Celebrating Our Graduates

Winter 2024

The School of Graduate and Postdoctoral Studies (SGPS) is proud of the accomplishments of our graduates and excited to showcase the diverse and impactful research they have undertaken and acknowledge their contributions to Ontario Tech's rich culture of innovation and excellence. To celebrate their achievements, we are pleased to present a selection of our recent graduates and details regarding their completed studies.

Abeer Badawi
PhD (Computer Engineering)
My study aims to understand the complicated behaviors of people living with dementia and predict when agitation or aggression occurs using wearable sensors. The study develops new ways to detect Neuropsychiatric Symptoms that will be acceptable to patients, families, and caregivers. The proposed system will reduce the risk of harm to people living with dementia and others in their environment.

Ashley Hope
MA (Education)
I examined the digital competence and technology use of a small sample of Registered Early Childhood Educators (RECEs) to assess their readiness for fully online professional learning. Using a multi-phase mixed-methods approach, she discovered that fully online collaborative discussions can meet RECEs' professional learning needs despite gaps in their digital awareness. Participants' experiences emphasize the importance of emotional intelligence, social interaction, and technological awareness when designing online learning experiences. The study suggests that fully online learning communities (FOLCs) could address logistical challenges and offer flexibility and continuous support for RECEs.

Ifrodet Giorgees
PhD (Applied Bioscience)
My research involved developing RNA-based combination therapeutic systems with potential applications in cancer treatment and diagnosis. For example, one of the systems I created targets cancer by combining gene silencing with localized cell toxicity through the use of siRNA and photodynamic therapy.

Heidi Allum
MA (Education)
I defended virtually, so no images of me were taken during the process. However, I took this photo when I was done. The closed computer, my presenter notes, and the small fidget toy represent the completion of my thesis.

My thesis gathered data on implementing blogging in a Grade 6 Ontario classroom as a method of trauma-informed care and practice. Over the duration of an academic school year, results demonstrated, through student questionnaires, teacher observations, and conferences, that allowing and encouraging blogging allowed students to process emotions, reflect on their identities, and offer well-being. There is potential in using blogging as a micro-move that teachers can implement to support trauma-informed care.

Nikolas Scuro
PhD (Nuclear Engineering)
This journey has been the toughest yet most rewarding challenge of my life. It was filled with obstacles and moments of self-doubt, but the ups and downs are what make the academic experience so unique. These challenges made the achievement even more satisfying. I am incredibly grateful to my amazing supervisor, Markus Piro, for his guidance and friendship. His support allowed me to expand my research by visiting various institutions in Germany and Italy. This project has been one of the most memorable experiences of my life. Completing my PhD has also given me the technical expertise needed to join the nuclear industry in Ontario, where I am excited to contribute to the development of nuclear energy.

Pardis Haghi
MSc (Nuclear Engineering)
During my thesis defense, I was 35 weeks pregnant. I was so nervous that I thought my baby might arrive during the session! Although it was a long, tough day, everything went great. Four weeks after that day, my baby girl Sophie arrived. For the past seven weeks, my life has been filled with love.

Seham Shahid
PhD (Mechanical Engineering)
My PhD thesis explores the hybrid thermal management strategies for lithium-ion batteries by combining air, liquid, and phase change materials. The research aims to enhance battery performance, safety, and lifespan by maintaining optimal thermal environment under various operating conditions. The study includes experimental validation and computational modeling to evaluate the effectiveness and efficiency of the proposed hybrid strategies.

Dr. Sharif Abu darda
PhD (Nuclear Engineering)
My research was about the mass separation of high-level radioactive waste (HLRW). Using high temperature plasma, HLRW can be subjected to mass separation based on the atomic mass group of the conposit. The goal is to separate the highly radioactive fission products from the used nuclear fuel. The research was carried out using simulation and an experimental demonstration.

Ulya Sabeel
PhD (Computer Science)
In today's digital environment, enhancing network security is paramount as cyber threats continue to evolve rapidly. My research introduces a sophisticated AI-driven Intrusion Detection System (IDS) that effectively detects dynamic polymorphic attacks. Utilizing a combination of Deep Learning techniques such as Conditional Variational Autoencoders and Generative Adversarial Networks, the system generates and identifies realistic adversarial attacks for continuous testing and refinement of the IDS. Rigorous quality analysis ensures these attacks closely mimic original threats, enhancing the system's capability in countering emerging and underrepresented threats. My findings confirm the system's superior detection accuracy, outperforming traditional methods.

Noor Khabbaz
MASc (Mechanical Engineering)
My research focus is in robotics, specifically regarding the collaboration between aerial and ground-based robots. For my thesis project, I worked with robot hardware and software to develop a method for robots to collaborate in missions that could be used in a variety of sectors, including construction, agriculture, and search-and-rescue.

Rachit Desai
MHSc (Health Informatics)
My research focuses on the intersection of A.I and Laboratory Data. Premature infants often receive multiple blood transfusions within the first few weeks of life because of their physiological needs. Anemia is a major contributor to the need for transfusions in premature infants, and current detection practices rely on laboratory testing of blood samples. My research introduces a Clinical Decision Support System (CDSS) framework that utilizes high frequency streaming physiological data and laboratory information for clinical insights through visual analytics. The framework leverages the Artemis platform, a Big Data and Artificial Intelligence based CDSS, by exploring relationships between blood transfusions and heart rate variability (HRV). Using Artemis, my research aimed to identify patterns in HRV to enable non-invasive detection of physiologically significant anemia through data visualization. This work contributes to health informatics by presenting an integrated CDSS framework and to laboratory sciences by demonstrating the potential of laboratory data integration for non-invasive anemia detection.