Doctor of Philosophy Programs

The Department of Electrical Engineering and Computer Science (EECS) in the College of Engineering and Computer Science at Syracuse University offers Ph.D. degrees in computer and information science and engineering (CISE) and in electrical and computer engineering (ECE).

The objective of these programs is to graduate doctoral students who:

1. Are scholars in their field of research as evidenced by:
   • their ability to do independent research by synthesizing original ideas that are evaluated to be non-trivial contributions by other researchers,
   • the mastery of their discipline by being able to recall, comprehend, apply, analyze, synthesize, and evaluate ideas with intellectual rigor using the major concepts and results of their discipline.
2. Can communicate their ideas effectively as evidenced by:
   • their ability to write papers, dissertations, and proposals that are judged to be well-written, well-presented, and well-argued,
   • their ability to give technical presentations that are judged to be clear, concise, and informative.

The requirements for the Ph.D. programs combine coursework with research work emphasizing mastery of a field of knowledge, familiarity with allied areas, facility in the use of research techniques, responsibility for the advancement of knowledge, and effective communication of ideas. These are tested primarily by comprehensive examinations and the defense of the dissertation rather than by a summation of courses, grades, and credits.

Student research work is led by internationally renowned researchers in their areas of expertise. One of the strengths of our doctoral programs lies in the ability of the faculty to participate in many research areas of an interdisciplinary nature. Even though EECS offers Ph.D. programs in the two areas indicated above, the research interests of many of our faculty connect these areas.

The CISE doctoral program targets those students with research interests in topics generally associated with computer and information science and with software aspects of the computer-engineering field. The ECE doctoral program targets students with research interests in topics encountered in the electrical-engineering field and in the hardware area of computer engineering.

Students in these programs are subject to all regulations of the Graduate School.

The basic structure of the requirements for a Ph.D. degree is the same for both degrees. What differentiates the programs are the details, namely:

1. The list of topics in which students must demonstrate competencies by completing coursework.
2. The topics covered in the written Qualifying Examination Part I.

Ph.D. Degree Programs

Ph.D. Degree Programs in Computer and Information Science and Engineering (CISE) and Electrical and Computer Engineering (ECE)

Admission Requirements

Admission to the Ph.D. programs is highly selective. Only those individuals with superior qualifications and a B.S. and/or M.S. from an accredited institution in computer engineering, computer and information science, electrical engineering, or a related field are invited to apply. Accepted students must start their doctoral program of study in the fall semester. No students will be accepted to start the program in the spring semester. Applicants must provide scores on the general test of the Graduate Record Examination (GRE).

In addition, applicants whose native language is not English must provide scores on the Test of English as a Foreign Language (TOEFL).

Each program has its own admission committee that evaluates the overall academic record of an applicant. Each of these committees uses the following general guidelines during the evaluation process:

• GRE Verbal score of 153 or better (using New GRE Score System);
• GRE Quantitative score of 155 or better (using New GRE Score System);
• GRE Analytical Writing score of 4.5 or better (the GRE Analytical multiple choice is not acceptable);
• For international students: TOEFL computer-based score of 250 (Internet-based score 100; paper-based score 600) or better;
• GPA of 3.5/4.0 or better.

Exceptional candidates who may not satisfy the above general guidelines but excel in other criteria (such as publications in technical conferences and/or journals, scholastic achievement) are encouraged to apply.

Students may apply online by completing the application given at the following web site: apply.embark.com/grad/syracuse/37/.

Guidance Committee

A two-person faculty Guidance Committee assists each newly admitted student with program planning. When identified, the dissertation advisor will serve as the principal source of academic advice and counsel.

Residence Requirements

Students must also satisfy the residency requirements of the Graduate School. These are given in Section 46.0 (Doctoral Degrees) of the Academic Rules and Regulations of Syracuse University at the following web site: syracuse.edu/policies/currentrr.pdf.

Academic Requirements

Degree programs are tailored to meet the needs of the individual, subject to certain general departmental requirements. The Ph.D. program consists of coursework, examinations, presentations, and a dissertation.

A minimum of 52 credits of coursework is required by the CISE and the ECE doctoral programs, beyond those taken for the bachelor’s degree.

Coursework

Each student must complete at least 48 credits of technical graduate courses at the 600-level or above (courses for graduate students only). Of these 48 credits, 30 credits (number of credits of coursework required for an M.S. degree EECS) provide broad knowledge in the student’s field of doctoral work and 18 credits provide depth in student’s research area. Therefore, these 18 credits are to be taken from specialized courses at the 700-level or above (graduate courses that have a graduate course as a prerequisite) that support the student’s area of research. Independent study courses cannot be used to satisfy the 700-level requirement. Programs of study for CISE Ph.D. students must include CIS 623 , CIS 655 , CIS 657 , and CIS 675 .

In addition, each student must complete at least 4 credits of professional development courses. This requirement is fulfilled by taking one 3-credit course in presentational speaking and one 1-credit course in fundamentals of research. The course in presentational speaking, taught by the Department of Communication and Rhetorical Studies, will equip our doctoral students with the ability to deliver effective technical presentations. The course in fundamentals of research will provide doctoral students with fundamental skills needed in their pursuit of a doctoral degree within the context of a small research project.

The following is the summary breakdown of credit requirements:

Doctoral Program Information

To ensure that all doctoral students have a broad knowledge in their field of doctoral work, they must demonstrate competence by completing coursework in at least three areas from the list associated with the doctoral program the student is pursuing. These two lists are maintained by the program committees of the department. The topics in these lists may vary to reflect the change of their importance in providing doctoral students with a broad education. For example, currently:

• A student in the CISE doctoral program must demonstrate competence by completing coursework in at least three of the following areas:
  • Algorithms
  • Architecture
  • Artificial Intelligence
  • Hardware Systems
  • Logic and Theory of Computation
  • Operating Systems
  • Programming Languages and Compilers
  • Software Systems
• A student in the ECE doctoral program must demonstrate competence by completing coursework in at least three of the following areas:
  • Algorithms
  • Circuits - Digital, Analog and RF
  • Communications
  • Computer Architecture and Hardware Design
  • Devices - Electronic, Microwave and Optical
  • Electromagnetics and Power
  • Engineering Mathematics
  • Signal Processing and Control
  • Software Systems

Examinations and Colloquium Presentations

Students must pass the qualifying examination associated with the doctoral program they are pursuing, proposal defense, and dissertation defense. In addition, students must present their research results to the faculty at the department Colloquium Series.

Qualifying Examination (QE)

The QE is composed of two parts: Qualifying Examination Part 1 (QE1) which consists of the written eligibility examination, and Qualifying Examination Part 2 (QE2) which consists of the research examination. To pass the QE, doctoral students must pass both of
these examinations.

The objective of the Q E1:

Written Eligibility Examination is to ensure that students have mastered the fundamentals pertinent to their doctoral program of study and possess the mathematical maturity necessary to undertake doctoral research. The QE1 must be taken by all students in a doctoral program in the spring semester of their first year of matriculation into the program regardless of whether they have entered the program with a bachelor’s or master’s degree. In the beginning of each fall semester, the department provides students with the scopes of these examinations. The scopes may vary to reflect the current importance of the topics covered by them.

The objective of the Q E2:

Research Examination is to ascertain that the doctoral student is ready to engage in research. It will include the student’s presentation of results of a mini research project, chosen by the student after passing the QE1. It must be taken by all students in a doctoral program in the spring semester of their second year of matriculation into the program.

Candidacy

Doctoral students are admitted to candidacy after passing the QE. Therefore, they are considered Ph.D. candidates only after passing this examination.

Research Committee

After passing the QE, the student must identify a faculty member of EECS who will supervise his/her dissertation. The dissertation advisor will guide the student in forming a research committee consisting of two additional faculty members. If any one of these additional faculty members is not from the EECS department, then the membership of the committee must be approved by the chair of EECS. The dissertation advisor will be the chair of this three-member committee. This committee will guide the student during the dissertation work.

Proposal Defense (PD)

The objective of this oral exam is for the student to demonstrate suitable selection of a dissertation topic and adequate preparation for said research. This exam must be taken within two years of passing the QE.

After passing the PD, the student prepares a dissertation, normally carried out under the supervision of the dissertation advisor. While preparing the dissertation, the student gives a presentation(s) of his/her research work at the department Colloquium Series.

Colloquium Presentation

The objective of the student’s presentation(s) at the Department Colloquium Series is to communicate the student’s research results to the faculty and students of the department. The student must give at least one talk at this colloquium based on his/her dissertation prior to the final dissertation defense.

The student may request a final oral examination only upon completion of the dissertation and after its approval by the student’s research committee. The research committee is responsible for assessing that the doctoral candidate is a scholar in his/her field of research and can communicate ideas effectively. The assessment demonstrating that the doctoral student has achieved scholarly status must include an outside evaluation by a scholar in the field of the student’s dissertation work. This outside evaluation can be in the form of an outside reader who is not a member of the student’s research committee, publication in technical journals, or publication in proceedings of refereed conferences.

Dissertation Defense

The objective of this oral exam is to give final certification of doctoral dissertations. It consists of a capstone seminar to communicate main contributions in the doctoral dissertation, open to general audience, followed by an in-depth technical assessment of student’s work by the examining committee. The examining committee will assess mainly the student’s dissertation work but may also assess the student’s mastery of related topics and previous work in the field.

Financial Support

Financial support for Ph.D. students is available in many forms. Such support normally entails a stipend in addition to a scholarship. Graduate teaching assistants, graduate research assistants, fellows, and other students supported financially by the University must exhibit satisfactory progress toward the chosen degree to be reappointed each year. Satisfactory progress is determined by EECS faculty during the yearly review of all doctoral students.

Time Limit

As required by the Graduate School, all requirements for the Ph.D. degree must be met within five years of the satisfactory completion of the QE.

Master of Philosophy

The master of philosophy is an intermediate degree between the academic master’s degree and the doctor of philosophy. In order for the master of philosophy degree to be awarded, a student must complete all the requirements for the doctoral degree except the dissertation.

Current Research Areas

Artificial Intelligence Image segmentation and restoration; pattern and shape recognition; computer vision; expert systems; intelligent systems and other applications of fuzzy logic, neural networks and evolutionary algorithms; learning classifier systems; social network analysis; multi-agent systems.

Communication and Information Theory Cognitive radio systems; Shannon theory for multiuser systems; information theoretical security; joint source-channel coding; cooperative communications; energy efficient communications; communication under channel uncertainty and queuing constraints; multiuser MIMO communication systems; MIMO communication with airborne platforms.

Communications and Signal Processing Detection and estimation theory; distributed signal processing and data fusion; adaptive signal processing algorithms and architectures; radar signal processing; knowledge-based signal processing; image processing; digital communications; information theory and processing of auditory signals by the nervous system; coding; parallel algorithms for signal processing; complexity of DSP algorithms; communication networks; photonic communications; weak signal detection in non-Gaussian environments; analysis of bistatic radars.

Complex Systems Evolutionary algorithms, neural networks, self-organizing systems, dynamical systems, distributed multi-agent systems.

Computer System Security

Applying security principles to secure computer, network, and information systems; authentication; access control; data protection; privacy; securing web browsers, web servers, and web applications; Smartphone and mobile system security; malware detection and analysis; applying executable code analysis and virtualization techniques to improve computer security; digital forensic analysis; protocol steganography; detecting and thwarting code injection attacks; developing effective methods and materials to improve security education.

Distributed Information Systems Multimedia systems; object-oriented databases; multimedia transport protocols; high bandwidth networks; distributed conferencing; visualization and virtual reality; multimedia storage systems, including optical systems; video on demand; distributed multimedia applications; web technology.

Dynamical Systems and Control Control of dynamical systems; Optimal control; Distributed control of large scale interconnected systems subject to communication and/or structural constraints; Synchronization and coordination of multi-agent networks; Computational tools for optimal control of distributed systems; Analysis and control of spatially-periodic, time-periodic, and sampled-data systems.

Electromagnetic Fields and Antennas Electromagnetic aperture problems; application of matrix methods to radiation and scattering systems; iterative methods for large electromagnetic problems; analysis of printed circuits; adaptive and smart antennas; antenna arrays; antenna array synthesis; development of high-pulsed power systems; analysis of small radomes; time-domain radar; microwave remote sensing of earth terrain; wave propagation in random media; scattering from random surfaces; scattering from composite dielectric and conducting targets; waves in anisortropic media; radar clutter modeling; millimeter and microwave integrated circuits; numerical solution of electromagnetic field problems.

High Confidence Design Formal methods; formal specification, synthesis and verification of software and hardware; computer security; network security.

Information Fusion and Wireless Sensor Networks Architectures and algorithms for information fusion; wireless sensor network design; detection, estimation, localization, tracking and classification in wireless sensor networks; security and assurance.

Logic in Computer Science Mathematical foundations of hybrid systems and continuous computation, logics for hybrid and continuous computation, quantum computation.

Low-Power System/Circuit Design CPU load/tasking scheduling; job scheduling and task migration for multi-node data centers; job scheduling for temperature control; audio/video circuit board design; innovative signal processing algorithms; redundant logic operation elimination for datapath modules; gate sizing and buffer insertion; bias voltage control at transistor level.

Microelectronics Solid state sensors; nonlinear dielectric and optical materials; thin film growth and processing, high speed electronic devices and circuits; and power electronics.

Neural Networks

New learning algorithms, adaptive connection systems, self-organizing networks, pattern recognizers, spatio-temporal networks, modular networks, hierarchical networks, evolutionary algorithms, fault-tolerant neural networks, models of biological systems, classification and clustering algorithms.

Optics and Wave Phenomena

Wave propagation and applications, linear and nonlinear, dispersive and nondispersive; acousto-optic interactions; optical information processing and optical bi stability; optical wave mixing; holography; optical interconnects; optical computing algorithms and architectures; pipelined optical binary computing; wave propagation through random media; waves and fields in anisotropic media; nonlinear echoes.

Photonics and Optical Engineering

Optical information processing; interconnection and communication networks; fiber optics, fiber light amplifiers, and lasers; photorefractive and bio-optical materials and their applications in wave-mixing and dynamic holography; micro-optic fabrication; optical computing; electro-optics; optical memory; optical wave propagation and diffractions.

Power Engineering and Smart Grid:

Application, control, and use of distributed energy resources and storage devices; economic, ancillary, and emergency demand response and scheduling optimization under grid and customer- defined constraints; advanced metering infrastructure; communications, information management, and automated power system control technologies.

Programming Languages

Denotational semantics, logics of programs, formal methods, semantic models of parallel programs, fair behavior and liveness properties of parallel programs, applications of semantic models to program design, parallel program correctness.

RF and Wireless Engineering Analysis and design of RF and Wireless and satellite communication circuits and systems.

Software Engineering

Software models; metric and formal methods; fault-tolerant software and software reliability; software reusability; object-oriented software engineering methods and tools; techniques for software engineering data analysis; distributed and parallel software development; trusted systems.

Statistical Signal Processing Detection and estimation theory; decentralized signal processing and data fusion; adaptive signal processing algorithms and architectures; compressive sensing; stochastic resonance and noise enhanced signal processing; remote sensing and image processing; radar signal processing, computer vision and pattern recognition; signal processing for security and information assurance; machine learning.

Systems Assurance

Systems assurance focuses on the design, development, and deployment of information systems with a particular emphasis on networked systems, information assurance, information security, information integrity, and privacy. Our research focuses on the ways information systems are designed to work reliably, safely, correctly, and securely. These methods also aim to reduce the complexity of systems assurance. Our research also focuses on developing algorithms and protocols to achieve security and privacy in network and distributed computing.

Theory of Computation

Computational complexity of higher-order functionals, complexity of “lazy” computation, biological models of computation, and computational learning theory.

VLSI Computer-aided design and architectures design, verification and testing of VLSI systems aided by EDA tools (Cadence, Synopsys, etc.); design of digital, analog, and mixed-signal systems; functional verification; testing; computer-aided design techniques for routing, simulation, verification, and synthesis; silicon compilation; formal verification; high-level synthesis; system integration; applications of declarative programming languages; algorithms and architectures for parallel and distributed systems.

Wireless Networks Cross-layer design and resource allocation; mobile phone sensing; mobile and distributed computing; wireless smart camera networks; energy efficient wireless networks; market based designs; game theoretic formulations for adversarial environments.

Systems Assurance Institute (SAI)

The SAI is a collaboration of four renowned Syracuse University institutions: L.C. Smith College of Engineering and Computer Science, School of Information Studies, S.I. Newhouse School of Public Communications, and the Maxwell School of Citizenship and Public Affairs. SAI advances the understanding and state-of-the-practice of systems assurance by providing a collaborative focus among Syracuse University faculty and external affiliates. The collaboration encompasses three major areas: basic and applied research, academic education and workforce development training, and technology transfer prompting economic growth. Technology transfer is accomplished through Syracuse University’s Computer Applications and Software Engineering (CASE) Center. For more information about SAI, visit: sai.syr.edu/. Information about the NSF Scholarship for Service may also be found at this web site.

Research Laboratories

Communication Laboratory This laboratory is dedicated to communication and signal processing research. On-going research projects include information theoretic study of multi-user communications; decentralized statistical signal processing for information fusion; MIMO communications for airborne platforms; and various enabling technologies for cognitive wireless networks.

DOPL Laboratory is the home for doctoral students working on management and restructuring of large software systems, high performance computing using GPUs and computer clusters, and tools for visualizing and understanding complex software systems.

Distributed Multiagent Laboratory (DMA Lab)

The DMA lab provides a unique environment for exploring basic research and applications on distributed multiagent systems. Areas of research include software agents, real-time intelligent distributed systems, evolutionary and Bayesian game theory, applications of artificial intelligence techniques on computer systems problems, and Internet algorithms and applications.

Fiber Fabrication Research Laboratory

This laboratory has a facility for fabricating specialty optical fibers; vacuum systems, including a special ultra-high vacuum system for evacuating ampoules; various furnaces, including a high-pressure furnace for preform fabrication; a fiber-pulling tower capable of drawing about 3 km of fiber from a 20 cm preform; and extensive fiber analysis equipment, including a special fiber microscope and an automatic optical spectrum analyzer. A process has been developed here for fabricating fibers with very thin layers of optically active material at the core cladding boundary. The optically active materials are semiconductors, metals, lithium niobate, and magnetic materials. These fiber devices are typically 3 to 20 mm long and have a large variety of applications in communication, computer memories, and sensors. Examples of these applications are fiber light amplifiers, sonar detectors, and true image light amplifiers in full color and 3-D, etc. Both graduate and undergraduate students participate in this research.

Microelectronics Laboratory

This laboratory has processing and measuring instrumentations for the fabrication and characterization of integrated devices and circuits. The laboratory is equipped with thin film deposition systems, including ion beam assisted sputtering system, thermal evaporation system.

Photolithography, high temperature diffusion furnace and chemical processing set ups allow students to build semiconductor devices, thin film sensors, and integrated circuits. Measurement equipments include four-point probe system for measuring capacitance and dielectric loss as a function of frequency and temperature, hall measurement, etc. This laboratory facility is used for both research and teaching. Ongoing research projects involve development of metal-oxide gas sensors, conductive transparent film for solar applications.

Photonics Laboratory

The Photonics Laboratory has five fully equipped optics rooms. Each has a vibration isolated optical table and various kinds of optical devices and elements. It has a one-dimensional detector array, a digital rail, a CCD camera and image processing system, a digital scope, and various photo-detectors and laboratory accessories. In addition, we have a 5-W Argon Ion laser, a 50 mW He-Ne laser, and a number of semiconductor lasers. Research efforts include information processing for two-dimensional and three-dimensional data related to military as well as commercial applications, micro-fabrication of electro-optical diffractive optical elements, photonic switching as related to computer and communication networks, real-time holography for free-space beam steering and optical intersections, and three-dimensional optical memory and molecular electronics for the future generation of high-density and large-capacity digital storage devices.

Power Engineering and Smart Grid Laboratory has three specialized units. First unit is for Power Electronics experiments, equipped with two switching power pole boards for DC-DC power conversion with capabilities of analog and digital output control and for Electromechanical Devices, equipped with two switching power boards for DC-DC and DC-AC power conversion with capabilities of digital output control along with a set of controlled electromechanical DC and AC devices. Second unit is Smart grid lab, which includes a micro-grid with renewable energy (such as wind, solar) conversion and control, energy storage and control, a double transmission line, a distribution network, 7 feeders and smart meters, a static and a dynamic load, and a power factor correction device. Third unit is Smart home lab, which includes smart home appliances, smart meters with communication node and data processing interfaces. Primary goals are to provide hands-on experience to students to understand power system operations, to collect and analyze data using the model of a real micro-grid power network, to test different vendors’ equipment, to investigate and compare new system components for measurement and control, and to develop new solutions for local and remote control as well as investigate cyber security.

RF, Wireless, and Signal Processing Laboratory

Fabrication facilities exist here to make printed circuits with accuracy up to 70 microns, both for VLSI and microwave CAD. Equipment for charactering devices directly in both time and frequency domains is also available. The laboratory is equipped with a Waveform Processing System capable of analyzing devices up to 18 gigahertz. In addition, a Vector Network analyzer operating from 45 megahertz to 26.5 gigahertz can not only characterize noise figures of devices, but can also measure various network parameters of printed circuits, devices, and antennas. This equipment is computer controlled for higher accuracy and ease of measurement. In addition, a high-power Quantronix laser system provides the capability of performing research in impulse radar technology. With the help of laser-activated photo-conductive switches it is possible to generate kilovolt amplitude electrical pulses of 300 picoseconds duration. Several high-end workstations provide the capability of solving challenging problems in electromagnetics and signal processing. By adding DSP boards to Pentium processors it is also possible to carry out real-time adaptive signal processing.

Sensor Fusion Laboratory

The primary focus of this laboratory is research related to statistical signal processing for multi-sensor systems and cognitive wireless networks. Current research projects involve signal processing for distributed detection and estimation, fusion algorithms for multimodal sensors, cognitive radio networks, security and assurance of cognitive wireless networks and sensor networks, compressive sensing, theory and application of stochastic resonance and wireless sensor networks applications. This laboratory provides state-of-the-art computing facilities.

VLSI Systems Design and CAD Laboratory aims to develop design methodologies and techniques that empower designers to design, test, verify, and build systems on a chip. Current research focus is around high-level synthesis for digital and mixed-signal systems, reconfigurable computing, and CAD for physical design.

Web and Smartphone Security Lab Conducts research on web and Smartphone security. Current research projects involve access control systems for web browsers, web servers, and web applications, authentication, access control, and data protection for Smartphones, and security enhancement for the Android operating system and applications. The lab is also the owner of the SEED project, which produces hands-on lab exercises for computer security education; these exercises are being used by over a hundred universities worldwide. The lab is equipped with Smartphone devices and development technologies, as well as powerful servers for system development.