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Hi, I'm Zijie (Jason) Zhou, a passionate Robotics Engineering student at the University of Toronto with a keen interest in artificial intelligence and deep learning. I've had hands-on experience developing neural networks and computer vision systems, as well as optimizing battery heat prediction models during my internship and research roles. I love tackling challenges with innovative technology and constantly learning new skills. Outside of my studies and work, I enjoy leading teams and organizing engineering competitions to foster a community of curious minds. I'm enthusiastic about applying AI and machine learning techniques to real-world problems and collaborating with others who share a similar passion.…Hi, I'm Zijie (Jason) Zhou, a passionate Robotics Engineering student at the University of Toronto with a keen interest in artificial intelligence and deep learning. I've had hands-on experience developing neural networks and computer vision systems, as well as optimizing battery heat prediction models during my internship and research roles. I love tackling challenges with innovative technology and constantly learning new skills. Outside of my studies and work, I enjoy leading teams and organizing engineering competitions to foster a community of curious minds. I'm enthusiastic about applying AI and machine learning techniques to real-world problems and collaborating with others who share a similar passion.

Zijie (Jason) Zhou

Developer, AI Engineer, Data Scientist, +2

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Hi, I'm Zijie (Jason) Zhou, a passionate Robotics Engineering student at the University of Toronto with a keen interest in artificial intelligence and deep learning. I've had hands-on experience developing neural networks and computer vision systems, as well as optimizing battery heat prediction models during my internship and research roles. I love tackling challenges with innovative technology and constantly learning new skills. Outside of my studies and work, I enjoy leading teams and organizing engineering competitions to foster a community of curious minds. I'm enthusiastic about applying AI and machine learning techniques to real-world problems and collaborating with others who share a similar passion.…Hi, I'm Zijie (Jason) Zhou, a passionate Robotics Engineering student at the University of Toronto with a keen interest in artificial intelligence and deep learning. I've had hands-on experience developing neural networks and computer vision systems, as well as optimizing battery heat prediction models during my internship and research roles. I love tackling challenges with innovative technology and constantly learning new skills. Outside of my studies and work, I enjoy leading teams and organizing engineering competitions to foster a community of curious minds. I'm enthusiastic about applying AI and machine learning techniques to real-world problems and collaborating with others who share a similar passion.

Available to hire

Hi, I’m Zijie (Jason) Zhou, a passionate Robotics Engineering student at the University of Toronto with a keen interest in artificial intelligence and deep learning. I’ve had hands-on experience developing neural networks and computer vision systems, as well as optimizing battery heat prediction models during my internship and research roles. I love tackling challenges with innovative technology and constantly learning new skills.

Outside of my studies and work, I enjoy leading teams and organizing engineering competitions to foster a community of curious minds. I’m enthusiastic about applying AI and machine learning techniques to real-world problems and collaborating with others who share a similar passion.

Skills

Experience Level

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Work Experience

Undergraduate Researcher at St. Michael’s Hospital

April 30, 2025 - July 18, 2025

Developed a computer vision pipeline on NVIDIA Jetson to classify CT scanning stages and to support operational optimization; achieved 83% overall classification accuracy after overfitting diagnostics and tuning. Trained models using NVIDIA’s TAO Toolkit and visualized outputs with DeepStream; optimized performance with 3D temporal modeling, containerized training via Docker, and deployment using ONNX and TensorRT. Annotated datasets using YOLOv8 and Grounded SAM for object detection and segmentation.

Electrical Engineering Intern, Battery Technology at Litens Automotive

August 31, 2024 - July 18, 2025

Developed a U-Net-based neural network in Python as a world model to predict battery pack heat maps; evaluated multiple architectures and optimized coolant inlet placement, achieving a 90% reduction in simulation time and a 12% reduction in maximum temperature. Performed uncertainty quantification on simulation models using RAMDO; applied advanced statistical methods to analyze model reliability, calibrating model against experimental data, achieving 18% increase in accuracy. Built a battery cell aging prediction and optimization framework in MATLAB and Simulink.