This post outlines the requirements and structures for three primary graduate programs in the ECE Department during the 2026-2027 academic year:
1. Master of Science in Robotics Engineering (MS ERE)
2. Master of Science in Electrical and Computer Engineering (MS EECE)
3. PhD in Electrical and Computer Engineering (PhD ECE)
Program Comparison Summary
| Feature | MS Robotics (MS ERE) | MS ECE (MS EECE) | PhD ECE (with MS) | PhD ECE (Direct/no MS) |
| Total Credits | 30 | 30 | 30 | 60 |
| EE Course Credits MIN |
Core required courses Coursework – 15-18 Report – 15 Thesis – 15 Elective courses Coursework 12 Report 6-13 Thesis 2-9 |
Coursework – 15 Report – 12 Thesis – 10 |
9-12 | 21 |
| 3000-level Courses | Not permitted | Not permitted | Not permitted | Not permitted |
| 4000-level MAX |
Coursework – 12 Report – 12 Thesis – 9 |
Coursework – 12 Report – 12 Thesis – 9 |
Not permitted | 9 credits |
| Max Co-op Credits | 3 credits (UN 5000-5003) | 3 credits (UN 5000-5003) | Not permitted | 3 credits (UN 5000-5003) |
| RCR Requirement | 1-3 credits (Report/Thesis) | 1-3 credits (Report/Thesis) | 1-3 credits | 1-3 credits |
| Typical Duration | 1.5 – 2 Years | 1.5 – 2 Years | 3 – 5 Years | 4 – 6 Years |
Academic Flexibility & Course Load
Unlike undergraduate degree programs, graduate degrees are more flexible, allowing students to tailor their plan of study to their specific goals and interests. A Master of Science student may select courses of their choosing, provided they conform to the degree requirements. The standard course load for a graduate student is nine (9) credits per semester. Please contact the ECE Graduate Program Director to schedule an advising session.
Online Course Registration Guidelines
Specific regulations govern online enrollment for on-campus graduate students:
Dual-Delivery Courses (+OL): Online sections of courses offered concurrently with on-campus sections are unavailable to on-campus students.
CPT Exception: On-campus students participating in Curricular Practical Training (CPT) are permitted to enroll in these online course sections.
Exclusively Online Courses: Graduate courses that are offered only in an online format (without an equivalent on-campus section) are open to on-campus students.
Spring 2027 Graduate Course Recommendations & Class Descriptions
To assist with academic planning and elective registration, the active graduate-level courses offered in Spring 2027 are listed below. Courses covering multi-disciplinary domains are cross-listed in all applicable technical areas. The indicator (+OL) identifies courses that offer online enrollment options.
1. Power & Energy
Focus: Power transmission, conversion, machines, and smart-grid integration.
EE 4219 – Intro to Elec Mach & Drives (+OL)
Covers how electric machines can be used to drive loads with control of speed, torque and position. Topics include basic electro-mechanics, rotating machinery, dc machines, ac machines, power electronics and load modeling.
EE4220 – Intro to Elec Mach & Drives Lab
Provides a hands on understanding of how electric machines can be used to drive loads with control of speed, torque, and position.
EE 4222 – Power System Analysis 2 (+OL)
Topics covered include symmetrical components; symmetrical faults; unbalanced faults; generating the bus impedance matrix and using it in fault studies; power system protection; power system operation; power system stability.
EE 4226 – Power Engineering Lab
A laboratory based course highlighting single phase and three phase power concepts, including: power factor, single and three phase transformer configurations, non-ideal transformers, synchronous machines, renewable energy, power flow and fault simulations, relay settings and relay testing and calibration.
EE 5223 – Power System Protection (+OL)
Real-time monitoring and protection of modern power systems. Secure and reliable operation of radial and grid systems. Protection of transmission lines, buses, generators, motors, transformers, and other equipment against disturbances.
EE 5224 – Power System Protection Lab (+OL)
Theory-based application of software and hardware used for power system protection. Fault simulations, protective relay settings and coordination, and test operation of relays under static, dynamic, and transient conditions.
EE 5232 – Power Systems Optimization (+OL)
Linear, non-linear, and integer programming, simplex method, branch and bound, steepest descent method, convex, stochastic, and distributed optimization, interior-point method, evolutionary algorithm, optimal power flow, unit commitment, vot/var optimization, state estimation, feeder reconfiguration.
EE5240 – Computer Model of Power System (+OL)
Topics include modeling and computer methods applied to electrical power systems, matrix formulations, network topology and sparse matrix data structures, load flow, short- circuit and stability formulations, constrained optimization methods for load flow and state estimation, and time-domain simulation methods for transient analysis.
2. Signals & Systems
Focus: Processing, analysis, systems modeling, and communications engineering.
EE 4250 – Modern Communication Systems
Introduces the mathematical theory of communication science. Topics include baseband and digital signaling, bandpass signaling, AM and FM systems, bandpass digital systems, and case studies of communication systems.
3. ElectroPhysics
Focus: Physical systems, devices, electromagnetic fields, and semiconductor material processing.
EE 4232 – Electronic Applications
Study of electronic circuits under small- and large-signal conditions. Typical topics include analysis and design of power and RF amplifiers, feedback circuits, oscillators, timing circuits, and wave-shaping circuits.
EE 4331/ EE 5331 – Chip Packaging
This course provides an introduction to the science and engineering involved in semiconductor device packaging technologies associated with microelectronic chips through lecture and laboratory exercises.
EE 4800/ EE5900 – Photonic Quantum Comp. & Info
Quantum mechanics, physical and mathematical foundations of photonic quantum computing for engineers and applied physics. Rigorous treatment of optical implementations of quantum logic gates and algorithms, quantum communications, and imaging.
EE 5900 – Advanced Electronic Applications
Covers advanced electronic circuits; includes analysis and design of power and RF amplifiers, feedback circuits, oscillators, timing circuits, and advanced wave-shaping circuits.
4. Computer Engineering
Focus: Processing hardware, algorithms, networking, and automotive computer systems.
EE 4173 – Comp Sys Engineering & Perform
Covers quantitative performance evaluation of: memory hierarchies, from cache through virtual memory; pipelined processors with advanced hazard management; and combined processor/memory systems. Introduces RAID, superscalars, parallel processing, cache coherence, performance simulation software.
EE 4272 – Computer Networks
Computer network architectures and protocols; design and implementation of datalink, network, and transport layer functions. Introduction to the Internet protocol suite (TCP, UDP, IP), domain name service and protocols, file sharing protocols, wireless networks, and network security.
EE 4723 – Network Security
Learn fundamental of cryptography and its application to network security. Understand network security threats, security services, and countermeasures. Acquire background knowledge on well known network security protocols. Address open research issues in network security.
EE 4737 – Embedded System Interfacing
Covers the use of low-power microcontrollers and hardware- dependent C for embedded sensing and control systems. Emphasizes direct interfacing with analog and digital sensors and actuators of several different modalities, to implement end-to-end embedded systems for applications including robotics and wireless sensor nets.
5. Robotics
Focus: Industrial automation, autonomous perception, intelligence algorithms, control design, and embedded architectures.
EE 4262 – Digital and Non-linear Control
Introduction to state space analysis and design (state feedback, observers, and observer feedback); digital control system design and analysis; introduction to nonlinear systems and experiments with physical systems.
EE 4533/ EE5533 – Neuromorphic Robotic Systems
This course introduces brain-inspired AI for robotics. Students explore neuromorphic AI, spiking neural networks, core neuroscience concepts, and biologically plausible learning algorithms. Key topics include applying computational brain models for robot perception and navigation with various sensors.
EE 4615/ EE 5615 AI Engineering Applications
This course introduces practical AI/ML tools for solving real engineering problems. Students learn end-to-end workflows and basic deployment using modern Python libraries. Core topics include supervised learning, unsupervised learning, and reinforcement learning. Application domains emphasize common engineering contexts.
EE 5531 – Introduction to Robotics
Introduction to autonomous systems and robotics with focus on automated ground vehicles. Project based course using distributed computing to solve problems related to motion planning, perception, and localization. Requires experience with Linux operating systems variants, version control systems, and C++ or Python.
EE 5841 – Deep Learning
Covers foundational techniques of machine learning. Topics are pulled from the areas of unsupervised and supervised learning. Specific methods covered include naive Bayes, decision trees, support vector machine (SVMs), ensemble, and clustering methods.
6. Automotive
Focus: Powertrains, hybrid architecture, electric vehicles, vehicle modeling, and dynamic system optimization.
EE 5295 – Adv Propulsion Sys for HEV (+OL)
Hybrid electric vehicles (HEV) will be studied and simulated using advanced powertrain component analysis and modeling. An in-depth analysis and study of power flows, losses, and energy usage are examined for isolated powertrain components and HEV configurations.
EE 5315 – Cyber Security Auto Sys I (OL only)
Modern automotive control and communications systems from a cyber security perspective. Topics include: V2X communications, vehicle attack surfaces and vulnerabilities, in-vehicle networks, threat analysis and vulnerabilities, security mechanisms and architectures, security requirements analysis, hardware security modules, and standards.
EE 5812 – Automotive Control Systems (+OL)
Introduction to automotive control systems for engine, transmission, cruise and headway control, active suspension systems, hybrid electric vehicles, and autonomous driving. Advanced control methodologies include linear-quadratic optimal control, model predictive control, dynamic programming, and equivalent consumption minimization strategy.