Courses, curriculum, design projects, and educational infrastructure for electronics and intelligent hardware.
Teaching is organized around increasing design responsibility: circuit and system fundamentals, microprocessor and embedded work, advanced mixed-signal topics, and open-ended capstone or graduate research. The emphasis is on making design choices explicit and carrying them through implementation, test, and explanation.
The official course descriptions below are paired with the recorded teaching history to show both the course content and the breadth of teaching experience. Offering counts summarize the available course records.
Circuit quantities and elements; Ohm's law; nodal and mesh analysis; source transformation and superposition; filters, op amps, digital logic, ADCs, sensors, actuators, simple control, and a microcontroller-embedded mechatronic project.
Signal properties; sources and basic circuit elements; Kirchhoff's laws; linearity and superposition; Thévenin and Norton equivalents; AC phasor analysis and frequency response; RL/RC transients; and RLC resonance.
Vector calculus; electrostatics and magnetostatics; field boundary conditions; Poisson and Laplace equations; electric and magnetic matter; magnetic circuits; Lorentz force; motional EMF; induction; and Maxwell's equations.
Microprocessor and bus architectures; instruction sets and pin functions; memory and I/O interfacing; interrupts; direct memory access; special processors; and multiprocessor systems, reinforced through laboratory work.
Monolithic analog signal processing; continuous active filters; MOS IC technology; operational-amplifier design; sampled-data concepts and Z transforms; switched-capacitor filters; circuit noise; and bipolar/RF integrated-circuit design.
Student teams integrate prior engineering knowledge in a major professional design project. The course requires a proposal, interim report, presentations, and a comprehensive final report; supervised projects span RF/optical blocks, converters, biomedical and wearable systems, FPGA/ASIC work, photonics, XR, and intelligent hardware.
Integrated-circuit design methodology across full-custom design, standard cells, gate arrays, and sea-of-gates in CMOS and BiCMOS, using contemporary computer-aided design tools and preparing students for project-level IC implementation.
Integrated analog signal-processing structures including CCDs, transversal and recursive filters, switched-capacitor filters, detailed CMOS op-amp design, nonideal op-amp effects on filters, and sampled-data fundamentals.
A project-based predictive-maintenance workflow for motors, pumps, compressors, and fans using open vibration and current datasets, MATLAB analytics, machine-learning fault classification, reliability analysis, two technical reports, and an industry-facing oral presentation.
A focused introduction to event-driven neural computation and its hardware implications, connecting neuron and spike representations to practical FPGA/ASIC research questions.
This consolidated course list combines regular course offerings with directed studies associated with course-based master's supervision. Course titles and descriptions link to Carleton's calendars where available.
| Code | Course | Level | Last recorded offering |
|---|---|---|---|
| EGEN 5099 | AI-Based Predictive Maintenance for Rotating Equipment | Graduate | 2025 Fall |
| ECOR 1032 | Circuits and Mechatronics | Undergraduate | 2025 Fall |
| ELEC 4707 | Analog Integrated Electronics | Undergraduate | 2025 Winter |
| ELEC 4907 | Capstone Project | Undergraduate | 2024 Fall |
| ECOR 1055 | Introduction to Engineering Disciplines I | Undergraduate | 2024 Fall |
| Directed Studies | Spiking Neural Network Building Blocks | Graduate | 2024 Fall |
| ECOR 1044 | Mechatronics | Undergraduate | 2024 Summer |
| ELEC 5804 | VLSI Design | Graduate | 2023 Fall |
| ELEC 4601 | Microprocessor Systems | Undergraduate | 2023 Fall |
| Directed Studies | Introduction to Spiking Neural Networks | Graduate | 2023 Summer |
| Directed Studies | Electrospinning Analysis | Graduate | 2019 Winter |
| Directed Studies | Analog Circuits for fNIR | Graduate | 2018 Fall |
| Directed Studies | Standard Cell Library Design | Graduate | 2017 Winter |
| Directed Studies | Binary Weighted Current Sources Digital-to-Analog Converter | Graduate | 2014 Summer |
| Directed Studies | Digital Power Management | Graduate | 2012 Fall |
| ELEC 3105 | Electromagnetic Fields | Undergraduate | 2012 Winter |
| ELEC 2501 | Circuits and Signals | Undergraduate | 2010 Fall |
| ELEC 5808 | Analog Signal Processing | Graduate | 2002 Fall |
Recent invited presentations
These presentations extend teaching beyond the classroom: one examines a transparent human-in-the-loop workflow for engineering assessment at scale; the other considers how AI is changing professional workload, responsibility, competence, and engineering judgement.
A transparent, auditable workflow for large engineering cohorts, including AI-assisted deliverables, validation, content creation, what worked, what failed, and the concerns that remain.
View presentation PDF
A profession-facing discussion of how AI changes workload, shifts liability, alters expectations of competence, and makes evidence, review, and engineering judgement more important.
View presentation PDFCourse development has included first-year engineering redevelopment, microprocessors and applied AI, integrated-circuit design, directed studies, capstone projects, and proposals for a Photonics and Optoelectronics stream. Project work connects schematic and layout, embedded systems, FPGA/ASIC design, instrumentation, and research questions.
A proposed pathway within the BEng Electrical Engineering framework, including stream courses, elective baskets, and capstone alignment.
Hands-on FPGA boards, peer support, workshops, projects, and practical support across several course contexts.
A planned experiential-learning and compute centre for GPU/Linux, AI, HPC, CAD, simulation, and local-LLM work.