computer science phd virginia tech

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Computer Science & Applications Introduction

Funding opportunities.

• Graduate Teaching Assistantship (GTA): The number of GTAs awarded in a given year is difficult to predict and is driven by undergraduate (not graduate) enrollments. A fraction of the GTAs (approximately one-third) are offered to new students. Students on assistantships are exempt from tuition and a significant fraction of the costs for a University sponsored healthcare plan are covered.
• Graduate Research Assistantship (GRA): Many faculty have active research programs that include funds for research assistants. Note that GRAs are most commonly awarded to students who have been in the Department for at least one semester. GRAs receive the same stipends, tuition exemption, and healthcare benefits as GTAs.
• Computer Science Scholars and Pratt Fellowships : a limited number of exceptional applicants are admitted as CS Scholars or Pratt Fellows, which guarantees them multiple years of support. These positions may include summer support for research as well.
• University/College-level Fellowships : Our applicants are eligible to compete for University- and College-level fellowships including the Cunningham Fellowship and Dean's Fellowships. These fellowships typically include multiple-year support guarantees, summer research support, and possibly travel or discretionary funds. Some are only available to US citizens and permanent residents.
• Minority Scholarships : Virginia Tech provides a number of scholarships for minority students who are US citizens. Contact the CS Department at [email protected] for further information about applying to these programs.

Degree Requirements

Computer science & applications facilities introduction, bioinformatics lab, center for human-computer interaction (chci), discovery analytics center (dac), general departmental resources, human-centered design.

An introduction to human-centered design benefits your graduate research and broadens your career prospects. Whether studying to be a designer, engineer, scientist or artist, your work ultimately impacts real people. Taking users seriously improves how projects are conceived and executed. 

Design matters. The act of creating something new shows up in many human endeavors. It can be a solution to a mundane problem like holding sheets of paper together or something as complex as the formulation of new institutions. Human Centered Design (HCD) is an approach to design charged with understanding the needs, wants, and limitations of end-users. This is accomplished through methodologies and practices where these considerations are integrated at every stage of the design process. 

In the Certificate program, students learn the core ideas of HCD, explore how it applies in their own professional domains, and discover how their own research connects with projects in other disciplines. In particular, it leverages inter-disciplinarity to see how to learn from the world around. The ability to collaborate across disciplines is a high-demand skill set in the private and public sectors and higher education careers, because institutions recognize that creative solutions to the most important societal challenges requires integrating aesthetics, analysis, and technological development. 

CO-Director of HCD-  Ico Bukvic [email protected]

Laboratory for Advanced Scientific Computing and Applications (LASCA)

Stack@cs center for computing systems, course listing for computer science & applications.

2023-2024 Academic Catalog

2023-2024 course catalog.

Welcome to Virginia Tech! We are excited that you are here planning your time as a Hokie.

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The Field of Computer Science

In a contemporary world where every educated person must have some knowledge of computing, the Department of Computer Science offers degree programs and courses to meet a variety of needs. The department offers a bachelor of science degree to prepare specialists in the area of computer science itself, a minor in computer science, minors in specialized areas such as cybersecurity and human-computer interaction, and individual courses directed to the needs of non-majors who will be using computers as tools in their chosen careers. The department also offers the M.S., M.Eng., and Ph.D. in computer science (see Graduate Catalog ).

Computer science involves far more than just writing computer programs. It is a technically rigorous field that requires a strong background in mathematics. Computer scientists must be good at problem solving. Their work requires the ability to think abstractly and to represent real-world objects and interactions in ways that can be manipulated by a computer. The field of computer science is characterized by rapid change and entrepreneurship, with new opportunities emerging every year to improve life in diverse areas such as education, communication, science, commerce and entertainment.

Accreditation and Program Objectives

The Bachelor of Science degree in Computer Science is accredited by the Computing Accreditation Commission of ABET, www.abet.org .

Part of the accreditation process is a clear statement of program objectives and desired outcomes for graduates. The following program educational objectives describe what graduates of the Virginia Tech Computer Science undergraduate program are expected to attain within a few years of graduation. Alumni will have:

• Demonstrated technical expertise by applying computer science knowledge and practice to solve challenging problems, whether in employment, graduate study, or individual pursuits;
• Advanced their skills in communication, teamwork, and professional and ethical behavior;
• Demonstrated leadership in their technical or professional pursuits;
• Engaged in post-graduate learning through graduate studies, professional improvement opportunities, or self-study;
• Served society through professional or personal contribution.

These objectives are supported by a curriculum that seeks to have its graduates achieve the following student outcomes upon graduation. Graduates of the program will have an ability to:

• Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
• Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program's discipline.
• Communicate effectively in a variety of professional contexts.
• Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
• Function effectively as a member or leader of a team engaged in activities appropriate to the program's discipline.
• Apply computer science theory and software development fundamentals to produce computing-based solutions.

Degree Requirements

Students pursuing the Bachelor of Science Degree in Computer Science choose one of three majors. The Computer Science major is designed to provide a broad computer science background that will prepare a student for a wide variety of professional careers or to continue study at the graduate level. The Secure Computing major offers a more specialized path for students who are especially interested in secure computing and cybersecurity topics. The Data-Centric Computing Major offers a focus on topics in data science, data analytics, and computational aspects of big data computing. All majors include a set of foundational courses in software design and development, algorithms, and computer organization at the freshmen and sophomore level. Students at the junior and senior level select one theoretical course, several elective courses and a capstone course according to their individual interests.

Please visit the undergraduate program website at https://cs.vt.edu/Undergraduate.html for detailed requirements.

Opportunities for Majors

The department offers computer science majors the opportunity to enhance their education through a variety of curricular and extracurricular activities. Students who meet the requirements for independent study or undergraduate research can pursue research or individualized study under the direction of a faculty member. Through the Honors College, qualified students can work toward earning an Honors Laureate Diploma for their degree. Students may also elect to earn both the bachelor's and master's degrees in an accelerated undergraduate/graduate program. The Cooperative Education Program makes it possible for students to acquire professional experience while pursuing their degree. The department's corporate partnership program hosts large career fairs in both Fall and Spring semesters.

The department sponsors multiple student organizations, including the student chapter of the Association for Computing Machinery (ACM), the Association for Women in Computing (AWC), the CS Community Service organization, and the Programming Team. Additional opportunities for experiential learning and professional development include serving as a teaching assistant or department ambassador, attending a professional development or research conference, and participating in annual research competitions and hackathons. Financial aid is available through numerous college and department endowed scholarships.

Information for Non-Majors

The department offers a Computer Science minor for non-majors seeking a solid general background in computer science. The department also offers minors focused on human-computer interaction and cybersecurity. Please visit the department's undergraduate program website for more information.

Computational Facilities

The Department of Computer Science possesses extensive computational facilities for both instruction and research. There are several undergraduate teaching laboratories and a number of specially equipped research laboratories. These include large parallel computing clusters and numerous compute and file servers for research and instruction in areas such as artificial intelligence, machine learning, digital libraries, software engineering, bioinformatics and networking. The department also operates extensively equipped laboratories for human-computer Interaction, virtual environments and information visualization. Students studying computer science are supported by two department-specific Undergraduate Learning Centers on campus.

• Computer Science Major
• Data-Centric Computing Major
• Secure Computing Major

Head: C. J. Ribbens Associate Department Head for Undergraduate Studies: S. H. Edwards Associate Department Head for Graduate Studies: C. A. Shaffer Associate Department Head for Faculty Development: A. R. Butt Associate Department Head for Research: T. M. Murali Thomas L. Phillips Professor: N. Ramakrishnan Frank J. Maher Professor: D. Bowman W.C. English Professor: W. Lou John W. Hancock Professor: D. Nikolopoulos Professors:  O. Balci, A. R. Butt, K. W. Cameron, I. R. Chen, S. H. Edwards, W. Feng, E. A. Fox, L. S. Heath, B. Knapp, C. T. Lu, T. M. Murali, C. Noh, C. L. North, A. Onufriev, C. Reddy, A. Sandu, C. A. Shaffer, E. Tilevich, L. T. Watson, D. Yao, and L. Zhang. Associate Professors:  G. Back, D. Bhattacharya, Y. Cao, J. H. Cho, H. Eldardiry, D. Gracanin, M. Hicks, B. Ji, A. Karpatne, K. Luther, D. S. McCrickard, N. Meng, and S. Raghvendra. Assistant Professors:  C. Brown, Y. Chen, T. Chung, B. David-John, P. Gao, M. Gulzar, S. Hasan, T. Hoang, L. Huang, X. Jian, S. W. Lee, H. Li, I. Lourentzou, A. Mantri, E. Rho, J. Sikora, K. Sundararajah, C. Thomas, B. Viswanath, X. Wang, D. Williams, I. Williams, P. Yanardag, Y. Yao, and D. Zhou. Associate Professors of Practice:  M. Ellis and G. Kulczycki Collegiate Associate Professors: S. Hamouda, S. Hooshangi, E. Olimpiew, and R. Jafari. Collegiate Assistant Professors : S. Basir, M. Cameron, B. Edmison, O. Emebo , M. Farghally, T. Mengistu, and M. Seyam Advanced Instructors: D. McPherson Instructors: S. Cao, H. Hillman, A Senger, and P. Sullivan Professor Emeritus:  D. C. S. Allison, J. D. Arthur, R. W. Ehrich, D. G. Kafura, J. A. N. Lee, H. R. Hartson, R. E. Nance, B. Ryder, and D. Tatar

E-mail: [email protected]

Undergraduate Course Descriptions (CS)

An exploration of basic ideas of computational thinking focusing on the perspectives, thought processes, and skills that underlie computational approaches to problem formulation and problem solving. Applications of computational tools to investigate complex, large-scale problems in a variety of knowledge domains. Basic introduction to algorithms and a practical programming language. Examination of the societal and ethical implications of computational systems.

Fundamental concepts underlying software solutions of many problems. Structured data, statement sequencing, logic control, input/output, and functions. The course will be taught using a structured approach to programming. Partially duplicates 1344.

An introduction to object-oriented programming using the Java language. Fundamental concepts underlying programming and software solutions to many problems. Structured data, statement sequencing, logic control, classes, objects, methods, instantiation of classes, sending messages to objects. The impact of computing on issues of diversity and inclusion.

Introduction to programming in Python contextualized with scientific and engineering problems. Computational problem-solving skills and software solutions in addition to Python language fundamentals. The basics of control flow with loops and conditionals, state tracing and manipulation, simple and complex types, organization of code using functional and object-oriented coding strategies, and data processing. Create, interpret, and debug programs. Ethically debate important issues in computing culture.

Fundamental concepts of programming from an object-oriented perspective. Basic software engineering principles and programming skills in a programming language that supports the object-oriented paradigm. Simple data types, control structures, array and string data structures, basic algorithms, testing and debugging. A basic model of the computer as an abstract machine. Modeling and problem-solving skills applicable to programming at this level. Partially duplicates 1054, 1124, and 1705.

Introduces the concepts, software, data organization and issues involved with using networked information. Also covers file formats (as applied in networked hypermedia and multimedia sound/video documents), local and global (Internet) network access, electronic mail, transferring files, network news, the World Wide Web, digital libraries, on-line public access catalogs and electronic journals, CD-ROMs and on-line databases, and commercial and other networks. Word processing ability required.

An introduction to academic and career planning for computer science majors.

Advanced uses of control flow and data processing, data structures, computational techniques, object-oriented programming, and modern data science pipelines. Creating, interpreting, and debugging complex programs. Problems and projects contextualized for scientists and engineers. Implementation of Python programs in data science and production environments, production of object-oriented solutions to complex problems, and ethical implications of technological change.

This course introduces the student to a broad range of heuristics for solving problems in a range of settings that are relevant to computation. Emphasis on problem-solving techniques that aid programmers and computer scientists. Heuristics for solving problems in the small (classical math and word problems), generating potential solutions to real-life problems encountered in the profession, problem solving through computation, and problem solving in teams.

A programming-intensive exploration of software design concepts and implementation techniques. Builds on knowledge of fundamental object-oriented programming. Advanced object-oriented software design, ethics in computing, algorithm development and analysis, and classic data structures. Includes a team-based software project.

Fundamentals of algorithms, data structures, and implementation techniques, taught in a setting that combines collaborative practice with competitive exercise. Students practice to solve problems using a computer, which are judged by automated evaluation software for correctness and efficiency. Practice with data structures including arrays, lists, maps, and trees, as well as algorithmic strategies including recursion, divide-and-conquer, dynamic programming, search and traversal algorithms, graph representations, and computational geometry. Macro- and micro optimization techniques to improve efficiency are emphasized.

Introduction to multiple analytical perspectives on contemporary security environments, including political, legal, ethical, technical, environmental and historical and cultural perspectives relative to the conception, design and implementation of security solutions, practices, and policies. Emphasizes applying and analyzing the effectiveness of diverse procedures, tools and policies used in security and privacy solutions, decision-making, risk management and operational policy to mitigate local, national, international and global threats.

Guided self-study in a specific programming system, its syntax and applications. Based on prior knowledge of the programming process and experience in programming with some high-level language. Systems include JavaScript, C++, CUDA, Ruby, SQL, FORTRAN, UNIX, etc. May be taken three times for credit with different system each time. May be taken only twice for CS major or minor credit.

An introduction to the design and operation of digital computers. Works up from the logic gate level to combinational and sequential circuits, information representation, computer arithmetic, arithmetic/logic units, control unit design, basic computer organization, relationships between high level programming languages and instruction set architectures. A grade of C or better is required in CS prerequisite. Corequisites: MATH 2534 or MATH 3034 .

An introduction to the design and operation of digital computers. Instruction formats and construction, addressing modes, instruction execution, memory hierarchy operation and performance, pipelining, input/output, and the relationships between high level programming languages and machine language. A grade of C or better is required in CS pre-requisite 2505 and 2114.

Advanced data structures and analysis of data structure and algorithm performance. Sorting, searching, hashing, and advanced tree structures and algorithms. File system organization and access methods. Ethical issues in the context of data analysis and software performance. Course projects require advanced problem-solving, design, and implementation skills.

Introduction to computer systems as they are relevant to application programmers today, with emphasis on operating system principles. Operating system design and architectures; processes; threads, synchronization techniques, deadlock; CPU scheduling; system call interfaces, system level I/O and file management; shell programming; separate compilation, loading and linking; inter-process communication (IPC); virtual and physical memory management and garbage collection; network protocols and programming; virtualization; performance analysis and optimization. A grade of C or better is required in CS pre-requisites 2506 and 2114.

Theory and practice of software reverse engineering, static and dynamic analysis techniques and tools, reverse engineering of malware, obfuscated binaries, communications and command and control analysis, reverse engineering of non-binary software.

This course in programming language constructs emphasizes the run-time behavior of programs. The languages are studied from two points of view: (1) the fundamental elements of languages and their inclusion in commercially available systems; and (2) the differences between implementations of common elements in languages. A grade of C or better required in CS prerequisite 3114.

Theoretical basis of programming languages, including formal languages, computability theory, type theory, and programming language design. Standard syntax notations. Fundamental programming language features for control flow and data representation. Language implementation strategies. Unsolvable problems in the context of programming languages and computing.

Computational methods for numerical solution of non-linear equations, differential equations, approximations, iterations, methods of least squares, and other topics. A grade of C or better required in CS prerequisite 1044 or 1705. A student can earn credit for at most one of 3414 and MATH 4404 .

Studies the ethical, social, and professional concerns of the computer science field. Covers the social impact of the computer, implications and effects of computers on society, and the responsibilities of computer professionals in directing the emerging technology. The topics are studied through case studies of reliable, risk-free technologies, and systems that provide user friendly processes. Specific studies are augmented by an overview of the history of computing, interaction with industrial partners and computing professionals, and attention to the legal and ethical responsibilities of professionals. This is a web-supported course, incorporating writing intensive exercises, making extensive use of active learning technologies. A grade of C or better required in CS prerequisite 3114.

Survey of computer science concepts and tools that enable computational science and data analytics. Data structure design and implementation. Analysis of data structure and algorithm performance. Introduction to high-performance computer architectures and parallel computation. Basic operating systems concepts that influence the performance of large-scale computational modeling and data analytics. Software development and software tools for computational modeling. Not for CS major credit.

Basic principles and techniques in data analytics; methods for the collection of, storing, accessing, and manipulating standard-size and large datasets; data visualization; and identifying sources of bias.

Explores the principles of software design in detail, with an emphasis on software engineering aspects. Includes exposure of software lifecycle activities including design, coding, testing, debugging, and maintenance, highlighting how design affects these activities. Peer reviews, designing for software reuse, CASE tools, and writing software to specifications are also covered. A grade of C or better required in CS prerequisite 3114.

Technologies and concepts underlying software development for mobile devices (handheld computers). Mobile computing platforms, including architecture, operating system, and programming environment. Software design patterns and structuring for mobile applications. Network-centric mobile software development. Data persistence. Programming for mobile device components such as cameras, recorders, accelerometer, gyroscope and antennas. Location-aware software development. A grade of C or better required in CS prerequisite.

Survey of human-computer interaction concepts, theory, and practice. Basic components of human-computer interaction. Interdisciplinary underpinnings. Informed and critical evaluation of computer-based technology. User-oriented perspective, rather than system-oriented, with two thrusts: human (cognitive, social) and technological (input/output, interactions styles, devices). Design guidelines, evaluation methods, participatory design, communication between users and system developers. A grade of C or better required in CS prerequisite 2114.

Design and implementation of object-oriented graphical user interfaces (GUI) and two-dimensional computer graphics systems. Implementation methodologies including callbacks, handlers, event listeners, design patterns, layout managers, and architectural models. Mathematical foundations of computer graphics applied to fundamental algorithms for clipping, scan conversion, affine and convex linear transformations, projections, viewing, structuring, and modeling. A grade of C or better is required in CS pre-requisite 2114.

Fundamentals of cloud software development, including design patterns, application programming interfaces, and underlying middleware technologies. Development of distributed multi-tiered enterprise software applications that run on a server computer and are accessed using a web browser over the Internet on a network-connected computer such as desktop, laptop, or handheld computer (tablet, smartphone, or mobile device. A grade of C or better is required in prerequisite.

Introduction to computational biology and bioinformatics (CBB) through hands-on learning experiences. Emphasis on problem solving in CBB. Breadth of topics covering structural bioinformatics; modeling and simulation of biological networks; computational sequence analysis; algorithms for reconstructing phylogenies; computational systems biology; and data mining algorithms. Pre-requisite: Grade of C or better in CS 3114 .

Application of academic knowledge and skills to in a work-based experience aligned with post-graduation goals using research-based learning processes. Satisfactory completion of work-based experience often in the form of internship, undergraduate research, co-op, or study abroad; self-evaluation; reflection; and showcase of learning. Pre: Departmental approval of 3900 plan.

Data structures and algorithms from an analytical perspective. Theoretical analysis of algorithm efficiency. Comparing algorithms with respect to space and run-time requirements. Analytical methods for describing theoretical and practical bounds on performance. Constraints affecting problem solvability. A grade of C or better is required in CS prerequisite 3114.

The course presents a study of formal languages and the correspondence between language classes and the automata that recognize them. Formal definitions of grammars and acceptors, deterministic and nondeterministic systems, grammar ambiguity, finite state and push-down automata, and normal forms will be discussed.

Theoretical analysis of the computational process; fundamental concepts such as abstract programs, classes of computational machines and their equivalence, recursive function theory, unsolvable problems, Churchs thesis, Kleenes theorem, program equivalence, and generability, acceptability, decidability will be covered.

Quantum states and quantum phenomena. Quantum communication concepts such as superdense coding, teleportation, and complexity. Classical and quantum circuits and gate sets for computation. Quantum algorithms and comparison to classical algorithms. Quantum computational complexity theory and complexity classes. Quantum information concepts such as density operators, measurements, and quantum channels. Error correction, the stabilizer formalism, and fault-tolerance. The adiabatic theorem and adiabatic quantum computation. Entanglement and entanglement measures.

Deeper treatment of advanced algorithms, data structures, and implementation techniques, taught in a setting that combines collaborative practice with competitive exercise. Students practice to solve problems using a computer, which are judged by automated evaluation software for correctness and efficiency. Practice with advanced searching and graph algorithms, advanced dynamic programming, linear programming techniques, computational geometry, and numerical algorithms. Problems are drawn from multiple areas in computer science. Macro- and micro optimization techniques to improve efficiency are emphasized.

Identification and analysis of complex, real-world security problems and threats to people, organizations, and nations across multiple domains, roles and future scenarios. Crisis communication, decision making tools, ethical principles and problem-solving methods to respond, assess options, plan, scope, and communicate before, during and after conflicts, disasters and attacks. Use of an experiential learning facility, and participation in a reality-based team simulation of cascading security and disaster events.

Hardware and software techniques for the display of graphical information. 2D and 3D geometry and transformations, clipping and windowing, software systems. Interactive graphics, shading, hidden surface elimination, perspective depth. Modeling and realism. A grade of C or better required in CS prerequisite 3114 and 3744.

Overview of discrete-event digital computer simulation and modeling. Fundamentals of model development, Monte Carlo simulation, the life cycle of a simulation study, input and output data analysis, world views and time control, random number and variate generation, credibility assessment of simulation results, simulation languages, applications of simulation using the General Purpose Simulation System (GPSS). A grade of C or better required in CS prerequisite 2114.

Design and internal organization of the Linux operating system kernel. Kernel subsystems, boot process, memory management, process and thread model, scheduling, interrupt and exception handling, virtual file system and the concrete file system, block I/O and I/O scheduler, network stack, and device drivers. Modification of existing kernel code. Design, implementation, test and evaluation of new kernel modules. Kernel and full software stack debugging techniques, and virtualization as an aid for operating system development and debug. Software engineering techniques to analyze, modify and run a large, complex open-source code base.

Survey of parallel computer architectures, models of parallel computation, and interconnection networks. Parallel algorithm development and analysis. Programming paradigms and languages for parallel computation. Example applications. Performance measurement and evaluation. A grade of C or better required in CS prerequisite 3214.

Key technology underlying the World-Wide Web. Web architecture, including client and server design, network protocols, and related standards. Static and dynamic content, caching, state management, fault tolerance, error handling. Programming systems and abstractions, e.g., sockets, remote procedures, Web services, frameworks and component models. Document representations and processing. Security. Entrepreneurial issues and emerging technologies. A grade of C or better required in CS 3214 prerequisite.

Introduction to computer network architecture, and methods for programming network services and applications (e.g. DNS, Email and MIME, http, SNMP, multimedia). Wired, wireless, and satellite network architectures. OSI protocol model, with an emphasis on upper layers. Congestion control, quality of service, routing. Internet protocol suite (e.g. IP, TCP, ARP, RARP). Server design (e.g. connectionless, concurrent). Network programming abstractions (e.g. XDR, remote procedure calls, sockets, DCOM). Case studies (e.g. TELNET). A grade of C or better required in CS prerequisite 3214.

Survey of computer problems and fundamental computer security design principles and models for software systems. Cryptographic models and methods. Modern cyber security techniques for robust computer operating systems, software, web applications, large-scale networks and data protection. Privacy models and techniques. Contemporary computer and network security examples. A grade of C or better is required in prerequisites.

Advanced topics in cybersecurity and secure computing. Threat modeling through identification and analysis of security threats. Reasoning about the efficacy, complexity, cost, and ethical tradeoffs of computer security systems. Team-based approach to solving open-ended computer security problems. Designing, implementing, documenting, and presenting advanced computer systems.

Advanced topics in computer systems & networking, e.g. distributed and parallel processing, emerging architectures, novel systems management & networking design, fault- tolerance, and robust and secure data management. Team- based approach to solving open-ended computer systems & networking problems. Designing, implementing and documenting advanced computer/networking systems. A grade of C or better required in CS prerequisites.

This course includes the theory, the design, and the implementation of a large language translator system. Lexical analysis, syntactic analysis, code generation, and optimization are emphasized. A grade of C or better required in CS prerequisite 3214.

Theory and techniques of modern computational mathematics, computing environments, computational linear algebra, optimization, approximation, parameter identification, finite difference and finite element methods and symbolic computation. Project-oriented course; modeling and analysis of physical systems using state-of-the-art software and packaged subroutines.

Overview of the structure, elements and analysis of modern enterprise computers. Performance evaluation of commercial computing. Past and emerging technology trends. Impact of parallelism at multiple levels of computer architecture. Memory and storage. Fundamental computer system descriptions, Amdahls Law, Flynns Taxonomy. A grade of C or better required in prerequisites.

Multidisciplinary, project-oriented design course that considers aspects of wireless and mobile systems including wireless networks and link protocols, mobile networking including support for the Internet Protocol suite, mobile middleware, and mobile applications. Students complete multiple experiments and design projects.

Emphasis on introduction of the basic data base models, corresponding logical and physical data structures, comparisons of models, logical data design, and data base usage. Terminology, historical evolution, relationships, implementation, data base personnel, future trends, applications, performance considerations, data integrity. Senior standing required. A grade of C or better required in CS prerequisite 3114.

Introduces the architectures, concepts, data, hardware, methods, models, software, standards, structures, technologies, and issues involved with: networked multimedia information and systems, hypertext and hypermedia, networked information videoconferencing, authoring/electronic publishing, and information access. Coverage includes how to capture, represent, link, store, compress, browse, search, retrieve, manipulate, interact with, synchronize, perform, and present: text, drawings, still images, animations, audio, video, and their combinations (including in digital libraries).

Survey of the higher-order properties that allow data to become information, that is, to inform people. The course focuses on the analysis of user needs, user comprehension and local semantics; the design of information organization; and the design of information display appropriate to use and setting. A grade of C or better is required in CS prerequisites 3114 and 3724.

Capstone computer science course at the intersection of arts and technology. Intensive immersion in different approaches to digital arts such as game design, interactive art, digital music, and immersive virtual reality. Students work in teams to conduct an end-to-end integrative design project. A grade of C or better is required in prerequisite CS 3724 .

A technical analytics course. Covers supervised and unsupervised learning strategies, including regression, generalized linear models, regulations, dimension reduction methods, tree-based methods for classification, and clustering. Upper-level analytical methods shown in practice: e.g., advanced naive Bayes and neural networks.

Advanced, project-based course on deriving valuable insights from real-world data collected from a variety of sources. Team-based end-to-end projects explore the entire data science workflow: problem statement, formulating the research questions, collecting preparing and cleaning data, alternating between analyzing data and interpreting results, and synthesizing results into a written report and an interactive executable codebase.

Senior project course integrating software engineering knowledge and skills acquired in previous courses. Team- based approach to problem formulation, requirements engineering, architecture, design, implementation, integration, documentation and delivery of software system that solves a real-world problem. Pre: A grade of C or better in CS 3704 .

Project-based design course in human-computer interaction. Team-based, end-to-end, integrative interface design project drawn from interdisciplinary areas of student expertise, e.g., virtual reality, augmented reality, embodied cognition, visualization, semiotic engineering, game design, personal information management, mobile computing, design tools, educational technology, and digital democracy. Not for CS major credit. Senior standing.

Advanced, project-based course in Human-Computer Interaction. Team-based, end-to-end, integrative interface design project drawn from area of expertise in the department, e.g., virtual reality, augmented reality, embodied cognition, visualization, semiotic engineering, game design, personal information management, mobile computing, design tools, educational technology, and digital democracy. Pre-requisite: Senior Standing required. A grade of C or better is required in CS pre-requisite 3724 and 3744

Overview of the areas of problem solving, game playing, and computer vision. Search trees and/or graphs, game trees, block world vision, syntactic pattern recognition, object matching, natural language, and robotics. Senior standing required. A grade of C or better required in CS prerequisite 3114.

Algorithms and principles involved in machine learning; focus on perception problems arising in computer vision, natural language processing and robotics; fundamentals of representing uncertainty, learning from data, supervised learning, ensemble methods, unsupervised learning, structured models, learning theory and reinforcement learning; design and analysis of machine perception systems; design and implementation of a technical project applied to real-world datasets (images, text, robotics). A grade of C- or better in prerequisites.

Advanced topics in computational biology and bioinformatics (CBB). Team-based approach to solving open-ended problems in CBB. Projects drawn from areas of expertise in the department, e.g., algorithms for CBB, computational models for biological systems, analysis of structure-function relationships in biomolecules, genomic data analysis and data mining, computational genomics, systems biology. Design, implementation, documentation and presentation of solutions. A grade of C or better required in CS prerequisite 3824.

Advanced undergraduate topics in the design, development, use, and impact of computer science solutions or software systems. Topics may include blockchain systems, DevOps, new programming languages, social media software, software as a service, micro-services, and end user programming systems. May be repeated 2 times with different content for a maximum of 9 credits.

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BIT PhD Program Overview

The Business Information Technology (BIT) PhD program at Virginia Tech is a highly innovative and interdisciplinary program that prepares students to become leading faculty members in top-tier research universities. The program's STEM-based curriculum fuses operations management, supply chain management, management information systems, information systems, artificial intelligence, business analytics, decision science, and information technology. This allows students to produce cutting-edge, transdisciplinary research that appears in the most elite of journals, on which our faculty serve as editors and routinely publish in high volume—including but not limited to: Management Science , MIS Quarterly , Information Systems Research , Production and Operations Management, Journal of Management Information Systems , Journal of Operations Management , Journal of the Association for Information Systems , Manufacturing & Service Operations Management , Decision Support Systems, Decision Sciences, INFORMS Journal on Computing , Computers & Security, Computers and Human Behavior , and others.

The faculty in the Business Information Technology (BIT) PhD program at Virginia Tech is consistently ranked in the top 25 in the world in all major research productivity rankings. Two of our faculty members are perennially ranked in the top 5 in the world across all forms of research rankings, and several others are also highly ranked and rising. The program is further supported by the exceptional success of the BIT department, which annually attracts over 1,500 full-time undergraduate students to its immensely popular and successful programs.

Moreover, we are supported by facilities and resources that are not typically found even at the most elite business schools. In fact, we are the only leading business school with our own massive 100,000-square-foot Decision & Data Sciences building (part of the Global Business and Analytics Campus), which houses the BIT PhD program and its faculty. In this building, we collaborate with leading computer science, statistics, and data science faculty and their PhD students, facilitating true interdisciplinary opportunities.

If you have any questions about our program or the application process, please contact us at [email protected] .

BIT PhD Highlights

Computer Science

Computer scientists study the design, implementation, performance, and usability of computer systems. The program emphasizes software—the aspect of computation that makes computing the powerful and transforming technology it is.

The Computer Science (CS) degree program offers three majors in Computer Science, Data-Centric Computing, and Secure Computing. Students acquire a strong foundation in algorithms, problem-solving, and software development. A diverse set of elective courses provides experience with emerging technologies in areas such as artificial intelligence, bioinformatics, data analytics, graphics, human-computer interaction, Internet programming, networking, cybersecurity, parallel computing, and software engineering. A computer science (CS) degree prepares students for a wide range of employment options. The degree also serves as good preparation for graduate study in computer science or other information technology fields, as well as business and law.

Curriculum:

Review the Graduation Requirements (Checksheet) for your entering class year to see the required coursework.

Interest Areas and Related Degrees/Minors

The undergraduate CS program provides courses and experiences related to the following areas within computer science: computational biology and bioinformatics; digital education; human-computer interaction; knowledge, information, and data; scientific computing; security; software engineering; systems and networking . A short description of each area and related degrees and minors are provided below to enhance your major exploration experience.

Computational Biology and Bioinformatics Encompasses the study of problems inspired by biology through computational means. Related Engineering Degrees: Biological Systems Engineering | Biomedical Engineering Related Degrees: Biochemistry | Biological Sciences | Environmental Data Science  | Mathematics | Multimedia Journalism | Statistics Related Minors: Biological Sciences | Biomedical Engineering | Physics

Digital Education Understand and create new processes for improving computer science education, online courses, and deploying technology in the classroom.

Human-Computer Interaction Addresses all aspects of the interplay between people and interactive technologies, with applications in every domain. Related Engineering Degrees: Computer Engineering | Industrial and Systems Engineering Related Degrees: Cinema | Communication Studies | Creative Technologies | Industrial Design | Multimedia Journalism | Psychology Related Minors: Business | Communication | Human-Computer Interaction |  Industrial Design | Psychology

Knowledge, Information, and Data Understand not just the algorithmic aspects of converting data to knowledge but also the importance of human-in-the-loop analytics to arrive at insights. Related Engineering Degrees: Electrical Engineering | Industrial and Systems Engineering Related Degrees: Accounting and Information Systems | Business Information Technology | Computational Modeling and Data Analytics |  Environmental Data Science  | Geography | Mathematics | Multimedia Journalism | Neuroscience | Statistics Related Minors: Business | Cybersecurity | Mathematics | Philosophy | Statistics

Scientific Computing Topics include the use of supercomputer and computer clusters are used to solve advanced computational problems in engineering, science, and business. Related Engineering Degrees: Aerospace Engineering | Materials Science and Engineering | Mechanical Engineering Related Degrees: Computational Modeling and Data Analytics | Creative Technologies | Environmental Data Science  | Mathematics |  Neuroscience | Physics | Statistics Related Minors: Human-Computer Interaction |  Mathematics | Statistics

Security Encompasses cybersecurity, cryptography, and privacy aimed at characterizing and detecting vulnerabilities and creating innovative defenses to protect computing systems, networks, and data. Related Engineering Degrees: Computer Engineering Related Degrees: Computational Modeling and Data Analytics Related Minors: Cybersecurity

Software Engineering Debugging, testing, refactoring, transformation, and optimization of different kinds of software applications (e.g., enterprise applications, mobile apps, big data analytics, web applications, desktop applications), security hardening, and build management. Related Engineering Degrees: Computer Engineering Related Degrees: Accounting and Information Systems | Business Information Technology Related Minors: Cybersecurity | Entrepreneurship

Systems Understanding systems allow for the creation of new designs for all aspects of computer system stacks from architecture, compiler, operating system, parallel processing, and cloud in the greater context of software engineering, security, and high-performance computing. Related Engineering Degrees: Computer Engineering Related Degrees: Business Information Technology | Neuroscience Related Minors: Cybersecurity

Getting Involved

Ambassadors Professional Society  – Association for Computing Machinery (ACM) Undergraduate Research Student Organizations Study Abroad

Additional Opportunities: Artificial Intelligence and Machine Learning Club Association for Women in Computing (AWC) Blockchain at Virginia Tech Linux and Unix Users Group (VTLUUG) TechHackers at Virginia Tech Virginia Tech Game Development Group Web Mobile Application Development (WMAD)

Career Resources

Our Engineering Career Resource  provides you with all of the most frequently used career information websites in one place for ease of access. This list includes links to VT First Destination Post Grad Report, the Bureau of Labor Statistics, the Department of Defense, and many more. 

Department of Computer Science

1160 Torgersen Hall (0106) 620 Drillfield Dr. Blacksburg, Virginia, 24061 Phone: (540) 231-6931 Email CS

Cybersecurity Home

Cybersecurity @ virginia tech.

Tackling the world's toughest challenges in cybersecurity Preparing students for demanding careers in cybersecurity, and undertaking world-class research programs

Virginia Tech offers multidisciplinary opportunities in cybersecurity education and research, with participating faculty from the departments of Computer Science, Electrical and Computer Engineering, Political Science, and Business. With its strong engineering and science focus, Virginia Tech offers deeply technical undergraduate and graduate programs in cybersecurity, and our faculty conduct world-class research in information security, network security, hardware security, and software security. Centers such as the Hume Center for National Security and Technology researches defense and intelligence applications of cyber attack and defense. The IT Security Lab, part of the university's CIO organization, is able to use the university's production network as a teaching hospital for cybersecurity.

Below are some of the key designations held by virginia tech for both its education and research programs in cybersecurity..

National Center of Academic Excellence in Cyber Defense Research

Intelligence community center for academic excellence, cybercorps scholarship for service school, cybersecurity education programs, undergraduate.

Student Clubs

CYBERSECURITY RESEARCH PROGRAMS

Virginia Tech's faculty have wide-ranging research programs ongoing in cybersecurity. The university's core strength in world-class cybersecurity research are in the following key areas of expertise:

• Cyber-Physical System Security
• Cybersecurity Policy and Governance
• Wireless Communications and Networking Security

Six research centers and labs capture a large portion of the ongoing research activity. See faculty members' personal websites for more information.

$15 MILLION

Per year in research grants and contracts.

150 students

Per year supported as graduate research assistants, cybersecurity research centers & laboratories.

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Graduate Programs

Our graduate programs, ph.d. in computer science.

The Ph.D. degree culminates with the student writing and defending a dissertation based on the result of independent, original research that makes a significant scholarly contribution to the student's field of study.

M.S. in Computer Science

The M.S. degree requires course work plus a formal thesis.

Master of Computer Science

The M.C.S. degree is based on courses, but students have the option and indeed are encouraged to conduct a substantial project.

Computer Engineering Graduate Programs

We also offer graduate degrees in computer engineering in collaboration with the Department of Computer Science.

Graduate Certificate in Cyber-Physical Systems

The graduate certificate in cyber-physical systems (CPS) is designed to recognize the acquisition of CPS knowledge and skills through the completion of targeted courses. The graduate certificate in CPS is available to current graduate students in UVA's School of Engineering and Applied Science and will be awarded at the time of degree conferral. 

Resources for Current Students

Uva engineering graduate student resources.

Explore our resources for graduate students, including professional development support and ways to get involved at UVA Engineering.

Academic Planning

Find timelines, forms and guidance for completing your degree on schedule.

Current CS Graduate Students

Find information for new graduate students, program requirements and the graduate student handbook.

Upcoming Events

2024 cps rising stars workshop, our research & faculty .

The computer science department at the University of Virginia attracts federal research support in excess of $6 million annually, with total external research funding of more than $7 million each year. In addition to excelling in traditional research areas within computer science, we believe that many important research challenges lie at the boundary of computer science and other disciplines. With exceptional strength in experimental systems and applied research, our researchers are blazing new trails. d

UVAccelerate

Current UVA undergraduate students can apply to a Master of Engineering (M.E.), Master of Computer Science (M.C.S.), or Master of Materials Science and Engineering (M.M.S.E.) degree program in the third year of their undergraduate studies.

Graduate Program Contacts

Matthew b. dwyer .

Matthew B. Dwyer is the Robert Thomson Distinguished Professor in the Department of Computer Science at the University of Virginia.

Jack W. Davidson 

Jack W. Davidson is a Professor of Computer Science at UVA. He joined in 1981 after receiving his Ph.D. in Computer Science from the University of Arizona. His research interests include compilers, computer security, programming languages, computer architecture, and embedded systems. He is the principal investigator on several ongoing grants.

Felix Xiaozhu Lin 

Felix Xiaozhu Lin joined the Department of Computer Science as an associate professor in August 2020. Prior to his appointment at UVA Engineering, Lin was a tenured associate professor in the School of Electrical and Computer Engineering at Purdue University.

Six outstanding alumni inducted into Virginia Tech Academy of Engineering Excellence

Celebrating 25 years, the academy welcomed its newest class in May and brought its total membership to 185 alumni who have achieved exceptional career successes.

• Hayley Roulston

22 May 2024

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The Virginia Tech Academy of Engineering Excellence has welcomed six new members into its esteemed ranks.

Established 25 years ago under the guidance of Dean Emeritus F. William Stephenson and the college’s advisory board, this award recognizes members who have made enduring contributions to engineering and leadership throughout their careers. Selected from a pool of over 79,000 living alumni of the College of Engineering, the distinguished 2024 inductees have brought the academy’s total membership to 185.

This year’s inductees are:

• Mary Cunningham Boyce '81 of New York City
• Uma Jayaram M.S. '88, Ph.D. '91 of Los Gatos, California
• D. Fred McBagonluri M.S. '98 of Accra, Ghana
• Jay Parikh '94 of Mountain View, California 
• Ed Reynolds '85 of Ellicott City, Maryland
• Preston Mason White '63 of Virginia Beach, Virginia

“We are thrilled to welcome a cohort of extraordinary inductees whose accomplished careers have significantly influenced the engineering landscape,” said Julie Ross, the Paul and Dorothea Torgersen Dean of Engineering . “As academy members, they epitomize the pinnacle of professional achievement attainable through a Virginia Tech engineering education.”

Read more about the academy and each of its 184 members .

2024 Academy of Engineering Excellence inductees

Mary Cunningham Boyce

Bachelor's degree in engineering science and mechanics, 1981.

Always drawn to mathematics and physics, engineering was a natural decision for Boyce. Between supportive faculty, taking Mechanics of Deformable Bodies, a co-op opportunity, and being part of a study abroad trip to the former Soviet Union, Boyce found her footing in engineering mechanics. 

After graduating from Virginia Tech, she went on to receive her master’s degree and Ph.D. in mechanical engineering from the Massachusetts Institute of Technology (MIT). Boyce has spent her career in academia since completing her degrees. She is best known for the Arruda-Boyce model of the behavior of polymeric materials and her innovative product development of rubber and other soft materials.

“My academic experiences at Virginia Tech were a launching point for my entire career,” Boyce said. “These opportunities gave me the confidence to pursue a doctoral degree at MIT and my ongoing academic career in research in a highly interdisciplinary field.”

Between MIT and Columbia University, Boyce has led a distinguished career, including:

• Receiving the Benjamin Franklin Medal in Mechanical Engineering from The Franklin Institute; the Timoshenko Medal for Advances in Applied Mechanics, Applied Mechanics Division from the American Society of Mechanical Engineers; and the Engineering Science Medal from the Society of Engineering Science
• Membership in the National Academy of Engineering
• Fellowships in the American Society of Mechanical Engineers, American Academy of Arts and Science, and the American Academy of Mechanics.
• Roles as department head, dean, provost, and chief academic officer

Learn more about Boyce .

Uma Jayaram

Master's degree in mechanical engineering, 1988, ph.d. in mechanical engineering, 1991.

An accomplished engineer and leader, Jayaram began her journey as the first woman admitted to the mechanical engineering program at the Indian Institute of Technology, Kharagpur. Her time at Virginia Tech was profoundly influenced by her Ph.D. advisor, Arvid Myklebust , and the ACSYNT consortium, which taught her the value of co-creation with external partners. These experiences shaped Jayaram’s approach toward team building and leadership and have been instrumental in her career, which spans academia, startups, and corporations.

“A life lesson given by my seventh grade teacher was, ‘Give to the world the best you have, and the best will come back to you.’ I believe that we should strive to leave every interaction, every place, every group, and every organization a little better than how we found it,” said Jayaram. “This positive contribution, however small, is within everyone's reach and will improve the whole ecosystem and eventually come back to us in unexpected ways.”

Her journey to become the global head of Partnerships for Academia and Industry Research at Electronic Arts has crossed diverse sectors, including media and entertainment, engineering design, manufacturing, aerospace, and gaming. Jayaram’s highlights include:

• Leading the Intel Sports engineering team in transmitting the first streams from the Winter Olympics Opening Ceremonies in Pyeongchang, Korea, using the True VR end-to-end technology
• Co-founding three companies, two of which were acquired
• Being recognized as an American Society of Mechanical Engineers fellow in 2012
• Receiving her Ph.D. with her mother, husband, and 3-month-old daughter at her side

Learn more about Jayaram .

D. Fred McBagonluri

Master's degree in engineering sciences and mechanics, 1998.

In his formative years, McBagonluri was inspired by a local mechanic and his uncle who was a doctor. After earning an engineering scholarship, he combined the influences of these two fields and dedicated 16 years to the medical devices and equipment sectors. Recognizing the need to educate Africa’s emerging engineers, McBagonluri has been committed to ensuring they receive appropriate training for the past eight years.

Currently the provost and president of Academic City College in Ghana, McBagonluri’s career highlights include:

• Recipient of the 2008 New Jersey NJBiz Innovator Hero Award, a finalist for the 2009 NASA Astronaut Candidate Corps, and most recently the 2018 Ashesi University Innovator of the Year
• Written over 40 U.S. patents and patent applications, 22 of which were issued 
• Pioneered innovative product development and manufacturing processes, leading to over $250 million in new markets
• A distinguished career as a hands-on, progressive innovator in corporate America working at senior levels for Siemens Healthcare, Becton Dickinson & Co., and Joerns Healthcare

When asked what being inducted into the academy means to him McBagonluri said, “The dreams that come true are the dreams we dream while awake.” 

Learn more about McBagonluri .

Bachelor's degree in mechanical engineering, 1994

A mechanical engineer by education, Parikh saw an incredible opportunity in the internet technology industry. The fast-paced learning environment intrigued him from the very beginning. Equipped with the systems thinking and problem-solving skills that Virginia Tech instilled in him, he’s gravitated to tackling the more difficult problems in his career. 

With a career focused on engineering and product, Parikh’s accomplishments include:

• Growing Facebook from 300 million people to more than 3 billion
• Introducing and scaling disruptive technologies from zero to billions in revenue
• Climbing up the ladder from consultant to chief executive officer

“I am humbled and honored to be inducted into the Academy of Engineering Excellence,” said Parikh. “I never thought that when I graduated I’d become a member of such an accomplished group of Virginia Tech alumni.”

Learn more about Parikh .

Ed Reynolds

Bachelor's degree in electrical engineering, 1985.

Reynolds has made significant contributions to space exploration throughout his career. His defining moment came in 1990, when he, as a systems engineer for the Applied Physics Laboratory (APL), won a mission to rendezvous with a near-Earth asteroid against the Jet Propulsion Laboratory. This success led to further missions to Mercury, Pluto, and the sun. 

Following his work at Johns Hopkins University APL, Reynolds has spent over 20 years with NASA as a project manager for its missions. Other career milestones include:

• Being named to TIME Magazine's 100 Most Influential People in 2023
• Having asteroid (33486) 1999GN8 renamed Edreynolds by the International Astronomical Union Naming Committee
• Receiving the American Institute of Aeronautics and Astronautics Award for Aerospace for the Double Asteroid Redirection Test mission

“Being inducted into the Virginia Tech Academy of Engineering Excellence is a remarkable achievement for me. It signifies not only technical capability but leadership and dedication to advancing knowledge and solving real-world challenges,” said Reynolds. “Personally, it recognizes my contributions to deep space missions to better understand and protect Earth from solar coronal mass ejections and asteroid impacts.” 

Learn more about Reynolds .

Preston Mason White

Bachelor's degree in building construction, 1963.

At Virginia Tech, White embarked on a transformative journey that not only shaped his career but also impacted many lives. His most memorable moment at Virginia Tech was a setback in his first year. However, with his mentor Bill Favro’s advice, he returned to pursue a degree in building construction, marking a pivotal point in his life. White credits the building construction program for requiring courses that provided him with the skills needed to run a business.

Recently retired, White’s accomplishments are noteworthy, including:

• Establishing a $10 million endowed diversity scholarship as part of Virginia Tech Advantage which recently named its first recipient 
• Building a company from the bottom up, turning Century Concrete Inc. into a powerhouse with over 500 employees across three cities
• Living out the spirit of Ut Prosim (That I May Serve) through his involvement on over a dozen boards, including sitting on the Board of Visitors for Virginia Tech and Christopher Newport University
• Nearly a decade serving in the U.S. Coast Guard Reserve early in his career

On being inducted into the academy, White said, “Many who have come before me in this distinction are well deserving and I hope I can live up to the expectations. One bit of irony is that building construction was not part of the College of Engineering until several years ago, so I might not have been eligible for this back then. However, I am glad to be honored with this award, and for that part, I am glad I was a part of getting the major moved to the College of Engineering.”

Learn more about White .

Chelsea Seeber

540-231-2108

• Biomedical Engineering and Mechanics
• Building Construction
• College of Engineering
• Electrical and Computer Engineering
• Engineering Excellence
• Honors and Awards
• Mechanical Engineering
• Myers-Lawson School of Construction

Related Content

Meet our Masters Students

Insert your title here.

Master's Students

Virginia Tech Master of Engineering students come from a variety of backgrounds, and have specialized in different areas during their undergraduate years and work experiences. But they all have one thing in common – for them, the Master of Engineering program enhances their future career opportunities.

Their tech talent is in demand .

Hear from some of our Master's students below!

Corey Salmon

Master of Engineering, Computer Science and Applications; Boeing Scholar; Intern, Front End Developer, IBM; Undergraduate degree from Georgia Tech, Computational Media

Shano Ezzell

Master of Engineering, Computer Engineering. Undergraduate degree from Coast Guard Academy, Electrical Engineering

Jonathan Roof

Master of Engineering, Computer Science and Applications. Undergraduate degree from Virginia Tech, Chemistry

Elsa Gonzalez-Aguilar

Master of Engineering, Computer Science and Applications; Boeing Scholar; Lead Software Developer, Leidos; Undergraduate degree from University of Texas at El Paso, Computer Science

Teaching and research faculty

New faculty cohort 2023-24.

Collegiate assistant professor

Assistant professor

Professor; Director, Center for Quantum Architecture and Software Development; Quantum Architecture and Software Development lead

Collegiate associate professor

Find faculty by research area

Associate professor

Frank J. Maher Professor and director of the Center for Human-Computer Interaction

Professor and associate department head for faculty development

Professor and faculty lead, Virginia Tech Innovation Campus

Collegiate assistant professor and online teaching and learning coordinator

Professor and associate department head for undergraduate studies

Associate professor of practice

Collegiate associate professor and director of the Master of Engineering in Computer Science program

W.C. English Endowed Professor

Professor and Northern Virginia Center program director

Associate professor and associate director of research, Center for Human-Computer Interaction

Advanced instructor and director of academic operations

Professor and associate department head for research

John W. Hancock Professor of Engineering

Professor and associate director of the Sanghani Center for Artificial Intelligence and Data Analytics

Thomas L. Phillips Professor of Engineering and director of the Sanghani Center for Artificial Intelligence and Data Analytics

Professor and department head

Collegiate assistant professor and experiential learning coordinator

Professor and associate department head for graduate studies

Courtesy appointments

Ella Atkins (AOE)

Joseph Gabbard (ISE)

Myounghoon Philart Jeon (ISE)

Tom Martin (ECE)

Ico Bukvic (SOPAP)

Tom Hou (ECE)

Rouxi Jia (ECE)

Scott Midkiff (ECE)

Lance Collins (ME)

Ben Jantzen (Philosophy)

Song Li (SPES)

Jeff Reed (ECE)

Affiliate faculty

Eric Burger

Andrea Kavanaugh

Yinlin Chen

Nicholas Polys

Mark Gardner

Shin'ichiro Matsuo

Adjunct faculty

Steve Atkinson

Dave Noller

Kevin Shinpaugh

Yalong Yang

Robert Berwick

Michael Irwin

Ismini Lourentzou

Todd Stevens

Aisling Kelliher

James McClue

Francisco Servant

John Wenskovitch

Emeritus faculty

Donald Allison

Steve Harrison

Deborah Tatar

James Arthur

Rex Hartson

Richard Nance

Layne Watson

Roger Ehrich

Dennis Kafura

Barbara Ryder

Benedicta Ada Ottairoegbu

Igc fellow     |   global change center, ph.d. student  •  biological sciences, advisor:  dr. susan whitehead, research interests:  plant adaptation to rapid environmental changes., [email protected] •   twitter   •  linkedin.

Benedicta received her Bachelor's degree in Botany from the University of Lagos and graduated among the top five in her department with a CGPA of 4.72/5.0. During her undergraduate studies, she conducted research work on the plant growth analysis of  Costus spectabilis  and identified genetic diversity among four  Costus  species using RAPD markers. This experience drove her to want to understand how plants are able to adapt to their environments and how climate change affects these changes to ensure conservation and sustainable agriculture.

She has participated in joint research that aims to understand the epidermal tissues of plant and how they have been shown changes over time. She is interning as an African Learning Partner with the African Women in Agricultural Research and Development focusing on the effect of salinity and drought on the seed germination, growth parameters and phytochemical composition of  Vigna subterranea .

For her PhD, she is interested in understanding how plants respond and adapt to rapidly changing environmental conditions. Through the IGC program, Benedicta hopes to become an advocate for change, armed with a diverse background, a passion for interdisciplinary research, and a vision of contributing to a more resilient and equitable world.

The Interfaces of Global Change IGEP provides PhD students with a unique intellectual focus and training.

Each igc fellow gains depth in their specific scientific area of expertise (e.g. biology or engineering), while simultaneously gaining breadth in the multifaceted realm of global change and the science-policy interface..

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Grant named AAAS Fellow

Christine Grant, professor and inaugural associate dean for faculty advancement in the College of Engineering at North Carolina State University, has been elected as a Fellow of the American Association for the Advancement of Science (AAAS) for 2024.

A professor in NC State’s Department of Chemical and Biomolecular Engineering for more than 33 years, Grant served as associate dean for 12 years. In this role, she was responsible for faculty development, promotion and tenure processes in the College of Engineering.

Grant has been a lifelong advocate for broadening participation, promotion and retention of men and women in science, technology, engineering and mathematics. She has served as a mentor and role model for women, particularly women from underrepresented groups, in engineering from students to faculty members and has been recognized widely for her mentoring efforts. A prolific speaker nationally and internationally, she also engages in career coaching, and professional development workshops.

Grant was elected by AAAS “for outstanding contributions to colloids, surfaces, and interfacial phenomena of solid films and surfactants, and for extraordinary support for advancing women and minorities within faculty and students in science and engineering.”

Grant’s awards for mentoring activities include the Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring, an award established by the White House in 1995; the AAAS Mentoring Award; and the Women in Engineering Pro-Active Network (WEPAN) Bevlee A. Watford Inclusive Excellence Award, which honors individuals or groups who actively and creatively support the success of women of color in engineering at the undergraduate, graduate, faculty and/or administrative levels.

Grant is a Fellow, Life Member and the 2022 President of the American Institute of Chemical Engineers (AIChE), a global organization of 60,000+ members in 110 countries. She previously served the AIChE as a member of the Board of Directors, Chemical Technology Operating Council (CTOC), Environmental Division, National Awards and Nominating Committees and the Henry & Melinda Brown Endowment Steering Committee. She also served as the chair of the Minority Affairs Committee.

Grant received a Sc.B. in chemical engineering from Brown University, and M.S. and Ph.D. degrees, both in chemical engineering, from the Georgia Institute of Technology. She has also served as a visiting professor at Duke, Caltech and the University of Minnesota.

Grant is one of six NC State faculty members to be honored this year by AAAS, the world’s largest scientific society and the publisher of the journal  Science .

Each year, the AAAS Council, the policymaking body of the society, elects members who have shown scientifically or socially distinguished efforts to advance science or its applications. Fellows are nominated by their peers and undergo an extensive review process.

Grant said that she recently learned that her selection comes 120 years after the selection of the prolific African American scholar W.E.B. Du Bois as an AAAS Fellow in 1904.

“It means even more now,” she said.

• American Association for the Advancement of Science (AAAS)
• Department of Chemical and Biomolecular Engineering

Engineering faculty members among those recognized for excellence 

Scholarship endowment honors longtime Forest Biomaterials professor Peter Hart 

Bottomley honored by Virginia Tech as an outstanding alumna