Curriculum Planner

This course provides an introduction to design methods used in the development of innovative and realistic customer-driven engineered products, services, and systems. Design methods and tools are introduced and the student’s design ability is developed via a series of short design process modules: design research, analysis and synthesis, concept generation and creativity. Students will be expected to use tools and methods of professional practice to consider the social, economic and environmental implications of their products, services, or systems. There is an emphasis on hands-on innovative thinking and professional practice.

The current rapid evolution of manufacturing technology is reshaping where, when, and by whom objects are produced. In particular, the emergence of increasingly sophisticated additive manufacturing processes, coupled with greater automation, mean that mass customization, decentralized production and more complex geometries and material combinations are now more attainable than ever before. The environmental impacts of these new ways of transforming material are challenging to quantify and are subject to a wide range of differing opinions and assumptions. This course provides participants with a framework for critically analyzing new processing routes, so that decisions can be made with a clearer view of their implications for energy consumption, recyclability, and consumption of finite resources.

This course takes the students from atomic arrangements, to crystal structure, grain structure, texture, defects in materials, and finally to thermodynamic assessment of materials microstructure. The main focus is on metallic materials with steel metallurgy and steel classification being commonly used to demonstrate course content, while an introduction to ceramics are provided. Basic introduction in materials characterization is provided to give the students the background necessary to distinguish different materials in use.

Continuum mechanics is a powerful method of modeling physical systems of a very large variety. In this course students will learn the basic elements for describing system state and how balance laws are formulated to ensure correct system response. The developed methodology will first be applied to basic problems in elasticity, followed by application to poroelastic systems, batteries, and piezoelectric material systems.

The foundations gained from this course will allow students to understand how continua, both simple and complex, are properly modeled. It will set them up to be able to formulate continuum mechanical problems and it will allow them to more fully understand numerical solutions that are arrived at via modern computational methods, such as the finite element method. This course sets students up for the ability to contribute a sophisticated perspective on modeling questions that arise in a wide variety of engineering problem classes.

This course covers the materials science and processing of thin film coatings that incorporates fundamental knowledge of materials transport, accumulation, defects and epitaxy. Through this course, an understanding of the fundamental physical and chemical processes which are involved in crystal growth and thin film fabrication will be gained. Important synthesis and processing techniques used for the fabrication of electronic and photonic devices will be discussed. Finally, this course will provide an understanding of how material characteristics are influenced by processing and deposition conditions. This course is designed to directly address current challenges and future needs of the semiconductor and coating industries.

This course is designed to give an introduction, and overview of, the techniques used in fabrication of electronic devices. Topics such as materials deposition, patterning, laboratory safety and best practices will be covered. The students will learn basic processes used in the fabrication of silicon-based devices and novel semiconducting materials. After covering the fundamental processes and technologies needed to form an electronic device, the fabrication flow of NMOS devices will be studied in detail.

This course provides an introduction to design methods used in the development of innovative and realistic customer-driven engineered products, services, and systems. Design methods and tools are introduced and the student’s design ability is developed via a series of short design process modules: design research, analysis and synthesis, concept generation and creativity. Students will be expected to use tools and methods of professional practice to consider the social, economic and environmental implications of their products, services, or systems. There is an emphasis on hands-on innovative thinking and professional practice.

Optimization is a fascinating topic that finds applications across a wide array of disciplines, including finance, energy, data science, physical sciences, public policy, social science, and more. After completing the course, students will have an entirely new perspective on designing systems using mathematical optimization. Specifically, this course provides students with an introduction to mathematical optimization from the point-of-view of data science applications, e.g. mobility, energy, finance. Foundational concepts include optimization formulations, linear programming, quadratic programming, convex optimization, and machine learning.

This course takes the students from atomic arrangements, to crystal structure, grain structure, texture, defects in materials, and finally to thermodynamic assessment of materials microstructure. The main focus is on metallic materials with steel metallurgy and steel classification being commonly used to demonstrate course content, while an introduction to ceramics are provided. Basic introduction in materials characterization is provided to give the students the background necessary to distinguish different materials in use.

Introduction to the physical principles underlying the electronic properties of solids from macroscopic to nano dimensions. General solid state physics will be taught in the context of technological applications, including the structure of solids, behavior of electrons and atomic vibration in periodic lattice, and interaction of light with solids. Emphasis will be on semiconductors and the materials physics of electronic and optoelectronic devices.

This course covers the materials science and processing of thin film coatings that incorporates fundamental knowledge of materials transport, accumulation, defects and epitaxy. Through this course, an understanding of the fundamental physical and chemical processes which are involved in crystal growth and thin film fabrication will be gained. Important synthesis and processing techniques used for the fabrication of electronic and photonic devices will be discussed. Finally, this course will provide an understanding of how material characteristics are influenced by processing and deposition conditions. This course is designed to directly address current challenges and future needs of the semiconductor and coating industries.

This course is designed to give an introduction, and overview of, the techniques used in fabrication of electronic devices. Topics such as materials deposition, patterning, laboratory safety and best practices will be covered. The students will learn basic processes used in the fabrication of silicon-based devices and novel semiconducting materials. After covering the fundamental processes and technologies needed to form an electronic device, the fabrication flow of NMOS devices will be studied in detail.

Climate change is arguably the preeminent issue of our time. The transition to a clean energy society can help avoid the worst impacts of climate change. The energy systems engineer’s role is to deeply understand the challenges and develop creative technical solutions. This course provides students with an introduction to the technical fundamentals of clean energy challenges and opportunities. Challenges include urbanization, renewable energy integration, and sectors that are difficult to decarbonize. Opportunities include clean energy generation technologies, energy storage, microgrids, and electrified transportation.

The current rapid evolution of manufacturing technology is reshaping where, when, and by whom objects are produced. In particular, the emergence of increasingly sophisticated additive manufacturing processes, coupled with greater automation, mean that mass customization, decentralized production and more complex geometries and material combinations are now more attainable than ever before. The environmental impacts of these new ways of transforming material are challenging to quantify and are subject to a wide range of differing opinions and assumptions. This course provides participants with a framework for critically analyzing new processing routes, so that decisions can be made with a clearer view of their implications for energy consumption, recyclability, and consumption of finite resources.

Electricity production from nuclear energy is highly concentrated and free of green-house gasses. The pressure to decarbonize electricity generation is leading many to think of nuclear as a near term solution. Nevertheless, public opinion remains in general skeptical of nuclear. This course aims to familiarize students with nuclear energy, the way it is produced, and its overall environmental impact. The course will cover fundamental characteristics of nuclear energy, will provide students with a practical understanding of nuclear reactors, and will review the benefits and the challenges that nuclear energy can provide.

One of the leading causes of damage during earthquakes is soil liquefaction, and it can have devastating consequences on critical infrastructure such as dams, ports and other lifelines. This course will serve as a great introduction of the phenomenon of soil liquefaction, as well as go into details on simplified and advanced methods of analyses. Specifically, the phenomenon of soil liquefaction will be presented, as well as empirical and mechanistic methods to determine soil liquefaction triggering and post-liquefaction strength loss and its consequences for a range of materials (gravels, sands and silty soils). Laboratory and field testing to collect data that helps determine liquefaction triggering and post-liquefaction soil behavior (e.g. strength loss, dilation, and hardening) will be discussed. The state of the art with respect to numerical modelling of liquefaction will also be included, as well as relevant constitutive soil models. Finally, possible mitigation measures will be presented.

Ocean Engineering is gaining a renewed flood of attention as energy companies (oil, mining, renewables) eagerly look for extra resources in the oceans, entailing concerns about the environment and the planet. This course intends to introduce the basics of engineering principles for working in the area of ocean engineering. Specifically, topics of wave dynamics, wave, wind and current loads on ocean structures, and cables and mooring are covered. Each lecture is accompanied with examples from real-life problems, and for each subject a review of state of the art applications is provided through videos and presentations.

This course takes the students from atomic arrangements, to crystal structure, grain structure, texture, defects in materials, and finally to thermodynamic assessment of materials microstructure. The main focus is on metallic materials with steel metallurgy and steel classification being commonly used to demonstrate course content, while an introduction to ceramics are provided. Basic introduction in materials characterization is provided to give the students the background necessary to distinguish different materials in use.

This course provides an introduction to design methods used in the development of innovative and realistic customer-driven engineered products, services, and systems. Design methods and tools are introduced and the student’s design ability is developed via a series of short design process modules: design research, analysis and synthesis, concept generation and creativity. Students will be expected to use tools and methods of professional practice to consider the social, economic and environmental implications of their products, services, or systems. There is an emphasis on hands-on innovative thinking and professional practice.

The purpose of this course is to make the student fluent with the context, concepts and key content of the technologies that are driving what is collectively known as “Digital Transformation” (DT), and more specifically, focus on the industrial impact of DT, as captured under the term “Industry 4.0” (I4.0). This topic is quite important: for millennia we have improved our circumstances by managing our material surroundings: tools, shelter, supplies, land. Access to information is meant to enhance our efficiency in doing so, and dwindling resources, impeding climate change, and geopolitical strife are now stressing our planet. But this will not be a course in sociology, economics or geopolitics. Rather, it will be an engineering course, taught in these contexts.

This course aims at providing basics of Data Science to students and professionals who need to work with and analyze a large volume of data. The base programming language is Matlab, but techniques taught, and topics covered can be coded in any programming language (examples from Python and Fortran will be discussed). The course is aimed at graduate students in engineering, and therefore examples, assignments and the course project are from real life scenarios and engineering problems.

Optimization is a fascinating topic that finds applications across a wide array of disciplines, including finance, energy, data science, physical sciences, public policy, social science, and more. After completing the course, students will have an entirely new perspective on designing systems using mathematical optimization. Specifically, this course provides students with an introduction to mathematical optimization from the point-of-view of data science applications, e.g. mobility, energy, finance. Foundational concepts include optimization formulations, linear programming, quadratic programming, convex optimization, and machine learning.

This course provides a basic introduction to nonlinear dynamical systems and their control. The first module begins with an overview of nonlinear system models, and types of behaviors that can only arise in nonlinear systems. It then introduces phase portraits for systems with two state variables, states basic existence and uniqueness results for solutions of ordinary differential equations, and concludes with sensitivity equations that allow one to evaluate the sensitivity of the solutions with respect to parameters and initial conditions. The second module introduces Lyapunov stability theory and Lyapunov functions. It proceeds to linearization as a method for determining local stability properties around operating points, and defines the notion of a region of attraction. The third module focuses on feedback control design for nonlinear systems, starting with backstepping as an example of Lyapunov-based feedback design to stabilize an operating point. It continues with input/output linearization for trajectory tracking, by first introducing requisite concepts such as relative degree. The fourth module introduces feedback linearization for stabilization, then proceeds to sliding mode control for stabilization in the presence of model uncertainty. The course will illustrate all concepts with physically-motivated examples, and will point to resources for further study.

Bipedal robot locomotion is a challenging problem. This course will introduce students to the math behind bipedal legged robots. We will cover modeling and dynamics of legged robots, trajectory planning for designing walking and running gaits, and common control strategies to achieve the planned motions. The course will also include applied techniques of programming up a simulator with a dynamical model of a bipedal robot as well as a controller that stabilizes a walking gait. This short course will take students through every step of the process, including:

• Mathematical modeling of walking gaits in planar robots.
• Analysis of periodic orbits representing walking gaits.
• Algorithms for synthesizing feedback controllers for walking.
• Algorithms for optimizing energy-efficient walking gaits.
• Detailed simulation examples.

Aerial robots are increasingly becoming part of our daily lives. This course is aimed at a broad audience, and intends to give an introduction to the main considerations made when designing aerial robots. We will consider sizes ranging from less than 1 kilogram to vehicles that can carry multiple passengers. Using simple physics, we will derive some fundamental constraints and trade-offs. We will also discuss autonomy of such systems, and specifically different components used in the sense-decide-act feedback control loop.

In recent years Python has emerged as an indispensable programming language for engineers, both practicing and academic, as well as data scientists, web developers, and many others. However the language is vast and includes many features that are not immediately relevant to most engineers. The goal of this course is to help students to quickly gain a foothold with the parts of the language that they are most likely to use. We will begin with a high-level description of Python and how it differs (both in syntax and in philosophy) from other popular programming languages. We will learn about Python’s extensive offering of libraries, starting with the standard library, and including Numpy and Pandas. We will set up our programming environment with Anaconda, Jupyter, and Spyder. We will then delve into the basic constructs of the language (data types, program flow, etc). We will also cover code organization and object-oriented programming. As well, we will begin using numerical libraries such as Numpy and Pandas to solve more advanced problems. The course will be suffused with demonstrations of the concepts, and sample visualizations created with Matplotlib.