Bachelor of Science in Cyber-Physical Systems Engineering
Program Overview
Introduction to Cyber-Physical Systems Engineering
The University of Maryland offers a Bachelor of Science in Cyber-Physical Systems Engineering (CPSE), a program designed to train future engineers in both hardware and software design, with specializations in networks, cybersecurity, and machine learning.
Program Overview
The CPSE curriculum is cohort-based and designed to be completed in two years at the Biomedical Sciences and Engineering Building (BSE) at the Universities of Shady Grove campus in Rockville, MD. During their junior year, students focus on foundational knowledge to prepare them for advanced-level topics in their senior year.
Accreditation
The Bachelor of Science in Cyber-Physical Systems Engineering degree program at the University of Maryland is accredited by the Engineering Accreditation Commission of ABET, under the General Criteria. This accreditation makes it the first undergraduate program in the United States to receive ABET accreditation for CPSE.
Program Educational Objectives (PEO's)
The program education objective of this program is to produce a well-trained workforce in the emerging technologies of the internet of things. The Bachelor of Science in Cyber-Physical Systems Engineering will produce engineering graduates who:
- Use their hardware and software engineering design training and problem-solving skills to contribute professionally in an industrial, research, and applications environment; or pursue graduate education.
- Demonstrate initiative, leadership, teamwork, and continued professional development;
- Demonstrate understanding of the impact of their professional activities on society.
Student Learning Outcomes
The program aims to produce graduates with the following skills:
- An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
- An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
- An ability to communicate effectively with a range of audiences.
- An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
- An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
- An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
- An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
Tracks
The program offers four tracks:
- General Track
- Hardware Track
- Computational Track
- Security Track
Included Foundational Topics
The program covers the following foundational topics:
- Analog Circuitry
- Discrete Mathematics
- Computer Organization
- Networks & Protocols
- Microelectronics
- Introduction to Internet of Things
- Coding Languages: C, Python, Java & Verilog
Included Advanced Topics
The program also covers the following advanced topics:
- Firmware Development
- Real-time Operating Systems
- Network & Hardware Security
- Embedded Systems-focused Machine Learning
- Individualized Year-Long Capstone Design Project
Course Requirements
The CPSE major requires a total of 62 credits, with 60 credits completed prior to enrollment in the CPSE program. Students will take the program required courses in their junior and senior years, in addition to general elective coursework in the second semester of their senior year.
Sample Four Semester Plan Course Descriptions
The following courses are part of the sample four-semester plan:
- ENEB302: Analog Circuits
- ENEB304: Microelectronics and Sensors
- ENEB340: Intermediate Programming Concepts and Applications for Embedded Systems (C/C++)
- ENEB341: Introduction to Internet of Things
- ENEB344: Digital Logic Design for Embedded Systems
- ENEB345: Probability and Statistical Inference
- ENEB346: Linear Algebra for Machine Learning Applications
- ENEB353: Computer Organization for Embedded Systems
- ENEB354: Discrete Mathematics for Information Technology
- ENEB355: Algorithms in Python
- ENEB408A: Capstone Design Lab I
- ENEB408B: Capstone Design Lab II
- ENEB444: Operating Systems for Embedded Systems
- ENEB454: Embedded Systems
- ENGL393: Technical Writing
Elective Courses
The following elective courses are available:
- ENEB352: Introduction to Networks and Protocols
- ENEB443: Hardware/Software Security for Embedded Systems
- ENEB451: Network Security
- ENEB452: Advanced Software for Connected Embedded Systems
- ENEB453: Web-Based Application Development
- ENEB455: Advanced FPGA Systems Design Using Verilog for Embedded Systems
- ENEB456: Machine Learning Tools
- ENEB457: Foundations of Databases for Web Applications
First-year CPSE Retention, Graduation Rate Average, and Current Student Enrollment
- First-year CPSE retention average over all cohorts: 88.9% (24/27 Students, 2022-Present)
- CPSE graduation rate average: 78.6% (11/14 Students, 2022-Present)
- Current Junior Cohort Enrollment: 8 Students
- Current Senior Cohort Enrollment: 12 Students
- Total CPSE Enrollment: 20 Students