Students within the Preston M. Green Department of Electrical & Systems Engineering graduate with the knowledge and skills to pursue a professional career or advanced degrees in fields that rely on key electrical engineering and systems principles and practices.

We offer four bachelor's degree options, including two professional degree programs, which are accredited by the Engineering Accreditation Commission of ABET:

We also offer applied science degrees, which prepare students for fields that benefit from an in-depth knowledge of electrical and systems engineering:

Learn to think like an engineer

As a first-year student, you'll be required to take ESE 105: Introduction to Electrical & Systems Engineering. From day one, you'll learn what it means to be an electrical or systems engineer, and how to use mathematics in a depth and manner you may have never seen before.

Once you learn to use math as a language to communicate ideas about electrical and other types of systems, you'll have a powerful tool to design those systems to solve society’s biggest challenges.

Curriculum & Electives

The Department of Electrical & Systems Engineering offers courses across a broad range of topic areas. Suggested example courses within several areas are listed below. To ensure courses fulfill the requirements for your degree or program, consult the Bulletin.

For planning your degree, review the Curriculum Flowchart, which maps degree requirements for our BS degrees in Electrical Engineering and Systems Science and Engineering.

Devices and Circuits
  • ESE 431: Introduction to Quantum Electronics
  • ESE 436: Semiconductor Devices
  • ESE 461:Design Automation for Integrated Circuit Systems
  • ESE 562: Analog Integrated Circuits
  • ESE/CSE 362: Computer Architecture
  • ESE/CSE 462: Computer Systems Design
Optics and Photonics
  • ESE 429: Basic Principles of Quantum Optics and Quantum Information
  • ESE 438: Applied Optics
  • ESE 531: Nano and Micro Photonics
  • ESE 582: Fundamentals and Applications of Modern Optical Imaging
Quantum Engineering
  • ESE 429: Quantum Optics and Quantum Information
  • ESE 431: Introduction to Quantum Electronics
  • ESE 439: Introduction to Quantum Communications
  • ESE 532: Introduction to Nano-Photonic Devices
  • ESE 536: Introduction to Quantum Optics
Imaging/Signal Processing
  • ESE 417: Introduction to Machine Learning and Pattern Recognition
  • ESE 471: Communications Theory and Systems
  • ESE 482: Digital Signal Processing
  • ESE 488: Signals and Communication Laboratory
  • ESE 520: Probability and Stochastic Processes
  • ESE 582: Fundamentals and Applications of Modern Optical Imaging
  • ESE 589: Biological Imaging Technology
Control, Cyber-physical Systems (CPS) and Internet of Things (IoT)
  • ESE 444: Sensor and Actuators
  • ESE 446: Robotics: Dynamics and Control
  • ESE 471: Communications Theory and Systems
  • ESE 551: Linear Dynamic Systems I
  • Math 429: Linear Algebra
Dynamics and Data
  • ESE 415: Optimization
  • ESE 482: Digital Signal Processing
  • ESE 520: Probability and Stochastic Processes
  • Math 429: Linear
Optimization and Theory of Learning
  • ESE 404: Applied Operations Research
  • ESE 415: Optimization
  • ESE 417: Introduction to Machine Learning and Pattern Recognition
  • ESE 519: Convex Optimization
  • Math 429: Linear Algebra

Suggested courses from the Physics department are listed below, suitable as Engineering and Science Breadth requirement for Electrical Engineering students and Outside Concentration courses for Systems Science & Engineering students.

Suggested Physics Courses
  • Physics 361: Optics and Wave Physics Laboratory
  • Physics 322: Physical Measurement Laboratory
  • Physics 350: Physics of the Brain
  • Physics 354: Physics of Vision
  • Physics 360: Biophysics Laboratory
  • Physics 427: Introduction to Computational Physics
  • Physics 472: Solid State Physics