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Ontario Tech acknowledges the lands and people of the Mississaugas of Scugog Island First Nation.

We are thankful to be welcome on these lands in friendship. The lands we are situated on are covered by the Williams Treaties and are the traditional territory of the Mississaugas, a branch of the greater Anishinaabeg Nation, including Algonquin, Ojibway, Odawa and Pottawatomi. These lands remain home to many Indigenous nations and peoples.

We acknowledge this land out of respect for the Indigenous nations who have cared for Turtle Island, also called North America, from before the arrival of settler peoples until this day. Most importantly, we acknowledge that the history of these lands has been tainted by poor treatment and a lack of friendship with the First Nations who call them home.

This history is something we are all affected by because we are all treaty people in Canada. We all have a shared history to reflect on, and each of us is affected by this history in different ways. Our past defines our present, but if we move forward as friends and allies, then it does not have to define our future.

Learn more about Indigenous Education and Cultural Services

Meet the participants

3MT participants

All participants will present at the university's 3MT® virtual heats on Wednesday, March 23. The top six will advance to the virtual finals to be held on Thursday, March 24 at 2:30 p.m. The finals will be a live streamed event.

Faculty of Engineering and Applied Science

  • Abbas Ajorkar

    2022 3MT participant headshot abbas ajorkarProgram

    Mechanical Engineering (PhD)


    Yuping He, PhD


    Autonomous Driving Control of Vehicles

    To increase the safety of vehicles, attention has been paid to exploring active vehicle safety systems. A resolution to the problem is autonomous driving, which removes human factors from the control loop, and this presentation addresses the problem of vehicle autonomous driving control.

    ABOUT Abbas

    Abbas's interests include mountain climbing, reading, watching films, and calligraphy.

  • Kavian Khosravinia


    Mechanical Engineering (PhD)


    Xianke Lin, PhD


    Healthy Fast Charging Strategy for Electric Vehicles Using Deep Neural Networks

    The success of transportation electrification depends largely on energy storage systems. As one of the most promising energy storage systems, lithium-ion batteries (LiBs) have many important properties to meet the wide range of requirements of electric mobility. Although, one of the primary limitations of electric vehicles (EVs) today is the lengthy recharging time of LiBs, which can take several hours compared to the 3-7 minute refueling time of the gas-fueled car. Therefore, the US Department of Energy's current goal is to increase changing speed by offering extreme fast charging (XFC), which allows an electric vehicle to recharge to 80 percent of full capacity in less than 15 minutes. A minimum of 300 kW charging power is necessary to achieve the 15-minute recharge time for a big battery pack size.

    However, reaching extreme fast charging is often rejected due to the increased formation of anodic lithium deposits. Lithium plating is one of the most destructive reactions, resulting in battery degradation and rapid loss of capacity over cycling. The battery community is still looking for a real-time detection technique that can identify lithium plating while the battery is being charged and also be simple to implement into the battery management system (BMS). Therefore, the primary goal of this research is to optimize the fast charging strategy for commercial cylindrical cells by developing a new real-time algorithm based on data-driven and electrochemistry approaches that can detect and forecast lithium plating before it occurs and is easily integrated into the BMS.

    ABOUT Kavian

    I am a Rower in the early mornings, a researcher in the day time during the week.

  • Oluwabukola Grace Adegboro

    2022 3MT participant headshot oluwabukola Program

    Electrical and Computer Engineering (MASc)


    Hossam Gaber, PhD


    Identifying Faults in Industrial Computed Tomography Scans using Deep Learning

    In the nuclear energy sector, particularly in nuclear power plants, timely detection and monitoring of faults are essential for operational safety and performance enhancement. Operation of the plant involves a high level of safety, capability, and reliability. To ensure that the plants run at maximum capacity with minimal downtime, effective routine maintenance procedures are necessary for appropriate repair and inspection. These procedures require the use of the right tool/equipment. Oftentimes, manual inspection has to be carried out on each industrial tool before and after maintenance. This is to ensure that the tool remains in good shape without defects/missing parts and no tool is left behind in the vault. If otherwise, this could pose a safety hazard and lead to a higher risk of workplace accidents, higher repair cost, etc. To alleviate these problems, our research proposes a fault detection method to identify/classify defects on industrial maintenance tools automatically and aid the tool inspection process.

    ABOUT Oluwabukola 

    I am Oluwabukola Grace Adegboro, a 2nd-year master's student under the Electrical & Computer Engineering (MASc.) program. I am passionate about volunteering, making a positive impact, spending quality time with loved ones, and baking.

  • Sifatul Mostafi

    2022 3MT participant headshot sifatul mostafiProgram

    Electrical and Computer Engineering (PhD)


    Khalid Elgazzar, PhD


    A Real Time Jaywalking Detection and Notification System using Deep Learning and Multi Object Tracking

    Jaywalking refers to pedestrians walking or crossing in a roadway that is not dedicated to pedestrians. Due to illegal jaywalking every year a lot of accidents happen worldwide that cause a significant amount of death and other physical injuries. Real-time jaywalking detection and notification system can save both the pedestrian and traffic vehicle to avoid any severe accident. Many computer vision-based image processing techniques are proposed to detect jaywalking including deep learning, motion path analysis, motion object segmentation, trajectory forecasting and position localization. However, these techniques are developed for specific geographic locations and traffic settings.

    In this paper, we propose a deep learning and multi-object tracking-based real-time jaywalking detection and notification system that can be applied to any road intersection worldwide. Our system takes advantage of manual segmentation of regions of interest in traffic roads as well as road crossings. We use state-of-the-art Deep Learning model YOLO and multi-object tracking algorithm DeepSORT for real-time object detection and tracking respectively. The system We run our experiment at the intersection of Conlin and Simcoe Street in Oshawa, ON, Canada. Performance evaluation shows that our proposed approach can effectively detect jaywalking with competetive accuracy in real-time.

    ABOUT Sifatul

    I am a free thinker who loves to explore the mystery behind human life, and almost everything in the whole universe. I have struggled in my whole life to have a decent living, yet never let go of my dream to contribute for the betterment of human life.

Faculty of Health Sciences

  • Danielle Bates

    2022 3MT participant headshot danielle batesProgram

    Health Sciences (MHSc) - Kinesiology


    Serene Kerpan, PhD


    Moving Towards Inclusive and Engaging Physical Education for Girls

    The amount of boys ages 5-17 years old meeting guidelines is nearly double the percentage of girls. In addition, girls often report multiple barriers to participating in school-based physical activity opportunities, including physical education (PE). Common barriers they report include: believing PE will make them appear masculine, intimidation from male aggression in competitive settings, teachers catering to activities that boys enjoy, lack of motor skill competence, and lack of support from their peers/teachers. Since a majority of school-aged children’s time is spent in school, PE provides an opportunity to increase female children’s PA and help them acquire the knowledge and skills to live a healthy, active life. However, research shows that some teachers are using outdated teaching practices that perpetuate gender bias in PE. Furthermore, in Canada, 63% of elementary PE is taught by generalist teachers with no specialized knowledge, training or support.

    There is a large body of literature outlining evidence-based practices that can successfully include and engage female students. In spite of this, translating this research into classroom practices has yet to be done. Gender disparities occurring within the PE environment have the potential to be changed and challenged by physical educators. The purpose of this qualitative inquiry is to develop recommendations for future professional development to support generalist teachers in their teaching practices that are inclusive and engaging for girls, based on views and experiences of Ontario generalist teachers.

    ABOUT Danielle

    In addition to her academics, Danielle is also a dance educator and choreographer that teaches at studios and various kid’s programming across Durham and Northumberland regions. When she isn’t working on her thesis or dancing, she can be found hiking and camping with her goldendoodle pup.

  • Emmeline Meens Miller

    2022 3MT participant headshot emmeline millerProgram

    Health Sciences (MHSc) - Kinesiology


    Shilpa Dogra, PhD


    Identifying Salivary Cytokines Associated with Prolonged Sitting

    Canadians are engaging in more sitting and are sitting for prolonged periods of time without interruption. Higher volumes of sedentary time have been attributed to increased sedentary lifestyles. This increase in the volume of sedentary time being accumulated by an individual, across the lifespan, can be attributed to a substantial shift in our lifestyles and an increased reliance on technology. The shift to a more sedentary lifestyle has made it difficult for Canadians to maintain their physical activity and reduce their time spent sitting. Sedentary time is associated with poorer health outcomes and increased risk of multiple diseases. Prolonged sedentary time has been associated with cardiovascular, respiratory, and metabolic disease, all of which can contribute to premature death. Sedentary time has also been associated with increased risk of certain types of cancer, cardiovascular disease, chronic disease, joint diseases such as osteoarthritis, depression, and increased inflammation.

    The field of sedentary physiology explores and aims to understand why sitting is so detrimental. Sedentary time can be measured directly using biomarkers. Previous research has examined using biomarkers to measure inflammation during prolonged and interrupted sitting. The use of salivary biomarkers, or salivary cytokines, to measure inflammation has been previously documented with individual inflammatory markers being identified. This novel research aims to identify which salivary biomarkers are affected by prolonged versus interrupted sitting. By identifying which inflammatory markers respond to increased sitting periods, this research aims to contribute to finding new ways to measure the effectiveness of sedentary interventions.

    ABOUT Emmeline

    Emmeline is a member of the Varsity Women's Rowing team and is from Courtice, Ontario. Emmeline enjoys the outdoors, travelling, sports (hiking, skiing, water-sports and biking), coaching gymnastics and has two Golden Retrievers named Bo and Archie. 

  • Hailey Tabbert

    hailey tabbery headshotProgram

    Health Sciences (MHSc) - Kinesiology


    Bernadette Murphy, PhD


    Neck vibration alters cortical processing and motor control

    Altered afferent input from the neck has been shown to impact cortical processing and motor control. Given that the cerebellum is the main site for sensorimotor integration of sensory input from the neck and is primarily responsible for motor learning, it is likely that altered afferent input from the neck will impact cerebellar processing and the construction of accurate internal models that permit proper motor learning and motor control. This model is known as body schema and has been frequently examined through the lens of subclinical neck pain.

    Subclinical neck pain is thought to alter body schema by altering sensory information as it travels through the neck. However, neck pain has the potential to alter multiple types of afferent feedback through the involvement of pain afferents, muscle spindles and other receptor types making it difficult to determine its contributions to altered body schema. It is important to understand how altered sensory input from the neck in itself impacts central processing and motor control. Previous research has determined that high frequency, low amplitude vibration over a muscle belly excites Ia afferents of muscle spindles. Since muscle spindles are the major proprioceptors of the neck, and body schema is constructed using this input, we can use vibration to alter sensory information as it travels through this region without the involvement of other receptor types. This would allow us to examine the effects of altered afferent input in and of itself on cortical processing and motor learning.

    ABOUT Hailey

    Hi, I'm Hailey! My hobbies include playing guitar, sports and walking my puppy. I come from a small town called Ridgeway but I've moved around a lot in the past five years. A random fact about me - I once won a taco eating contest.

  • Katie Mikkelsen

    2022 3MT participant headshot katie mikkelsenProgram

    Health Sciences (MHSc) - Community, Public and Population Health


    Mika Nonoyama, PhD


    Analyzing Standards for Rapidly Manufactured Ventilator Systems

    During the COVID-19 pandemic, a shortage of mechanical ventilators became a major issue. In an attempt to solve this issue knowledgeable individuals from various academic disciplines collaborated to design "emergency ventilators" (or rapidly manufactured ventilator systems (RMVS)) from open-source designs. However, out of all of the emergency ventilators that have been published in the literature none have reached the clinical setting. This is in part due to the lack of standards that exist for these machines outlining what is absolutely necessarily to ensure patient safety and quality assurance. Therefore, I am looking to create a list of standards for these machines and analyze the published literature on emergency ventilators to see which ones closely align with the standards, what missing components are common across most designs and provide recommendations for future designers to ensure their machines meet clinical standards.

    ABOUT Katie

    In my undergrad at the University of Guelph I played on the varsity women's ice hockey team and had the privilege of becoming a National Champion after winning gold in PEI. This was the first time in history the Guelph Gryphons women's ice hockey team won a National Championship.

  • Marie Abu Itham

    2022 3MT participant headshot marie ithamProgram

    Health Sciences (MHSc) - Kinesiology


    Meghann Lloyd, PhD


    Parent Perceptions of the Active Play Behaviours of their 4-11-Year-Old Twins and Triplets with Autism

    Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by life-long differences in social, communication and behavioural development. In Canada, 1 in 66 children have a diagnosis of ASD. In twins where one sibling has received a diagnosis of ASD, research demonstrates a high probability of the other twin also having ASD.

    Children with autism engage in active play in different ways than children who are neurotypical. Active play refers to the gross motor or total body movements that young children use to expend energy in a way that is freely chosen, fun, and unstructured. The active play behaviours of children with autism are not well understood. There are many opinions regarding the characteristics of their active play, but there is a lack of empirical research supporting these claims.

    Even more so, there is a lack of research on the active play behaviours of twins and triplets with autism, where both or all children have a diagnosis of ASD. The lack of research describing the active play of twins and triplets with autism is important because this population offers a unique opportunity to control for other variables such as environment, socioeconomic status, and age. This research addresses a gap in the literature as most other research compares play behaviours between children with autism and children who are neurotypical.

    To our knowledge, this qualitative study is the first to explore and describe the active play behaviours of twins and triplets with autism from the perspective of their parents.

    ABOUT Marie

    I love stories. One thing I love about qualitative research is the opportunity to collect the stories that people carry of their experiences. It is a privilege to present these narratives in a way that honors my participants and adds to the generation of knowledge in my field.

  • Sarah Pistritto

    sarah pistritto headshotProgram

    Health Sciences (MHSc) - Community, Public and Population Health


    Winnie Sun, PhD


    Designing a rehabilitation program for mild to moderate dementia patients

    Dementia is a highly prevalent condition that mainly affects older adults. Due to this growing number, it is essential to develop strategies that help delay the onset and progression of cognitive decline. Neuroplasticity can play a key part in rehabilitating cognitive decline by providing an opportunity to enhance cognitive abilities and strengthen areas of the brain that promote motor function, learning, and memory, which can lead to improvements in activities of daily living (ADLs) thus improving an individual’s independence. Existing literature underscored the combination of physical activity and cognitive stimulation interventions providing significant benefit to mild to moderate dementia patients’ functionality, cognitive abilities, and quality of life. However, exploring how to facilitate a neural response and stimulate plasticity to promote the cognitive reserve has not been trialed, nor creating and tailoring an intervention that is specific to dementia has not been established. Therefore, the purpose of this proposed study aims to design a rehabilitation program for mild to moderate dementia patients that utilizes physical activity and cognitive stimulation to achieve a neural and cognitive response through motor learning principles and task-specific training.

    ABOUT Sarah

    Hi my name is Sarah Pistritto, and I am in the first year of my Masters Program. I grew up in Markham, Ontario. My hobbies include being active, playing sports, baking, and painting. Fun fact, my family and I rescued a dog named Coco!

Faculty of Science

  • Mir Afgan Talpur

    2022 3MT participant mir afgan talpurProgram

    Computer Science (MSc)


    Faisal Qureshi, PhD


    Improving Image Matting Through Deep Learning

    Image matting, the art of creating an alpha matte to define the foreground or background of an image or video, is a fundamental computational photography technique in image and video editing. It is used to compose images by introducing new backgrounds to different foregrounds by using this alpha matte. While this technique has been used regularly in film production for quite some time, it is now prominent in everyday life. Throughout this pandemic, we have relied on video conferencing calls to communicate with our colleagues and loved ones. Applications like Zoom and Google Meet introduced features like background blurring and background replacement for both entertainment and professional purposes. Additionally, similar features have been introduced in various smartphones as Portrait Mode or Live Focus. However, this functionality is notorious for being inaccurate and unreliable in many situations, such as a moving object in the background or a busy background in general.

    As these applications become more relevant in everyday use, improving the reliability of these systems becomes more worthwhile. Over the past decade, deep learning has continued to increase its prevalence throughout everyday life. It has solved previously seemingly impossible tasks and has allowed for more research in computational photography due to recent advances in compute power and the introduction of massive datasets. Our research aims to utilize these advancements in deep learning to develop more efficient solutions to the image matting problem.

    ABOUT Mir

    I am a biology graduate, a computer science graduate, and an award-winning filmmaker! A fun fact about me, my first ever job in high school was based in Ontario Tech back in 2010, then known as UOIT.

  • Nadia Goralski


    Computer Science (MSc)


    Jeremy Bradbury, PhD


    Adaptive Coding Puzzles

    Parsons Problems are mixed up blocks of code which a user must rearrange to form a correct solution for a given problem. We look to improve upon existing Parsons Problems by introducing adaptive measures building up to writing code solutions through different levels of increasing difficulty.

    ABOUT Nadia

    Nadia enjoys hockey, hiking and camping. 

  • Stacey Koornneef

    2022 3MT participant headshot stacey koornneefProgram

    Computer Science (MSc)


    Jeremy Bradbury, PhD and Michael Miljanovic, PhD


    Run, Llama, Run: A Collaborative Physical and Online Coding Game for Children

    Computational thinking and computer science are now being introduced in K-5 classrooms and this has led to a demand for more engaging and interactive tools designed for a younger audience. Educational games and block-based programming are two approaches that have been shown to be effective at engaging children to learn computer science. While existing tools have value, they also have limitations with respect to their support for collaborative learning and with respect to equitable access. Run, Llama, Run, is a collaborative educational game designed to be played by K-5 students both with and without access to a tablet or computer. The game includes physical programming blocks where a group of students work together to find a solution for a given scenario. A digital interface is available to execute and animate student solutions and a non-digital alternative allows students to act out their solutions. Future work in this research will involve a study to determine the effectiveness of the different versions of the game to encourage collaboration between students.

    ABOUT Stacey

    Stacey completed her undergraduate degree in computer science at the University of Ontario Institute of Technology. Outside of school, Stacey can often be found reading, painting, or playing music.

Faculty of Social Science and Humanities