Undergraduate EEC 193 Courses
Fall 2022
EEC 189U - Quantum Mechanics for Engineers
- CRN: 52819, Units: 4
- Professor Jeremy Munday
- Day/Time: MW 12:10 PM - 1:30 PM
- Prerequisites: MAT 21B, MAT 22A, PHY 9A
- Course Description: This course aims to provide engineering students with a basic background in quantum mechanics, enabling them to understand the fundamental concepts necessary in many cutting-edge areas of research involving nanotechnology, materials science, nanoscale devices, quantum information and computation, etc. Quantum mechanics describes the fascinating and bizarre world in which we live, where particles take on wave-like behavior and measurements affect what is observed. Students will be introduced to quantum mechanical wave functions and their associated mathematics and will learn how to apply these concepts to practical problems faced by engineers and scientists studying nanoscale phenomena.
Fall 2022 - Winter 2023
EEC 193AB - Internet of Things
- CRN: 31179, Units: 6 (3 for EEC 193A, 3 for EEC 193B)
- Professor Avesta Sasan
- Date/Time: TR 10:30 AM - 11:50 AM
- Prerequisites: EEC 18 and (either EEC 110A or EEC 111)
- Course Description: This course introduces the principles, technologies, challenges, and required expertise needed for building the Internet of Things (IoT) solutions. Topics covered in this course include analog and digital sensing, interfacing sensors with microcontrollers, digital communication protocols, microcontroller choices and capabilities, gateways, fog computing, networking, cloud computing, need and challenges for cryptography and compression, security issues, and low power/energy challenges.
Winter 2023
EEC 189L - Quantum Computing
- CRN: 22446, Units: 4
- Professor: Marina Radulaski
- Date/Time: TBA
- Prerequisites: PHY 9A, MAT 021B, completed or concurrent MAT 022A (Linear Algebra), completed ENG6 (Engineering Problem Solving) or another programming course
- Course Description: Learn the principles of and get hands-on experience with quantum computing! This course is aimed at sophomore and junior students with interest in quantum computing who are familiar with the basics of linear algebra such as vector spaces and matrix manipulations. The course learning goals aim for students to:
- Understand how quantum information is represented and how it differs from classical information,
- Become familiar with the unintuitive concepts of quantum mechanics such as the superposition and entanglement,
- Become familiar with the physical implementations of quantum hardware,
- Learn to design a quantum circuit,
- Learn to program in Qiskit open-source quantum computing software development framework,
- Learn basics of quantum algorithms,
- Develop interdisciplinary communication and presentation skills.
Spring 2023
EEC 189Q Applied Machine Learning
- CRN: 62389, Units: 4
- Professor: Houman Homayoun
- Date/Time: MW 1:10-2:30PM
- Prerequisites: Statistics
- Course Description: The recent popularity gained by the field of machine learning (ML) has led to its adaptation into almost all the known applications. The applications range from smart homes, smart grids, and forex markets to military applications and autonomous drones. There exists a plethora of machine learning techniques that were introduced in the past few years, and each of these techniques fits greatly for a specific set of applications rather than a one-size-fits-all approach. In order to better determine the application of ML for a given problem, it is nontrivial to understand the current state of the art of the existing ML techniques, pros and cons, their behavior, and existing applications that have already adopted them. This introductory course to applied ML thus aims at researchers and practitioners who are familiar with their application requirements, and are interested in the application of ML techniques in their applications not only for better performance but also for ensuring that the adopted ML technique is not an overkill to the considered application. This course will provide a structured introduction and relevant background to aspiring engineers who are new to the field, while also helping to revise the background for the researchers familiar with this field. This introduction will be further used to build and introduce current and emerging ML paradigms and their applications in multiple case studies. This is NOT an intro to Python programming! You are here to learn how machine learning methods are developed and applied on data. Course objectives:
- Perform Exploratory Data Analysis (Understanding Data)
- Data Preprocessing (Data Normalization)
- Develop traditional supervised and unsupervised machine learning models
- Evaluating Models
- Applying machine learning practices to a problem domain
Graduate EEC 289 Courses
Note: Register for the number of units based on what is stated on the syllabus for the course.
Fall 2022
EEC 289U - The Fourier Transform and Its Applications in Imaging
- CRN: 52823, Units: 4
- Professor Brian Kolner
- Day/Time: TR 4:10-6:00 PM
Winter 2023
EEC 289K - Ultrafast Photonics
- CRN: 22685, Units: 4
- Professor William Putnam
- Day/Time: TR 2:10-4:00PM
- Course Description: Ultrafast lasers are rapidly finding their way into laboratories all over the world. In this course, we will explore what makes these short-pulse lasers useful for applications ranging from bio-imaging to x-ray generation. Specifically, we will cover the essentials of ultrafast photonics, including the basic science of ultrashort laser pulses, the technology to generate and manipulate these pulses, and a few of the numerous applications of ultrafast photonic systems.
EEC 289Q - Introduction to Hardware Security
- CRN: 22689, Units: 4
- Professor: Houman Homayoun
- Course Description: This course will cover topics related to the security and trust in Hardware related to both ASIC and
FPGA. Topics discussed in this course include: ASIC and FPGA manufacturing supply chain, discussion of threats and security challenges related to supply chain including IP Piracy, Overproduction, Counterfeiting, Trojan Insertion, Reverse Engineering, etc. This course also discusses various attacks against hardware including: Physical, invasive, destructive, Logical, and side channel attacks. The course also spans various Hardware defense solutions including metering, locking, obfuscation, watermarking, access control, Trojan testing, IP core isolation, and the theory and use of physical unclonable functions.
Spring 2023
EEC 289L - Quantum Information Technologies
- CRN: 41506, Units: 4
- Professor Marina Radulaski
- Day/Time: TR 1:10 PM - 2:30 PM
-
Course Description: This course is aimed at graduate and advanced undergraduate students with interest in quantum technologies who have a solid background in linear algebra and have encountered basic concepts of quantum mechanics and programming. The course learning goals aim for students to:
- Become familiar with the unintuitive concepts of quantum mechanics such as the superposition, entanglement, and the no-cloning theorem
- Command the basics of the Dirac notation (i.e. the mathematical formalism of quantum information)
- Learn the concepts of quantum computing, quantum communication and quantum sensing
- Understand and apply the operating principles of the most prevalent physical implementations of quantum information systems, including photonics, trapped ion and superconducting hardware
- Learn to program in Qiskit open-source quantum computing software development framework
- Develop interdisciplinary communication and presentation skills
EEC 289L - Solid-State Devices and Physical Electronics
- CRN: 62399, Units: 4
- Professor Jerry Woodall
- Day/Time: MW: 6:10-7:30PM
- Course Description: The purpose and goals of this course are to provide a detailed knowledge of all aspects of compound semiconductor materials and devices. The students who are enrolled in the course will teach the course. The goal of this method is to give each and every student the practice and experience of both learning and teaching a course and improving public speaking skills, and skills in organizing lectures
EEC 289Q - Introduction to Hardware Security
- CRN: 41509, Units: 4
- Professor Avesta Sasan
- Date/Time: TR 2:10-3:30PM
- Course Description: This course will cover topics related to hardware security including: Cryptographic processing and the analysis of its overhead, physical attacks, side-channel attacks and counter measures, physically unclonable functions, hardware-based random number generators, watermarking of Intellectual Property (IP) blocks, FPGA security, PCB security, passive and active metering for prevention of piracy, and access control. Background on digital design is needed. Introductory lectures will cover basic background on cryptography, authentication, secret sharing, and VLSI design. The main goals for this course are: learning the state-of-the-art security methods and primitives; integration of security as a design metric, not as an afterthought; better understanding of attacks and providing countermeasures against them; and hands-on learning approach, via projects, homework’s, and review assignments.