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).

For more information: https://www.seas.upenn.edu/prospective-students/undergrad/majors/electrical-engineering/

Electrical Engineering (EE) Major Requirements

Engineering
CIS 1100Introduction to Computer Programming 11
ESE 1110Atoms, Bits, Circuits and Systems 21
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:
ESE 3190
Fundamentals of Solid-State Circuits
ESE 3400
Medical Devices Laboratory
ESE 3500
Embedded Systems/Microcontroller Laboratory
ESE 3600
TinyML: Tiny Machine Learning for Embedded Systems
ESE 3700
Circuit-Level Modeling, Design, and Optimization for Digital Systems
ESE 4190/5720
Analog Integrated Circuits
ESE 4730/5730
Chips-design
ESE 4750/5750
Chips-measurements
ESE 5150
Internet of Things Sensors and Systems
ESE 5160
IoT Edge Computing
ESE 5180
IoT Wireless, Security, & Scaling
ESE 5190
Smart Devices
ESE 5320
System-on-a-Chip Architecture
ESE 5370
Hardware Security
ESE 5390
Hardware/Software Co-Design for Machine Learning
ESE 5700
Digital Integrated Circuits and VLSI-Fundamentals
ESE 5780
RFIC (Radio Frequency Integrated Circuit) Design
ESE 5800
Power Electronics
ESE 6650
Datacenter Architecture
ESE 6710
High Frequency Power Electronics
ESE 6720
Integrated Communication Systems
Nanodevices and Nanosystems:
ESE 3200
Qubit Lab – A Hands on Introduction to Quantum Devices
ESE 3300
Principles of Optics and Photonics
ESE 3360
Nanofabrication of Electrical Devices
ESE 5090
Quantum Circuits and Systems
ESE 5100
Electromagnetic and Optics
ESE 5210
The Physics of Solid State Energy Devices
ESE 5230
Quantum Engineering
ESE 5290
Introduction to Micro- and Nano-electromechanical Technologies
ESE 5360
Nanofabrication and Nanocharacterization
ESE 6210
Nanoelectronics
ESE 6250
Nanorobotics
ESE 6730
Integrated Photonic Systems
Information and Decision Systems:
ESE 3030
Stochastic Systems Analysis and Simulation
ESE 3040
Introduction to Optimization
ESE 3050
Foundations of Data Science
ESE 3060
Deep Learning: A Hands-on Introduction
ESE 3250
Fourier Analysis and Applications in Engineering, Mathematics, and the Sciences
ESE 4040
Engineering Markets
ESE 4070/5070
Introduction to Networks and Protocols
ESE 4380/5380
Machine Learning for Time-Series Data
ESE 5000
Linear Systems Theory
ESE 5050
Feedback Control Design and Analysis
ESE 5060
Introduction to Optimization Theory
ESE 5120
Dynamical Systems for Engineering and Biological Applications
ESE 5140
Graph Neural Networks
ESE 5280
Estimation and Detection Theory
ESE 5310
Digital Signal Processing
ESE 5460
Principles of Deep Learning
ESE 5480
Transportation Planning Methods
ESE 5500
Advanced Transportation Seminar
ESE 6050
Modern Convex Optimization
ESE 6060
Combinatorial Optimization
ESE 6150
F1/10 Autonomous Racing Cars
ESE 6180
Learning for Dynamics and Control
ESE 6190
Model Predictive Control
ESE 6500
Learning in Robotics
ESE 6740
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 3
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 Probability 41
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) 5.5
Professional Electives 6
Math, Science, or Engineering Electives3
Professional Elective - Select from the following:1
Math, Science, or Engineering Elective
ESE 4000
Engineering Economics
EAS 5450
Engineering Entrepreneurship I
EAS 5950
Foundations of Leadership
MGMT 2370
Management of Technology
OIDD 2360
Scaling Operations in Technology Ventures: Linking Strategy and Execution
General Electives 7
LAWM 5060ML: Technology Law 81
or EAS 2030 Engineering Ethics
Select 4 Social Science or Humanities courses4
Select 2 Social Science or Humanities or Technology in Business & Society courses2
Total Course Units37
1

Only the Python section of CIS 1100 will count for the degree.

2

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

3

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

4

ESE 3010 is a requirement of the program. STAT 4300 cannot be taken in its place or in addition to ESE 3010.

5

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 Lab, PHYS 0050 Physics Laboratory I, MEAM 1470 Introduction to Mechanics Lab, CHEM 1101 General Chemistry Laboratory I or another department approved Natural Science lab.

6

At most, two freshman-level (1000-level) engineering courses may be used as a Professional Elective.

7

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

8

Only the "Technology Law and Ethics" section satisfies the Engineering Ethics requirement.

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 2025 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.