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Computer Science & Applications
College of Engineering
Torgersen Hall is a 150,000-sq.-ft., $28-million building completed in 2000. It is connected to Newman Library by a dramatic bridge that spans Alumni Mall. It is named for Paul E. Torgersen, Tech's 14th president. There are classrooms, three rooms that can be configured for televised distance learning, and 150- and 300-seat auditoriums. The first floor also includes an atrium with tables, chairs, and computer hookups that serves as an electronic study court and a space where people can gather.
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3210B Torgersen Hall
Mail Code 0106
Blacksburg, VA 24060 Blacksburg VA 24061
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Department Head : Calvin Ribbens
Graduate Program Director(s) : Clifford Shaffer (Associate Head for Graduate Studies),
Sara Hooshangi (Director of MEng in CS Program),
Richard Mayo (Director of Graduate Programs)
Emeriti Faculty:
James Arthur;
Roger Ehrich;
Steven Harrison;
Hillyard Hartson;
Barbara Ryder;
Francisco Servant Cortes;
Deborah Tatar
Professors:
Osman Balci;
Douglas Bowman;
Ali Butt;
Kirk Cameron;
Ing Ray Chen (National Capital Region);
Stephen Edwards;
Wu-Chun Feng;
Edward Fox;
Lenwood Heath;
Dennis Kafura;
Benjamin Knapp;
Wenjing Lou (National Capital Region);
Chang Tien Lu (National Capital Region);
T Murali;
Dimitrios Nikolopoulos;
Sam Hyuk Noh;
Christopher North;
Alexey Onufriev;
Nicholas Polys;
Narendran Ramakrishnan (National Capital Region);
Chandan Reddy (National Capital Region);
Calvin Ribbens;
Adrian Sandu;
Clifford Shaffer;
Eli Tilevich;
Layne Watson;
Danfeng Yao
Associate Professors:
Godmar Back;
Debswapna Bhattacharya;
Young Cao;
Jin-Hee Cho (National Capital Region);
Hoda Eldardiry;
Denis Gracanin;
Bo Ji;
Aisling Kelliher;
Kurt Luther (National Capital Region);
Donald McCrickard;
Sharath Raghvendra;
Liqing Zhang
Assistant Professors:
Dwayne Brown;
Yan Chen;
Taejoong Chung;
Brendan David-John;
Peng Gao;
Muhammad Ali Gulzar;
Shaddi Hasan;
Matthew Hicks;
Thang Hoang;
Lifu Huang;
Xun Jian;
Anuj Karpatne;
Sang Won Lee;
Ismini Lourentzou;
Na Meng;
Ha Rim Rho;
Jamie Sikora;
Christopher Thomas;
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Bimal Viswanath;
Xuan Wang;
Daniel Williams;
Ihudiya Williams;
Dawei Zhou
Visiting Faculty:
Pi-Yueh Chuang
Frank J. Maher Professor:
Douglas Bowman
Thomas L. Phillips Professor of Engineering:
Narendran Ramakrishnan (National Capital Region)
Elizabeth and James E. Turner, Jr. '56 Faculty Fellow; CACI Faculty Fellow:
Danfeng Yao
W.C. English Professor:
Wenjing Lou (National Capital Region)
Assistant Professor of Practice:
Gregory Kulczycki (National Capital Region)
Associate Professor of Practice:
Margaret Ellis
John W. Hancock, Jr Professor of Engineering:
Dimitrios Nikolopoulos
Instructors:
Siwei Cao;
Heath Hillman;
David McPherson
Research Professors:
Mohammed Seyam
Collegiate Associate Professors:
Sally Hamouda;
Sara Hooshangi (National Capital Region );
Reza Jafari (National Capital Region);
Erika Olimpiew (Innovation Campus-Alexandria)
Collegiate Assistant Professors:
Melissa Cameron (Innovation Camous-Alexandria);
Kenneth Edmison;
Onyeka Emebo;
Andria Esakia;
Mohammed Farghally;
Tessema Mengistu (National Capital Region);
Allyson Senger (blacksburg)
Director of MEng:
Affiliate Professor in Computer Science:
Senior Research Scientist:
Andrea Kavanaugh
Research Scientists:
Andrea Kavanaugh
Computer Science & Applications Introduction
The graduate program at the Department of Computer Science at Virginia Tech is poised to become one of the top programs in the country. #40 in the US News and World Report 2018 rankings for graduate CS programs, additional accolades include being ranked in the top 20 CS departments in US Colleges of Engineering by number of Ph.D. degrees awarded.
Funding Opportunities
There are several possible sources of funding with or near the University for qualified graduate students. Well over half of CS graduate students are typically funded through departmental fellowships, teaching, or research assistantships. Others were supported elsewhere within the University, or at the nearby Corporate Research Center. The vast majority of students seeking support will find it in one of the following ways:
- 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 gradprog@cs.vt.edu for further information about applying to these programs.
MS Thesis and PhD Students who received Departmental support in their first year can normally expect to receive continued support during the remainder of their course of study (typically 2 years for MS, 4 or 5 years for PhD), so long as their job performance and degree progress is good. PhD students whose job performance is good are normally guaranteed three years of funding once they have passed their PhD Qualifier process.
Offered In (Blacksburg, National Capital Region)
Degree Requirements
Minimum GPA: 3.0
Institution code: 5859
The Master of Science degree provides a solid foundation in computer science while still offering flexibility to meet the needs and interests of individual students. The MS Thesis option requires 30 credits of course work of which typically 21 credits must derive from graded courses. Students in good standing typically complete this option in two years.
Students taking a terminal MS degree are expected to complete the thesis. The MS coursework-only option is intended for PhD students who seek a "MS along-the-way". Students who wish a coursework-only degree at the Master's level should enroll in the MENG degree program.
The MS thesis option requires 30 credits of course work of which typically 21-24 credits derive from courses and 6-9 credits from research work. At least one advanced graduate course must be included on the plan of study. Students must satisfy the breadth requirement by taking CS courses at the 5000 and 6000 levels that span four (4) different areas, adhere to an appropriate credit distribution, complete the graduate seminar twice, comply with the ethics and diversity requirements by completing either CS5014 or CS5024, and complete an oral and written final exam (also known as a Master's Thesis). Students in good standing typically complete the degree option in two years. The Computer Science department offers the accelerated BS/MS degree programs in accordance to graduate school polices and the following criteria. Students must be accepted into the program prior to the beginning of the semester in which they would enroll in courses to be used on the accelerated program. Students qualifying for the program must be in the last 12 months of their undergraduate degree and must have a minimum GPA of 3.5. Once completion of the undergraduate degree has been verified, students accepted into this accelerated program will be classified as regular graduate students. A maximum of 12 credits of graded coursework may be used in the program. No more than 6 of the double-counted credits may be at the 4000 level; all others must be offered for graduate credit. A grade of B or higher must be earned in each course to be double counted. Courses must not be taken pass-fail if a graded option is available.
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Concentrations
Bioinformatics Option
Students receiving the option will have that fact noted on their transcript upon successful graduation. To receive the option, students will take a minimum of seven (7) additional credits beyond those necessary for the degree without the option. Other requirements include:
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Students receiving the Bioinformatics option must take PPWS 5314 Biological Paradigms for Bioinformatics (3 credits), BCHM 5024 Computational Biochemistry for Bioinformatics (3 credits), and GBCB 5004 Seminar (1 credit). PPWS 5314, BCHM 5024, and GBCB 5004 may not be used both to complete the option and to satisfy CSA degree course requirements. Students who already have background equivalent to PPWS 5314 and/or BCHM 5024 may be permitted to substitute more advanced courses to satisfy this requirement.
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Students receiving the Bioinformatics option must take ONE of STAT 5615 (Statistics in Research), STAT 5616 (Statistics in Research), MATH 5515 (Modeling and Simulation of Biological Systems), or MATH 5516 (Modeling and Simulation of Biological Systems). These courses may also be used to fulfill CSA coursework requirements.
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Students must complete the final exam requirement for their respective CSA degree using a topic suitable for the Bioinformatics option. MS coursework-only students must take GBCB 5874 Problem Solving in Genetics, Bioinformatics, and Computational Biology, and use the final report from this course to satisfy their final exam requirement.
Graduate Certificate in Human-Computer Interaction
The Graduate Certificate in Human-Computer Interaction is administered by the Center for Human Computer Interaction and can be obtained in conjunction with either the M.S. or Ph.D. degree. Master's degree students complete 9 hours and doctoral students 15 hours of coursework for the certificate, where at least two of the courses taken must be outside the student's degree program requirements and outside the department. Students interested in the Graduate Certificate in Human-Computer Interaction should confer with the director of the Center for Human Computer Interaction prior to submitting a program of study to the Graduate School. to submitting a program of study to the Graduate School. (http://www.hci.vt.edu)
Human Centered Design Graduate Certificate
The act of creating something new shows up in many human endeavors. Human Centered Design (HCD) is an approach to design charged with understanding the needs, wants, and limitations of end-users which can be an important perspective for graduate research. The Human Centered Design graduate certificate combines technical expertise with critical inquiry to develop reflective practitioners equipped to meet vital human needs; it is based in the Interdisciplinary Graduate Education Program of the Graduate School. The HCD/IGEP degree is built around competencies in four core areas: (1) Interdisciplinary Research, (2) Design Studies, (3) Understanding People, and (4) Design Realization. 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. Ico Bukvic ico@vt.edu
Graduate Certificate In Data Analytics
The Graduate Certificate in Data Analytics prepares students for technical careers in big data analytics and data science. Students learn to develop new analytical methods and tools by integrating the computational, statistical, and engineering techniques that form the heart of big data analytics. The certificate is open to degree- and non-degree seeking students. Students complete four courses from an interdisciplinary selection, spanning Computer Science, Statistics, and Electrical and Computer Engineering. Details and checksheet are available at http://dac.cs.vt.edu/.
Graduate Certificate in Urban Computing
The Graduate Certificate in Urban Computing trains students in the latest methods in analyzing massive datasets to study key issues concerning urban populations. Students learn to apply methods in data analytics, computational modeling, and visualization. The certificate is open to degree- and non-degree seeking students. Students complete12 hours of coursework for the certificate from an interdisciplinary selection, spanning Civil and Environmental Engineering, Computer Science, Electrical and Computer Engineering, Mathematics, Population Health Sciences, Sociology, Statistics, and Urban Affairs and Planning. Details and checksheet are available at https://dac.cs.vt.edu/academics/urban-computing/.
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Offered In (Blacksburg, National Capital Region)
Degree Requirements
Minimum GPA: 3.0
Institution code: 5859
A student pursuing the Ph.D. degree is expected to exhibit a comprehensive knowledge of a broad cross section of the computer science discipline and to contribute significant new knowledge to the discipline through the research contribution contained in the doctoral dissertation. A PhD student must complete a minimum of 90 credits of graduate study, of which at least 27 must derive from courses. The PhD program is intended to be completed in about five years from entering the graduate program with a BS degree in Computer Science or a related field, or about four years if the student already has an MS degree in Computer Science or a related field. To encourage Ph.D. graduates to exhibit sufficient breadth of computer science and its application areas, Ph.D. students must take CS courses spanning four (4) computer science different areas and one to three cognate (i.e., outside CS) courses. At least two 6000-level CS graduate courses must be included on the plan of study.
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Concentrations
Bioinformatics Option
Students receiving the option will have that fact noted on their transcript upon successful graduation. To receive the option, students will take a minimum of seven (7) additional credits beyond those necessary for the degree without the option. Other requirements include:
-
Students receiving the Bioinformatics option must take PPWS 5314 Biological Paradigms for Bioinformatics (3 credits), BCHM 5024 Computational Biochemistry for Bioinformatics (3 credits), and GBCB 5004 Seminar (1 credit). PPWS 5314, BCHM 5024, and GBCB 5004 may not be used both to complete the option and to satisfy CSA degree course requirements. Students who already have background equivalent to PPWS 5314 and/or BCHM 5024 may be permitted to substitute more advanced courses to satisfy this requirement.
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Students receiving the Bioinformatics option must take ONE of STAT 5615 (Statistics in Research), STAT 5616 (Statistics in Research), MATH 5515 (Modeling and Simulation of Biological Systems), or MATH 5516 (Modeling and Simulation of Biological Systems). These courses may also be used to fulfill CSA coursework requirements.
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Students must complete the final exam requirement for their respective CSA degree using a topic suitable for the Bioinformatics option. MS coursework-only students must take GBCB 5874 Problem Solving in Genetics, Bioinformatics, and Computational Biology, and use the final report from this course to satisfy their final exam requirement.
Graduate Certificate in Human Computing Interaction
The Graduate Certificate in Human-Computer Interaction is administered by the Center for Human Computer Interaction and can be obtained in conjunction with either the M.S. or Ph.D. degree. Master's degree students complete 9 hours and doctoral students 15 hours of coursework for the certificate, where at least two of the courses taken must be outside the student's degree program requirements and outside the department. Students interested in the Graduate Certificate in Human-Computer Interaction should confer with the director of the Center for Human Computer Interaction prior to submitting a program of study to the Graduate School. to submitting a program of study to the Graduate School. (http://www.hci.vt.edu)
Human centered Design Graduate Certificate
The act of creating something new shows up in many human endeavors. Human Centered Design (HCD) is an approach to design charged with understanding the needs, wants, and limitations of end-users which can be an important perspective for graduate research.The Human Centered Design graduate certificate combines technical expertise with critical inquiry to develop reflective practitioners equipped to meet vital human needs; it is based in the Interdisciplinary Graduate Education Program of the Graduate School. The HCD/IGEP degree is built around competencies in four core areas: (1) Interdisciplinary Research, (2) Design Studies, (3) Understanding People, and (4) Design Realization. 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.
Graduate Certificate in Data Analytics
The Graduate Certificate in Data Analytics prepares students for technical careers in big data analytics and data science. Students learn to develop new analytical methods and tools by integrating the computational, statistical, and engineering techniques that form the heart of big data analytics. The certificate is open to degree- and non-degree seeking students. Students complete four courses from an interdisciplinary selection, spanning Computer Science, Statistics, and Electrical and Computer Engineering. Details and checksheet are available at http://dac.cs.vt.edu/.
Graduate Certificate in Urban Computing
The Graduate Certificate in Urban Computing trains students in the latest methods in analyzing massive datasets to study key issues concerning urban populations. Students learn to apply methods in data analytics, computational modeling, and visualization. The certificate is open to degree- and non-degree seeking students. Students complete12 hours of coursework for the certificate from an interdisciplinary selection, spanning Civil and Environmental Engineering, Computer Science, Electrical and Computer Engineering, Mathematics, Population Health Sciences, Sociology, Statistics, and Urban Affairs and Planning. Details and checksheet are available at https://dac.cs.vt.edu/academics/urban-computing/.
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Offered In (Blacksburg, National Capital Region)
Degree Requirements
Minimum GPA: 3.0
Institution code: 5859
The Master of Engineering (MEng) degree provides advanced training in Computer Science at the graduate level, with an emphasis on practical coursework that prepares students for a wide range of employment in the computing field. The MEng degree program is open to students with less formal Computer Science background, since it includes the coursework needed to prepare such students for more advanced Computer Science courses.
The MEng degree has a single coursework-only option that requires 30 credits derived from graded courses. This includes a required course related to ethics in computing and a project-oriented Capstone course. Students are required to complete a cluster of three courses to ensure depth in some practical aspect of computing. Full-time students in good standing can typically complete the program in three academic terms.
The Computer Science department offers the accelerated BS/MEng degree program in accordance to graduate school polices and the following criteria. Students must be accepted into the program prior to the beginning of the semester in which they would enroll in courses to be used on the accelerated program. Students qualifying for the program must be in the last 12 months of their undergraduate degree and must have a minimum GPA of 3.3. Once completion of the undergraduate degree has been verified, students accepted into this accelerated program will be classified as regular graduate students. A maximum of 12 credits of graded coursework may be used in the program. No more than 6 of the double-counted credits may be at the 4000 level; all others must be offered for graduate credit. A grade of B or higher must be earned in each course to be double counted. Courses must not be taken pass-fail if a graded option is available..
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Computer Science & Applications Facilities Introduction
Laboratories in the Department of Computer Science in Blacksburg are distributed across three buildings: McBryde Hall, Torgersen Hall, and the KnowledgeWorks II (KWII) building in the Corporate Research Center (CRC). The Department of Computer Science at NCR is housed at the Virginia Tech NCR building in Falls Church and VTRC building in Arlington.
Bioinformatics Lab
The bioinformatics group on campus hosts and maintains several dedicated resources. The Expresso database server provides over 2TB of storage and is accessible to any of our research workstations & servers via our internal Gig-E network. Baobab is a 6 node Gig-E research cluster with 8 processor cores & 32GB of memory per node. Mnemosyne and Mnemosyne2 are high memory dedicated servers for intense memory usage calculations and is used by graduate and faculty researchers for large dataset manipulation. Kuprin is a NVidia cuda GPU processor machine using triple nVidia GTX680 cards.
Center for Human-Computer Interaction (CHCI)
Many Computer Science faculty and students are affiliated with the Center for Human-Computer Interaction (CHCI; hci.vt.edu), an interdisciplinary community of scholars focusing on human aspects of computing—understanding and designing for human use of interactive systems. Current CHCI research is focused on 3D Experiences (virtual reality, augmented reality, and visualization) and Social Informatics. Faculty and students affiliated with CHCI have access to a wide variety of resources for research, including the Cube (large motion-capture and spatial audio theater in the Moss Arts Center), the Visionarium (visualization facility including a four-wall CAVE system), a 3D Experiences Studio in the Moss Arts Center, additional design studios in the Media Building and Moss Arts Center, usability laboratories in McBryde Hall, and project rooms in VT KnowledgeWorks II. The CHCI maintains an inventory of shared mobile equipment (cameras, tablets, input devices, eye trackers, etc.) that can be reserved and checked out by affiliated faculty and students.
Discovery Analytics Center (DAC)
The Discovery Analytics Center (DAC; http://dac.cs.vt.edu) is an interdisciplinary research center at Virginia Tech with labs and facilities across the commonwealth in Blacksburg, Falls Church, and Arlington. The center’s focus is on data analytics and machine learning to tackle knowledge discovery problems in important areas of national interest, such as intelligence analysis, sustainability, and public health. DAC currently is comprised of 16 academic faculty members, 6 research and professional faculty and over 90 Ph.D. students from computer science, statistics, electrical and computer engineering, and mathematics. DAC administers the graduate certificate in data analytics and the graduate certificate in urban computing. Our curriculum emphasizes not just the algorithmic aspects of converting data to knowledge but also the importance of human-in-the-loop analytics to arrive at insights. DAC researchers have access to high-performance computing facilities for big data analytics (including clusters and GPU machines), large-screen visualization displays and, most importantly, a variety of massive datasets collected in real-world contexts (e.g., social media, transportation, publishing, and real estate).
General Departmental Resources
The department maintains a pool of highly available virtualized servers to support email, web, and file services. Computer Science resources available to graduate students include: an @cs.vt.edu email address, a personal web site, and central file storage. Additional resources are available for research and instruction. Resources available for research include: virtualized servers, web site space, and backups. Resources available for instruction include: IaaS (infrastructure as a service), web site space, and a remote login cluster. Various research groups also offer special-purpose facilities to their members.
Human-Centered Design
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 ico@vt.edu How to Apply: Fill out the online application for participation in the certificate program.
Laboratory for Advanced Scientific Computing and Applications (LASCA)
The goal of the Laboratory for Advanced Scientific Computing and Applications (LASCA) is to provide expertise and leadership in high-end scientific computing research and education at Virginia Tech. Located in Torgersen Hall, the laboratory is a visible and strategic center of activity in applied high-performance computing on campus. LASCA participants do basic research in high-performance parallel computation and assist scientists and engineers in applying high-end computing resources to their problems. By bringing together experts in scientific computing and its applications, LASCA helps build the kind of multidisciplinary teams needed to address today's most challenging computational science problems.
stack@cs Center for Computing Systems
The stack@cs Center for Computer Systems (http://stack.cs.vt.edu) tackles challenging problems that transcend any single component of the application software and architecture stack and require interdisciplinary solutions. This requires the collaborative expertise of computer scientists and engineers, domain scientists, and educators spanning multiple departments across the College of Engineering and the College of Science as well as other research organizations such as ICAT and ICTAS. stack@cs Center faculty have a rich history of interdisciplinary collaborations that contribute to the evolving education and research missions of the college and university.
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