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Education
Our educational initiatives focus on preparing students for careers in emerging technology fields through specialized coursework, hands-on training, and research opportunities in neuromorphic computing, quantum technologies, and artificial intelligence.
Courses
Specialized courses taught by our faculty members
VLSI Digital System Design
Course Description
This course introduces Very-Large-Scale Integrated (VLSI) systems design methods; complementary Metal-Oxide Semiconductor (CMOS) technology is emphasized. VLSI Computer-Aided Design (CAD) tools and CMOS layout rules and techniques. This course covers not only the layout and the design of digital logic in VLSI/CMOS technology, but also the beyond-CMOS technology roadmap based on emerging materials and architecture. Project-oriented. For more details about the concepts covered by this course, see the syllabus in the link below. (The details and timing of the syllabus may change each semester; however, the concepts will remain the same)
Topics Covered
Prerequisites
Digital Logic Design, Electronics Fundamentals
Measurement and Automation
Course Description
This course provides an introduction to two main methods of controlling, measuring, and carrying out tasks in complex manufacturing and industrial applications. You will review the fundamentals of data acquisition and control, and you will do a series of design projects in data acquisition, logging, and real-time analysis, including but not limited to machine vision and image processing, as well as vibration, motion, and real-time control. The controlling software will be covered in this course, including LabVIEW software and CLICK PLC software.
Topics Covered
Prerequisites
ECE 3793 or instructor permission or systems course in another major. Prerequisites by topic: Laplace Transform, Differential Equations (eigenvalues, eigenvectors), Numerical Methods, Basic Systems theory (filters, sampling, transforms), Logic Gates, Basic knowledge of Signal and Systems
AI System & Hardware Acceleration
Course Description
This course provides a comprehensive introduction to machine learning systems, integrating theoretical foundations with practical engineering principles. It adopts a systems-level perspective, equipping engineers with the skills needed to design and implement efficient, real-world AI solutions. The course also delves into the cutting-edge domain of neuromorphic computing, which mimics the neural architecture of the human brain to enable high-performance, low-power computational systems. Students will collaboratively engage in learning through lectures, discussions, and presentations, gaining hands-on experience through experimental projects and hardware implementations.
Topics Covered
Project Types
Learning Outcomes
Prerequisites
ECE 5833: VLSI Digital System Design
Optical and Quantum Optical Devices and Systems
Course Description
Optical and quantum optical technologies are rapidly transforming the landscape of modern engineering, powering breakthroughs in sensing, imaging, computing, and communication. This course charts a new direction designed specifically for engineering students to bridge the gap between theory and applied optics. The course integrates theory with measurement-driven laboratory modules, empowering students to build, align, and test key optical setups and analyze system-level behavior. This course offers a new vision and direction for engineering students, equipping them with essential skills at the intersection of photonics, quantum technologies, and modern system design.
Topics Covered
Applications
Practical Skills
Prerequisites
Basic background in electromagnetic waves
Degree Programs
Academic programs available in our department
Ph.D. in Electrical and Computer Engineering
Advanced research program focusing on neuromorphic computing, quantum technologies, and AI systems.
Key Requirements:
M.S. in Electrical and Computer Engineering
Graduate program with thesis and coursework options in emerging technology fields.
Key Requirements:
B.S. in Electrical and Computer Engineering
Kickstart your research journey with hands-on projects that tackle real challenges in brain-like computing, quantum photonics, AI, and hardware design.
What You Can Expect & Learn:
Educational Resources
Tools and materials to support your learning
Resource Library Coming Soon
We're developing a comprehensive collection of educational resources, including reading materials, tutorials, software tools, and learning modules for students interested in neuromorphic computing, quantum technologies, and AI systems.