Ph.D. in Computing and Information Sciences

A research degree designed to produce independent scholars, cutting-edge researchers, and well-prepared educators, you'll benefit from world-class faculty, diverse academic offerings, and modern facilities as you identify and research challenges within and beyond computing.

The Ph.D. in computing and information sciences is a research degree designed to produce independent scholars, cutting-edge researchers, and well-prepared educators. You will conduct both foundational and applied research to address diverse and important challenges within and beyond computing, and benefit from world-class faculty, diverse academic offerings, and modern facilities. Our graduates are poised to excel in both computing and interdisciplinary environments in academia, government, and industry.

The doctoral program in computing and information sciences highlights two of the most unique characteristics of the Golisano College for Computing and Information Sciences: its breadth of program offerings and its scholarly focus on discovering solutions to real-world problems by balancing theory and practice.

The program focuses on the theoretical and practical aspects of cyberinfrastructure as applied to specific problems across multiple domains. It is a blend of intra-disciplinary computing knowledge areas and inter-disciplinary domain areas.

Cyberinfrastructure

Cyberinfrastructure (CI) is the comprehensive integration of hardware, data, networks, and digitally-enabled sensors to provide secure, efficient, reliable, accessible, usable, and interoperable suites of software and middleware services and tools. The doctorate program plays a leadership role in CI research by providing human-centered tools for the science and engineering communities. These tools and services focus on such areas as high-performance computing, data analysis and visualization, cyber-services and virtual environments, and learning and knowledge management.

Intra-disciplinary knowledge

There are three intra-disciplinary computing knowledge areas: infrastructure, interaction, and informatics.

Infrastructure comprises aspects related to hardware, software (both system software and applications), communications technology, and their integration with computing systems through applications. The focus is on the best organization of these elements to provide optimal architectural solutions. On the hardware side, it includes system-level design (e.g., for system-on-a-chip solutions) and their building block components. On the software side it covers all aspects of systems and applications software development, including specification and design languages and standards; validation and prototyping, and multi-dimensional Quality-of-Service management; software product lines, model-driven architectures, component-based development, and domain-specific languages; and product estimation, tracking, and oversight. The communications subtopic includes sensor networks and protocols; active, wireless, mobile, configurable, and high-speed networks; and network security and privacy, quality of service, reliability, service discovery, and integration, and inter-networking across heterogeneous networks. At the system level, there are issues related to conformance and certification; system dependability, fault tolerance, verifiable adaptability, and reconfigurable systems; real-time, self-adaptive, self-organizing, autonomic systems. Some of the specialties available in this area are networks and security, digital systems and VLSI, software design and productivity, and systems software.

Interaction refers to topics related to the combined action of two or more entities (human or computational) that affect one another and work together when facilitated by technology. It encompasses several subtopics relating to how people and technology interact and interface. Several common threads weave through all of these areas, many of which rely heavily and build upon foundations in the social and behavioral sciences with an emphasis on understanding human and social/organizational phenomena. To some extent, these fields follow an engineering approach to the design of interactions in which solutions are based on rules and principles derived from research and practice but require analyses that go beyond the analytical approach. From this perspective, solutions can be measured and evaluated against goals and intended outcomes. However, while efficiency and effectiveness are often the watchwords of these fields in practice, this is also where science meets art in computing. Creative design and sensitivity to human needs and aesthetics are critical. Some of the specialties available in this area are human-computer interaction, computer-based instructional systems, and access technologies.

Informatics is the study of computational/algorithmic techniques applied to the management and understanding of data-intensive systems. It focuses on the capture, storage, processing, analysis, and interpretation of data. Topics include algorithms, complexity, and discovery informatics. Data storage and processing require investigation into tools and techniques for modeling, storage, and retrieval. Analysis and understanding require the development of tools and techniques for the symbolic modeling, simulation, and visualization of data. The increased complexity of managing vast amounts of data requires a better understanding of the fundamentals of computation. These fundamentals include complexity, theory to determine the inherent limits of computation, communication, cryptography, and the design and analysis of algorithms to obtain optimal solutions within the limits identified. Some of the specialties available in this area are core informatics, discovery informatics, and intelligent systems.

Interdisciplinary domains

The program focuses on domain-specific computing, or the interaction between computing and non-computing disciplines, in the areas of science, engineering, medicine, arts, humanities, and business. By incorporating domain-specific computing, the research conducted in this program applies computing and information science principles to the solution of problems in application domains that lie outside the scope of the traditional computing discipline. The research requirement incorporates fundamental concepts in cyberinfrastructure that are necessary for understanding the problems commonly encountered in advancing scientific discovery and product development in cross-disciplinary domains.

Active research areas

Computing

• Algorithm and theory
• Artificial intelligence and machine learning
• Communication and networking
• Computer vision and pattern recognition
• Data management and analytics
• Education research
• Game design
• Graphics and visualization
• Human-computer interaction
• Natural language processing
• Pervasive and Mobile Computing
• Programming languages
• Security and privacy
• Software engineering

Domain applications

• Accessibility and inclusion
• Biomedical computing
• Cognitive sciences
• Computational astrophysics
• Computational finance
• Geographic information system
• Imaging and image informatics
• Service sciences
• Social computing

Plan of study

The program requires a minimum of 60 credit hours beyond the baccalaureate level comprised of graduate-level course work, including seminar attendance and research credits.

Required courses

Students complete 18 credit hours of required foundation and core elective courses and 2 credit hours of teaching skills courses.

Electives

Elective courses provide foundation support for the student's dissertation research area. These courses come from cyberinfrastructure courses, domain courses, and other electives.

Dissertation and research

Students are required to conduct original research that leads to peer-reviewed publications.

Assessments

Each student must pass three assessment examinations in the following order:

• Research potential assessment: qualifying exam
  Completed after the first year, this assessment evaluates the research tasks students have worked on in their first year in the program. Passing this assessment will qualify students to continue in the doctoral program.
• Thesis proposal defense: candidacy exam
  This is an oral examination completed after the thesis proposal is written. Formal admission to candidacy will be granted after successfully passing the research potential assessment requirement and having a research proposal approved by the dissertation committee. The dissertation committee will have a minimum of four members including the student's adviser.
• Dissertation defense
  This is the final examination. The dissertation defense includes the dissertation committee and an optional external reader from outside RIT. The exam consists of a formal, oral presentation of the thesis research by the student, followed by questions from the audience.

Research

Our faculty and students conduct research to change how we live, work, and interact, focusing on both novel computing technology and how computing can support, facilitate, enable, and inspire progress in other domains.

• Artificial Intelligence
• Data Science
• HCI and Accessibility
• Software Engineering
• Security and Privacy
• Systems
• Theory