Teaching

This is a graduate-level course that introduces digital image processing. It focuses on the theory and algorithms underlying a range of tasks including acquisition and formation, enhancement, segmentation, and representation. It covers both classical Two-dimensional systems theory, image perception, sampling and quantization, transform theory and applications, as well as the latest deep-learning based approaches on enhancement, image analysis, and image processing systems

  • Cybersecurity (Undergraduate/Graduate) – Sp’14, Sp’15, Sp’16, Sp’17, F’18 [Sample Syllabus]

This is an undergraduate/graduate-level course that provides an up-to-date survey of developments in cyber-security through study of the theoretical foundation and hands-on practical implementation with DeterLab. Topics covered will include basic security technology, cryptography, security management, risk assessment, operations and physical security, software and network security, as well as ethical and legal issues.

  • Senior Capstone Design (Undergraduate) – F’15, Sp’16, F’16, Sp’17, F’17, Sp’18, F’18 [Sample Syllabus]

This is a two-semester intense design sequence for senior students in electrical engineering. Topics important in product design and manufacturing are emphasized, including considerations of economics, safety, and communication. Students are expected to formally propose, build, and validate a design project that involves customer exploration, requirements, specification, design, testing and demonstration. Students work in teams to develop and complete the designs.

  • Computer and Switching Networks (Undergraduate/Graduate) – F’08, F’09, F’10, F’12, F’13, F’14, F’15, F’16 [Sample Syllabus]

This course is an introductory course of the design and implementation of computer networks. The course focuses on the concepts and fundamental design principles that have contributed to the global Internet's scalability and robustness. There is a strong hands-on emphasis with projects on OPNET network simulation, packet sniffing, network programming and a final design project on Internet of Things.

  • Introduction to Electric Circuits (Undergraduate) – Sp’10, Sp’12, Sp’13, Sp’14, Sp’15, Su’15, Su’16 [Sample Syllabus]

This course is an introductory circuit course taught at UK and UM-SJTU. Topics include basic concepts of voltage and current; Kirchhoff's voltage and current laws; Ohm's law; voltage and current sources; Thevenin and Norton equivalent circuits; DC and low frequency active circuits using operational amplifiers; time- and frequency-domain analysis of RLC circuits; basic passive and active electronic filters as well as laboratory-in-a-box experience using Digilent’s Discovery Boards and MultiSim.

  • Probabilistic Graphical Model (Graduate) – F’06, F’08, F’09, F’12, F’13, F’14 [Sample Syllabus]

This is a graduate-level course that covers the fundamentals in Probabilistic Graphical Models. Major topics include various types of graphical models, junction tree algorithm, belipropagation, model selections, and non-parametric techniques. Applications in computer vision, communications, and data mining are discussed.

This is a graduate-level course on random processes, which builds on a first-level (undergraduate) course on probability theory. It provides a measure-theoretic introduction of probability theory and random processes, and also discusses applications to communications, signal processing and control systems engineering.

This course is primary for master and PhD students to survey the state-of-the-art key technologies behind the new field of Intelligent Video Surveillance, including background subtraction, crowd and traffic analysis, object tracking, activities and event detection, multi-camera calibration, placement and planning, as well as security and privacy. The focus is on the core mathematical concepts such as probabilistic graphical models, image features, multi-view geometry that enable these new technologies.

  • Signals and Systems II (Undergraduate) – Sp’05, F’05, F’06, F’06, Sp’07 [Sample Syllabus]

This undergraduate-level course is a continuation of the analysis of signals and linear systems with an emphasis on feedback and discrete-time systems. Topics include the Laplace and Z-transforms, state-variable, discrete-time signal and system, analysis and design of digital filters, discrete and fast Fourier Transform.

This undergraduate-level core course provides an introduction to some of the essential modeling and analysis tools used by practicing engineers. The concepts covered include discrete and continuous LTI systems, convolution, Fourier series and transforms, Laplace transforms, modulation and bandwidth concepts.

This graduate-level course introduces important technologies and standards in building Multimedia Information Systems (MIS). The emphasis is on using signal processing and pattern recognition techniques for representing, coding, search, visualizing and protecting multimedia information.