professional development activities, or other organized events). Each student researcher is responsible for self-reporting their activities with the Office of the Vice President for Research. CS Selectives (12 credits)
Students must take at least four graduate-level CS courses. Suggested list below. Generally, any CS courses at the 500 level or above is allowed, when taught by a faculty member whose primary appointment is in the CS department (except CS 50100, 50010, 50011, and certain CS 59000, 59200, and 59300 courses). Research Areas (xx credits)
Students should choose a research area to focus their studies, described below. Students must consult with their major professor to ascertain area-specific requirements and satisfy those requirements. Students are responsible for knowing and completing area-specific requirements by the assigned deadlines. Artificial Intelligence, Machine Learning, and Natural Language Processing
This research area’s members study and devise core machine learning and artificial intelligence methods to solve complex problems throughout science, engineering, and medicine. The area’s goal is to enhance human lives and bring advanced technologies to augment human capabilities. This research involves both deployments in real-world applications as well as development of fundamental theories in computer science, mathematics, and statistics. Research Area Website Bioinformatics and Computational Biology
Faculty in the area of bioinformatics and computational biology apply computational methodologies such as databases, machine learning, discrete, probabilistic, and numerical algorithms, and methods of statistical inference to problems in molecular biology, systems biology, structural biology, and molecular biophysics. Research Area Website Computer Architecture
Computer Architecture research studies the interplay between computer hardware and software, particularly at the intersection of programming languages, compilers, operating systems, and security. Research Area Website Computational Science and Engineering
The research area of Computational Science and Engineering answers questions that are too big to address experimentally or are otherwise outside of experimental abilities. Using the latest computers and algorithms, this group addresses those questions through numerical modeling and analysis, high-performance computation, massive distributed systems, combinatorial algorithms in science applications, high-speed data analysis, and matrix-based computations for numerical linear algebra. Research Area Website Databases and Data Mining
The data revolution is having a transformational impact on society and computing technology by making it easier to measure, collect, and store data. The databases and data mining (big data) research group develops models, algorithms, and systems to facilitate and support data analytics in large-scale, complex domains. Application areas include database privacy and security, web search, spatial data, information retrieval, and natural language processing. Research Area Website Distributed Systems
The DS group focuses on designing distributed systems that are scalable, dependable, and secure, behaving according to their specification in spite of errors, misconfigurations, or being subjected to attacks. Areas of focus include virtualization technologies with emphasis on developing advanced technologies for computer malware defense and cloud computing. Research Area Website Graphics, Visualization, and Geometric Modeling
This group performs research in graphics, visualization, computational geometry, and related applications. Focus areas include model acquisition, image generalization, scientific visualization, urban modeling, robust computational geometry, and geometric computations and constraints. Research Area Website Human-Computer Interaction
Human-Computer Interaction (HCI) is a discipline that is concerned with the design, evaluation, and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them. Research Area Website Information Security and Assurance
Strong security and privacy is needed to defend our records, communications, finances, governments and infrastructure against all manner of threats and attacks, while also enhancing legitimate uses. Research in Information Security and Assurance focuses on the analysis, development, and deployment of technologies, algorithms, and policies to protect computing and data resources against malicious access or tampering, and to validate authenticity. Research Area Website Networking and Operating Systems
This area works on fundamental problems at different layers of the network protocol stack - from the medium access control layer up to the application layer - using theoretical models, simulation, emulation, and extensive testbed experimentation to develop and evaluate proposed solutions which leverage techniques from game theory, information theory, complexity theory, optimization, and cryptography. Research Area Website Programming Languages and Compilers
The PL group engages in research spanning all aspects of software systems design, analysis, and implementation. Active research projects exist in functional and object-oriented programming languages, both static and dynamic compilation techniques for scalable multicore systems, generative programming, assured program generation, scripting languages, distributed programming abstractions and implementations, real time and embedded systems, mobile and untrusted computing environments, and runtime systems with special focus on memory management and parallel computing environments. Research Area Website Robotics and Computer Vision
The Robotics and Computer Vision area includes elements of machine learning, signal processing, and image processing to further develop robotics and computer vision systems from a computational science perspective. Research Area Website Software Engineering
The software engineering area conducts research on applying advanced program analyses towards problems related to fault isolation and various kinds of bug detection, including those related to race conditions in concurrent programs, and specification inference for large-scale software systems. Research Area Website Theory of Computing, Algorithms, and Quantum Computing
Members of the group work in areas that include analysis of algorithms, parallel computation, computational algebra and geometry, computational complexity theory, digital watermarking, data structures, graph algorithms, network algorithms, distributed computation, information theory, analytic combinatorics, random structures, external memory algorithms, and approximation algorithms. Research Area Website Dissertation Research (xx credits)
The thesis must present new results worthy of publication. At least two academic sessions of registration devoted to research and writing must elapse between the preliminary and final doctoral examinations. The student must defend the thesis publicly and to the satisfaction of the examining committee, which consists of the student’s advisory committee and of one additional faculty member who represents an area outside that of the thesis, and who is approved by the graduate committee. The thesis should be defended at the latest by the end of the fourth semester following the one in which the student passes the preliminary examination. Concentrations
Interdisciplinary concentrations: GPA Requirements
All courses included in the plan of study must have a student evaluation component, and they must be graded in the usual manner so they can be used to compute the GPA. In particular, courses graded on a pass/no pass or satisfactory/unsatisfactory basis cannot be included in the plan of study. A student receiving a grade lower than C- in a course on the plan of study will have to repeat or replace the course. If a course is repeated, only the last grade, even if lower, is used to compute all GPAs involving that course. Graduate Programs Disclaimer
- The student is ultimately responsible for knowing and completing all degree requirements. Students should consult with their advisor/department for more information.
- Not all graduate programs may be actively recruiting students and course modality availability may vary.
- Please refer to the Explore Graduate Programs website for a list of currently available graduate programs.
- Transfer credit policy: Credits earned for graduate study at other universities (both domestic and international) may be applied toward an advanced degree. Only credit hours associated with graduate courses for which grades of B- or better were obtained will be eligible for transfer. Any additional conditions under which credit transfers may be made are determined by the various departments.
- Comparative information about Purdue University and other U.S. educational institutions is also available through the College Navigator tool, provided by the National Center for Education Statistics, and through the U.S. Department of Education College Scorecard.
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