The SMART program is committed to recruiting and nurturing a diverse cohort of 96 HQP over six years: 18 undergraduate students, 34 Master’s students, 34 PhD students, and 10 postdoctoral fellows (PDFs). Graduate students will apply to the SMART program after being admitted to their home institutions, where their academic excellence has already been demonstrated. Current graduate programs are often siloed in technical specialization and lack the interdisciplinary focus needed to integrate these technologies into cohesive, real-world applications. Industry partners seek graduates who not only have technical knowledge but also understand how technologies interact within the broader mobility ecosystem. SMART meets this need by fostering an interdisciplinary research environment. Trainees are mentored to think beyond their specific disciplines and consider the entire lifecycle of mobility technologies—from design to deployment. Trainees test and refine their research innovations using York’s campus-wide Living Lab and Digital Campus Twin for real-time evaluations.
Year 1 Trainees
Jowel Akkeh
I am currently a first-year PhD candidate in Transportation Engineering at York University. I completed my Bachelor of Engineering in Civil Engineering at York University and, in 2025, earned my master's degree there as well. My research focuses on the integration of Sidewalk Autonomous Delivery Robots (SADRs) into urban spaces, with a specific emphasis on developing a new Pedestrian Level of Service (PLOS) framework and establishing design planning guidelines for mixed-use environments.
Mohammadjavad Ghorbanalivakili
I was born in Tehran, Iran, in 1996. I received a B.S. degree in mechanical engineering from the University of Tehran, Iran, in 2019 and an M.S. degree in mechanical engineering from Sharif University of Technology, Tehran, Iran, in 2021. From 2017 to 2019, I was a research assistant at the Center of Advanced Systems Analysis and Design (CDSAD), University of Tehran. From 2019 to 2021, I was a researcher at the Agricultural Robotics Lab at Sharif University of Technology. Since late 2021, I have been a research assistant and Ph.D. student with the Earth and Space Science and Engineering Department, York University, Toronto, Canada. I am currently researching railway autonomy with the focus on rail scene understanding using data gathered by different sensors installed on the train. Current research goal is to generate rail path proposals in front of a moving train using camera and LiDAR sensors based on computer vision and deep learning techniques.
Arian Haghparast
I am a fourth-year Computer Science undergraduate student with a research focus in machine learning and its applications to intelligent mobility systems. My work spans reinforcement learning, deep learning, and data-driven modeling, with an emphasis on trajectory representation learning, multi-agent coordination, and decision-making in complex transportation networks. I am also interested in learning-based control for autonomous platforms and in exploring how ML-driven approaches can enhance safety, efficiency, and adaptability. Ultimately, I aim to contribute to the development of scalable and sustainable mobility solutions.
Omar Hassanin
I am currently pursuing my PhD at the University of Calgary with Dr. Sayeh Bayat and Dr. Carolyn Emery on how concussions affect the driving behaviours of youths. I use advanced tools such as artificial intelligence and driving monitoring systems to study how their driving changes during recovery. I am passionate about using this research to improve safety and health. I completed two Master’s degrees. My first MSc in Transportation Engineering from Tongji University in 2022 focused on improving autonomous vehicle safety and performance, and I earned a Chinese patent for my work. My second MSc in Transportation Engineering from the University of Calgary in 2024 focused on improving the trip-based macroscopic fundamental diagram (MFD), while studying the impact of integrating connected and automated vehicles (CAVs) from a macroscopic perspective.
Van Hung Le
I am a master's student in EECS with prior experience as a software developer using Java and Ruby. My current research focuses on applying diffusion models to wireless communication systems, particularly for denoising in image transmission. I am interested in computer vision, especially image generation. I also enjoy coding as a hobby.
Zehao Li (Hugo)
I am a master’s student in Electrical and Computer Engineering at Western University. My research focuses on on-demand route optimization for delivering daily necessities from urban pickup hubs to remote households. I am interested in modeling and simulation of multi-stop delivery operations.
Anthony Loschiavo
My name is Anthony Loschiavo and I am a fourth-year undergraduate student in the Sustainable Environmental Management honours bachelor's program concurrently obtaining a certificate in Geomatics: Geographic Information Systems and Remote Sensing. My research focuses on the use of geospatial tools to solve complex environmental issues that correlate to physical and socioeconomic data. I have applied my work through a series of internships at the City of Richmond Hill and the Toronto and Region Conservation Authority for water-related spatial analysis. I look to continue my research in a Master of Science program in Geography with a concentration in Geomatics. I enjoy hiking, playing hockey, reading, and exploring new places on my free time.
Abed Matinpour
I am a master’s student at the Lassonde School of Engineering. My research focuses on performance engineering and optimization of large language model inference, with a particular emphasis on efficiency and scalability. I also specialize in deep learning for spatio-temporal data such as trajectory and GPS data, exploring transformer-based models for these applications. Abed has received several awards and scholarships in research, mathematics, and competitive problem-solving, and I have a strong interest in the mathematical and probabilistic foundations of computer science. In addition to my academic work, I serve as the CEO and Co-Founder of a startup dedicated to enhancing road safety through the application of machine learning.
Bara Rababah
I am a PhD student in Civil Engineering at Toronto Metropolitan University, working in the Laboratory of Innovations in Transportation (LiTrans). My research focuses on pedestrian–vehicle interaction using immersive virtual reality and stress-response sensors, with an emphasis on surrogate safety metrics, including PET, TTC, and wait time. I work with large-scale behavioural datasets from Toronto and Newcastle to model crossing decisions and assess the effectiveness of urban safety interventions. My goal is to support safer and more sustainable mobility systems through the use of advanced simulation and data-driven methods. I look forward to being part of the SMART-CREATE program and collaborating with the cohort.
Ahmed Radwan
I am an M.Sc. Computer Science student and Research Assistant at York University, currently working as an Applied Machine Learning Intern on the AI Engineering team at the Vector Institute. My work focuses on improving AI generalization and efficient deployment for multimodal data, with projects that span WiFi sensing, video understanding, and natural language. I am especially interested in making these systems genuinely trustworthy and explainable, so that their behavior can be understood, studied, and improved by humans. In the long term, I aim to build AI technologies that move smoothly from research to practice while remaining reliable, fair, and transparent.
Jingwen Rao
I am a PhD candidate in Civil and Environmental Engineering at Western University. I received my B.S. in Transportation from Southwest Jiaotong University in 2023 and my M.S. in Civil and Environmental Engineering from the University of Illinois Urbana–Champaign in 2024. My current research focus is on the integration of autonomous vehicles and autonomous transit into future mobility systems, with an emphasis on emission impacts, network modeling, and mobility service design. I aim to develop rigorous modeling, data-driven modeling and optimization frameworks that capture congestion, emission dynamics, and autonomous system interactions to inform transportation planning and regulatory decision-making. Ultimately, my work seeks to support the development of more efficient, sustainable, and equitable mobility systems.
Lingmin Tan
I am a second-year PhD student in the ESSE at York University. My research interests include low-cost GNSS high-precision positioning, smartphone precise point positioning, and machine learning applications in navigation. I am passionate about advancing accessible and accurate positioning technologies. In the future, I hope to continue working in academia through teaching and research.