Course subject: Electrical & Computer Engineering (ECE)

Fundamental optimization techniques. Modelling. Shortest path. Network flow. Matching. Set packing, covering partitioning. Branch and bound. Cutting Planes, Dynamic programming. Search Heuristics. (Students will gain valuable background in optimization techniques that are applicable to a wide range of engineering problems. They will also gain experience using a state of the art optimizer, in solving an optimization problem of their own choice using techniques discussed in the course).

Theory of random variables, vectors and processes. Conditional probabilities and expectations. Convergence of sequences of random variables. Markov chains in discrete and continuous time. Poisson processes. Basic renewal processes. Stationary random processes, correlation, and power spectra. Emphasis on problem solving using probabilistic approaches.

This is an introductory course on algorithms at the graduate level. It assumes familiarity with basic data structures such as lists, queues, trees and graphs, and emphasizes creativity in the design of algorithms, and rigorous analysis. Correctness (soundness and completeness) and efficiency (with respect to average-, best- and worst-case time and space) properties are considered in the context of algorithms for classes of problems such as optimization and decision problems. The course also gives insights into when a problem may be intractable, and how we may deal with intractability.

This biomedical engineering core course focuses on topics related to the use of quantitative tools in biomedical engineering research studies. It will teach students how to conduct statistical analysis of biomedical data, design biomedical experiments that can offer statistical insight, and apply computational methods to solve problems in biomedical engineering. Educational emphasis will be placed on developing students' core competence in biostatistics and biomedical computing, so as to prepare them to pursue biomedical engineering investigations that are backed by quantitative reasoning and numerical insights.

This course is concerned with the fundamentals of broadband communication networks including network architecture, Switch fabrics, design methodology; traffic management, connection admission control (CAC), usage parameter control (UPC), flow and congestion control; capacity and buffer allocation, service scheduling, performance measures, performance modeling and queueing analysis.

An introduction to information measures, entropy, mutual information and information divergence, noiseless codes and the noiseless coding theorem, channel capacity for discrete and continuous channels, randomly chosen code words, the noisy coding theorem, error rate exponents, computational cut-off rate and its application to digital communications.

Overview of mobile communications, characterization and modeling of wireless fading dispersive channels, optimum receiver structure, transmission performance in fading channels, diversity and performance improvement, co-channel interference, spread spectrum and multiple access, capacity analysis in cellular environments.

Organization of high performance digital computers, high speed arithmetic algorithms, control unit and data flow organization. Pipeline systems. Stack machines, associative processors, parallel processors. Performance evaluation.

Evolution of computer security. Types of security threats, hardware threats, software threats, physical threats, cryptanalysis. The theory of secure message passing. Methods of encryption, private networks, Data Encryption Standard, Public Key Cryptosystems. Secrecy and Privacy in a network environment, long haul networks, local area networks. Protocols for computer network security.

Sources and purification of materials, crystal structure, diffusion, oxidation, ion implantation, alloying expitaxy, impurity profiling methods, metallisation, photo lithography. Technologies for VLSI.

This course will cover the following topics; Basics of quantum mechanics; Quantum confinement; Boundary conditions; Schrodinger equation; Basic function; Density matrix; Energy bands; Subbands; Reciprocal lattice; Brillouin zone; Graphene and graphene nanoribbon; Transport in nanoelectronic devices.

The research in nanoscale science and technology has seen a very fast growth in the past years. The cornerstone for this exciting growth is the ability to create nanoscale patterns, which is the object of the current course. The course will cover all major nano-lithography technologies capable of generating or duplicating sub-lOOnm patterns, including lithographies based on photons, charged beams, scanning probes, replication and self-assembly. Within each lithographic technique, the students will learn its working principle, related materials and instrument, process and limit. This course is complementary to ECE 631 (Microelectronic Processing Technology), but takes fabrication and associated theory into nanoscale.

Design of CMOS digital integrated circuits at the transistor level. Related topics include MOSFET switch and 1-V models, logic gate design, transistor sizing, interconnect parasitics, gate delay, timing design, logical effort, static and dynamic logic families, arithmetic structures, latch and flip-flop elements, memory cells and arrays, and input/output circuitry. Students enrolling in this course are expected to have a background equivalent to the material covered in ECE 242, formerly ECE 332.

Growth and structure of amorphous silicon (morphology, growth mechanisms, silicon bonding structure, continuous random network, hydrogenation). Electronic states in amorphous silicon (density of states, band tails, optical transitions, defects and defect states). Doping of amorphous silicon, defect reactions and metastable effects. Electronic transport and recombination in amorphous semiconductors. Using amorphous silicon in practice (contacts and surfaces). Applications of amorphous silicon (Schottky diodes, solar cells, optical and radiation sensors, thin film transistors, flat panel displays, large-area electronics).

Formulation of equations for arbitrary circuits, active network analysis; sensitivity calculations in the frequency domain; simple integration methods for time domain solution; numerical laplace inversion for transient solution of linear lumped and distributed networks; solution of nonlinear circuits; detailed time domain solution of nonlinear networks; simulation of switched networks in time domain; introduction to switched capacitor networks; iterative simulation methods.

This is a project course, designed exclusively for MEng students completing the Nanoelectronic Circuits and Systems specialization. Students will carry out a research project over one academic term, under the direct supervision of an ECE faculty member from the associated research area. At the end of the term, a written Project Report has to be submitted, which will be evaluated and marked by the Supervisor.

Fundamentals of software requirement analysis, software development as an engineering activity, basic process models, software specifications, modularity, cohesion, coupling, encapsulation, information hiding, principles of object oriented design, software project management, quality assurance and control. Priniciples of Software Architecture: Fundamental software architecture styles, synchronous & as synchronous communication of software components. Languages for software design specification: UML (class diagrams, sequence diagrams, collaboration diagrams, state diagrams). Overview of verification and validation techniques. Maintenance, evolution and reengineering, configuration management. Software metrics, quality assurance, fundamental cost and effort prediction models. Trends in software engineering (e.g., model-driven development, agile approaches).

Introduces students to systematic testing of software systems. Software verification, reviews, metrics, quality assurance, and prediction of software reliability and availability. Students are expected to have programming experience with reading and writing code for large projects.

This course is concerned with the architecture, protocol and software aspects of mobile systems. The topics to be discussed include mobile communication and computing systems, supporting ad hoc networks, mobile network and transport layers, wireless application protocol, support for mobility, service advertisement and discovery in mobile systems, and emerging issues such as enviornment-aware software and low-power protocols and software.

Conventional approaches for tackling complex systems are usually implemented under the assumption of a good understanding of the process dynamics/functionalities and its operating environment. These techniques fail, however, to provide satisfactory results when applied to ill-defined processes (for which analytical and experimental modeling may not be easily obtained) that may operate in unpredictable and possibly noisy environment. Recent developments in the area of intelligent systems and soft computing have presented powerful alternatives for dealing with the behavior of this class of systems. This course outlines fundamentals of soft computing based design approaches using such tools as approximate reasoning, fuzzy inferencing, neural networks, evolutionary algorithms, and neuro-fuzzy systems. Fundamentals and advances on these procedures are outlined along with their potential applications to various real world applications in virtually most fields of engineering including pattern recognition, system planning, classification, power generation, intelligent transportation, systems and control, intelligent mechatronics, optimization, communication, robotics and manufacturing, to name a few.

Building large-scale and complex software systems from available parts with the goal of increasing return on investment, decreasing time to market, and assuring quality and reliability. The course covers the basic software component concepts, overview of advanced topics on software components and component-based software engineering from research and practice.

Discuss in detail the basic structure, functional characteristics and protection schemes of the main components that make up a powers system, in particular generators, transformers, transmission lines, cables, loads, HVDC and FACTS controllers. Understand the modelling and simulation of these components for detailed electromagnetic transients analyses, as well as phasor models for power flow and stability studies.

The course addresses all dimensions of Power Quality (PQ) issues including mitigation strategies. The focus is mainly on qualitative concepts and comprehensive coverage. The course introduces PQ definitions, limitations, related international standards and mathematical techniques for PQ analysis of power systems. Different identification, localization and classification techniques for PQ problems will be investigated. The various kinds of PQ problems and their effect on the load/system equipment will be looked at in detail. The mitigation strategies such as passive filtering, active and hybrid power filtering, static VAR compensation, DVR, UPQC, etc. will be investigated. Areas covered include voltage sags, interruptions, transients, flickers, harmonics and modeling and simulation of utility systems. The grounding imperfection as a major cause for PQ problems will be addressed in detail. Moreover, requirements and impact of distributed generation (DG) on network power quality will be studied in detail. Effect of DG on voltage regulation, relaying, losses, islanding and standards will be examined. Recommended Background: Basic understanding of modeling of power system elements and analysis techniques is required. Familiarity with a programming language and/or a simulation package such as EMTDC / PSCAD and MATLAB is desirable.

Power system protections schemes are designed primarily to minimize the duration of a fault as well as to minimize the number of customers affect by the fault. The scope of this course is to study the main elements and techniques for power system protection. The course is divided into two main parts; protective equipment and protective techniques. In the protective equipment; circuit breakers, relay, enclosures, fuses and isolating switches are discussed. Different protection techniques dedicated to protect feeders, transformers, generators and motors are discussed in the second part of the course. Recommended Background: Basic knowledge in power system engineering is required, basic knowledge in optimization techniques, statistics, and electric circuits.

The course deals in detail with power system operation and control in the deregulated electricity market environment. The topics include electricity market design and auction mechanisms, price formation, role of the independent system operator in pool versus bilateral markets, generation scheduling in deregulation, transmission pricing paradigms, congestion management, transmission rights, ancillary services procurement and pricing, and security management in deregulation. A highlight of the course is the country- specific information provided on various operational aspects of restructured power systems worldwide. Recommended Background: Basic understanding of power system engineering is required. Knowledge of mathematical programming is desirable.

This course deals with generation and measurement aspects of high voltages and industrial applications of high voltage engineering. The first part concentrates on generation of high voltage ac, dc and impluse voltages of both switching and lightning surges. Measurements techniques based on different types of potential dividers and spark gaps for ac, dc, and impulse measurements will be covered. The second part deals with generation and measurements of special types of high voltages needed for industrial applications. The course also covers non-destructive measurements like surface and internal discharges, capacitance and loss factor and some optical techniques. Recommended Background: Basic knowledge of circuit analysis and low voltage measurement techniques is required. Familiarity with electrical power system components is useful.

This course covers a wide range of topics in power electronics including: power semiconductor devices with emphasis on their operating characteristics, power converter topologies for ac-to-dc, dc-to-dc, dc-to-ac and ac-to-ac conversions, multi-converters and multi-level converters, control techniques in power converters, modeling of power converters, applications of power converters, converter design aspects (snubber circuits, gate/base-drive circuits, thermal management, series/parallel combinations of switches), and computer simulation of power electronic systems. Recommended Background: Basic understanding of circuit analysis and control theory is required. Familiarity with electric machinery and power systems is desirable.

FACTS controllers are studied in detail from the functional, structural and control points of view. The course concentrates on studying the most common thyristor-controlled FACTS controllers, in particular Static Var Compensators (SVC), Thyristor-Controlled Series Compensators (TCSC) and Thyristor Controlled Voltage and Phase Regulators (TCVR and TCPAR), and voltage-sourced converter controllers, specifically the Static Compensator (STATCOM), Static Synchronous Series Compensator (SSSC) and the Unified Power Flow Controller (UPFC). Detailed and approximate models for various control strategies and practical applications of these controllers are discussed. Recommended Background: Basic understanding of power electronic converters and power systems.

Extensive electricity utilization represents one of the hallmarks of a modern society. In this course, the basic cooncepts related to use of electric energy in various industrial applications and important issues related to such usage will be examined. The course also discusses issues related to economics of energy system usage and the concept of load management. The primary objective of the course is to provide students with the skills to understand the analytical methods and modern tools for solution of problems associated with utilization of electric energy in industrial sectors.

Grounding of power systems and equipment has great impact on system performance, system equipment integrity, safety of personnel as well as safety of the public at large. It acquires special relevance for distribution systems where grounding directly affects the reliability of supply to the customer, survivability of end-use equipment and safety of individuals. The main objectives of this course are - a) Discuss in detail the basic safety issues for low, medium and high voltage systems, b) Designing a reliable grounding system, c) Discuss the safety management and organizational structure and the human factor that affect electric safety.

Vast urbanization and increasing pressure to meet high demand in power delivery have resulted in a significant growth in underground cable network. In addtiion, underground cables being a critical asset group, any outages due to their failure will result in considerable service delivery and economic impact on the operation of distribution networks. Understand the basic dielectric theory, material properties and design details of underground cables and their accessories. Understand typical failure modes and their early detection of underground cable and their accessories. Discuss in detail various off-line and on-line diagnostic tests for condition monitoring of underground cables.

This course is intended to embrace power electronic aspects together with the broader issues of the systems of energy processing for emerging technologies. Within this framework, topics include performance, selection and optimization of power semiconductor devices including thyristors, GTOs, triacs, BJTs, MOSFETs, IGBTs and MCTs; classification, circuits and performance of converting circuits including rectifiers, inverters, choppers and cycloconverters; control and protection of conversion circuits; requirements and constraints of energy processing systems such as variable speed drives, high energy battery installations, transportation, solar and wind generators and industrial processes.

This course deals with the new emerging technology in high voltage engineering. It is divided into five parts. The first part of the course in a review of the basic fundamentals of high voltage engineering. The second part deals with the new techniques in partial discharge measurements. The third part of the course deals with measurements of charge distribution in solid dielectric. The fourth part of the course discusses the optical fiber based monitoring techniques of the high voltage high power equipment. The last part of the course deals with the application of high voltage engineering in power systems.

This course covers topics related to sustainable and clean energy resources; distributed generation and utility interfacing. The following topics are covered: Wind power generators; construction; operation theory, modeling and analysis. Wind turbine interfacing techniques with the grid. Photovoltaic energy sources; construction, modeling, loading characteristics and interfacing requirements. Fuel cells; types, construction, modeling and characteristics, operation theory and interfacing requirement. Distributed generation concept; Barriers to DG interfacing; Reactive power control applications using the DG interfacing; Ancillary services supplied by DG. System protection requirements with DG.

Selected topics from theory of solid insulation breakdown. Conduction process in insulating liquids. Hydro dynamic processes. Theories of breakdown due to gaseous inclusion, moisture inclusion and particle contamination. Kinetic theory of gases. Breakdown mechanism in uniform electric fields. Corona and breakdown in non-uniform electric fields. Compressed gas insulation.

Overview of optical properties of semiconductors and elements of plane wave propagation, theory and design of light emitting diodes, laser diodes, and detectors, optical spectra and transitions, spontaneous and stimulated emission, population inversion, carrier and optical confinements in heterostructures, quantum-well lasers, optoelectronic detectors, bandgap engineered graded structures, staircase type or superlattice structures for detectors, detailed quantum efficiency calculations and detector noise considerations, Introduction to monolithic integrated circuits.

This course introduces the fundamental concepts and the most recent achievements in physical realization of quantum information devices and systems in three platforms; Nuclear Magnetic Resonance (NMR), quantum photonics, and superconducting electric circuits.

Analysis of two-dimensional linear systems, Scalar diffraction theory, Fourier transforming properties of lenses, Frequency analysis of optical imaging systems, Spatial filtering and optical information processing, Synthetic Aperture Radar (SAR) - data processing, Wavefront-reconstruction.

Estimation theory, linear and nonlinear regression, numerical techniques for parameter estimation for static and dynamic models, the Kalman filter and extensions, stochastic approximation, empirical dynamic models - especially for linear sampled data systems with stochastic inputs.

Equilibrium points, linearization; second order systems; contraction mapping principle; existence and uniqueness of solutions to nonlinear differential equations; periodic solutions; Lyapunov stability; the Lure problem; introduction to input-output stability, introduction to nonlinear control techniques.

This course is intended to introduce fundamental concepts and give an overview of recent developments in solid-state photonic devices, as well as their applications in quantum optics and information. These solid-state based photonic devices can be shaped at the nanoscale in order to control the light collection efficiency, integrated in control structures to manipulate their electronic properties, as well as photonic circuits to influence light at the single photon level. Applications include transferring quantum information over long distances for secure communication; generation and detection of non-classical states of light for use in metrology, imaging, and the quantum internet; and the manipulation and storage of quantum information ¿ the fundamental element in a quantum processor.

Application of formal methods to the verification of computer-based systems. Algebraic and automata preliminaries. Temporal logic and model checking. Decision procedures. Mechanized theorem proving. Advanced topics chosen by the instructor.

As the cost of computing decreases at a phenomenal rate, the use of large format CCD area image sensors increases. Applications of CCD image sensors include industrial such as web inspection, document scanning, manufacturing product inspection for quality and process control, manufacturing product sorting and many other industrial applications. Multimedia and computers increasingly use their CCD image sensors or active pixel CMOS type image sensors. This course will start with the basic theory of CCD image sensors and graduate to CMOS type solid state image sensors. It will concentrate on the state of the art of this field and will deal with the basic device theory, the circuit design and architectures. Photosensitivity, noise, modulation transfer function and other aspects of spatial resolution will be covered. Related Background: E&CE semiconductor and circuit undergraduate courses.

Advanced study of software design and architecture; representation of architecture/design; software design methods; patterns in software design; analysis, assessment, verification and quality control for software design; case studies, current research issues and challenges. Related Background: Basic exposure to programming using C or C++, previous graduate or undergraduate course in software specifications, or software engineering should be sufficient.

This course discusses a broad range of techniques in reducing the negative impact of software bugs to improve software reliability and security. Main topics include: fundamental concepts of software reliability and security, software bug detection and diagnosis, software bug tolerance and recovery, and text analytics.

This course addresses all the dimensions of Power Quality (PQ) issues including mitigation strategies. The focus is mainly on qualitative concepts and comprehensive coverage. This course introduces PQ definitions, limitations, related international standards and mathematical techniques for PQ analysis of Power Systems. Different identification, localization and classification techniques for PQ problems will be investigated. The various kinds of PQ problems and their effects on load/system equipment will be looked at in detail. Mitigation strategies like passive filtering, active and hybrid power filtering, static VAT compensation, DVR, UPQC, etc. will be investigated. Areas covered include voltage sags, interruptions, transients, flickers, harmonics and modeling and simulation of utility systems. Grounding imperfection as a major cause for PQ problems will be addressed in detail. Moreover, the requirements and impacts of distributed generation (DG) on network power quality will be studies in detail. Effects of DG on voltage regulation, relaying losses, islanding and standards will be examined. Background Required - Basic understanding of modeling of power system elements and analysis techniques. Familiarity wit a programming language and/or a simulation package such as EMTDC/PSCAD and MATLAB is desirable.

This course provides an overview of the fundamentals and the recent research in the field of humanoid robotics. The course covers kinematics and dynamics, postural stability, control, gait and trajectory generation and inertial parameter estimation. Additional advanced topics in learning, human-robot interaction, manipulation and grasping are introduced.