Time domain and frequency domain analysis and synthesis techniques for linear continuous-time feedback control systems. Topics include benefits and costs of feedback, modeling of dynamic systems,steady-state and transient performance, stability, PID control, root locus, frequency response, Nyquist stability cri-terion, and introduction to loop-shaping.

Introduction to fundamental biological neuron models, algorithms and techniques for learning spatiotemporal patterns, and software frameworks for implementing spike-based computation. Understanding of the hardware foundation for bio-inspired computation from transistors and emerging devices to neuromorphic circuits and systems. Investigation of low-power, low-latency applications of neuromorphic engineering in machine vision, robotics, autonomous vehicles, etc.

Quantitative study of pipelined processor architectures, memory hierarchy, cache memory, Input/Output, RISC processors and vector machines.

The course presents a modern approach to logic design and verification of digital circuits. Topics in logic synthesis cover high-level and architectural synthesis, decision and word-level diagrams, combinational and sequential logic optimization. Topics in verification include: simulation-based validation and functional test generation; formal verification techniques; combinational and sequential equivalence checking; and Boolean satisfiability (SAT). Prerequisite: introductory digital circuits; hardware design and organization (undergraduate level). Open to senior undergraduate students.

The field of Image Processing is concerned with the study of computational approaches for the analysis, storage, and interpretation of digital content. In modern times, Image Processing applications have expanded to include an assortment of fields ranging from medical diagnostics to remote sensing to AI. This course introduces students to basic concepts and techniques in digital image processing. Topics covered will include characterization and representation of digital images, image enhancement, image restoration, image analysis, and image segmentation.

Signal sampling and reconstruction. Z Transforms for systems analysis: transfer functions, stability. IIR and FIR digital filter design. Minimum phase, all-pass, and linear phase filters. Implementation of DT systems. Signal representations in vector spaces. Linear inverse problems. Matrix approximation using least squares. Computing solutions to linear least squares problems.

With lab. Introduction to VLSI design and custom design methodology in MOS. Topics include: MOS devices and circuits, fabrication, structures, sub-system and system design, layout, CAD techniques, and testing.

Introduces key concepts in biosensors and bioelectronics. The course starts from the basics of molecular and cellular biology, followed by discussions on important biomedical devices and system in electrical, optical, magnetic and mechanical domains. The class will focus on working principles, basic concepts, and important bio-EE applications. It has prerequisites on semiconductor devices and electronics.

This course provides an introduction to fundamental concepts in network security and data privacy. Network security topics covered include principles of cryptography, secure protocols such as TLS, and firewalls. We will also cover privacy topics including Web privacy and privacy-preserving data analytics such as differential privacy, homomorphic encryption, secure multiparty computation.

This course introduces the students to the design of embedded systems with a focus in emerging cyber-physical systems and internet of things applications such as health care, connected vehicles, and augmented/virtual reality. This course presents the unique capabilities of embedded technologies, and takes a holistic approach to design end-to-end systems. These systems span various thrusts that cut across both horizontal and vertical architectural layers.