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Civil Engineering 2025

CIVE 001: Duration of extreme synoptic wind storms for performance-based wind design of tall timber buildings (Bezabeh)

Professor Matiyas Bezabeh

matiyas.bezabeh [at] mcgill.ca
4383248337
Research Area
Wind Engineering
Description
The increasing popularity of timber construction is primarily driven by the ongoing effort to decarbonize the construction industry. With engineered timber panels, tall mass timber buildings have reached heights equivalent to mid-rise concrete and steel buildings. Engineered timber panels are lightweight and less stiff than concrete and steel buildings, which makes the design of tall mass timber buildings wind-critical. However, existing wind design approaches in building codes and literature are formulated considering tall buildings constructed with conventional materials such as concrete and steel. Consequently, their use for tall mass timber building design may produce costly design solutions requiring timber cross sections that are commercially unavailable. Recent studies have proved that an optimal design can be achieved through performance-based wind design (PBWD). In traditional design methods, the specified design wind loads and the capacity of structural members are not dependent on the duration of wind loads. Contrary to the current design approach, when structural damage is considered in PBWD, the nonlinear inelastic response and damage accumulation depend highly on wind duration (dwell time). Therefore, this research project will develop new analytical equations to estimate the duration of synoptic wind storms for PBWD of tall timber buildings. In the project, full-scale extratropical cyclone (synoptic) wind data will be used for validation. The proposed project will contribute to the decarbonization of the construction industry and the increase in the use of timber, thereby enabling Canada to achieve its objective of becoming a carbon-neutral economy by 2050.
Tasks per student
Step 1: Use upcrossing method to fit the directional distribution of wind climate data for various cities in Canada.
Step 2: Develop analytical equations to estimate the duration of extreme synoptic wind for structural design of timber buildings based on the directional fit in Step 1.
Step 3: Validate the equations developed in Step 2 based on full-scale wind speed data recorded in Denmark during Cyclone Anatol.

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Deliverables per student
New analytical equations to estimate the duration of synoptic wind storms for the wind design of tall buildings.
Number of positions

1

Academic Level

No preference

Location of project

in-person

CIVE 002: Field investigation and data analysis of weight-in-motion date for design loads on bridges (Chouinard)

Professor Luc Chouinard

luc.chouinard [at] mcgill.ca

514-398-6446
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Research Area
Structural engineering
Data analysis
Machine learning
Description听
The project is to participate in the collection and analysis of data from cameras and sensors on several bridges around Montreal, and to develop filters to identify the various of trucks and obtain weight distributions for each class.
Tasks per student
Collect WIM data and correlate with image analysis data to identify trucks with special weight permits.
Develop filters to be applied to WIM data in order to automatically identify permit trucks and to estimate the effect on maximum annual mean loads on bridges using statistical approaches or machine learning.

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Deliverables per student
Literature review on the analysis of WIM for bridge design loads.
Propose filtering algorithms to identify trucks with special permits in EIM data.
Final report
Number of positions

1

Academic Level

Year 3

Location of project

in-person

CIVE 003: Enhanced TiO2 Solar Photocatalytic Nanomaterials for Water Treatment (Loeb)

Professor Stephanie Loeb

stephanie.loeb [at] mcgill.ca
438-872-7190
Research Area
Nanomaterial synthesis and characterization, environmental engineering, water treatment
Description
Harnessing solar energy for water treatment is a highly desirable approach to provide safe water in resource limited locations. Advanced oxidation using nanoparticle semiconductor photocatalysts has several advantages as it obviates the need to continuously supply precursor chemicals and can generate highly oxidative electron holes in addition to reactive oxygen species (ROS) that can contribute to the degradation of more challenging recalcitrant organics. The preferred photocatalytic nanomaterial for water treatment applications, TiO2, has a relatively wide bandgap (Eg) (~3.1 eV; 400 nm). Unmodified TiO2 can be applied in solar applications, however, its efficiency is limited by its poor spectral overlap with the most abundant solar wavelengths. Aluminum plasmonic materials are low-cost and highly tunable, with the ratio of Al:Al2O3 able to modulate absorption across UV and visible wavelengths. To enhance photocatalytic efficiency without reducing the bandgap, Al nanoparticle decorated TiO2 photocatalyst could operate within the narrow wavelengths range available for wide bandgap solar photocatalysis. This project involves the fabrication, characterization and evaluation of novel plasmonic TiO2 nanomaterials enhanced with Al nanoparticles. The student will work under the supervision of the PI and graduate students to systematically test these materials against the P25 TiO2 industry standard with probe compounds in terms of degradation capability, stability and durability in performance over periods of time.
Tasks per student
the fabrication, characterization and evaluation of novel plasmonic TiO2 nanomaterials enhanced with Al nanoparticles. Performance testing against industry standard material.

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Deliverables per student
Poster and summary report of experiment data
Number of positions

1

Academic Level

No preference

Location of project

in-person

CIVE 004: Mechanical characterization of masonry and geosynthetics materials (Malomo)

Professor Daniele Malomo

daniele.malomo [at] mcgill.ca
Research Area
Structural engineering, materials engineering
Description
Older masonry walls are prone to failure due to lateral and settlement loading. This project seeks to characterize mechanically the response of masonry assemblies and constituents in conjunction with geosynthetics-based repair materials. Students will be exposed and learn about typical tests done to assess the strength of building materials, through the lens of structural engineering. Project requires to spend most time in lab (in-person) and hands-on approach.
Tasks per student
Main tasks include:
1) perform small-scale mechanical tests assisted by graduate students and alone (after proper training)
2) organize and present data produced
3) support ongoing tests on larger specimens conducted by team members

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Deliverables per student
1) data (photos, recorded measurements) uploaded on team's SharePoint
2) group presentation
3) technical report
Number of positions

1

Academic Level

Year 3

Location of project

in-person

CIVE 005: Sensing Urban Heat Micro-Environments: A Data-Driven Approach to Mapping Heat Stress and Mitigation Strategies (Miranda-Moreno)

Professor Luis听Miranda-Moreno

luis.miranda-moreno [at] mcgill.ca
5146555947
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Research Area
Transportation Engineering and Climate Change Adaptation
Description
A comprehensive methodology for collecting data and assessing urban heat in micro-environments will be developed, combining disaggregate field measurements with deep-learning techniques for data processing and urban heat mapping. A data collection methodology will be designed using instrumented vehicles/bicycles equipped with a set of sensors including an environmental meter, thermal and visual-spectrum video cameras, and a bulb globe temperature meter. These sensors will measure ambient temperature, relative humidity, airspeed, heat index, heat stress, surface temperature and types, road features, vegetation density, and canopy cover, among others. A computer-vision-based approach will be adopted for automated surface temperature estimation using thermal imaging and for the classification of road surface types and built environment features using visible light cameras. State-of-the-art deep learning models will be trained on extensive image datasets from these micro-environments. The trained models will help map urban heat stress in the entire network capturing climate and surface conditions, as well as vegetation and built environmental factors.
Tasks per student
Literature review
Equipment selection and calibration
Study area definition
Definition of data collection protocols
Conduct field tests
Data collection including quality assurance
Regularly check sensor performance and data integrity during collection.
Extract and label images from thermal and visible-light cameras
Deep learning model training
Model validation and spatial analysis
Results interpretation and reporting: develop heat maps and visualizations to effectively communicate results.

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Deliverables per student
Bi-weekly progress presentations during meetings
Reports: on literature review, data collection protocol and preliminary analysis
Number of positions听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听听Academic Level

1听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 Year 3

Location of project

hybrid remote/in-person - a) students must have a Canadian bank account and b) all students must participate in in-person poster session.

CIVE 006: Integrating Artificial Intelligence into civil engineering education: Current trends and challenges (Ozcer)

Professor Pinar Ozcer

pinar.ozcer [at] mcgill.ca

514 655 3858

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Research Area
Engineering education
Description
With the rapid advancement of artificial intelligence (AI) in the civil engineering industry (E.g. structural health monitoring, infrastructure resiliency, sustainable design), it is important that civil engineering curricula keep up with field practices to prepare future civil engineers to work with AI-based applications. Whereas Canadian engineering accreditation requirements currently do not specifically incorporate AI in the curriculum, civil engineering undergraduate and graduate programs need to consider incorporating these concepts into university curricula to train civil engineers and help them keep up with industry standards after graduation. One of the main challenges for this endeavour is to determine to what extent data science and machine learning literacy is required from civil engineers, and how this training can be integrated into the curriculum when it is already quite intensive in technical content. As well, since AI concepts are relatively new in practice, civil engineering instructors may not fully be prepared to teach these concepts, and students may struggle with AI-literacy. This proposed study has two goals. The first goal is to determine what opportunities exist for integrating AI concepts into civil engineering coursework through a systematic meta-analysis of the current developments shaping AI integration in civil engineering education. The second goal is to determine the challenges and barriers for this integration, including from the standpoint of AI perceptions of instructors. The findings will shine a light on how civil engineering programs can support students and instructors by adapting existing curricula to the changing industry standards with AI.
Tasks per student
Perform a comprehensive global meta-analysis review of peer-reviewed literature discussing AI integration in civil engineering curricula

Assist in developing a quantitative survey that can be used to assess instructor comfort levels with integrating and teaching AI applications in civil engineering

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Deliverables per student
Weekly progress updates
Biweekly meetings to discuss research findings
A database of peer-reviewed literature and annotated bibliography
A repository of survey questions to evaluate instructor perspectives on AI in civil engineering education
A final literature review/report summarizing the findings from the study
A poster to be presented at the SURE fair
Number of positions

1

Academic Level

No preference

Location of project

hybrid remote/in-person - a) students must have a Canadian bank account and b) all students must participate in in-person poster session.

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CIVE 007: Sustainable structures through advanced materials (Shao)

Professor Yi Shao

yi.shao2 [at] mcgill.ca
5143495180
Research Area
Civil Engineering, Structural Engineering
Description
In this project, the student will work with graduate students on projects that utilize advanced materials (e.g., UHPC and GFRP) to develop sustainable structures. For example, we are developing seismic design guidance of GFRP reinforced concrete as well as develop material models for UHPC. We are also developing reconfigurable structures with demountable connections.
Tasks per student
Conduct lab tests for assessing material properties
Conduct lab tests for assessing structural behavior
Perform data analysis and prepare graphs for presentations

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Deliverables per student
Student 1: a material model for capturing the low-cycle behavior of UHPC
Student 2: a report of seismic behavior of GFRP reinforced beam-column joints
Number of positions

2

Academic Level

No preference

Location of project

in-person

CIVE 008: Eliciting and Providing Information in Urban Mobility Systems with AI Agents (Yu)

Professor Jiangbo Yu

jiangbo.yu [at] mcgill.ca
5147025675
/civil/jiangbo-yu
Research Area
Transportation Engineering
Description
Transportation systems often struggle with fragmented and inefficient information flow between travelers, mobility service providers, and public agencies. Travelers frequently lack timely updates on delays or disruptions, while service providers find it challenging to respond to changing demand due to limited user feedback. Public agencies, too, face difficulties in coordinating and optimizing the overall network.

This research project aims to address these challenges by developing a system where intelligent AI agents collaborate in real-time with travelers, service providers, and public agencies. These agents will actively collect and process data, such as user feedback, operational details, and public updates, to deliver actionable insights to each group. For example, travelers might receive personalized route suggestions based on current traffic or transit conditions, while service providers could adjust routes and schedules based on real-time demand patterns. Public agencies would gain a more comprehensive view of system performance, enabling better decision-making and network coordination. By designing and testing a prototype of this AI-driven collaborative system, this project will demonstrate how improving communication between all stakeholders can create more efficient, adaptive, and user-friendly transportation networks.

This project provides the student with hands-on experience in working with cutting-edge generative AI technologies, valuable skills in system integration and testing, and opportunities to contribute to impactful transportation solutions while working in a collaborative, team-oriented environment.
Tasks per student
The student will play a key role in the design, development, and testing of an AI-driven transportation system, collaborating closely with graduate students and postdoctoral researchers. They will assist in creating AI agents capable of collecting and processing real-time data from various sources, such as traveler feedback, service updates, and public information. The student will help integrate these data streams to ensure that the agents can provide accurate and actionable insights to stakeholders. In collaboration with the research team, the student will contribute to building a functional prototype that demonstrates how the agents can facilitate seamless communication and real-time updates between travelers, service providers, and public agencies. During the testing phase, the student will support performance evaluations and usability assessments, identifying areas for system improvement. Additionally, they will assist in preparing technical reports and presentations to communicate the project鈥檚 progress and findings effectively.

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Deliverables per student
The student will contribute to the development of functional AI agents that can collect, process, and integrate real-time data from travelers, service providers, and public agencies, along with algorithms for analyzing user feedback, service updates, and public information. The student will also assist in building a working prototype that demonstrates how the AI agents facilitate seamless communication and provide actionable insights. Deliverables include documentation of testing procedures, performance evaluations, and usability assessments, along with recommendations for system enhancements. A final report will summarize the project鈥檚 findings and outcomes, detailing the role of AI agents in improving transportation system efficiency. The student will also contribute to technical documentation outlining system design, algorithms, and results, and assist in preparing presentations to communicate progress and findings.
Number of positions

1

Academic Level

Year 3

Location of project

in-person

CIVE 009: Operation of reactors simulating human gut to evaluate the dispersal of antimicrobial resistance through the environment. (Frigon)

Professor Dominic Frigon

dominic.frigon [at] mcgill.ca

5147752475

/civil/dominic-frigon
Research Area
Environmental engineering, biochemical engineering, bioengineering, microbiology, biotechnology, wastewater, epidemiology, public health.
Description
It is now known that antimicrobial resistance can arise in farm animals and in humans that are treated by antimicrobials, and in the environment when antimicrobial residuals are discharged. Then, antimicrobial resistance spread from their original source to humans in part by accumulating in the gut microbiota. The goal of this project is to determine the factors determining the rate of transfer of antimicrobial resistance from wastewater to the human gut microbes. To do so, laboratory-scale reactors simulating the gut conditions will be operated with different food types and exposed to wastewater microbes. Molecular biology and genomic techniques will be used to track the establishment of resistance genes in the simulated gut microbiota. The SURE intern will be assisting a PhD student in conducting these experiments. They will be responsible for reactor maintenance and performing test to assess the reactors鈥� behaviours. They will also be introduced to molecular techniques.
Tasks per student
Perform the daily maintenance and sampling of the laboratory-scale reactors. Perform laboratory analyses to determine physico-chemical characteristics of samples. Contribute to computer data entry and trend analyses.

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Deliverables per student
A compilation report of the trends observed during the experiment is expected at the end of the study and an oral presentation during regular group meetings.
Number of positions

1

Academic Level

Year 2

Location of project

in-person

CIVE 010: Tracking antimicrobial resistance in different environments to protect humans from deadly infections (Frigon)

Professor Dominic Frigon

dominic.frigon [at] mcgill.ca

5147752475

/civil/dominic-frigon
Research Area
Environmental engineering, bioengineering, microbiology, biotechnology, wastewater, epidemiology, public health.
Description
The spread of antimicrobial resistance through environmental and human-associated microbes threatens to reduce the efficacy of medical treatment. One of the main sources of resistance in the environment is the release of bacteria from municipal wastewater treatment facilities. After disposal of treated wastewater and waste biosolids, the resistance genes rejected in the environment migrate back to humans via the consumption of foods and water. Therefore, tracking the various resistance genes in different environments is necessary to evaluate the risk of migration backs to humans. Our research group is developing a new approach based on PCR amplicon sequencing to achieve this with a high sensitivity. The goal of the project is to perform validation tests on the PCR primer sets that perform the detections. This will involve performing molecular manipulations in the lab and cultivation of environmental microbes. The PCR primers will then be applied to the analysis of antimicrobial resistance genes present in the microbial communities sampled in different environments. Thus, part of the project may entails helping with field sampling.
Tasks per student
Perform analyses of antimicrobial resistance genes in environmental and man-made using a suite of molecular (DNA or RNA based) and chemical analysis techniques in the lab. Cultivation of environmental microbes. Sampling surface water and wastewater in the field.

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Deliverables per student
A compilation report of the trends observed during the experiment is expected at the end of the study and an oral presentation during regular group meetings.
Number of positions

1

Academic Level

Year 2

Location of project

in-person

CIVE 011: Reducing the environmental footprint of crop agriculture through nanotechnology-enabled foliar application of fertilizers and pesticides (Ghoshal)

Professor听Subhasis Ghoshal

subhasis.ghoshal [at] mcgill.ca

514 398-6867
Research Area
environmental engineering and science
Description
Mesoporous silica-based nanocarriers (MSN) are highly efficient, safe, and biocompatible, controlled-release agents for delivering micronutrients or pesticides to plant crops by foliar application to increase agricultural productivity while minimizing agriculture鈥檚 carbon footprint. Our overall research goal is to develop a highly efficient way of delivering essential micronutrients, or pesticides, to plant crops, without contact of these chemicals to soil. Contact of these agrochemicals to soil results in uptake of only a minor fraction of the applied mass in plants, with the rest being lost to the environment and resulting in adverse environmental impacts. Significant research is needed to optimize agrochemical delivery through foliar application by tuning nanoparticle properties and application methods. The research to be performed will address the research needs for these aspects through experimental research and critical review of the research literature.
Tasks per student
1) Optimizing nanoparticle synthesis methods
2) Optimizing nanoparticle application on plants in laboratory growth chambers
3) Analyzing experimental data
4) Conducting literature review on the topic

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Deliverables per student
1) Documenting experimental protocols and data in a written report
2) Developing a critical literature review of effects of nanoparticle properties and foliar application formulations on agrochemical uptake in crop plants
2) Preparing a poster on the research
Number of positions

1

Academic Level

Year 3

Location of project

in-person

CIVE 012: Environmental life cycle assessment of net zero energy systems (Jordaan)

Professor Sarah Jordaan

sarah.jordaan [at] mcgill.ca

514-398-6860
Research Area
Environmental engineering, energy science, environmental science
Description
Life cycle assessment (LCA) provides a systematic method by which environmental burdens of products and processes can be quantified from materials extraction through waste disposal (i.e., cradle-to-grave). An ongoing challenge exists for LCA in decision support for sustainable energy: it is temporally static and does not capture the spatial patterns of infrastructure. Present advances in LCA include how to capture spatial and temporal variations across fuel supply through end use. The Energy Technology And Policy Assessment (ETAPA) research group focuses on quantifying impacts by developing LCA methods that examine the full portfolio of energy options in support of more sustainable environmental outcomes. Critical questions remain about present energy systems, 鈥渂ridge鈥� fuels, impacts and opportunities for energy storage, and transition pathways. Successful applicants will be involved with one of three tasks. The successful applicant for task (1) will focus on reviewing models and compiling energy datasets. The results will be examined in a comparative analysis of Canadian and US data, informing improvements in LCA. The successful applicant for task (2) will work on a large-scale, high-resolution assessment of wind energy by compiling data and running several analyses. The successful applicant for (3) will critically review data and develop inventories/models supporting LCA of transportation. Each SURE student will join an inclusive project team at ETAPA.
Tasks per student
Each student will focus on one of the outlined research tasks and produce the noted deliverables.

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Deliverables per student
The students will be expected to submit a written report of their findings as described above (including associated datasets, models, presentation, and an annotated bibliography) to supervising professor and (if applicable) to the graduate student team. At the end of the summer, the students will complete a short presentation to the ETAPA group.
Number of positions

3

Academic Level

No preference

Location of project

in-person

CIVE 013: Life cycle assessment of lithium-ion battery recycling (Jordaan)

Professor Sarah Jordaan

sarah.jordaan [at] mcgill.ca

514-398-6860
Research Area
Environmental engineering, energy science, environmental science
Description
Life cycle assessment (LCA) is a tool that can quantify the environmental impacts of large-scale deployment of batteries from materials extraction through waste disposal in support of designing solutions for superior environmental outcomes. Recycling of lithium-ion batteries is increasingly investigated as an option to reduce the demand for virgin materials. A SURE student will examine the forefront of knowledge in LCA of battery recycling by participating in a systematic review of available literature. Tasks will involve compiling and harmonizing data, then comparing to existing models. The Energy Technology And Policy Assessment (ETAPA) research group focuses on quantifying impacts by developing life cycle, circular economy, techno-economic and systems solutions that examine the full portfolio of energy options in support of more sustainable environmental outcomes. The successful applicant will join an inclusive project team.
Tasks per student
****Environmental engineering, energy science, environmental science

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Deliverables per student
The student will be expected to submit a written report of their findings as described above (including associated datasets, models, and an annotated bibliography) and complete a short presentation to the ETAPA group and/or colleagues. The powerpoint presentation will also be submitted with the final deliverables.
Number of positions

1

Academic Level

No preference

Location of project

in-person

CIVE 014: Methane emissions from non-producing oil and gas wells (Kang)

Professor Mary Kang

mary.kang [at] mcgill.ca

5143986860
Research Area
Environmental Engineering
Description听

Methane is a potent greenhouse gas and reducing its emissions can substantially combat global warming in the short term. Measurements have shown that non-producing oil and gas wells are sources of methane to the atmosphere. The project involves conducting one or more field trip(s) to oil and gas-producing regions, analyzing the results in the laboratory, and conducting data analysis. Various methods including flux chambers and portable instruments will be used to measure methane flow rates and other geochemical parameters. The findings from this study will provide quantitative data for evaluating and designing mitigation solutions for the tens of millions of non-producing oil and gas wells around the world.

A valid driver鈥檚 license and ability to travel for extended time periods (~4-7 weeks) are required.

Vehicles will be provided, and all travel expenses (transportation, meals, hotels, gas, etc.) will be covered
Tasks per student
Prepare for one or more field sampling trip(s), conduct field sampling, and analyze data.

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Deliverables per student
Database of measurements and measured sites and a final report providing an overview of the measurement trips.
Number of positions

3

Academic Level

No preference

Location of project

in-person

CIVE 015: Methane emissions from urban systems (Kang)

Professor Mary Kang

mary.kang [at] mcgill.ca
5143986860
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Research Area
Environmental Engineering
Description
Methane is a potent greenhouse gas and reducing its emissions can substantially combat global warming in the short term. Measurements have shown that natural gas distribution, landfills, and wastewater systems are sources of methane to the atmosphere. The project involves preparing one or more field trip(s) in multiple cities, conducting field measurements, analyzing the results in the laboratory, and analyzing the data. Various methods including flux chambers and portable instruments will be used to measure methane flow rates and other geochemical parameters. The findings from this study will provide quantitative data for evaluating and designing mitigation solutions for methane emissions from cities.

A valid driver鈥檚 license and ability to travel for extended time periods (~4-7 weeks) are required.

Vehicles will be provided, and all travel expenses (transportation, meals, hotels, gas, etc.) will be covered
Tasks per student
Prepare for one or more field sampling trip(s), conduct field sampling, and analyze data.

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Deliverables per student
Database of measurements and measured sites and a final report providing an overview of the measurement trips.
Number of positions

1

Academic Level

No preference

Location of project

in-person
Tags: 
Summer Undergraduate Research Opportunities
Undergraduate Research
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