This course provides an overview of the core design principles used in the holistic design of low power embedded computing systems. The topics for the course will include wireless and ambient energy harvesting, alternative energy storage technologies, low power radio design, efficient sensor data processing, and low power AI accelerators. The course will include a survey of papers from recent top-tier conferences and journals. Students will have the opportunity to design a low power embedded system for IoT, mobile health, or other HCI application and empirically evaluate its performance.

This course examines applications of Data Science in the planning and operations of decarbonized electrical power networks. The course covers (i.) basic power systems concepts for centralized and distributed electricity generation and storage (ii.) an introduction to relevant methods in geospatial data analysis and machine learning, and (iii.) trends affecting the electricity sector, with a focus on decarbonizing supplies and electrifying end-uses.

This course introduces concepts, techniques, and algorithms from artificial intelligence and machine learning, such as classification, regression, support vector machines, decision trees, and neural networks, as well as deep neural networks. The application of these techniques to solve practical problems is a focus of this course. Project assignments are used to reinforce concepts learned in lectures.

Not available at this time

Analysis and design of passive microwave devices, including resonators, filters, and ferrite devices, in various transmission-line media. Noise and noise effects in detectors, mixers, and modulators. Introduction to FET amplifier design. Prerequisite: E&C-ENG 584.

Theory and applications of modern optoelectronic components such as waveguides and optical fibers, photodetectors, light emitting diodes, and semiconductor lasers. Emphasis on the physics and operating characteristics of optoelectronic semiconductor devices. Prerequisite: E&C-ENG 344.

With lab. Semiconductor instructional processing laboratory (SIPL) and lectures. Principles and practice of modern microelectronic silicon device processing. Theory and practice of basic processing technology including photo-lithography, oxidation, diffusion, thin film deposition, ion implantation, packaging, yield, and process integration. State-of-the-art laboratory fabrication of working microelectronic devices and process simulation techniques. Prerequisite: E&C-ENG 344.

With lab. Semiconductor instructional processing laboratory (SIPL) and lectures. Principles and practice of modern microelectronic silicon device processing. Theory and practice of basic processing technology including photo-lithography, oxidation, diffusion, thin film deposition, ion implantation, packaging, yield, and process integration. State-of-the-art laboratory fabrication of working microelectronic devices and process simulation techniques. Prerequisite: E&C-ENG 344.

With lab. Semiconductor instructional processing laboratory (SIPL) and lectures. Principles and practice of modern microelectronic silicon device processing. Theory and practice of basic processing technology including photo-lithography, oxidation, diffusion, thin film deposition, ion implantation, packaging, yield, and process integration. State-of-the-art laboratory fabrication of working microelectronic devices and process simulation techniques. Prerequisite: E&C-ENG 344.

With lab. Semiconductor instructional processing laboratory (SIPL) and lectures. Principles and practice of modern microelectronic silicon device processing. Theory and practice of basic processing technology including photo-lithography, oxidation, diffusion, thin film deposition, ion implantation, packaging, yield, and process integration. State-of-the-art laboratory fabrication of working microelectronic devices and process simulation techniques. Prerequisite: E&C-ENG 344.