University of Michigan

What you'll study

The programme blends core engineering fundamentals with applied topics in sensing, actuation, control and intelligent systems. Early years focus on calculus, physics, linear algebra, introductory programming and foundational engineering science (mechanics, circuits, materials). In later years students study subjects such as:

• Embedded systems and microcontrollers — architecture, real‑time programming and interfacing with sensors and actuators.
• Control systems and mechatronics — classical and modern control, system identification, feedback design and implementation.
• Robotics — kinematics, dynamics, motion planning, manipulators and mobile robots.
• Sensors and perception — sensor technologies, signal conditioning, computer vision fundamentals and sensor fusion.
• Machine learning and AI for autonomy — supervised learning, probabilistic methods and perception pipelines used in autonomous systems.
• Power electronics and drives — motor control, power conversion and energy considerations for mobile and industrial systems.
• Manufacturing and industrial automation — PLCs, factory automation, robotics in production and human–robot collaboration.
• Design and project work — multidisciplinary laboratory courses and a capstone team design project that emphasises system integration, prototyping and testing.

Students choose electives to deepen knowledge in areas such as computer vision, advanced controls, artificial intelligence, autonomous vehicles, biomechanics, or industrial engineering. Laboratory work, maker spaces and team projects are integral to the curriculum to develop practical design and systems‑integration skills.

Entry requirements

Admission is through the University of Michigan College of Engineering. Typical successful applicants demonstrate strong achievement in mathematics (including calculus) and physics at high‑school level or equivalent, and solid preparation in chemistry or computer science is advantageous. The selection process considers academic record, rigor of secondary‑school programme, recommendations and personal statements that show interest in engineering and hands‑on design.

• Academic background — strong grades in STEM subjects, with coursework that includes advanced mathematics.
• Technical preparation — experience with programming, robotics clubs, electronics, engineering projects or relevant work experience strengthens an application.
• English language — international applicants must meet the university's English proficiency requirements.
• Other materials — references, a personal statement and any portfolio of projects can help demonstrate suitability for a multidisciplinary engineering programme.

Career prospects

Graduates are prepared for roles that require integration of mechanical, electrical and software systems. Typical career paths include:

• Robotics engineer or systems engineer in industrial, service or research settings.
• Controls and automation engineer for manufacturing, process industries and factory automation.
• Embedded systems or firmware engineer developing real‑time controllers for autonomous platforms.
• Perception and software engineer working on computer vision, sensor fusion and autonomy stacks.
• Product development and test engineering roles in automotive, aerospace, medical devices and consumer robotics.
• Entrepreneurship or technical roles in start‑ups building robotic products, or further study at graduate level in engineering, robotics or computer science.

Employers of graduates commonly include manufacturers, automotive and aerospace companies, automation and controls firms, technology companies focusing on autonomy and perception, as well as research labs and start‑ups.

Why study at University of Michigan

The University of Michigan offers this discipline within a top‑ranked engineering environment that emphasises interdisciplinary collaboration. Students benefit from access to specialised research groups and cross‑campus initiatives in robotics and automation, hands‑on laboratory facilities and maker spaces, and extensive opportunities for industry engagement through internships, sponsored projects and partnerships.

The curriculum is designed to balance theoretical fundamentals with experiential learning: team design courses, capstone projects and research opportunities allow students to apply classroom knowledge to real systems. Michigan’s strong alumni network and close ties with automotive, manufacturing and technology sectors provide a pathway to internships and employment across a broad range of industries.