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 celeste@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:
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.
| Course | Course details | Session offered | Instructor | Course areas |
|---|---|---|---|---|
| AER1410HF: Topology Optimisation Syllabus: Contact Instructor | Course Delivery: In-Person | Winter 2022, Annually | C. Steeves | Mechanics 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, Annually | R. Kwon | APS Engineering Courses |
| CIV1240HS: Building Performance Assessment Syllabus: Contact instructor | Course Delivery: not offered in Winter 2023 | Winter, Annually | M. Touchie | Thermal Sciences |
| MIE504HS: Applied Computational Fluid Dynamics | Schedule posted here | Winter 2023, Annually | A. Dolatabadi | Fluid Mechanics |
| MIE505H1: Micro/Nano Robotics Syllabus: Contact Instructor | Schedule posted here | Winter, Annually | E. Diller | Mechatronics and Dynamics |
| MIE506H1: MEMS Design and Microfabrication Syllabus: Contact Instructor | Schedule posted here | Winter 2023, Annually | M. Bakri-Kassem | Mechatronics and Dynamics |
| MIE507HS: Heating, Ventilating, and Air Conditioning (HVAC) Syllabus: Contact instructor | Schedule posted here | Fall 2022, Annually | M. Touchie | Fluid Mechanics |
| MIE515H1: Alternative Energy Systems Syllabus: Contact instructor | Schedule posted here | Fall 2022, Annually | A. Dolatabadi | Thermal Sciences |
| MIE516H1: Combustion and Fuels Syllabus: Contact instructor | Schedule posted here | Fall 2022, Annually | M. Thomson | Thermal Sciences |
| MIE517H1: Fuel Cell Systems Syllabus: Contact Instructor | Schedule posted here | Winter 2023, Annually | O. Kesler | Mechanics and Materials |
| MIE519H1: Advanced Manufacturing Technologies Syllabus: Contact Instructor | Schedule posted here | Winter 2023, Annually | P. Lee | Mechanics and Materials |
| MIE520H1: Biotransport Phenomena Syllabus: Contact instructor | Schedule posted here | Fall 2022, Annually | L. You | Fluid Mechanics |
| MIE523H1: Engineering Psychology and Human Performance Syllabus: Contact Instructor | Schedule posted here | Fall 2022, Annually | TBD | Human Factors & Ergonomics |
| MIE533HS: Waves and Their Applications in Non-Destructive Testing and Imaging | Schedule posted here | Winter 2023, Occasionally Research | A. Mandelis | Thermal Sciences |
| MIE540H1: Product Design Syllabus: Contact Instructor | Schedule posted here | Winter 2023, Annually | D. Nacson | Mechanics and Materials |
| MIE542H1: Human Factors Integration Syllabus: Contact Instructor | Schedule posted here | Winter 2023, Annually | R. Leger & K. Iwasa-Madge | Human Factors & Ergonomics |
| MIE550H: Advanced Momentum, Heat and Mass Transfer Syllabus | Schedule posted here | Winter 2023, Annually | A. 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, Annually | A. Esensoy | Operations Research |
| MIE562H1: Scheduling Syllabus: Contact Instructor | Schedule posted here | Fall 2022, Annually | C. Beck | Operations Research |
| MIE563H: Engineering Analysis II Syllabus: Contact Instructor | Schedule posted here | Fall 2022, Annually | D. Steinman | Thermal Sciences |
| MIE566H1: Decision Analysis Syllabus: Contact Instructor | Schedule posted here | Fall 2022, Annually | TBD | Operations 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, Annually | C.G. Lee | Operations Research |
| MIE1001HS: Advanced Dynamics Syllabus | Not offered in Winter 2022. | Winter, Annually Research | E. Diller | Mechatronics and Dynamics |
| MIE1005HF: Theory of Vibrations Syllabus | Course Delivery: In-Person Course Day & Time: Tuesday 1:00pm-4:00pm Room: RS 208 | Fall 2022, Annually | K. Behdinan | Mechatronics 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, Annually | J. O'Keefe | Mechatronics 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. Bakhari | Mechatronics 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, Annually | A. 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, Annually | J. Mills | Mechatronics 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, Annually | G. Nejat | Mechatronics 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, Annually | A. Goldenberg | Mechatronics 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, Annually | A. Goldenberg | Mechatronics 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 2022 | A. Goldenberg | Mechatronics 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. Sun | Mechatronics and Dynamics |
| MIE1101HF: Advanced Classical Thermodynamics Syllabus | Course is on Hiatus | Occasionally, Research | C. Ward | Thermal 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, Occasionally | S. Chandra | Thermal 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, Annually | D. Sinton | Thermal 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, Annually | O. Kesler | Mechanics 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, Annually | J. Lebenhaft | Thermal 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, Annually | H. Hasanein | Thermal 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, Biennially | D. Warnica | Thermal Sciences |
| MIE1199HS: Special Topics in Thermal Sciences - "Thermal Management of EV Batteries and Chargers’’ | Course Delivery: In-Person Course Day & Time: Wednesday 4:00pm-7:00pm Room: MY380 | Winter 2023, Occassionally | C. Amon | Thermal 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, Annually | E. Young | Fluid Mechanics |
| MIE1207HF: Structure of Turbulent Flows Syllabus | Course Delivery: In-Person Course Day & Time: Wednesday 10:00am-12:00pm Room: BA B024 | Fall 2022, Annually | P. Sullivan | Fluid 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, Annually | X. Liu | Fluid 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, Annually | H. Montazeri | Fluid 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, Biennially | J. Mostaghimi | Fluid Mechanics |
| MIE1222HF: Multiphase Flows Syllabus | Course Delivery: In-Person Course Day & Time: Tuesday 9:00am-12:00pm Room: SS 2114 | Fall 2022, Annually | N. Ashgriz | Fluid 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, Occasionally | A. Guenther | Fluid Mechanics |
| MIE1240HF: Wind Power Syllabus | Course Delivery: In-Person Course Day & Time: Monday 10:00am-1:00pm Room: BA 1210 | Fall 2022, Annually | J. Moran | Fluid Mechanics |
| MIE1241HF: Energy Management Syllabus | Course Delivery: In-Person Course Day & Time: Monday 3:00pm-6:00pm Room: BA 1210 | Fall 2022, Annually | J. Moran | Fluid 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, Annually | A. Nabovati | Fluid Mechanics |
| MIE1299HS: Special Topics in Fluid Mechanics Syllabus: Contact instructor | Not offered in 2022. | Occasionally | Fluid Mechanics | |
| MIE1301HS: Solid Mechanics Syllabus: Contact Instructor | Not offered in Winter 2023. | Winter, Annually | TBD | Mechanics 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, Annually | S. Meguid | Mechanics 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, Annually | Y. Sun and L. You | Mechanics 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, Annually | E. Kittel | Human 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 Research | M. Chignell | Human 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 Research | R. Kealey | Human 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, Annually | E. King | Human Factors & Ergonomics |
| MIE1412HS: Human-Automation Interaction | Not offered in Winter 2023. | Winter, Annually Research | G. Jamieson | Human Factors & Ergonomics |
| MIE1413HS: Statistical Models in Empirical Research | Not offered in Winter 2023. | Winter , Annually Research | B. Donmez | Human 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 Research | M. Masliah | Human 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 Research | A. Reiner & K. Christoffersen | Human 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, Annually | M. Alfred | Human 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, Annually | L. Shu | Human 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, Annually | M. Gruninger | Information Engineering |
| MIE1505HS: Enterprise Modelling Syllabus | Not offered in Winter 2023 | Winter, Biennially Research | M. Gruninger | Information Engineering |
| MIE1510HS: Formal Techniques in Ontology Engineering Syllabus: Contact Instructor | Not offered in Winter 2023 | Winter, Biennially Research | M. Gruninger | Information 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, Annually | M. Consens | Information 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, Annually | E. Cohen | Information 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, Annually | N. 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, Annually | S. Sanner | Information 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, Annually | S. Colic | Information 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, Annually | TBC | Information 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 Research | M. Bodur | Operations 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 Research | V. Sarhangian | Operations 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 Research | M. Bodur | Operations 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, Annually | V. Sarhangian | Operations 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 Research | C.G. Lee | Operations 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, Research | M. Carter | Operations 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, Biennially | C. Beck | Operations 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 Research | R. Kwon | Operations 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 Research | R. Kwon | Operations 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, Annually | O. Romanko | Operations 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, Annually | D. Aleman and M. Carter | Operations 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, Annually | O. Romanko | Operations 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, Annually | O. Romanko | Operations 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, Annually | S. Aref | Information 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, Annually | Sneha | Operations 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, Annually | Sneha | Operations 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, Annually | Sneha | Operations 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, Annually | M. Bodur | Operations 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, Annually | E. Khalil | Operations Research |
| MIE1699HF: Special Topics in Operations Research Syllabus | TBD | Fall, Occasionally | TBD | Operations 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, Annually | P. Lee | Mechanics and Materials |
| MIE1706HS: Manufacturing of Cellular and Microcellular Polymers Syllabus | Not offered Winter 2023. | Winter, Biennially | C. Park | Mechanics and Materials |
| MIE1707HS: Structure-Property Relationships of Thermoplastic and Composite Foams Syllabus: Contact Instructor | Not offered Winter 2023. | Winter, Biennially Research | C. Park | Mechanics 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, Annually | J. Catania | Mechanics 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, Annually | K. Behdinan | Mechanics 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, Annually | S. Coates | Mechanics 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, Annually | P. Rahimi | Mechanics 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. Benhabib | Mechatronics 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, Annually | L. Shu | Human 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, Annually | D. Banjevic | Operations 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, Annually | Janet Lam | Operations 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 2022 | Fall, Annually | TBD | Mechanics and Materials |
| MIE1725HF: Soft Materials and Machines | Not offered Winter 2023 | Winter, Occasionally Research | TBD | Mechanics 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, Biennially | TBD | Operations Research |
| MIE1740HS: Smart Materials and Structures | Not offered Winter 2023 | Winter, Annually | H. Naguib | Mechanics 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 Research | T. Filleter | Mechanics 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. Golovin | Mechanics 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, Annually | S. Meguid | Mechanics and Materials |
| MIE1809HS: Advanced Mechatronics Syllabus | Course Delivery: In-Person Course Day & Time: Wednesday 2:00pm-4:00pm Room: BA 2165 | Winter 2023, Annually | R. Ben Mrad | Mechatronics and Dynamics |
| MIE2002H: Readings in Industrial Engineering I | Supervisor | Reading Courses | ||
| MIE2003H: Readings in Industrial Engineering II | Reading Courses | |||
| MIE2004H: Readings in Mechanical Engineering I | Reading Courses | |||
| MIE2005H: Readings in Mechanical Engineering II | Reading Courses | |||
| MSE1043HS: Composite Materials Engineering | Course Delivery: In-Person Course Day & Time: Friday 12:00pm - 3:00pm Room: GB221 co-taught with MSE443 | Fall 2022, Annually | H. Naguib | Mechanics 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, Annually | A. Olechowski | APS Engineering Courses |
