McGill-UAE USRI Projects

Project code: PR14 

Supervisor: Thomas Durcan  

Project: We user patient-derived stem cells to develop new cellular models in neurodegenerative disease research. We generate large sets of microscopy images and use software-based analysis tools to characterize cellular phenotypes and ascertain differences in biomarker expression. It is an opportunity for a student to help establish image analysis pipelines with the team by using image analysis software like Image J. Other softwares will be used by the student like Cell profiler and Imaris to run analysis on data to characterize effects of treatments on our models.

Project code: PR15 

Supervisor: Brian Chen 

Project: What molecules give a brain cell its unique identity to make it wire up a specific way? Very little is known about how instructions encoded somehow within the genome can allow a brain to self-assemble and wire up to function correctly. Our goal is to uncover the exact molecular code that can be used to wire up a neural circuit. We address this by using the fruit fly genetic model organism because of its long history of use in biology and neurobiology research, and because of its hard-wired, or innate behaviors.

Project code: PR16

Supervisor: Qihuang Zhang

Project: Our lab focuses on developing and applying advanced computational and statistical methods to address challenging problems in genomics and health sciences. This project centers on spatial transcriptomics, a cutting-edge technology that combines gene expression data with spatial location information to uncover the biological architecture of tissues. By analyzing spatial transcriptomic data, we aim to uncover critical insights into how gene expression varies across different regions of the brain and how this may relate to diseases such as Alzheimer's or ADHD. The undergraduate student recruited for this position will assist in two main aspects of the research: (1) data processing and (2) statistical data analysis. For data processing, the student will work on handling large-scale spatial transcriptomics datasets. Tasks will include ensuring data quality, normalizing gene expression data, and preparing datasets for downstream statistical analysis. This will involve using bioinformatics tools in programming environments such as R or Python, along with specialized packages for genomic data processing. For data analysis, the student will conduct statistical analyses such as differential expression analysis to identify genes with significant changes across different tissue regions or experimental conditions. They will also perform regression analyses to investigate relationships between gene expression and spatial patterns. These analyses aim to generate meaningful biological insights and contribute to the overall objectives of the project. This opportunity can provide hands-on experience in data analysis and bioinformatics, and practical skills in statistics and computational biology. It is an excellent fit for students interested in genomics, data science, or biomedical research. Familiarity with R or Python is recommended. 

Project code: PR17

Supervisor: Sampath Loganathan 

Project: My research focus on studying the oncological mechanisms behind head and neck cancer. The project will use gene editing tools like CRISPR knock-out, base editing and prime editing to model the mutations found in patients and study the signaling mechanisms behind it. Our lab also utilizes CRISPR screens to identify any potential drug targets to treat this deadly cancer.

Project code: PR18 

Supervisor: Julia Burnier 

Project: Description: My research focuses on understanding the dynamic molecular changes during tumour progression and metastasis through “liquid biopsy”, a novel technique that involves sampling biofluids like the blood and saliva to detect cancer molecules. Traditional tissue biopsies are limited by inadequate sampling, complications, and the static nature of the data, which fails to capture tumour evolution. This approach provides only a snapshot of the tumour, missing critical information about its ongoing changes. To overcome these limitations, my lab tracks tumour evolution via liquid biopsy, using blood samples to monitor disease progression, recurrence, and treatment response. Detection of circulating tumour cells, DNA (ctDNA), and extracellular vesicles (EVs) provides insights into tumour biology and can help guide early diagnosis, personalized management, and treatment monitoring. We have two main themes: 1) By identifying specific mutations in ctDNA, we can track disease progression and adapt therapy accordingly. We correlate ctDNA levels to clinical outcomes using liquid biopsies from cancer patients. 2) In addition, we are investigating the role of EVs in cancer biology. EVs, which carry proteins, lipids, RNA, and DNA, facilitate intercellular communication and play a critical role in promoting tumour progression by aiding metastasis, immune evasion, and drug resistance. By analyzing the molecular cargo of these vesicles, we aim to uncover new pathways driving metastasis and identify novel therapeutic targets. To facilitate this research, we also synthesize lipid nanoparticles (LNPs), which are similar in lipid composition and membrane structure to EVs. LNPs serve as a model system to study EV behavior, providing a controlled platform to investigate how changes in lipid composition, size, and surface characteristics influence vesicle function. Furthermore, LNPs have significant potential as drug delivery vehicles, enabling targeted and efficient delivery of therapies to tumour sites. This work not only bridges tumour monitoring with therapy but also offers novel tools for early cancer detection, monitoring disease dynamics, and developing more effective, personalized treatments.

Project code: PR19 

Supervisor: Sirui Zhou  

Project: The genetic architecture of proteomics in blood has been investigated in large cohorts through genome-wide association studies (GWAS), common genetic variants associated with these blood proteins have been used to implicate diseases. However, rare and functional impactful variants that may lead to changes in blood circulating levels through affecting the protein structure and function have not been studied. In this project, we will investigate the rare variant burden and their impact on circulating proteins, using the UK Biobank proteomics cohort, variant and protein structure prediction tools and public database. The findings of this project may help to further understand certain protein-protein interactions and disease biological pathways linking blood proteins and rare variants.

Project code: PR20

Supervisor: Jun-Li Liu 

Project: Characterizing Tissue-Specific Impacts of CCN5/WISP2 with Cre-Inducible Overexpression: We found that IGF-1 stimulates CCN5 expression which is essential for its effect on β-cell proliferation. Our recent studies on CCN5 knockout mice further revealed reduced β-cell growth and sex-specific metabolic changes. Although adipocyte-specific overexpression of CCN5 increased lean body mass and insulin sensitivity, it did not expand or protect the β-cells from diabetes. Based on in vitro and in vivo evidence, we hypothesize that the effect of CCN5 on β-cells is paracrine, local, and tissue- and cell-specific and its overexpression will effectively promote β-cell growth and protection. i) The aim 1 is to validate Cre-inducible CCN5 overexpression in pancreatic β-cells using the cKI-CCN5 mouse model, a Rosa26-directed knock-in. Ins1-Cre, and Ins1-ER2-Cre will be used to achieve overexpression which will be validated through qRT-PCR, Western Blot, and immunohistochemistry. ii) The second aim is to assess the effects of CCN5 overexpression on β-cell function and glucose homeostasis. This will be achieved by inducing overexpression using tamoxifen injection in cKI-CCN5/Cre+ mice and evaluating endpoints such as β-cell mass, proliferation, functionality, and metabolic homeostasis. iii) The third aim is to explore functional interactions of CCN5 with key β-cell regulators and novel pathways activated by CCN5. Single-cell RNA sequencing will be used to identify novel genes and pathways altered by CCN5 overexpression. Impact: The proposed research will significantly contribute to identifying CCN5 as a novel regulator of β-cell growth, insulin secretion, and the intracellular signaling pathways involved. This will advance our understanding of β-cell biology and pave the way for new approaches to maintain and regulate glucose homeostasis. 

Project code: PR21

Supervisor: Daniel Taliun

Project: The Human Leukocyte Antigen (HLA) region on chromosome 6 of our DNA encodes genes responsible for the immune system and is associated with more diseases than any other DNA region. The HLA region is also one of the most difficult for gene-disease association mapping because of its high variability (known as high polymorphism) between and within populations worldwide and intriguing correlation patterns between genes. Thus, there is a constant need to develop and test new statistical and computational methods for analyzing the HLA region in the context of gene-disease association studies. In this summer project, you will have an opportunity to learn about the HLA region and to test different statistical/computational methods that will help researchers build strong methodology and analysis protocols for HLA-related research.

Project code: PR25

Supervisor: Jorge Armony 

Project:  The student will participate in a study investigaing emotional body sensations and interoceptive processes. Previous work from our group and others has investigated individual differences in emotional body sensations (feelings in the body associated with emotional experience) in relation to psychiatric diagnoses and subclinical personality traits, using the “bodily maps of emotion” task. This task, in which participants “paint” areas of their body where they feel different emotions, relies on interoceptive and somatosensory processes. Previous research has made a crucial distinction between interoceptive attention and interoceptive accuracy: the former refers to the salience of interoceptive signals in consciousness, while the latter refers to the accurate perception of interoceptive signals. While conceptually similar, research has shown that these processes are uncorrelated or even anticorrelated, and have different psychological correlates. Thus, the present project will center around distinguishing interoceptive attention and interoceptive accuracy in the perception of emotional body sensations. The research project will use an emotion-induction paradigm in combination with physiological recordings, self-reported emotion, and the bodily maps of emotion task to investigate the correspondence of actual physiological changes, self-reported emotion, and self-reported somatic sensation. This will allow us to investigate how differences in interoceptive processes manifest in emotional body sensations, and how these relate to personality and emotional experience. The student will be responsible for testing materials for this study (emotion induction procedures, physiological equipment, questionnaires and aspects of the experimental design), piloting it on a small sample to ensure its effectiveness, testing participants, and analyzing the data.

Project Code: PR26

Supervisor: Corina Nagy

Project: Major depressive disorder (MDD) is a leading cause of disability, and the limited efficacy of traditional antidepressants has driven the search for new cellular pathways and treatment targets. Physical exercise, a key component of lifestyle modification, is strongly associated with improved mental health and has profound effects on brain regions impacted by MDD. Exercise exerts its positive effects by inducing the release of proteins and metabolites from various tissues, including bones, liver, platelets, and muscles. One notable example is the increased levels of brain-derived neurotrophic factor (BDNF), a protein released during exercise. BDNF, classified as an exerkine—a bioactive molecule released in response to physical activity—has been shown to combat anxiety and depression in animal models and enhance cognitive function. While the beneficial effects of exercise are believed to be mediated by exerkines, the mechanisms linking peripheral exercise-induced changes to the brain remain unclear. Small extracellular vesicles (sEVs), a class of vesicles released by virtually all cell types and found in biofluids, are thought to cross the blood-brain barrier and play a role in synaptic plasticity, neuronal stress response, cell-to-cell communication, and neurogenesis. sEVs carry proteins, including known exerkines like BDNF, as well as microRNAs (miRNAs), which are epigenetic regulators often dysregulated in the brains of depressed patients. This project aims to establish three critical links to understand the biological effects of exercise on the brain, particularly in the context of MDD: 1) the impact of exercise on sEVs, 2) the potential transfer of exercise-induced sEVs from the periphery to the brain, and 3) the potential prophylactic and therapeutic effects of exercise-induced sEVs on depression. We aim to understand how exercise-induced sEVs affect brain function and mood, potentially uncovering new therapeutic targets for preventing and treating depression.

Project code: PR23

Supervisor: Peter Douglas

Project: : Tracing methane emissions hotspots in Montreal landfills: Methane is a major greenhouse gas, and globally landfills are a critical source of methane emissions to the atmosphere. Active and decommissioned landfills in Montreal are designed to capture and harvest methane for energy use, but we have found emissions hotspots at these landfills indicating that significant quantities of methane are escaping to the atmosphere. We are using greenhouse gas flux measurements and isotopic analyses to quantify these methane emissions, understand the source of carbon that is fuelling them, and determine how much methane is oxidized prior to its release to the atmosphere. The research project will entail weekly visits to landfill sites to install flux chambers and collect gases. It will also involve weekly laboratory analyses to 1) measure concentrations of methane and carbon dioxide; and 2) measure carbon isotope ratios of these gases. There may also be opportunities to prepare gas samples for more innovative analyses, including radiocarbon analysis. After several weeks of data collection, the student will have the opportunity to analyze the data and compare with datasest from previous years and from other landfill sites. The student will work with a team of graduate students, and potentially other undergraduate interns, on this project. The position requires experience with field work and laboratory analyses, and will entail working outdoors for significant periods of time.

Project code: PR27

Supervisor: Xin Zhao 

Project: This research project focuses on the mechanisms and dynamics of plasmid-mediated horizontal gene transfer (HGT) in antimicrobial resistance (AMR), specifically in bacterial strains isolated from poultry. Plasmids, which are mobile genetic elements, play a critical role in spreading antimicrobial resistance genes (ARGs) between bacterial populations, posing a significant challenge to public health. During this 8-week summer internship, undergraduate students will have the opportunity to contribute to ongoing research in our laboratory. The primary objective is to investigate plasmids that carry ARGs and their potential to transfer these genes via conjugation. Students will gain hands-on experience in essential microbiological and molecular biology techniques, including bacterial culture, plasmid extraction, electrophoresis, and plasmid typing using PCR-based methods. Advanced techniques, such as antimicrobial susceptibility testing and replicon analysis, may also be included, depending on the project’s progress. This project is designed to provide students with foundational research skills while exposing them to the interdisciplinary nature of microbiology, molecular genetics, and public health. They will also learn about experimental design, troubleshooting protocols, and data interpretation. Importantly, this experience will allow students to develop critical thinking and communication skills by discussing experimental results with the research team. The project is ideal for students interested in microbiology, biotechnology, or related fields and provides a glimpse into real-world research addressing global challenges such as AMR. Our lab is committed to mentoring students in a supportive environment and fostering curiosity and innovation in their research journey. 

Project code: PR32 

Supervisor: Amin Shmuel 

Project: Development of a pipeline for analyzing neurophysiology data recorded from the brain. Neurophysiology is a method commonly used to record the brain’s activity. Previously, neurophysiology was performed using one contact electrode, yielding time courses of activity recorded from a single brain site. With the advent of neurophysiology, we can now record activity simultaneously from several tens of brain sites. This increased spatial sampling makes it possible to study how different brain regions interact. The project aims to develop scripts for analyzing high-throughput neurophysiology data of the brain. The project will advance our understanding of the brain’s activity at the mesoscopic scale in the quest for the understanding of brain function. Contribution of the students: The students will review material to learn the basics of brain activity and neurophysiology. They will receive data and develop analysis pipelines using available scripts from software packages. They will create an analysis package for multi-channel neurophysiological recordings of brain activity. They will document the methods and the results. They will write a detailed report. Novel methods have the potential for publication. Required skills: The ideal candidates will have knowledge and skills in signal and/or image processing, statistics, and coding. Skills to be developed during the training: The students will gain knowledge and experience in the basics of the brain’s organization, neurophysiology, preparing analysis pipelines based on existing software packages, and how to write a journal paper. Description of your Research Group: https://www.mcgill.ca/neuro/amir-shmuel-phd 

Project code: PR24 

Supervisor: Suresh Krishna

Project: The lab investigates vision, hearing, eye-movements, attention, memory and phenomenological states using eye-tracking, behavioral studies (psychophysics), and computational modeling. Areas of interest include all aspects of visual and auditory perception, as well as attention, memory and the relationship of perception to breathing and heart-rate. Analysis of open datasets is also possible for quantitatively oriented candidates. 

Project code: PR06

Supervisor: Damiano Pasini 

Project: This project requires the use of principles of origami and other mechanical metamaterials to explore, design and analyze novel material concepts for a range of applications including but not limited to soft robotics, aerospace and biomedical engineering

Project code: PR07

Supervisor: Michael Hilke

Project: New physics in twisted bilayers: We are in the midst of a new generation of revolutionary materials that belong to the class of stacked two-dimensional crystals. These new materials have shown fascinating new properties, including superconductivity in twisted graphene bilayers and the observation of the fractional anomalous Hall effect, to name a couple. Most of these properties are electronic, however, vibrational properties are also expected to show fascinating new phenomena. The goal in this project is to synthesize large-scale twisted bilayers and to investigate their vibrational and thermal properties. This is a very hands-on project, which requires some patience, consistency, and the ability to learn and operate new technologies.

Project code: PR08

Supervisor: Abdolhamid Akbarzadeh 

Project: Smart, inflatable, and easy-to-make robotic muscles and crawlers, which demonstrate a dramatic shape change with effective cargo transportation and locomotion capabilities, are among the astonishing feats of future technology. Drawing inspiration from the ancient art form of paper folding and the embodied intelligence found in nature, the project introduces origami-inspired robots with transformable architectures that are remotely-controlled for multimodal deformation and haptic pressure and temperature sensing. The smart robots offer remote actuation, which obviates the need for wired conventional driving units. The correlation between geometrical features and shape morphing characteristics of the soft robots will be studied by adopting reduced-order models and nonlinear finite element simulation. To meet the underlying challenges in design and manufacturing, the research utilizes the diverse expertise of teams of mechanical engineers, materials scientists, chemists, designers, and computer scientists. The intern will have the chance of design and manufacturing of first-of-a-kind active multi-purpose soft robots. The intern will conduct the research in Advanced Multifunctional and Multiphysics Metamaterials Lab that provides highly-qualified personnel with well-defined training plans to gain a unique blend of expertise in architectural metamaterial design, non-classical continuum-based modelling, multiscale multiphysics simulation, 3D printing and advanced fabrication, and experimental material characterization. The trained intern will eventually contribute towards smart material innovation in additively-manufactured intelligent products.

Project code: PR09

Supervisor: Larry Lessard

Project: Evaluating the Recyclability and Performance of Fiberglass-Reinforced PETG Composites Across Successive Recycling Cycles: This study investigates the recycling potential of composite materials, with a focus on their recyclability and performance over multiple recycling cycles. The goal is to evaluate the feasibility of repeatedly recycling fiberglass/PETG filaments and determine the maximum number of viable recycling iterations. At each stage, the material’s thermal and mechanical properties are analyzed to assess its suitability for further processing. Recycling is deemed complete when either processing becomes infeasible or the mechanical properties fall below a defined threshold.

Project code: PR10

Supervisor: Regan J. Hill 

Project: : Ion transport in hydrated polyelectrolyte membranes is of fundamental importance to the operation of fuel cells and batteries. Our group is developing theoretical models to interpret impedance spectroscopy data, which provides a powerful means of evaluating the impact of materials-synthesis strategies to membrane performance. We are also developing a parallel experimental program for measuring impedance spectra in hydrated systems. In this project, the trainee will conduct impedance spectroscopy experiments on polyelectrolyte hydrogels, correlating how the spectra vary with prescribed changes in hydration, thickness, and composition. The results will be compared with evidence in the literature on how similar membranes perform in fuel cells, seeking to test an hypothesis that electroosmotic flow is responsible for some ionomer fuel-cell membranes dehydrating at the cathode, limiting their performance.

Project code: PR01

Supervisor: Jovan Nedic 

Project: Our applied aerodynamics research focusses on the interaction of propellers/rotors and finite wings with unsteady and turbulent inflows, as one would expect to find on helicopters and unmanned aerial vehicles as they navigate urban environments. We have several experimental projects in this field, where the student would work closely with either a graduate student or the professor directly, to take measurements of pressure, forces, and velocity in either our water or wind tunnel; this includes the use of laser diagnostics.

Project code: PR02

Supervisor: Ahmed Elgeneidy 

Project: Measuring the impacts of the new Réseau Express Métropolitain (REM) on mobility. In 2016, the Caisse de dépôt et placement du Québec (CDPQ) announced plans to build the Réseau express métropolitain (REM), a state-of-the-art, fully automated 67-kilometer light-rail network that will fundamentally reshape transport in areas on and off the island of Montreal. When complete, the $9.4 billion project will link numerous suburbs—and Montréal-Pierre Elliott Trudeau International Airport —to downtown with frequent, high-speed rail service, that is universally accessible, altering travel and land-use patterns throughout the region for various groups of population. These changes are likely to have impacts on the health, social, economic, physical, and psychological well-being of all Montreal residents for the coming decades. The first branch, connecting Montreal’s South Shore, started operation in 2023, with additional segments coming online in 2025 and a final opening in 2027 for the full system. As one of the most ambitious—and costly—public transport projects in Canada in decades. The goal of this research project is: 1.Measure the short-term changes in travel behaviour, physical activity, stress and wellbeing. 2. Monitor the short-term impacts of the REM on accessibility, particularly as it relates to social equity. 3. Observe and record alterations in the built environment around the REM stations on the short-term. Tasks will include the following: Data analysis and statistical modeling, conducting literature review, write policy briefs, help in drafting manuscripts, data collection on the ground including surveys, if you have a drone license it is a plus as we will be collecting drone images. Deliverables: Policy Briefs and educational videos. Students interested should send a CV and writing sample to mathew.page [at] mcgill.ca

Project code: PR03 

Supervisor: Ali Seifitokalani

Project: In this project students will receive training to perform density functional theory (DFT) computations. They will apply this technique to simulate electronic structure of model molecules and catalytic surfaces. They will calculate and plot the reaction energy diagram for select electrocatalytic systems such as CO2 reduction reaction, hydrogen evolution reaction and organic compounds oxidation.

Project code: PR04

Supervisor: Ipek Tureli

Project: : “Design for the Global Majority” traces the fifty years of groundbreaking contributions of the Minimum Cost Housing Group (MCHG) in the realm of architectural design under conditions of scarcity. It contributes to recent architectural histories and exhibitions on the rise of environmentalism in Architecture. Tasks include assistance to the managing of the editing of an exhibition catalogue; archival research and retrieval where necessary; copyediting; graphic design. Project website: https://www.mcgill.ca/mchg/design-global-majority

Project code: PR05

Supervisor: Ipek Tureli

Project: 

Turkiye Earthquake Memory Project (TEMP) [https://www.mcgill.ca/earthquake-memory-turkiye]: Over the last century, Türkiye experienced frequent and severe earthquakes that have repeatedly disrupted both the built environment and the social fabric of communities. Reconstruction efforts have often prioritized material losses while neglecting the cultural and historical significance of affected areas. This approach disregards the deep emotional and social connections that communities have with their surroundings, resulting in an erasure of cultural memory and a disconnect between communities and their rebuilt environments. This study will explore how people in Türkiye remember significant earthquakes. It aims to address a significant gap in the historiography of the built environment and of Türkiye by examining how memories of earthquakes are formed, preserved, and transmitted, through the concept of "memoryscapes."Tasks include transcription of oral histories, spatial mapping of oral histories, architectural analysis, GIS mapping, audiovisual presentation, building on an existing web source.

Project code: PR28 

Supervisor: Nicholas Cowan

Project:The summer researcher will join the McGill Exoplanet Characterization Alliance and will work with Professor Cowan on the target selection for the Ariel mission, a space telescope launching in 2029 to complete a survey of exoplanet atmospheres. The student will develop and use Python software tools to simulate Ariel observations of exoplanets. This will entail predicting the signal and noise for thousands of known exoplanets and planetary candidates, making parameter cuts to narrow down the sample of potential targets, parameterizing possible exoplanet trends, and calculating observational time required to detect these trends. The student will join weekly group meetings and 1-on-1 meetings with Professor Cowan. They will make weekly progress reports and post their next research objectives on the group Slack. The student will learn about scientific programming, atmospheric science, and exoplanet observations. They will develop their scientific writing and visualization skills to present results succinctly and elegantly. They will learn how to solve problems independently, how to ask more experienced researchers for help, and how to adapt strategies when facing seemingly intractable problems. Prior programming experience in Python is a requirement. Astronomy coursework and research experience are a plus.

Project code: PR29

Supervisor: Lizaine Bouvier 

Project: Automated analyses of speech, including transcription and acoustic measurements, are increasingly being used in speech-language pathology (SLP) research. These tools have the potential to streamline the assessment of speech disorders and provide objective, quantitative data. However, the accuracy and reliability of these automated methods when applied to individuals with motor speech disorders, particularly those with neurodegenerative diseases, remain largely unknown. This project aims to assess the performance of various automated speech analysis tools in both individuals with motor speech impairments and healthy speakers. The project will evaluate two main aspects of automated speech analysis: transcription accuracy (how well speech-to-text algorithms capture the spoken word) and acoustic analysis (how well speech patterns, such as pitch, rate, and prosody, are accurately quantified). Moreover, this project will compare the accuracy and reliability of these analyses: 1) between individuals diagnosed with neurodegenerative motor speech disorders and healthy speakers to determine the extent to which they may be affected by motor speech impairments; 2) between various speech production tasks to determine the effect of speech content and tasks features. The results of this study will provide valuable insights into the limitations and potential of automated speech analysis tools for diagnosing and monitoring speech disorders in neurodegenerative diseases. The findings will contribute to improving the reliability and precision of speech assessments in both research and healthcare settings, ultimately supporting better patient care and more effective therapeutic interventions.

Project code: PR11

Supervisor: Changhong Zao 

Project: Micro-LED (uLED) technology has emerged as a promising display solution due to its low power consumption, high brightness, and excellent resolution. These advantages make it suitable for a wide range of applications, including ultra-large TV displays, mini laptop screens, and virtual reality (VR) headsets. Despite the promising potential of Micro-LEDs, several challenges are remained in their commercial application. One of the key challenge is achieving mass transfer, a process that involves transferring millions of micro-LED pixels from the growth substrate to the target substrate of the display. This process must be carefully controlled to ensure high precision and efficiency. Traditional transfer methods, such as elastomeric transfer printing, laser-assisted transfer, and electrostatic transfer, face significant challenges. Due to the small size of micro-LEDs, not all micro-LEDs or their groups can be successfully transferred to the target substrate without defects. Precise placement and full control are critical to preventing malfunctions or substandard display performance. Even slight misalignment or damage to micro-LEDs can lead to visual defects or reduced display efficiency. Additionally, traditional transfer techniques face scalability issues, as they must maintain high precision while transferring large quantities of micro-LEDs without compromising quality or causing damage. For successful mass production, the technology must be adapted to support high-throughput manufacturing while maintaining the same level of precision and preventing damage to the micro-LEDs. Our research focuses on the novel transfer printing technologies such as capillary-force-based transfer method. The success of the transfer method depends on the adhesion forces between object and substrate. Ideally, a low-adhesion substrate is favored to realize an easier transfer. In this project, the student(s) will gain hands-on experience with this innovative transfer method and test various polymer-based substrates to identify the optimal candidate for our proposed transfer technology.

Project code: PR12

Supervisor: Yixiang Wang

Project: The utilization of biomass waste has attracted much interest, but there is a lack of enough attention to the abundant leaves. Leaves are composed of a variety of compounds including carbohydrates, lipids, proteins, minerals, and so on, and are a potential low-cost source of quality cellulose. As an emerging class of nanomaterials, cellulose nanocrystals (CNCs) have received considerable interest over the past decades and have been widely applied in food packaging, emulsion stabilization, quality sensor, and food thickener. The extraction of CNCs usually consists of pretreatments (removal of contaminations and soluble substances), purifications (removal of hemicellulose and lignin), and fragmentation (generation of nanostructure via hydrolysis), and CNCs can be obtained from many resources, such as plants, animals, bacteria. Recently, there is an increasing trend to obtain CNCs from waste biomass. Our previous work has demonstrated that lignin could be retained while isolating cellulose from maple leaves, and the prepared lignin-containing CNCs could act as natural Pickering emulsion stabilizers without the need of any chemical modifications. Therefore, in this project, CNCs with various properties will be extracted from fallen leaves and applied in functional food packaging. The student will learn the separation and purification of CNCs and the preparation and characterization of CNC-based composite materials. The student will have the access to our equipment to test the mechanical properties, oxygen/water vapor barrier properties, and biodegradability. After the training, the student will have knowledge of CNC extraction from leaves and materials fabrication and characterization, and be aware of the importance to develop biodegradable functional food packaging materials.

Project code: PR13

Supervisor: Salwa Karboune 

Project: The development of innovative approaches for the synthesis of bioactive molecules and the biotransformation of food processing by-products into added-value functional ingredients

Project code: PR22

Supervisor: Djordje Romanic 

Project: Rapid urbanization and climate change are intensifying the Urban Heat Island (UHI) effect, where urban areas experience higher temperatures than surrounding rural regions. In the UAE, cities like Abu Dhabi and Dubai face extreme summer heat, exacerbating energy demand for cooling, increasing heat stress, and affecting urban sustainability. Objectives: Quantify the intensity of the UHI effect in a UAE city using observational and remote sensing data. Identify urban hotspots and key drivers of the UHI effect, including land use and urban morphology. Propose evidence-based mitigation strategies, such as green roofs, reflective materials, and tree planting. Methodology: Data Collection: Utilize satellite data (e.g., MODIS for surface temperatures), weather station measurements, and urban land use maps. Analysis: Calculate UHI intensity by comparing urban and rural temperatures. Use Geographic Information Systems (GIS) to map spatial patterns of the UHI effect. Mitigation: Evaluate the potential impact of proposed strategies using urban climate models. Deliverables: A detailed report quantifying UHI intensity and identifying hotspots. Maps and visualizations of UHI spatial patterns. Policy recommendations for urban planning to mitigate the UHI effect. Potential Impact: This project aligns with UAE’s Green Growth Strategy and Vision 2030, supporting sustainable urban development and energy efficiency goals.

Project code: PR30

Supervisor: Sara Ahmed 

Project: Digital health technologies have shown significant potential in improving rehabilitation services, enhancing patient outcomes, and increasing efficiency. However, gaps persist in knowledge and research prioritization of this important field, particularly in interoperability, data availability, and personalization of rehab care in the public sector in Montreal, Canada and Dubai, UAE. This project will bridge the gap in knowledge and strong evidence provision by identifying barriers, facilitators, and scope of improvement associated with the effective integration of applied digital health technologies within rehabilitation services, and propose solutions for improving personalized rehabilitation services. It will also explore the inter sectoral collaborative efforts between the public and private sector in both the cities. Objectives: 1.Identify gaps in digital health integration in rehabilitation services by assessing the barriers and key facilitators of the provision of digital health services in rehabilitation services by studying a public sector governed hospital/ organization in Montreal and Dubai. 2. Determining the improvement opportunities and solutions for better integration of digital health technologies in rehabilitation services in Canada and U.A.E. Methodology: - Cross sectional design will be conducted applying the following methods: Literature review: Data sources like Scopus, PubMed etc within the timeline of publication of 2019-2024. Documents such as reviewed articles, conference reports, NGO reports and books will be selected which will help in understanding the landscape of digital health technologies in rehabilitation services in U.A.E. and Canada. - 20 in-depth interviews: 10 in each city/country, targeting levels of people who are involved in policy, management, and clinical levels of the rehabilitation service system. Different sector’s will be studied by interviewing 2 from each public, private, NGOs & patient associations and academia respectively.

Project code: PR31

Supervisor: Amir Shmuel

Project Description: Machine learning for identifying the brain’s cortical neurons and blood vessels. Tissue clearing and light-sheet microscopy are cutting-edge methods for 3D imaging of tissue components, e.g., neurons and capillaries. With the advent of these methods, we can now quantify and model the 3D brain's organization at a high resolution (voxels with 1-2 micron-long edges). The project aims to develop machine-learning scripts for analyzing high throughput cleared tissue with fluorescence emitted from neurons and cortical blood vessels. Contribution of the students: The students will review material to learn the basics of the brain’s organization and activity. They will receive data and develop analysis pipelines using available scripts from software packages. They will create an analysis package for identifying and segmenting neurons, blood vessels, and capillaries in the cerebral cortex. They will document the methods and the results. They will write a detailed report. Novel methods have the potential for publication. Required skills: The ideal candidates will have knowledge and skills in signal and/or image processing, statistics, and coding. Skills to be developed during the training the students will gain knowledge and experience in the basics of the brain’s organization, preparing machine-learning analysis pipelines based on existing software packages, and how to write a journal paper. Description of your Research Group: https://www.mcgill.ca/neuro/amir-shmuel-phd