ESE 1110: Atoms, Bits, Circuits and Systems

Introduction to the principles underlying electrical and systems engineering. Concepts used in designing circuits, processing signals on analog and digital devices, implementing computation on embedded systems, analyzing communication networks, and understanding complex systems will be discussed in lectures and illustrated in the laboratory. This course provides an overview of the challenges and tools that Electrical Engineers and Systems Engineers address and some of the necessary foundations for students interested in more advanced courses in ESE.

ESE 2150: Electrical Circuits and Systems

This course gives an introduction of modern electric and electronic circuits and systems. Designing, building and experimenting with electrical and electronic circuits are challenging and fun. It starts with basic electric circuit analysis techniques of linear circuits. Today mathematical analysis is used to gain insight that supports design; and more detailed and accurate representations of circuit performance are obtained using computer simulation. It continues with 1st order and 2nd order circuits in both the time and frequency domains. It discusses the frequency behavior of circuits and the use of transfer functions. It continues with introduction of non-linear elements such as diodes and MOSFET (MOS) transistors. Applications include analog and digital circuits, such as single stage amplifiers and simple logic gates. A weekly lab accompanies the course where concepts discussed in class will be illustrated by hands-on projects; students will be exposed to state-of-the-art test equipment and software tools (LabView, Spice).

ESE 2180: Electronic, Photonic, & Electromechanical Devices

This first course in electronic, photonic and electromechanical devices introduces students to the design, physics and operation of physical devices found in today’s applications. The course describes semiconductor electronic and optoelectronic devices, including light-emitting diodes, photodetectors, photovoltaics, transistors and memory; optical and electromagnetic devices, such as waveguides, fibers, transmission lines, antennas, gratings, and imaging devices; and electromechanical actuators, sensors, transducers, machines and systems.

ESE 2920: Invention Studio

This is a project-centric course for ESE majors to engage in circuit layout and prototype design skills. Students will work in teams to develop printed circuit boards usinga industry standard tools like Altium and learn mechanical prototyping skills using Solidworks . Emphasis will be on developing sound printed circuit board layout practices using circuitry knowledge that they acquire in ESE 2150 and ESE 3700. A module on using Cypress PSoC will introduce students to recent developments in analog/digital co-design.

ESE 3400: Medical Devices Laboratory

With the demand for personalized medicine and health care, the need for consumer medical devices has risen. Traditionally devices have been designed from the ground up, but with more standardized components and software tools devices can be built to fulfill this need. This course will introduce design of medical devices. Students will learn the basics of sensors, signal conditioning, data acquisition and analysis, biopotential, biopotential electrodes, biomedical instrumentation, examples of biological signal measurement and electronics safety. This will be a lab based inquiry into medical device design. Prerequisites: Some exposure to circuit/electronics; Calculus and familiarity with signals.

ESE 4210: Control For Autonomous Robots

This course introduces the hardware, software and control technology used in autonomous ground vehicles, commonly called “self-driving cars.” The weekly laboratory sessions focus on development of a small-scale autonomous car, incrementally enhancing the sensors, software, and control algorithms to culminate in a demonstration in a realistic outdoor operating environment. Students will learn basic physics and modeling; controls design and analysis in Matlab and Simulink; software implementation in C and Python; sensor systems and filtering methods for IMUs, GPS, and computer vision systems; and path planning from fixed map data. Prerequisite: If course requirement not met, permission of instructor required.

ESE 4500: Senior Design

This is the first of a two-semester sequence in electrical and systems engineering senior design. Student work will focus on project/team definition, systems analysis, identification alternative design strategies and determination (experimental or by simulation) or specifications necessary for a detailed design. Project definition is focused on defining a product prototype that provides specific value to a least one identified user group. Students will receive guidance on preparing professional written and oral presentations. Each project team will submit a project proposal and two written project reports that include coherent technical presentations, block diagrams and other illustrations appropriate to the project. Each student will deliver two formal Powerpoint presentations to an audience comprised of peers, instructors and project advisors. During the semester there will be periodic individual-team project reviews. Prerequisite: Senior Standing or permission of the instructor.

ESE 5160: IoT Edge Computing

This course was developed to bring lessons learned from the product design industry into the classroom – specifically focusing on Internet of Things (IoT) device development and deployment. To achieve the highest level of knowledge transfer, the course will incorporate device design theory with discussions of real-world product failures and successes – as well as a heavy hands-on component to build a device from end to end. Students will learn to use industry standard tools, such as Altium, Atmel Studio, and IBM Watson – allowing them the same level of power and customization at the disposable of startups and Fortune 500 companies alike. Prerequisite: If course requirement not met, permission of instructor required.

ESE 5190: Smart Devices

An embedded system is the product of a marriage between hardware and software. Embedded systems have grown to be ubiquitous in the modern world – from simple temperature controlled kettles to intricate smart watches with a plethora of functions squeezed into one small package to complex rovers for space exploration. This course introduces the theory and practice of developing embedded systems through exploration of modern microcontroller architectures and culminates in a final project where students have the opportunity to synthesize and apply their knowledge in a project of their own design. Previous programming experience (Preferably C); Some exposure to circuit/electronics; Undergraduates who have taken ESE 3500 are not permitted to take this course.

ESE 6710: High Frequency Power Electronics

Miniaturization remains a challenge in power electronic systems for energy applications, whose overall goal is to increase energy efficiency and reduce waste. In this course, we will study the design of resonant converters that can operate at higher frequencies than their hard-switched counterparts and achieve higher control bandwidth and power density. We will explore practical design issues and trade-offs in selecting converter topologies in high-performance applications. We will also discuss the design and modeling of high-frequency magnetic elements, gate drives, and resonant snubbers. Students should have taken a power electronics class like ESE 5800 or equivalent.

ESE 1120: Engineering Electromagnetics

This course covers basic topics in engineering electromagnetics, namely, electric charge, electric field, electric energy, conductors, insulators, dielectric materials, capacitors, electric current, magnetic field, inductors, Faraday’s law of induction, alternating current (AC), impedance, Maxwell’s equations, electromagnetic and optical wave propagation, with emphasis on engineering issues. Relevant engineering topics are emphasized in our lectures in order to prepare students for other courses in ESE that rely on the contents on this course. Several laboratory experiments accompany the course to provide hands-on experience on some of the topics in the lecture and prepare students for the capstone project. Pre-requisites MATH 1400 and PHYS 0150. It is recommended but not required that MATH 1410 be taken concurrently.

ESE 1500: Digital Audio Basics

Primer on digital audio. Overview of signal processing, sampling, compression, human psychoacoustics, MP3, intellectual property, hardware and software platform components, and networking (i.e., the basic technical underpinnings of modern MP3 players and cell phones). Prior programming experience (CIS 1100ENGR 1050) is sufficient for enrolling in this course.

ESE 1900: Silicon Garage

Project-centric learning course for non-ESE majors on microprocessor control of physical systems using open-source hardware and software platforms. Students will work in teams to develop software controlled systems based on the Arduino and Raspberry-Pi that interface with the real world (sensors, actuators, motors) and each other (networking). Prerequisite: High School Physics and Math.

ESE 3190: Fundamentals of Solid-State Circuits

Analysis and design of basic active circuits involving semiconductor devices including diodes and bipolar transistors. Single stage, differential, multi-stage, and operational amplifiers will be discussed including their high frequency response. Wave shaping circuits, filters, feedback, stability, and power amplifiers will also be covered. A weekly three-hour laboratory will illustrate concepts and circuits discussed in the class.

ESE 3500: Embedded Systems/Microcontroller Laboratory

An introduction to interfacing real-world sensors and actuators to embedded microprocessor systems. Concepts needed for building electronic systems for real-time operation and user interaction, such as digital input/outputs, interrupt service routines, serial communications, and analog-to-digital conversion will be covered. The course will conclude with a final project where student-designed projects are featured in presentations and demonstrations. Prerequisite: Prior programming experience in any language.

ESE 3600: TinyML: Tiny Machine Learning for Embedded Systems

Tiny Machine Learning for Embedded Systems is a cutting-edge field that brings the transformative power of machine learning (ML) to the performance-constrained and power-constrained domain of embedded systems to develop useful and exciting Internet of Things solutions. This is an introductory course at the intersection of Machine Learning (ML) and Embedded Internet of Things (IoT) Devices which covers machine learning applications and algorithms using embedded hardware, sensors, actuators and software. Embedding machine learning in a device at the extreme end point – right at the data source – is fundamentally different from general data-center style machine learning. Embedded ML is all about real-time processing of time-series data that comes directly from sensors. By the end of this course, students will collect and preprocess data to build a dataset, design a model, train a model, evaluate and optimize the pipeline, convert the model to run on hardware, deploy the model on a microcontroller, make inference and roll out applications. This will enable future applications development across medical devices, home appliances, industrial automation, wild-life conservation, smart agriculture and many more. Prerequisites: Basic knowledge of programming (CIS1100 or equivalent) and basic knowledge of Python and basic knowledge of electronics and circuits. We provide the background, tools and assignments for machine learning and embedded systems using TensorFlow, Google Colab, and ARM Cortex32 hardware platforms.

ESE 3700: Circuit-Level Modeling, Design, and Optimization for Digital Systems

Circuit-level design and modeling of gates, storage, and interconnect. Emphasis on understanding physical aspects which drive energy, delay, area, and noise in digital circuits. Impact of physical effects on design and achievable performance.

ESE 4510: Senior Design Project II – EE and SSE

This is the second of a two term sequence in electrical and systems engineering senior design. Student work will focus on completing the product prototype design undertaken in ESE 450 and successfully implementing the said product prototype. Success will be verified using experimental and/or simulation methods appropriate to the project that test the degree to which the project objectives are achieved. Each project team will prepare a poster to support a final project presentation and demonstration to peers, faculty and external judges. The course will conclude with the submission of a final project written team report. During the semester there will be periodic project reviews with individual teams.

ESE 5050: Feedback Control Design and Analysis

Basic methods for analysis and design of feedback control in systems. Applications to practical systems. Methods presented include time response analysis, frequency response analysis, root locus, Nyquist and Bode plots, and the state-space approach.

ESE 5150: Internet of Things Sensors and Systems

The course is designed to introduce sensors and their networks and systems that are increasingly pervasive and form the physical device layer of the Internet of Things. Sensors transduce input signals into measured outputs within and between chemical, thermal, mechanical, optical, electrical, and magnetic domains. The course will describe the physical principles of operation, the characteristics, and the figures of merit of different sensors and their integration in networks and systems, highlighting common electronic interfaces that are used. The sensors and systems will be described as case studies to show how these devices are used to monitor and regulate processes in applications in agriculture, the environment, the home, manufacturing, health, transportation, and human activity. The course is structured with a combination of lectures, in-class and at-home labs, and research paper reading/in-class discussion.

ESE 5800: Power Electronics

Addressing today’s energy and environmental challenges requires efficient energy conversion techniques. This course will discuss the circuits that efficiently convert ac power to dc power, dc power from one voltage level to another, and dc power to ac power. The lecture will discuss the components used in these circuits (e.g., transistors, diodes, capacitors, inductors) in detail to highlight their behavior in a practical implementation. In addition, the class will have lab sessions where students will obtain hands-on experience with power electronic circuits. Students should have taken an introductory circuits course like ESE 2150 or equivalent.

ESE 6150: F1/10 Autonomous Racing Cars

This hands-on, lab-centered course is for senior undergraduates and graduate students interested in the fields of artificial perception, motion planning, control theory, and applied machine learning. It is also for students interested in the burgeoning field of autonomous driving. This course introduces the students to the hardware, software and algorithms involved in building and racing an autonomous race car. Every week, students take two lectures and complete an extensive hands-on lab. By Week 6, the students will have built, programmed and driven a 1/10th scale autonomous race car. By Week 10, the students will have learned fundamental principles in perception, planning and control and will race using map-based approaches. In the last 6 weeks, they develop and implement advanced racing strategies, computer vision and machine learning algorithms that will give their team the edge in the race that concludes the course. Prerequisites: C++ and Python programming, Matrix algebra, Differential equations, Signals and Systems.