Below you will find the topics for the departmental Ph.D. Qualifying Examinations.
Computational Sciences and Informatics
Computational Sciences, and Informatics includes collecting, integrating, analyzing, modeling data (including time-varying multivariate and multidimensional data); applications of statistical methods; the systematic development and application of algorithms and computing systems for analyzing data obtained through experiments; modeling scientific and engineering phenomena; database searches and instrumentation; and reasoning and machine learning techniques for intelligent systems.
Computer and Software Systems
Computer and Software Systems includes understanding the design, implementation, and verification of the software and hardware components in computing systems; understanding the process of generating and running software that realizes the performance goals of the underlying problem domain; application of theory, knowledge, and practice for effectively and efficiently building software systems that satisfy user requirements (software engineering); understanding the fundamental principles of operating systems; and understanding the design and implementation of modern computer hardware architectures.
Languages, Semantics, and Formal Methods
Languages, Semantics, and Formal Methods includes understanding the foundations of high-level programming language design, language type systems, specification and verification of language semantics; understanding mathematical concepts of formal languages; understanding techniques for mathematically specifying, verifying, and synthesizing hardware and software artifacts; and understanding basic techniques for analyzing and predicting performance properties.
Microwave, EM and Optics
Microwave, EM, and Optics includes understanding the fundamental principles of electromagnetic phenomena—as described by Maxwell’s theory—including radiation, propagation, and scattering; understanding the mathematical tools required to analyze and evaluate electromagnetic solutions to practical electrical engineering problems; application of microwave engineering, EM, and Optics to communications and sensing problems.
Networking includes understanding fundamental principles of communication networks from the underlying physical transmission of information through to middle to upper layers of the protocol stack and understanding network architectures, design, protocols, and performance issues.
Signals and Systems
Signals and Systems includes signal processing, design and implementation of digital filtering, estimation and detection theory, communication theory, information theory, and optimization theory for the transmission, reception, and extraction of information-bearing signals from noise and interference.