Systems Science and Engineering, BSE

Systems Engineers provide technical management for societal-scale problems that often encompass the connections between the physical and the information world. Examples of the many cutting-edge applications include autonomous robotics, smart buildings, national power grid management, global networks, service optimization, and biological systems. Systems engineering is the set of reusable mathematics, intellectual tools, and methodologies for attacking large-scale engineering problems. These common tools are adaptable for problems in different engineering domains (e.g., electrical, mechanical, biological, chemical, and computing) and help us understand, design, and manage systems that contain elements from multiple domains. Systems engineering deals with how we extract useful, abstract models from lower level systems, use these models to analyze and predict behavior, and use the analysis to control behavior and optimize/synthesize solutions.   System engineering helps us understand what happens when we compose many elements, each with their own behavior, and how to design and constrain the individual elements to engineer desired behavior for the composed system.

Systems Science and Engineering (SSE) Major Requirements

37 course units are required.

Systems Foundations
CIS 1100Introduction to Computer Programming (or equivalent)1
or ENGR 1050 Introduction to Scientific Computing
ESE 1110Atoms, Bits, Circuits and Systems 11
CIS 1200Programming Languages and Techniques I1
ESE 2040Decision Models1
ESE 2100Introduction to Dynamic Systems1
ESE 2240Signal and Information Processing1.5
ESE 3030Stochastic Systems Analysis and Simulation1
Information Systems Electives
Select 3 from the following:3
Introduction to Computer Systems
Database and Information Systems
Artificial Intelligence Lab: Data, Systems, and Decisions
Foundations of Data Science
Fourier Analysis and Applications in Engineering, Mathematics, and the Sciences
Introduction to Networks and Protocols
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
Data Mining: Learning from Massive Datasets
Principles of Deep Learning
Modern Convex Optimization
Combinatorial Optimization
F1/10 Autonomous Racing Cars
Learning for Dynamics and Control
Model Predictive Control
Learning in Robotics
Information Theory
Scalable and Cloud Computing
Theory of Networks
Algorithmic Game Theory
Systems Project
Select one of the following:1
Introduction to Electrical and Systems Engineering Research Methodology
Deep Learning: A Hands-on Introduction
Embedded Systems/Microcontroller Laboratory
TinyML: Tiny Machine Learning for Embedded Systems
Control For Autonomous Robots
Feedback Control Design and Analysis 2
Biomechatronics 2
Medical Devices 2
ESE 4500Senior Design Project I - EE and SSE1
ESE 4510Senior Design Project II - EE and SSE1
Engineering Elective1
Engineering Elective 200 Level or above1
Math and Natural Science
MATH 1400Calculus, Part I1
MATH 1410Calculus, Part II1
MATH 2400Calculus, Part III1
ESE 3010Engineering Probability1
ESE 4020Statistics for Data Science1
or ESE 5420 Statistics for Data Science
PHYS 0140Principles of Physics I (without laboratory)1-1.5
or PHYS 0150 Principles of Physics I: Mechanics and Wave Motion
or PHYS 0170 Honors Physics I: Mechanics and Wave Motion
or MEAM 1100 Introduction to Mechanics
ESE 1120Engineering Electromagnetics1.5
or PHYS 0141 Principles of Physics II (without laboratory)
or PHYS 0151 Principles of Physics II: Electromagnetism and Radiation
or PHYS 0171 Honors Physics II: Electromagnetism and Radiation
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 3120Linear Algebra1
or MATH 3130 Computational Linear Algebra
or MATH 3140 Advanced Linear Algebra
or MATH 3700 Algebra
Natural Science Lab (if applicable) 3.5
Professional Electives
Technology Management Electives
ESE 4000Engineering Economics1
or EAS 5450 Engineering Entrepreneurship I
or EAS 5950 Foundations of Leadership
or MGMT 2370 Management of Technology
or OIDD 2360 Scaling Operations in Technology Ventures: Linking Strategy and Execution
Societal Problem Application
Select 3 Societal Problem Electives 43
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

If not taken by the end of freshman year, must be replaced by another department approved Engineering course.


If ESE 5050 or BE 5700 or ESE 3600 is taken, an additional .5 CU engineering credit is required.


This category requires 10 CU, including two .5 CU Natural Science Labs. Several of the courses above are 1.5 CU and already include .5 CU Natural Science Lab. If the courses selected do not total 10 CUs, you will be required to complete the additional CUs required with up to two .5 CU Natural Science Labs from the following list: BIOL 1124 Introductory Organismal Biology LabCHEM 1101 General Chemistry Laboratory IMEAM 1470 Introduction to Mechanics LabPHYS 0050 Physics Laboratory IPHYS 0051 Physics Laboratory II, or another department approved Natural Science Lab.


A complete list of approved SPA electives can be found on the ESE undergraduate programs webpage


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


 Students may select one of three concentrations:

  • Data Science and Artificial Intelligence
  • Decision Science
  • Robotics

The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2023 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.