Courses

Fall - Winter 2022/2023 Enrolment:

most MIE courses will open for enrollment on

Wednesday, August 3, 2022 at 6:00 A.M.

Non-MIE Students: Enrollment in Winter Term MIE courses with priority for MIE students will open January 4, 2023 at 10:00 A.M. (space permitting).

At this time, the University of Toronto and the Faculty of Engineering are working toward offering classes in-person for Fall 2022.  Should there be any changes to method of course delivery, MIE will continue to update students through the course offerings listed below.

For all Reading Courses (MIE 2002H, 2003H, 2004, 2005H) the Reading and/or Research Course form (signed by the student and their supervisor) must be submitted to gradoffice@mie.utoronto.ca. Reading courses are assigned a CR/NCR final grade.

MEng students who would like to enroll in a MEng Project (MIE 8888Y) are required to complete the project request form.  The MIE8888Y project is assigned a letter grade. See MEng projects for more details.

APS courses can be found on the Emphasis in Entrepreneurship, Leadership, Innovation and Technology in Engineering (ELITE) website.  For more information ELITE courses, please contact gradstudies@engineering.utoronto.ca.

2022-2023 Delivery Modes of each course are currently underway and we will update when we receive confirmation.  Some course delivery options are:

Online Synchronous: A course is considered Online Synchronous if online attendance is expected at a specific time for some or all course activities, and attendance at a specific location is not expected for any activities or exams.

Online Asynchronous: A course is considered Asynchronous if it has no requirement for attendance at a specific time or location for any activities or exams.

In Person: A course is considered In Person if it requires attendance at a specific location and time for some or all course activities. In Person delivery is subject to adjustments imposed by public health requirements for physical distancing.

Although students will see In Person sections alongside online sections of Winter courses, students are not yet able to enroll into Winter term in-person sections of Engineering courses through ACORN. Students will have opportunities to opt into limited, optional, in-person sections of Engineering courses for which they are already registered (not waitlisted) starting early September, provided they can confirm they will be available and in Toronto to attend all in-person sections. Student will be informed if, and once, it is possible to add in-person elements to courses. In-person activities will not be requirements of any course.

For all courses, including those delivered “In Person,” students should be aware of the minimum technical requirements needed for students to access remote/online learning.

U of T policy on Academic Appeals

for a course mark, course failure or other academic decisions

Appeals regarding departmental academic decisions are initiated within MIE. The exception to this are appeals related to Termination of Registration and Final Oral Examination failure which are appealed directly at the SGS level.

When possible, the Graduate Office will provide assistance to attempt to settle the appeal informally between the parties involved (e.g. student & instructor).

If the matter cannot be resolved informally, the first step in the appeals process is to send a notice of appeal to MIE's Graduate Department Academic Appeals Committee (GDAAC) Secretary.

The GDAAC is composed of 4 MIE faculty members and 1 student representative.  The committee will review the case and make a recommendation to the MIE Department Chair who then makes a decision.

The appeal can then subsequently be taken to the Graduate Academic Appeals Board (GAAB) of SGS, and then to the Academic Appeal Committee of the Governing Council of the University.

For more information, please visit:

SGS Website

SGS Calendar

UofT Grading Policy

or contact the GDAAC Secretary.

2021-2022 MIE GDAAC Committee secretary:

Celeste Francis Esteves celeste@mie.utoronto.ca

Fall - WInter 2022/2023 Enrolment:

most MIE courses will open for enrollment on

Wednesday, August 3, 2022 at 6:00 A.M.

Non-MIE Students: Enrollment in Winter Term MIE courses with priority for MIE students will open January 4, 2023 at 10:00 A.M. (space permitting).

All MIE graduate courses are open to all graduate students (MENG, MASc, and PhD)

Courses designated "research" are more narrowly focused, research oriented, and targeted to PhD and MASc students in those areas.

CourseCourse detailsSession offeredInstructorCourse areas
AER1410HF: Topology Optimisation

Syllabus: Contact Instructor
Course Delivery:
In-Person
Winter 2022, AnnuallyC. SteevesMechanics and Materials
APS502H1: Financial Engineering

This course provides an introduction to financial engineering concepts especially relevant for engineering students. The major topics include the theory of interest, applied interest rate analysis, fixed-income securities e.g. bonds, basic derivative securities e.g. options, portfolio (mean-variance) optimization theory (including practical engineering issues), the capital asset pricing model, and introduction to options and option pricing.

Schedule posted
here
Fall 2022, AnnuallyR. KwonAPS Engineering Courses
CIV1240HS: Building Performance Assessment

Syllabus: Contact instructor
Course Delivery:
not offered in Winter 2023
Winter, Annually

M. TouchieThermal Sciences
MIE504HS: Applied Computational Fluid DynamicsSchedule posted
here
Winter 2023, AnnuallyA. DolatabadiFluid Mechanics
MIE505H1: Micro/Nano Robotics

Syllabus: Contact Instructor
Schedule posted
here
Winter, AnnuallyE. DillerMechatronics and Dynamics
MIE506H1: MEMS Design and Microfabrication

Syllabus: Contact Instructor
Schedule posted
here
Winter 2023, AnnuallyM. Bakri-KassemMechatronics and Dynamics
MIE507HS: Heating, Ventilating, and Air Conditioning (HVAC)

Syllabus: Contact instructor
Schedule posted
here
Fall 2022, AnnuallyM. TouchieFluid Mechanics
MIE515H1: Alternative Energy Systems

Syllabus: Contact instructor
Schedule posted
here
Fall 2022, AnnuallyA. DolatabadiThermal Sciences
MIE516H1: Combustion and Fuels

Syllabus: Contact instructor
Schedule posted
here
Fall 2022, AnnuallyM. ThomsonThermal Sciences
MIE517H1: Fuel Cell Systems

Syllabus: Contact Instructor
Schedule posted
here
Winter 2023, AnnuallyO. KeslerMechanics and Materials
MIE519H1: Advanced Manufacturing Technologies

Syllabus: Contact Instructor
Schedule posted
here
Winter 2023, AnnuallyP. LeeMechanics and Materials
MIE520H1: Biotransport Phenomena

Syllabus: Contact instructor
Schedule posted
here
Fall 2022, AnnuallyL. YouFluid Mechanics
MIE523H1: Engineering Psychology and Human Performance

Syllabus: Contact Instructor
Schedule posted
here
Fall 2022, AnnuallyTBDHuman Factors & Ergonomics
MIE533HS:
Waves and Their Applications in Non-Destructive Testing and Imaging
Schedule posted
here

Winter 2023, Occasionally ResearchA. MandelisThermal Sciences
MIE540H1: Product Design

Syllabus: Contact Instructor
Schedule posted
here
Winter 2023, AnnuallyD. NacsonMechanics and Materials
MIE542H1: Human Factors Integration

Syllabus: Contact Instructor
Schedule posted
here
Winter 2023, AnnuallyR. Leger & K. Iwasa-MadgeHuman Factors & Ergonomics
MIE550H: Advanced Momentum, Heat and Mass Transfer
Syllabus
Schedule posted
here
Winter 2023, AnnuallyA. Taheri
Thermal Sciences
MIE561H1: Healthcare Systems

The purpose of MIE 561 is to give students an opportunity to integrate the engineering tools learned in previous courses by applying them to real world problems. While the specific focus of the case studies used to illustrate the application of engineering will be the Canadian health care system, the approach to problem solving adopted in this course will be applicable to any setting.
Schedule posted
here
Winter 2023, AnnuallyA. EsensoyOperations Research
MIE562H1: Scheduling
Syllabus: Contact Instructor
Schedule posted
here
Fall 2022, AnnuallyC. BeckOperations Research
MIE563H: Engineering Analysis II

Syllabus: Contact Instructor
Schedule posted
here
Fall 2022, AnnuallyD. SteinmanThermal Sciences
MIE566H1: Decision Analysis

Syllabus: Contact Instructor
Schedule posted
here
Fall 2022, AnnuallyTBDOperations Research
MIE567H1: Dynamic and Distributed Decision Making

This course is to provide fundamental concepts and mathematical frameworks for sequential decision making of a team of decision makers in the presence of uncertainty. Topics include Markov decision processes, reinforcement learning, theory of games, multi-agent reinforcement learning and decentralized Markov decision processes. The course is technical by nature and for advanced students with strong mathematical background and programming skills.
Schedule posted
here
Winter 2023, AnnuallyC.G. LeeOperations Research
MIE1001HS: Advanced Dynamics
Syllabus
Not offered in Winter 2022.Winter, Annually ResearchE. DillerMechatronics and Dynamics
MIE1005HF: Theory of Vibrations
Syllabus
Course Delivery:
In-Person
Course Day & Time: Tuesday 1:00pm-4:00pm
Room: RS 208
Fall 2022, AnnuallyK. BehdinanMechatronics and Dynamics
MIE1010HS: Acoustics and Noise Control

The purpose of the course is to introduce the theory and practical application of acoustics noise and vibration control. While the emphasis of the study will be on the built environment, both indoor and outdoor, the methods taught can also apply to other industries, e.g. the automotive industry. Both the physics and perception of sound will be discussed covering such wide ranging topics as concert hall design, speech intelligibility, HVAC noise control design and building isolation from rail noise, to name a few. The course combines theoretical introductions to the subjects of acoustics, noise and vibration and follows them up with case studies from industry.
Course Delivery:
In-Person
Course Day & Time: Tuesday 6:00pm-8:00pm
Room: BA 2165
Winter 2023, AnnuallyJ. O'KeefeMechatronics and Dynamics
MIE1050HF: Design of Intelligent Sensor Networks
(Formerly MIE1453HF: Introduction to Sensors and Sensor Networks)

This course will provide students with practical knowledge on sensor network design including sensor selection, calibration, digitization, and digital signal processing. Students will be introduced to theory and operation of various sensor technologies and their applications. Commonly used transducers such as chemical, mechanical, and magnetic as well as the more advanced organic and nuclear transducers are discussed. This course will also cover linear and non-linear multi-parameter calibration. Digitization, and a survey of digital signal processing techniques will be discussed with practical application of commonly used digital filters. Special focus will be placed on optimal design of sensor networks and multi-sensor data fusion. There will be a design project to enforce the lessons learned in class on sensor calibration and digital signal processing.
Course Delivery:
In-Person
Course Day & Time: Monday 1:00pm-3:00pm
Room: MY 490
Fall 2022, Annually A. BakhariMechatronics and Dynamics
MIE1052HS: Signal Processing (Formerly MIE1452HS: Signal Processing)
Course Delivery:
In-Person
Course Day & Time: Monday 2:00pm-4:00pm
Room: BA 2145

Winter 2023, AnnuallyA. Mandelis Mechatronics and Dynamics
MIE1064HF: Control Analysis Methods with Applications to Robotics

The main purpose of this course is to introduce a series of distinct topics in control to students who have not seen control system design beyond a first course in control, which includes classical methods such as root locus, and Bode design, for example. The topics discussed in MIE 1064 F are selected to give students a broad overview of a variety of control design methods and concepts in stability.
Course cancelled for Fall 2022

*Students must have the pre-requisite courses in order to get approval to take MIE1064.

*Students cannot directly enroll in the course and will need approval from Professor Mills
Fall 2022, AnnuallyJ. MillsMechatronics and Dynamics
MIE1070HY: Intelligent Robots for Society

This course introduces the design of intelligent robots- focusing on the principles and algorithms needed for robots to function in real world environments with people. Topics that will be covered include autonomy, social and rational intelligence, multi-modal sensing, biologically inspired and anthropomorphic robots, and human-robot interaction. Class discussions will centre on the interactive, personal assistive and service robotics fields.
Course Delivery:
ONLINE
Course Day & Time: Tuesday & Thursday, 2pm-5pm (EST)

*Course runs July 5th-7th, July 12th-14th, July 19th, 20th, and Aug. 16th-18th
Summer 2022, AnnuallyG. NejatMechatronics and Dynamics
MIE1075HF: AI Applications in Robotics

Syllabus: Contact instructor
Course Delivery:
In-Person
Course Day & Time: Wednesday 12:00pm-2:00pm
Room: BA 2159
Fall 2022, AnnuallyA. GoldenbergMechatronics and Dynamics
MIE1076H: AI Applications in Robotics II

Syllabus: Contact Instructor
Course Delivery:
In-Person
Course Day & Time: Thursday 11:00am-1:00pm
Room: BA B026

*Course prerequisite: MIE1075
*Interested students need to get instructor approval before enrolling
Winter 2023, AnnuallyA. GoldenbergMechatronics and Dynamics
MIE1077HY: AI Applications in Robotics III

Syllabus: Contact Instructor
Course Delivery:
In-Person
Course Day & Time: Thursday, 11am (EST)
Room: BA B024
Summer 2022A. GoldenbergMechatronics and Dynamics
MIE1080HS: Healthcare Robotics

This course provides students with knowledge on healthcare robotics including surgical, assistive, and rehabilitation robots. Specific topics include medical imaging-guided surgery; minimally-invasive surgery through miniaturization, novel actuation and sensing; robotic surgery at tissue and cell levels; autonomous robotic systems to assist with daily living activities; multi-modal robot interfaces; robotics-based rehabilitation technologies; upper limb rehabilitation robots; wearable exoskeletons and sensors; implanted neural interfaces. Students are provided with state-of-the-art advances in healthcare robotics.
Course Delivery:
ONLINE
Course Day & Time: Monday 9:00am-12:00pm

Pre-requisite: students should have taken a previous robotics or mechatronics course.
Winter 2023, Annually Y. SunMechatronics and Dynamics
MIE1101HF: Advanced Classical Thermodynamics
Syllabus
Course is on HiatusOccasionally, ResearchC. WardThermal Sciences
MIE1115HS: Heat Transfer with Phase Change

In this course you will learn about the phenomena that control phase change of pure substances. Most of the course will be devoted to studying liquid-vapour phase change, with an emphasis on boiling. We will study the thermodynamics of phase change, vapour bubble nucleation and growth, heat transfer during boiling, and fluid mechanics during the flow of a liquid-vapour mixture. All students are expected to have done undergraduate courses in thermodynamics, fluid mechanics and heat transfer.
Course Delivery:
In-Person
Course Day & Time: Friday 11:00am-1:00pm
Room: MY 490

Winter 2023, OccasionallyS. ChandraThermal Sciences
MIE1120HS: Current Energy Infrastructure and Resources

This course covers the basic principles of how global energy is currently supplied, by primary source. The aim is to provide an energy literacy that can inform research, technology development and effective policy in this area. The course content will be roughly divided according to the current global energy mix (i.e. 31% oil, 27% coal, 25% gas, 6.9% hydro, 4.3% nuclear, 2.5% wind, 1.4% solar, and 1.8% geothermal/biomass/biofuels). In each case background reading and critical analyses will be applied to: (a) the characteristics of the resource; (b) the infrastructure for extraction/development of the resource; (c) the usage of the resulting energy; and (d) the implications of usage. Assignments and exams will assess both background knowledge and the ability to apply fluid flow, thermodynamic and heat transfer analyses to energy supply systems.
Course Delivery:
In-Person
Course Day & Time: Monday 1:00pm-3:00pm
Room: GB 119
Winter 2023, AnnuallyD. SintonThermal Sciences
MIE1123HS: Fundamentals of Combustion
Syllabus
Not offered in Winter 2023.Winter, Biennially

TBD
Thermal Sciences
MIE1128HF: Materials for Clean Energy Technologies
Syllabus
Course Delivery:
In-Person
Course Day & Time:
Monday 3:00pm-5:00pm
Room: MS2172
Fall 2022, AnnuallyO. KeslerMechanics and Materials
MIE1129HF: Nuclear Engineering I

A first course in nuclear reactor theory, which introduces students to the scientific principles of nuclear fission chain reactions and lays a foundation for the application of these principles to the nuclear design and analysis of reactor cores. Topics covered include basic nuclear concepts, atomic fission, neutron propagation and interaction with matter, neutron thermalization, diffusion model of a nuclear reactor, criticality, nuclear reactor kinetics, and reactivity effects.
Course Delivery:
In-Person
Course Day & Time:
Tuesday 12:00pm-2:00pm
Room: MY 315

Thursday 2:00pm-4:00pm
Room: BA 2135

Friday 3:00pm-4:00pm
Room: MY 315

co-taught with MIE407

Fall 2022, AnnuallyJ. LebenhaftThermal Sciences
MIE1130HS: Nuclear Engineering II

This course covers the basic principles of the thermo-mechanical design and analysis of nuclear power reactors. Topics include reactor heat generation and removal, nuclear materials, diffusion of heat in fuel elements, thermal and mechanical stresses in fuel and reactor components, singlephase and two-phase fluid mechanics and heat transport in nuclear reactors, and core thermomechanical design.
Course Delivery:
In-Person
Course Day & Time:
Monday 9:00am-12:00pm
Room: BA 2195

Friday 4:00pm-6:00pm
Room: BA B025

co-taught with MIE408
Winter 2023, AnnuallyH. HasaneinThermal Sciences
MIE1132HS: Heat Exchanger Design

This course provides the fundamentals and applications for thermal and hydraulic design of heat exchangers. it covers a wide range of relevant topics including the main considerations for equipment selection and design, and different methods of analysis for sizing and rating. More specialized design considerations are also introduced. The objective is for students to become familiar with the design and specifications of industrial heat exchangers by solving practical problems using synthesis of other engineering subjects such as thermodynamics, heat transfer, and fluid mechanics.
Not offered in Winter 2023.Winter, BienniallyD. WarnicaThermal Sciences
MIE1199HS: Special Topics in Thermal Sciences - "Thermal Management of EV Batteries and Chargers’’Not offered in Winter 2023.

Winter, OccassionallyC. AmonThermal Sciences
MIE1201HF: Advanced Fluid Mechanics I

This fundamental course develops the conservation laws governing the motion of a continuum and applies the results to the case of Newtonian fluids, which leads to the Navier-Stokes equations. From these general equations, some theorems are derived from specific circumstances such as incompressible fluids or inviscid fluids. Basic solutions to, and properties of, the governing equations are explored for the case of viscous, but incompressible, fluids. Topics included involve exact solutions, low-Reynolds-number flows, laminar boundary layers, flow kinematics, and 2D potential flows.
Course Delivery:
In-Person
Course Day & Time: Tuesday 12:00pm-3:00pm
Room: UC 85
Fall 2022, AnnuallyE. YoungFluid Mechanics
MIE1207HF: Structure of Turbulent Flows
Syllabus
Course Delivery:
In-Person
Course Day & Time: Wednesday 10:00am-12:00pm
Room: BA B024
Fall 2022, AnnuallyP. SullivanFluid Mechanics
MIE1208HS: Microfluidic Biosensors

This course will present the fundamentals and applications of biosensors realized on microfluidic platforms. Topics to be covered include: • Microfabrication techniques for constructing silicon, glass, and polymer devices • Microfluidic principles • Biosensing mechanisms • Design and analysis of microfluidic biosensors • Microfluidic immunosensors • Microfluidic nucleic acid sensors • Microfluidic chemical sensors • Other applications of microfluidic biosensors
Course Delivery:
In-Person
Course Day & Time: Wednesday 11:00am-2:00pm
Room: MY 440
Winter 2023, AnnuallyX. LiuFluid Mechanics
MIE1210HF: Computational Fluid Mechanics and Heat Transfer

MIE1210 is an introductory course that will teach a Finite Volume (FV) and Finite Difference (FD) approaches to Computational Fluid Dynamics (CFD) and Heat Transfer. Since the advent of commercially available computers, CFD has been an important engineering research domain as it gave researchers the ability to solve analytically intractable problems of industrial relevance. In the last two decades, the immense demand for CFD research and expertise has spawned the commercialization of software packages such as Fluent/CFX and FEMlab. Despite these readily available software packages, there is a recognized importance to user expertise, fundamental knowledge, and critical understanding of their inner workings. In addition, home spun research codes are still prominent in academia and industry. This is due in large part to the fact that commercial software packages are geared toward a broad range of research topics, and may not function as efficiently as a code designed with a specific problem in mind, and to the fact that developments in CFD are typically achieved in research before they are adopted by software companies. This course is appropriate both for students who wish to become knowledgeable users of commercial CFD programs, and students who plan to create, develop, or enhance research codes. Therefore, the overreaching goals of this course are threefold: 1. To give you an introduction to fundamental discretization and solution techniques for heat transfer and fluid dynamics problems; 2. To give you an understanding of solution methodologies, advantages, downfalls, considerations (stability, accuracy, efficiency), and the inner workings of CFD software; and 3. To have you gain experience writing programs and solving 1D and 2D problems, and in using these programs to demonstrate and reinforce 1 and 2.
Course Delivery:
In-Person
Course Day & Time: Thursday 11:00am-2:00pm
Room: AP 120
Fall 2022, AnnuallyH. MontazeriFluid Mechanics
MIE1212HS: Convective Heat Transfer

The basic partial differential equations of material transport by fluid flow is derived along with the most significant analytical solutions of these equations, e.g., fully developed laminar flow and heat transfer in pipes and channels. Prediction of heat and mass transfer rates based on analytical and numerical solutions of the governing partial differential equations. Heat transfer in fully developed pipe and channel flow, laminar boundary layers, and turbulent boundary layers. Approximate models for turbulent flows. General introduction to heat transfer in complex flows. Discussion will be centered on boundary conditions for heat transfer, similarity and dimensionless parameters, and boundary layer approximations.
Course Delivery:
In-Person
Course Day & Time: Wednesday 2:00pm-4:00pm
Room: MY 420
Winter 2023, BienniallyJ. MostaghimiFluid Mechanics
MIE1222HF: Multiphase Flows
Syllabus
Course Delivery:
In-Person
Course Day & Time: Tuesday 9:00am-12:00pm
Room: SS 2114
Fall 2022, AnnuallyN. AshgrizFluid Mechanics
MIE1232HS: Microfluidics and Laboratory-on-a-Chip Systems

Tremendous opportunities are associated with shrinking large-scale (laboratory) processes to characteristic volumes of 10nL-100µL and translating them to continuous-flow formats. Applications of microfluidic and lab-on-a-chip technologies include assays for biomolecular detection, platforms for the perfusion culture of cells, organs and organisms, microfluidic bioprinting, and miniature chemical factories and energy conversion. The interdisciplinary course considers the different backgrounds of students and consists of a combination of lectures and project work. Projects will consist of individual and group contributions and involve the design, manufacture, testing and live demonstration a microfluidic device. Course participants will receive hands-on experience in several current technologies for the processes for the manufacture of microfluidic devices (soft lithography, hot embossing, 3D printing).
Not offered in Winter 2023.Winter, OccasionallyA. GuentherFluid Mechanics
MIE1240HF: Wind Power
Syllabus
Course Delivery:
In-Person
Course Day & Time: Monday 10:00am-1:00pm
Room: BA 1210
Fall 2022, AnnuallyJ. MoranFluid Mechanics
MIE1241HF: Energy Management
Syllabus
Course Delivery:
In-Person
Course Day & Time: Monday 3:00pm-6:00pm
Room: BA 1210
Fall 2022, AnnuallyJ. MoranFluid Mechanics
MIE 1242HF: Applied Thermal Management: Applications in EVs, Electronic Systems, and Datacenters

Syllabus

The course discusses thermal management of industrial systems, with a focus on
· Electric Vehicles
· Autonomous Self Driving Systems
· Datacenters and Supercomputers
· Consumer Electronics

The course will cover thermal management from a practical approach, as exercised in industry today. Each topic will be accompanied by examples from the leading designs on the market.

After a review of the fundamentals of heat transfer and fluid flow in industrial systems, we will discuss product design cycles from concept to mass production with a focus on thermal design.
Different types of cooling methodologies that are being used in industrial systems will be discussed and analyzed. We will also address practical aspects of thermal design, including acoustics, control, reliability, manufacturing, and service.
This course is suitable for those who are pursuing a career in industry as a thermal engineer, and those who wish to pursue an applied research path on thermal design.

Course Delivery:
In-Person
Course Day & Time: Friday 9:00am-12:00pm
Room: MP 134
Fall 2022, AnnuallyA. NabovatiFluid Mechanics
MIE1299HS: Special Topics in Fluid Mechanics
Syllabus: Contact instructor

Not offered in 2022.OccasionallyFluid Mechanics
MIE1301HS: Solid Mechanics

Syllabus: Contact Instructor
Not offered in Winter 2023.Winter, AnnuallyTBDMechanics and Materials
MIE1303HF: Fracture Mechanics

This course offers graduate students an in-depth study of fracture mechanics as applied to real engineering problems. The course is divided into three main components: failure analysis using fracture mechanics concepts, diagnostics using replicas of engineering failures, and failure prevention techniques. Mofdes of failure, brittle fracture, linear elastic fracture mechanics (LEFM), elastoplastic fracture mechanics (EPFM) and fatigue crack initiation and growth will constitute the failure analysis component. In-laboratory examinations of typical fractures will constitute the diagnostics component. Design considerations, Surface treatment and different processing techniques for crack arrest will conclude the final component. The course is supported by numerous aerospace case studies.
Not offered Fall 2022.Fall, AnnuallyS. MeguidMechanics and Materials
MIE1359HS: Engineering Cell Biology and Micro/Nanoengineered Platforms

Motivation/Objectives: A cell is the basic unit of life in all organisms. Understanding cellular structures and how cells function is fundamental to all aspects of biosciences and is the basis for disease diagnostics/therapeutics and drug discovery. For single cell studies, the development of enabling micro and nanoengineered techniques/systems is a highly active field. The objectives of this course are two folds: (1) The course targets engineering graduate students to introduce essential topics in cell biology. (2) The course will also discuss micro/nano fabricated/engineered techniques/systems for manipulating cells, stimulating cells, and quantitatively measuring cellular activities.
Course Delivery:
In-Person
Course Day & Time: Thursday 2:00pm-5:00pm
Room: BA 2159
Winter 2023, AnnuallyY. Sun and L. YouMechanics and Materials
MIE1401HF: Human Factors Engineering

• Learn the basic concepts of human factors engineering. • Learn the importance of considering human capabilities and limitations in the design of systems. • Develop skills to apply human factors principles to the analysis, design, and evaluation of systems.
Course Delivery:
In-Person
Course Day & Time: Friday 11:00am-2:00pm
Room: SS 1069

Enrollment priority given to MIE students
Fall 2022, AnnuallyE. KittelHuman Factors & Ergonomics
MIE1402HF: Experimental Methods in Human Factors Research

Syllabus: Contact Instructor
Course Delivery:
In-Person
Course Day & Time: Tuesday 2:00pm-5:00pm
Room: CR106

Enrollment priority given to MIE students
Fall 2022, Annually ResearchM. ChignellHuman Factors & Ergonomics
MIE1403HF: Analytical Methods in Human Factors Research

The course covers a variety of topics in Human Factors / Ergonomics research related to the acquiring, analysing, and modelling of human behavioural data. Topics to be covered include the following (in approximate order of presentation): • Selecting Measures for Human Factors Research • Psychophysical methods of measurement: - Classical psychophysical methods - Signal Detection Theory - Indirect and direct subjective scaling • Protocol Analysis - Interviewing and Questionnaires - Knowledge Elicitation • Estimating mental workload & situational awareness • Manual Control - Tracking paradigms - Modelling of human manual control performance
Course Delivery:
In-Person
Course Day & Time: Thursday 5:00pm-8:00pm
Room: MS 2173

Enrollment priority given to MIE students
Fall 2022, Annually ResearchR. KealeyHuman Factors & Ergonomics
MIE1411HS: Design of Work Places

Syllabus: Contact Instructor
Course Delivery:
In-Person
Course Day & Time: Monday 6:00pm-9:00pm
Room: BA 1230

Enrollment priority given to MIE students
Winter 2023, AnnuallyE. KingHuman Factors & Ergonomics
MIE1412HS: Human-Automation InteractionNot offered in Winter 2023.Winter, Annually ResearchG. JamiesonHuman Factors & Ergonomics
MIE1413HS: Statistical Models in Empirical ResearchNot offered in Winter 2023.
Winter , Annually ResearchB. DonmezHuman Factors & Ergonomics
MIE1414HS: Human Factors in Transportation

The course will cover a wide range of human factors topics related to road transportation, in particular motor vehicle safety. The course provides an understanding of road user characteristics and limitations and how these affect design of traffic control devices and the roadway. The course topics include: history and scope of human factors in transportation; vision and information processing in the context of driving; driver adaptation; driver education, driver licensing and regulation; traffic control devices; crash types, causes, and countermeasures; alcohol, drug, and fatigue effects; forensic human factors.
Course Delivery:
In-Person
Course Day & Time: Wednesday 6:00pm-9:00pm
Room: BA 2159

Enrollment priority given to MIE students
Winter 2023, Annually ResearchM. MasliahHuman Factors & Ergonomics
MIE1415HS: Analysis and Design of Cognitive Work

Frameworks, tools and methods to analyze and design support for cognitive work. The course will emphasize computer-based work in complex production- and/or safety-critical systems. Primary frameworks include Cognitive Work Analysis and Ecological Interface Design, with consideration of complementary perspectives in Cognitive Systems Engineering. The design element will emphasize the human-machine interface.
Course Delivery:
In-Person
Course Day & Time: Thursday 6:00pm-9:00pm
Room: BA 2139

Enrollment priority given to MIE students
Winter 2023, Biennially ResearchA. Reiner & K. ChristoffersenHuman Factors & Ergonomics
MIE1416H: Human Factors in Healthcare

This course provides an introduction to the application of human factors (HF) in the analysis of healthcare systems using case studies and current events. Various healthcare models are explored with a focus on aims of healthcare systems in Canada and the US. Applicable HF theory, models, principles and methods are covered. Emphasis is placed on the use of HF in prospective and retrospective system safety evaluation and integration of technology (including ML/AI) in clinical environments. Equity as a cross-cutting dimension of quality care, engagement of patients in system redesign processes, and research ethics and misconduct are also covered.
Course Delivery:
In-Person
Course Day & Time: TBD
Room: TBD

Instructor approval needed
Winter 2023, AnnuallyM. AlfredHuman Factors & Ergonomics
MIE1444H: Engineering for Psychologists

Syllabus: Contact Instructor.
Course open to students in psychology, or an equivalent field, only.

Online:

*** Do NOT contact instructor if your undergraduate degree is engineering ***.

• If you are interested in enrolling, please email ASAP
(shu@mie.utoronto.ca) with MIE1444 in the subject line, stating
1) the area of your *non-engineering* undergraduate studies, and
2) your graduate research area or interest
Summer 2022, AnnuallyL. ShuHuman Factors & Ergonomics
MIE1501HF: Knowledge Modelling and Management

Syllabus: Contact Instructor
Course Delivery:
In-Person
Course Day & Time: Monday 2:00pm-4:00pm
Room: BA B024

Enrollment priority given to MIE students
Fall 2022, AnnuallyM. GruningerInformation Engineering
MIE1505HS: Enterprise Modelling
Syllabus
Not offered in Winter 2023Winter, Biennially ResearchM. GruningerInformation Engineering
MIE1510HS: Formal Techniques in Ontology Engineering

Syllabus: Contact Instructor
Not offered in Winter 2023

Winter, Biennially ResearchM. GruningerInformation Engineering
MIE1512HS: Data Analytics

This course is a research seminar that focuses on recent developments in the area of Data Management for Analytics. Science, businesses, society, and government are been revolutionized by data-driven methods that benefit heavily from scalable data management techniques. The course provides an overview of data management concepts applied to analytics, covering methods and techniques, including distributed computations on massive datasets and frameworks for enabling large-scale parallel data processing on clusters of commodity servers. Emphasis is given to data management techniques for analyzing Web Data and Open Datasets. The course evaluation is based on student presentations, a focused bibliography survey, a hands on invigilated lab, and a course project (the last two using computational notebooks on scalable platforms). The project goal is to reproduce high quality published research in the area of data analytics, emphasizing data management aspects.
Course Delivery:
In-Person
Course Day & Time: Tuesday, 3pm-6pm
Room: RS 303

*Pre-requisites: An undergraduate level course in Databases, such as MIE253 Data Modelling, or equivalent
(including hands-on knowledge of SQL).

Enrollment priority given to MIE students
Winter 2023, AnnuallyM. ConsensInformation Engineering
MIE1513HS: Decision Support Systems

Syllabus: Contact Instructor
Course Delivery:
In-Person
Course Day & Time: Tuesday 10:00am-1:00pm Lecture
Room: RS 208

Wednesday 1:00pm-3:00pm Lab
Room: RS 303

Enrollment priority given to MIE students
Winter 2023, AnnuallyE. CohenInformation Engineering
MIE1514HF: Systems Design and Engineering: A Product Perspective

The course objective is to familiarize students with the principles and methods of systems engineering in the design of products. It includes specific practical examples and projects to aid in understanding and appreciating fundamental principles. Students will apply the various systems engineering methods and techniques as appropriate across all phases of a product’s life cycle. The course will prepare students who are or will be involved in high technology complex systems, and the preliminary and detailed design of products.


Course Delivery:
In-Person
Course Day & Time: Wednesday 5:00pm-8:00pm
Room: MS 3278

Enrollment priority given to MIE students
Fall 2022, AnnuallyN. Youssef Information Engineering
MIE1516HS: Structured Learning and Inference

This Research Course will provide students with the conceptual, theoretical, and implementational foundations of fundamental tools for structured learning and inference: probabilistic graphical models, probabilistic programming, and deep neural networks. The course will focus on the design and training of structured models for specific application use cases such as answering probabilistic queries over data, sequence tagging and classification, and image recognition through programmingintensive projects including a final independently proposed research project with report component.
Not offered in Winter 2022 or Winter 2023.Winter, AnnuallyS. SannerInformation Engineering
MIE1517HF:
Introduction to Deep Learning

Course Delivery:
In-Person
Course Day & Time: Wednesday 1:00pm-4:00pm
Room: GB 221

Enrollment priority given to MIE students
Fall 2022, AnnuallyS. ColicInformation Engineering
MIE1517HS:
Introduction to Deep Learning

Course Delivery:
In-Person
Course Day & Time: Thursday 1:00pm-4:00pm
Room: RS 208

Enrollment priority given to MIE students
Winter 2023, AnnuallyTBCInformation Engineering
MIE1603HS: Integer Programming (for Research students)

Formulation of integer programming problems and the characterization of optimization problems representable as integer and mixed-integer programs. The degree of difficulty of classes of integer programs and its relation to the structure of their feasible sets. Optimality conditions. Branchand-bound, cutting plane, and decomposition methods for obtaining solutions or approximating solutions.
Course Delivery:
In-Person
Course Day & Time: Wednesday 10:00-12:00pm
Room: BA1230
Thursday 4:00pm-5:00pm
Room: MC 254

Enrollment priority given to MIE students
Winter 2023, Annually ResearchM. BodurOperations Research
MIE1605HF: Stochastic Processes

Syllabus

This course is an introduction to stochastic processes with an emphasis on applications to queueing theory and service Engineering
Course Delivery:
In-Person
Course Day & Time: Tuesday 1:00pm-4:00pm
Room: PB 255

*Course is designed for research students. MEng students interested in taking the course must get permission from Prof. Sarhangian to enrol.

Enrollment priority given to MIE students
Fall 2022, Annually ResearchV. SarhangianOperations Research
MIE1607HS: Stochastic Modeling and Optimization
Syllabus
Course is on Hiatus.Occasionally
Research
Operations Research
MIE1612HF: Stochastic Programming and Robust Optimization

Official course description: Stochastic programming and robust optimization are optimization tools dealing with a class of models and algorithms in which data is affected by uncertainty, i.e., some of the input data are not perfectly known at the time the decisions are made. Topics include modeling uncertainty in optimization problems, two-stage and multistage stochastic programs with recourse, chance constrained programs, computational solution methods, approximation and sampling methods, and applications. Knowledge of linear programming, probability and statistics are required, while programming ability and knowledge of integer programming are helpful.
Course Delivery:
In-Person
Course Day & Time: Thursday 3:00pm-5:00pm
Room: GB 304

Friday 12:00pm-1:00pm
Room: SS 1085

Enrollment priority given to MIE students
Fall 2022, Annually ResearchM. BodurOperations Research
MIE1613HS: Stochastic Simulation
Syllabus

Course Delivery:
In-Person
Course Day & Time: Thursday 9:00am-12:00pm
Room: WB 219

Enrollment priority given to MIE students
Winter 2023, AnnuallyV. SarhangianOperations Research
MIE1615HS: Markov Decision Processes

This is a course to introduce the students to theories of Markov decision processes. Emphasis will be on the rigorous mathematical treatment of the theory of Markov decision processes. Topics will include MDP finite horizon, MDP with infinite horizon, and some of the recent development of solution method.
Course Delivery:
In-Person
Course Day & Time: Tuesday 9:00am-12:00pm
Room: HA 401

Enrollment priority given to MIE students
Fall 2022, Annually ResearchC.G. LeeOperations Research
MIE1616HS: Research Topics in Healthcare Engineering

This is a seminar-based course in which we will review a variety of papers in the field of healthcare OR. We will survey and evaluate several papers within topic areas and try to identify areas for potential future research. Some papers will be distinctly OR, while others will come from researchers in the field of health policy and health economics. One thing that you will notice as we go through the literature is that the area of healthcare engineering is interdisciplinary in nature and encourages solutions that are derived from various areas of expertise. This interdisciplinary approach is also encouraged through the many funding bodies that currently support healthcare engineering research in North America. The Canadian Institute of Health Research, CIHR, (http://www.cihr-irsc.gc.ca) funds the majority of healthcare research in Canada. It is composed of 14 virtual ‘institutes’ that represent all facets of health research. The Institute of Health Services and Policy Research, IHSPR, is most related to the type of collaborative research discussed above. It supports innovative research, capacity-building and knowledge translation in order to improve health care service delivery. In 2001 and 2004, IHSPR was involved with national consultations on health services priorities entitled “Listening for Direction”. The result of these consultations was a set of priorities for Canadian researchers in the area of health care policy and management. Of course, not all of the topics are relevant to Healthcare Engineering, but many of the readings and articles discussed in this class will align with the most recent set of priorities:
Course Delivery:
In-Person
Course Day & Time: Friday 1:00pm-4:00pm
Room: UC 161

Enrollment priority given to MIE students

Winter 2023, Annually, ResearchM. CarterOperations Research
MIE1619HS: Constraint Programming and Hybrid Optimization

The topic of MIE1619 is the “non-traditional” optimization technique Constraint Programming (CP) and hybrids of CP with approaches in OR. Heavy emphasis will be placed on similarities and differences between CP and mathematical programming including the unified framework of search, relaxation, and inference. The primary hybrid approaches will be based on constraint generation approaches including Logic-based Benders Decomposition and SAT Modulo Theory. This is an advanced graduate level course intended for research-stream students. MEng students are not admitted without special permission from the instructor. The course will be challenging. Students are expected to read material in preparation for each lecture and, in a few cases, view online lectures. An objective of this course is to impart skills necessary for an academic career such as paper writing, presentation skills, and writing peer reviews. The main evaluation will be a project where the student is expected to apply techniques discussed in the course to their own research interests: you should do something you weren’t already planning to do as part of your research. A goal of this course is that these projects will be publishable in a peer-reviewed forum.
Course Delivery:
In-Person
Course Day & Time: Tuesday 1:00pm-4:00pm
Room: RS 208

Enrollment priority given to MIE students
Winter 2023, BienniallyC. BeckOperations Research
MIE1620HF: Linear Programming and Network Flows

Rigorous introduction to the theory of linear programming. Simplex method, revised simplex method, duality, dual simplex method. Post-optimality analysis. Interior point methods. Decomposition methods. Network flow algorithms. Maximum flow, shortest path, assignment, min cost flow problems.
Course Delivery:
In-Person
Course Day & Time: Thursday 12:00pm-2:00pm
Room: HS 106

Enrollment priority given to MIE students
Fall 2022, Annually ResearchR. KwonOperations Research
MIE1621HS: Non-Linear Optimization

Course Description: Theory and computational methods of non-linear optimization. Convex sets, convex and concave functions. Unconstrained and Constrained Optimization. Quadratic Programming. Optimality conditions and convergence results. Karush-Kuhn-Tucker conditions. Introduction to penalty and barrier methods. Duality in nonlinear programming.
Course Delivery:
In-Person
Course Day & Time: Monday 3:00pm-6:00pm
Room: MS3278

Enrollment priority given to MIE students
Winter 2023, Annually ResearchR. KwonOperations Research
MIE1622HS: Computational Finance and Risk Management

The objective of the course is to examine the construction of computational algorithms in solving financial problems, such as risk-aware decision-making, asset pricing, portfolio optimization and hedging. Considerable attention is devoted to the application of computational and programming techniques to financial, investment and risk management problems. Materials in this course are quantitative and computational in nature as well as analytical. Topics include mean-variance portfolio optimization, simulation (Monte Carlo) methods, scenario-based risk optimization, hedging, uncertainty modeling, asset pricing, simulating stochastic processes, and numerical solutions of differential equations. Python is the primary computational and modeling software used in this course, we also briefly describe other programming environments such as R, Matlab and C/C++ used in financial engineering. Practical aspects of financial and risk modeling, which are used by industry practitioners, are emphasized.
Course Delivery:
In-Person
Course Day & Time: Monday 6:00pm-9:00pm
Room: BA 1200

Enrollment priority given to MIE students
Winter 2023, AnnuallyO. RomankoOperations Research
MIE1623HS: Introduction to Healthcare Engineering

This course illustrates the use of industrial engineering techniques in the field of healthcare. Common strategic, tactical, and operational decision-making problems arising in healthcare will be approached from an operations research perspective. Unique aspects of healthcare compared to other industries will be discussed. Real-world datasets will be provided to illustrate the complexity of applying standard operations research methods to healthcare.
Course Delivery:
In-Person
Course Day & Time: Wednesday 5:00pm-8:00pm
Room: GB 119

Enrollment priority given to MIE students
Winter 2023, AnnuallyD. Aleman and M. CarterOperations Research
MIE1624HF: Introduction to Data Science and Analytics

The objective of the course is to learn analytical models and overview quantitative algorithms for solving engineering and business problems. Data science or analytics is the process of deriving insights from data in order to make optimal decisions. It allows hundreds of companies and governments to save lives, increase profits and minimize resource usage. Considerable attention in the course is devoted to applications of computational and modeling algorithms to finance, risk management, marketing, health care, smart city projects, crime prevention, predictive maintenance, web and social media analytics, personal analytics, etc. We will show how various data science and analytics techniques such as basic statistics, regressions, uncertainty modeling, simulation and optimization modeling, data mining and machine learning, text analytics, artificial intelligence and visualizations can be implemented and applied using Python. Python and IBM Watson Analytics are modeling and visualization software used in this course. Practical aspects of computational models and case studies in Interactive Python are emphasized.
Course Delivery:
In-Person
Course Day & Time: Tuesday 6:00pm-9:00pm LEC
Room: SF 1105

Thursday 2:00pm-3:30pm TUT
Room: NF 003

Enrollment priority given to MIE students
Fall 2022, AnnuallyO. RomankoOperations Research
MIE1624HS: Introduction to Data Science and Analytics

The objective of the course is to learn analytical models and overview quantitative algorithms for solving engineering and business problems. Data science or analytics is the process of deriving insights from data in order to make optimal decisions. It allows hundreds of companies and governments to save lives, increase profits and minimize resource usage. Considerable attention in the course is devoted to applications of computational and modeling algorithms to finance, risk management, marketing, health care, smart city projects, crime prevention, predictive maintenance, web and social media analytics, personal analytics, etc. We will show how various data science and analytics techniques such as basic statistics, regressions, uncertainty modeling, simulation and optimization modeling, data mining and machine learning, text analytics, artificial intelligence and visualizations can be implemented and applied using Python. Python and IBM Watson Analytics are modeling and visualization software used in this course. Practical aspects of computational models and case studies in Interactive Python are emphasized.
Course Delivery:
In-Person
Course Day & Time: Tuesday 6:00pm-9:00pm
Room: SF 1101

Enrollment priority given to MIE students
Winter 2023, AnnuallyO. RomankoOperations Research
MIE1626HF: Data Science Methods and Quantitative Analysis

This course will equip the students with the fundamental skills and knowledge for: • understanding the statistical foundation of data science and machine learning methods, • approaching active and passive data as artifacts for scientific evaluation, • combining, pre-processing, and cleaning data in practical data science projects, • performing exploratory data analysis and uncovering patterns in data, • analyzing data and making inference using methods from statistical learning, • resampling data and evaluate the error of any computational estimate, • using confidence intervals, analysis of variance, and hypothesis testing to explain data, • implementing linear and nonlinear regression models for prediction and inference, • designing and understanding tree-based models and support vector machines, • detecting and avoiding misleading statistical figures, information visualization, and other forms of data presentation which lack a logical coherence. This is an intensive and high-demand course which requires active engagement and participation.
Course Delivery:
In-Person
Course Day & Time: Tuesday 10:00am-12:00pm Lab
Room: RS303
Thursday 9:00am-12:00pm Lecture
Room: RS208

Enrollment priority given to MIE students
Fall 2022, AnnuallyS. ArefInformation Engineering
MIE1628HF: Cloud-Based Data Analytics (formerly Big Data Science)

This course covers Big Data fundamentals including an overview of Hadoop MapReduce and Spark. Covers Cloud fundamentals and Big Data Analytics on Cloud-based platforms including an introduction to a specific Cloud platform such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform along with common practices for this platform. Covers Cloud technologies to store and process structured, unstructured and semi-structured data. Covers Cloud-based implementation of Real-time Analytics and Machine Learning.
Course Delivery:
Section 0101: In-Person
Course Day & Time: Friday 4:30pm-7:30pm
Room: SS 2105

Section 0201: ONLINE
Course Day & Time: Saturday 12:30pm-3:30pm

Enrollment priority given to MIE students

*It is strongly recommended that students take APS1070 before enrolling in this course.

*MIE1624H, ECE1513H, CSC2515 (or equivalent) are strongly recommended but not required.
Fall 2022, AnnuallySnehaOperations Research
MIE1628HS: Cloud-Based Data Analytics (formerly Big Data Science)

This course covers Big Data fundamentals including an overview of Hadoop MapReduce and Spark. Covers Cloud fundamentals and Big Data Analytics on Cloud-based platforms including an introduction to a specific Cloud platform such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform along with common practices for this platform. Covers Cloud technologies to store and process structured, unstructured and semi-structured data. Covers Cloud-based implementation of Real-time Analytics and Machine Learning.
Course Delivery:
Section 0101: In-Person
Course Day & Time: Friday 4:30pm-7:30pm
Room BA 1220

Section 0201: ONLINE
Course Day & Time: Saturday 12:30pm-3:30pm

*It is strongly recommended that students take APS1070 before enrolling in this course.

*MIE1624H, ECE1513H, CSC2515 (or equivalent) are strongly recommended but not required.

Enrollment priority given to MIE students
Winter 2023, AnnuallySnehaOperations Research
MIE1628HY: Cloud-Based Data Analytics (formerly Big Data Science)

This course covers Big Data fundamentals including an overview of Hadoop MapReduce and Spark. Covers Cloud fundamentals and Big Data Analytics on Cloud-based platforms including an introduction to a specific Cloud platform such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform along with common practices for this platform. Covers Cloud technologies to store and process structured, unstructured and semi-structured data. Covers Cloud-based implementation of Real-time Analytics and Machine Learning.
Course Delivery:

Section 0101: ONLINE
Course Day & Time: Friday, 5:00pm-8:00pm (EST)

Section 0201: ONLINE
Saturday, 12:00pm-3:00pm (EST)

* Course start date is May 6th, ending August 5th, 2022

*It is strongly recommended that students take APS1070 before enrolling in this course.

*MIE1624H, ECE1513H, CSC2515 (or equivalent) are strongly recommended but not required.
Summer 2022, AnnuallySnehaOperations Research
MIE1653HS: Integer Programming Applications (for M.Eng. students)

Formulation of integer programming problems and the characterization of optimization problems representable as integer and mixed-integer programs. The degree of difficulty of classes of integer programs and its relation to the structure of their feasible sets. Optimality conditions. Branchand-bound, cutting plane, and decomposition methods for obtaining solutions or approximating solutions.
Course Delivery:
In-Person
Course Day & Time: Wednesday 10:00-12:00pm
Thursday 4:00pm-5:00pm
Room: TBD

Enrollment priority given to MIE students
Winter 2023, AnnuallyM. BodurOperations Research
MIE1666HF: Machine Learning for Mathematical Optimization
Course Delivery:
In-Person
Course Day & Time: Monday 3:00pm-6:00pm
Room: SF 2202

Enrollment priority given to MIE students
Fall 2022, AnnuallyE. KhalilOperations Research
MIE1699HF: Special Topics in Operations Research
Syllabus
TBDFall, OccasionallyTBDOperations Research
MIE1705HF: Thermoplastics Polymer Processing

This course is designed to provide the background for an understanding of the wide field of polymer processing, and provide a strong foundation including fundamentals and applications of polymer processing. Topics include: fundamentals of polymers, extrusion, injection molding, die forming, mixing, and other common plastics processes such as fiber spinning, blow molding, rotational molding, coating, etc.
Course Delivery:
In-Person
Course Day & Time: Friday 9:00am-12:00pm
Room: BA 2179
Winter 2023, AnnuallyP. LeeMechanics and Materials
MIE1706HS: Manufacturing of Cellular and Microcellular Polymers
Syllabus
Not offered Winter 2023.Winter, BienniallyC. ParkMechanics and Materials
MIE1707HS: Structure-Property Relationships of Thermoplastic and Composite Foams

Syllabus: Contact Instructor
Not offered Winter 2023.Winter, Biennially ResearchC. ParkMechanics and Materials
MIE1708HS: Collision Reconstruction

This course provides the participant with a comprehensive understanding of widely-accepted techniques of vehicular collision reconstruction based on physical and engineering principles. The course covers Energy, Impulse and Momentum fundamentals and how they are engaged to obtain valuable information from collisions, in order to answer important questions about culpability in various litigation arenas. Content is reinforced with real-world examples. A wide variety of collision types (passenger vehicle, motorcycle, cyclist, pedestrian, heavy truck) and modes (high speed, low speed, rollover, tire failure) are addressed in the context of various contributors to collisions, whether they be from the operator, vehicle, or the roadway environment. Specialized techniques for evaluation of the use, performance, and effectiveness of restraint systems, and the avoidability of collisions are also covered. The latest technologies for harvesting data from ‘black boxes’ are covered, and state of the art computer simulation techniques are incorporated into the teachings.
Course Delivery:
In-Person
Course Day & Time: Wednesday 3:00pm-5:00pm
Room: BA 2159

Winter 2023, AnnuallyJ. CataniaMechanics and Materials
MIE1709HF: Continuum Mechanics

Continuum Mechanics is the study of the response of the matter on a macroscopic scale to different loading conditions, neglecting the structure of the matter on the smaller scale (i.e., molecular scale). It brings out the general principles common to all media and discusses the assumptions for developing constitutive equations of idealized materials (e.g., solid and fluid). The developed fundamentals can be applied to engineering problems such as elasticity, viscoelasticity, plasticity, linearly viscous fluid, etc.
Course Delivery:
In-Person
Course Day & Time: Thursday 1:00pm-4:00pm
Room: RS 208
Fall 2022, AnnuallyK. BehdinanMechanics and Materials
MIE1714HF: Failure Analysis

Engineering is the science of predictive modelling based on application of Physical Laws, and prototyping to verify designs. This applies to all fields. Good Engineering prevents Failure. The course centers on the Theory of Failure Analysis and how it directs engineering activity: design, research, quality systems, continuous improvement, innovation, new knowledge creation, systemic failure, and business management.
Course Delivery:
In-Person
Course Day & Time: Thursday 6:00pm-9:00pm
Room: WB 219
Fall 2022, AnnuallyS. CoatesMechanics and Materials
MIE1715HF: Life Cycle Engineering

This course introduces the fundamentals of both product and process engineering with an emphasis on life cycle models. A mixture of practical and theoretical topics, methodologies, principles, and techniques are covered such as Life Cycle Analysis, Design For Assembly (DFA), Design For Manufacturing (DFM), Design For Environment (DFE), etc. Students develop an understanding of the performance, cost, quality and environment implications of both product design and manufacture and become capable of translating these into engineering “cradle-tograve” responsibility requirements, goals, and specifications in order to maximize the values of products and the effectiveness of supply chain management while containing the costs to manufacturer, the user, and the society.
Course Delivery:
In-Person
Course Day & Time: Wednesday 4:00pm-7:00pm
Room: MS 2173
Fall 2022, AnnuallyP. RahimiMechanics and Materials
MIE1718H: Computer Integrated Manufacturing
Syllabus
Summer, 2022
ONLINE
May 1 – Aug 19
10am-3pm (EST)
*Class dates are May 2, 3, 6, 9, 10
*Project Presentation will be held in August.

Registration to be approved by Prof. Benhabib (please submit pertinent transcripts, via email, for approval).
Summer 2022, Occasionally

B. BenhabibMechatronics and Dynamics
MIE1720HS: Creativity in Conceptual Design

Syllabus: Contact Instructor
Course Delivery:
In-Person
Course Day & Time: Thursday 12:00pm-2:00pm
Room: UC 63

Enrollment priority given to MIE students
Winter 2023, AnnuallyL. ShuHuman Factors & Ergonomics
MIE1721HS: Reliability
Syllabus
Course Delivery:
In-Person
Course Day & Time: Thursday 6:00pm-9:00pm
Room: BA 1240

Enrollment priority given to MIE students
Winter 2023, AnnuallyD. BanjevicOperations Research
MIE1723HF: Engineering Asset Management

This course is concerned with the determination of optimal maintenance and replacement practices for components and capital equipment. The lectures will be supplemented by case study assignments including short-term deterministic replacement; short-term probabilistic replacement; use of OREST, PERDEC, AGE/CON, EXAKT and SMS software for the optimization of physical asset management decisions. Professor Taghipour will cover the topic: Role of Emerging Technologies in Physical Asset Management along with a brief introduction to inspection optimization of assets with hidden failures or soft failures, sustainable asset management along with the application of sustainable asset management for utilization, purchase, and disposal of a fleet of assets.
Course Delivery:
In-Person
Course Day & Time: Wednesday 5:00pm-8:00pm
Room: ES B149

Enrollment priority given to MIE students
Fall 2022, AnnuallyJanet LamOperations Research
MIE1724HF: Additive Manufacturing in Engineering Applications

The aim of this course is to help students understand the concepts of AM and their role in design and fabrication of complex structures. Also, the course will introduce state-of-the-art approaches to “3D printing”, which is the more common term to the more professionally utilized “Additive Manufacturing” (AM) term. Students will be able to follow a design paradigm through careful analysis of complex structures and complete an AM process flow through CAD conceptualization, conversion to STL files, transfer to AM machine, machine conditioning, removal/clean up and post-processing. Also, design for AM (DfAM) is introduced to optimize product fabrication, controlled by part orientation, support design, hollowing out components, constraining features/undercuts, interlock structures and multi-material compatibilities. Case studies will be introduced with AM for investment casting and part fabrication without a conventional CAD file, with focus on medical modeling and reverse engineering data. In recent years, new approaches to AM solutions have produced a large range of controllability and size ranges. Examples of emerging technologies are Multi-Jet Printing (MJP), AM+CNC, two-photon lithography (for nanoscale AM) and Volumetric 3D Printing. Ultimately, students will be able to apply and scale models from the most focused technical perspective to eventual AM fabrication of complex lightweight designs… and never rely on randomized approaches to AM.
Not offered Fall 2022Fall, AnnuallyTBDMechanics and Materials
MIE1725HF: Soft Materials and Machines
Not offered Winter 2023Winter, Occasionally Research
TBDMechanics and Materials
MIE1727HF: Statistical Methods of Quality Assurance

Awareness of the importance of quality has increased dramatically. Understanding and improving quality is a key factor leading to company’s success and its enhanced competitive position. The course focuses on the following topics in Quality Assurance: Introduction to quality engineering, TQM, costs of quality, quality and productivity, statistical process control, process capability analysis and supplier-producer relations, quality standards and certification, six sigma philosophy and methodology, quality/process improvement using designed experiments, and an overview of acceptance sampling.
Course Delivery:
In-Person
Course Day & Time: Monday 1:00pm-3:00pm
Room: BA 2139
Wednesday 1:00pm-2:00pm
Room: GB 248

Enrollment priority given to MIE students
Winter 2023, BienniallyTBDOperations Research
MIE1740HS: Smart Materials and StructuresNot offered Winter 2023
Winter, Annually
H. NaguibMechanics and Materials
MIE1744HF: Nanomechanics of Materials

Materials can exhibit dramatically altered mechanical properties and physical mechanisms when they have characteristic dimensions that are confined to small length-scales of typically below ~ 100 nm. These size-scale effects in mechanics result from the enhanced role of surfaces and interfaces, defects and material variations, and quantum effects. Nanostructured materials which exhibit these size-scale effects often have extraordinary mechanical properties as compared to their macroscopic counterparts. This course is designed to provide an introduction to nanomechanics and size-scale mechanical phenomena exhibited by nanostructured materials, and provide a platform for future advanced studies in the areas of computational/experimental nanomechanics and nanostructured materials design and application. Topics include: an introduction to nanomechanics; atomic/molecular structure of materials & nanomaterials synthesis; limitations of continuum mechanics, nanomechanical testing techniques (AFM, nanoindentation, in situ SEM/TEM); atomistic modeling techniques (DFT, MD, Course-grained MD); size-scale strength, plasticity, and fracture ; Hall-Petch strengthening, superplasticity; nanotribology, atomistic origins of friction, nanoscale wear; nano-bio-mechanics; mechanics of nanocomposites.
Course Delivery:
In-Person
Course Day & Time: Thursday 1:00pm-3:30pm
Room: UC A101
Fall 2022, Annually ResearchT. FilleterMechanics and Material
MIE1745HF: Surface Engineering

One materials-related topic that is important for mechanical, civil engineers is the interactions between solids and liquids. Why do some materials absorb water when others do not? How does broccoli remain dry after washing it? How to non-stick pans work? Why is the build plate adhesion of 3D printers so important? What properties of the molten plastics are important for additive manufacturing? This course will discuss how liquids interact with solids, and how these interactions are affected by the chemical, physical, and mechanical properties of the solid, in addition to the viscosity, surface tension, and chemical structure of the liquid. The objective is for students to gain a deep understanding about how liquids and solids interact at interfaces. Examples will be drawn from all fields of engineering and the course is not tilted towards any one discipline in particular.
Course Delivery:
In-Person
Course Day & Time:
Tuesday 9:00am-10:30am
Room: BA B024

Thursday 9:00am-10:30am
Room: BA B024
Fall 2022, Annually K. GolovinMechanics and Material
MIE1804H1: Finite Element Analysis in Engineering Design

Course Delivery:
In-Person
Course Day & Time:
Monday 2:00pm-4:00pm
Room: MB 123 & AB114

Thursday 9:00am-11:00am
Room: BA 1210
Fall 2022, AnnuallyS. MeguidMechanics and Materials
MIE1809HS: Advanced Mechatronics
Syllabus
Course Delivery:
In-Person
Course Day & Time: Wednesday 2:00pm-4:00pm
Room: BA 2165
Winter 2023, AnnuallyR. Ben MradMechatronics and Dynamics
MIE2002H: Readings in Industrial Engineering I SupervisorReading Courses
MIE2003H: Readings in Industrial Engineering IIReading Courses
MIE2004H: Readings in Mechanical Engineering IReading Courses
MIE2005H: Readings in Mechanical Engineering IIReading Courses
MSE1043HS: Composite Materials EngineeringCourse Delivery:
In-Person
Course Day & Time: Friday 12:00pm - 3:00pm
Room: GB221

co-taught with MSE443
Fall 2022, AnnuallyH. NaguibMechanics and Materials
TEP1502HF: Leadership in Product Design

The objective of this course is to prepare students for the teams, processes and decisions encountered during complex socio-technical engineering design projects. The course will equip students with tools and strategies for leading and following other leaders in this context. Students will have the opportunity to apply their learning on a term-long project. The course readings will be sourced from real industry cases and experiences.
Course Delivery:
In-Person
Course Day & Time: Tuesday 9:00am-12:00pm
Room: TBD
Fall 2022, AnnuallyA. OlechowskiAPS Engineering Courses

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