Special Topics

Special Topics

Note: Register for the number of units based on what is stated on the syllabus for the course. You may edit units on Schedule Builder by pressing the "edit" button by units. 

Undergraduate Courses

Fall 2023

EEC 189U Quantum Mechanics For Engineers

  • CRN: 31045, Units: 4
  • Professor: Jeremy Munday
  • Date/Time: TR 10:30-11:50AM
  • 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.

Graduate EEC 289 Courses

Fall 2023

EEC 289Q - Performance Engineering of Software Systems

  • CRN: 52431, Units: 4
  • Professor John Owens
  • MW 10:00-11:20AM
  • Prerequisites: all students in course need to know C programming
  • Course Description: Hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, caching optimizations, parallel programming, and building scalable systems. The course programming language is C.


EEC 289Q Introduction to Hardware Security

  • CRN 52430, Units: 4
  • Instructor: Houman Homayoun
  • MW 12:10-1:30PM
  • Prerequisites: EEC 18 or EEC 118, or equivalent
  • 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 
    • Hands-on learning approach, via projects, homework’s, and review assignments

EEC 289Q Deep Learning Hardware

  • CRN 53174, Units: 4
  • Instructor: Avesta Sasan 
  • TR 1:40-3:00PM
  • Prerequisites: EEC 170 or equivalent
  • Course Description: This course is designed to equip students with a comprehensive understanding of the hardware aspects of machine learning. The lecture-style course will cover fundamental concepts in deep learning, hardware accelerators, hardware co-optimization, and techniques for improving hardware efficiency when executing inference on deep learning networks. Students will also assigned and conduct individual research on a given topic related to hardware for machine learning, which they will present in the form of a survey and a 20-minute lecture. By the end of the semester, students will be expected to present their research findings to the class.