Electrical Engineering, BSE

Electrical engineering connects the physical world with the information world. Electrical engineers apply physics and chemistry in modern nanotechnology devices, encode and manipulate information in circuits and networks, and mathematically understand and reason with large amounts of data in real time. This makes electrical engineering one of the broadest forms of engineering, resulting in a multitude of possible careers. The societal impact of electrical engineering can be found in numerous domains, from smartphones, 5G wireless, and medical imaging to electric/driverless cars and the Internet of Things. Electrical engineering includes the engineering of electrons, magnets, photons, electro-magnetic waves, quantum states, and electro-mechanical structures. Electrically engineering systems provide communication, sensing, actuation, display, storage, conversion, control, and computation. The electrical engineering discipline includes both the design and implementation of physical realizations (devices, circuits, antennas) and the mathematical tools for optimizing the exploitation of these systems (control theory, information theory, digital logic, signal processing).

Electrical Engineering (EE) Major Requirements

37 course units are required.

Engineering
CIS 1100Introduction to Computer Programming1
ESE 1110Atoms, Bits, Circuits and Systems 11
CIS 1200Programming Languages and Techniques I1
or CIS 2400 Introduction to Computer Systems
ESE 2150Electrical Circuits and Systems1.5
ESE 2180Electronic, Photonic, and Electromechanical Devices1.5
ESE 2240Signal and Information Processing1.5
Intermediate or Advanced ESE Elective1
Intermediate ESE courses are considered 2000 level and above
Advanced ESE courses
Choose four advanced electives from the following lists:4-4.5
Circuits and Computer Engineering:
Fundamentals of Solid-State Circuits
Medical Devices Laboratory
Embedded Systems/Microcontroller Laboratory
TinyML: Tiny Machine Learning for Embedded Systems
Circuit-Level Modeling, Design, and Optimization for Digital Systems
Analog Integrated Circuits
Chips-design
Chips-measurements
Internet of Things Sensors and Systems
IoT Edge Computing
IoT Wireless, Security, & Scaling
Smart Devices
System-on-a-Chip Architecture
Hardware/Software Co-Design for Machine Learning
RFIC (Radio Frequency Integrated Circuit) Design
Power Electronics
Datacenter Architecture
High Frequency Power Electronics
Integrated Communication Systems
Nanodevices and Nanosystems:
Qubit Lab – A Hands on Introduction to Quantum Devices
Principles of Optics and Photonics
Nanofabrication of Electrical Devices
Quantum Circuits and Systems
Electromagnetic and Optics
The Physics of Solid State Energy Devices
Quantum Engineering
Nanoelectronics
Nanorobotics
Integrated Photonic Systems
Information and Decision Systems:
Stochastic Systems Analysis and Simulation
Foundations of Data Science
Fourier Analysis and Applications in Engineering, Mathematics, and the Sciences
Introduction to Networks and Protocols
Machine Learning for Time-Series Data
Linear Systems Theory
Feedback Control Design and Analysis
Introduction to Optimization Theory
Dynamical Systems for Engineering and Biological Applications
Graph Neural Networks
Estimation and Detection Theory
Digital Signal Processing
Principles of Deep Learning
Transportation Planning Methods
Advanced Transportation Seminar
Risk Analysis and Environmental Management
Modern Convex Optimization
Combinatorial Optimization
F1/10 Autonomous Racing Cars
Learning for Dynamics and Control
Model Predictive Control
Learning in Robotics
Information Theory
One of the Advanced Electives may be an Advanced ESE elective, BE 5210 or CIS 4710 or CIS 5200
Design and Project Courses 2
ESE 2900
ESE 2910
Introduction to Electrical and Systems Engineering Research Methodology
and Introduction to Electrical and Systems Engineering Research and Design
1.5
or ESE 3190 Fundamentals of Solid-State Circuits
or ESE 3360 Nanofabrication of Electrical Devices
or ESE 3500 Embedded Systems/Microcontroller Laboratory
or ESE 4210 Control For Autonomous Robots
or BE 4700 Medical Devices
ESE 4500Senior Design Project I - EE and SSE1
ESE 4510Senior Design Project II - EE and SSE1
Math and Natural Science
MATH 1400Calculus, Part I1
MATH 1410Calculus, Part II1
MATH 2400Calculus, Part III1
or ESE 2030 Linear Algebra with Applications to Engineering and AI
ESE 3010Engineering Probability1
MEAM 1100Introduction to Mechanics1
or PHYS 0140 Principles of Physics I (without laboratory)
or PHYS 0150 Principles of Physics I: Mechanics and Wave Motion
or PHYS 0170 Honors Physics I: Mechanics and Wave Motion
ESE 1120Engineering Electromagnetics (students passing the ESE E&M review module may substitute an ESE approved E&M course)1.5
CHEM 1012General Chemistry I1
or EAS 0091 Chemistry Advanced Placement/International Baccalaureate Credit (Engineering Students Only)
or BIOL 1101 Introduction to Biology A
or BIOL 1121 Introduction to Biology - The Molecular Biology of Life
Math Elective1
Math or Natural Science Elective1
Natural Science Lab (if applicable) 3.5
Professional Electives 4
Math, Science, or Engineering Electives3
Professional Elective - Select from the following:1
Math, Science, or Engineering Elective
Engineering Economics
Engineering Entrepreneurship I
Foundations of Leadership
Management of Technology
Scaling Operations in Technology Ventures: Linking Strategy and Execution
General Electives 5
EAS 2030Engineering Ethics (or equivalent)1
or LAWM 5060 ML: Technology Law
Select 4 Social Science or Humanities courses4
Select 2 Social Science or Humanities or Technology in Business & Society courses2
Total Course Units37
1

If not taken freshman year, must be replaced by another department approved engineering course.

2

If BE 4700 is taken, an additional .5 CU engineering credit is required

3

If BIOL 1121, CHEM 1012, EAS 0091, MEAM 1100 or PHYS 0140 are taken, choose one natural science lab from the list: BIOL 1124 Introductory Organismal Biology LabPHYS 0050 Physics Laboratory IMEAM 1470 Introduction to Mechanics Lab, CHEM 1101 General Chemistry Laboratory I or another department approved Natural Science lab.

4

At most, two freshman-level engineering courses may be used as a Professional Elective

5

Must include a Writing Seminar (a list of approved Writing Seminars can be found in the SEAS Undergraduate Handbook)

Concentrations 

Students may select one of six concentrations:

  • Data Science
  • Microsystems and Nanotechnology
  • Mixed-Signal and RF Integrated Circuits
  • Photonics and Quantum
  • Robotics
  • System-on-A-Chip Design

The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2024 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.