Global Arc

The course will cover topics related to electronic system design through the various layers of abstraction from devices to ICs. The emphasis will be on understanding fundamental system-design tradeoffs, related to the speed, precision, power with intuitive design methods, quantitative performance measures, and practical circuit limitations. The understanding of these fundamental concepts will prepare students for a wide range of advanced topics from circuits and systems for communication to emerging areas of sensing and biomedical electronics.

Intro to fundamentals and operations of semiconductor devices and sensors and micro/nano fabrication technologies used to make them. Devices include field-effect transistors, photodetectors and solar cells, light-emitting diodes and lasers. Applications include: computing and microchips, optical transmission of info (the internet backbone), displays and renewable energy. Students will fabricate their own devises in a clean room and test via microprobes. Special emphasis placed on the interplay between the material properties, fabrication capabilities, device performance and ultimate system performance. Prerequisites:MAT103-104 and PHY103-104.

The physics and technology of solid-state devices. Topics include: p-n junctions and two terminal devices, transistors, silicon controlled rectifiers, field effect devices, silicon vidicon and storage tubes, metal-semiconductor contacts and Schottky barrier devices, microwave devices, junction lasers, liquid crystal devices, and fabrication of integrated circuits. Three hours of lectures. Prerequisite: 308 or the equivalent.

Fundamentals of quantum mechanics and statistical mechanics needed for understanding the principles of operation of modern solid state and optoelectronic devices and quantum computers. Topics covered include Schrödinger Equation, Operator and Matrix Methods, Quantum Statistics and Distribution Functions, and Approximation Methods, with examples from solid state and materials physics and quantum electronics. Prerequisites: (PHY 103 or PHY 105) and (PHY 104 or PHY 106) or EGR 151 and EGR 153. MAT 201 and MAT 202, or EGR 152 and EGR 154.

Robotic systems are quickly becoming more capable and adaptable, entering new domains from transportation to healthcare. To operate in dynamic environments, interact with other agents, and accomplish complex tasks, these systems require sophisticated decision-making. This course delves into the core concepts and techniques underpinning modern autonomous robots, including planning under uncertainty, active perception, learning-based control, and multiagent decision-making. Lectures cover the theoretical foundations and the practical component introduces the Robot Operating System (ROS) framework through hands-on assignments with mobile robots.

This course provides the students with a broad and solid background in electromagnetics, including both statics and dynamics, as described by Maxwell's equations. Fundamental concepts of diffraction theory, Fourier optics, polarization of light, and geometrical optics will be discussed. Emphasis is on engineering principles, and applications will be discussed throughout. Examples include cavities, waveguides, antennas, fiber optic communications, and imaging. Prerequisite: PHY 103 and PHY 104 or equivalent.

Fundamental and practical aspects of physical optics. Lenses and ray optics, lens maker's formula, wave propagation, Fourier optics, Gaussian beams are all considered. Design and use of practical optical systems including optical beam steering in medicine, fiber optics. Three hours of lectures. Prerequisite: PHY 104.

An informal introduction to the physical basis of electronic and optical devices used in information processing, storage, and communications. The course provides accessible coverage of the principles of the classical theory of metals, semiconductors, and dielectrics; physical optics; introductory quantum mechanics; and the theory of radiation. The covered material lays the foundation for understanding the way transistors, micro-processors, lasers, DVDs, and many other modern devices operate.

Machine learning for predictive data analytics; information-based learning; similarity-based learning; probability-based learning; error-based learning; deep learning; evaluation.

Communication systems have become a ubiquitous part of modern life. This course introduces students to the fundamental of digital communication and wireless systems. Topics include concepts from information, compression, channel, modulation, radio propagation to principles of wireless cellular, and WiFi systems. At the end of the semester, students are expected to gain a deep understanding of the basis of wireless communication systems and the connection between theoretical concepts and real-world systems.