Nguyen Anh Khang
I'm Nguyen Anh Khang, a results-driven MS in Computer Science and AI researcher with hands-on experience designing and optimizing deep learning models, especially in computer vision and multi-modal AI.
About
I’m Nguyen Anh Khang, a results-driven MS in Computer Science and AI researcher with hands-on experience designing and optimizing deep learning models, especially in computer vision and multi-modal AI. I enjoy turning research prototypes into production-ready solutions, as demonstrated by winning first place in the IEEE AVSS 2025 AI Safety Challenge and building multi-modal medical AI systems.
I thrive in bridging research with scalable cloud infrastructure, leveraging PyTorch, ONNX Runtime, Docker, AWS, and GitHub Actions to create robust pipelines. I’m excited to contribute to innovative AI systems in healthcare, autonomous safety, and multi-modal reasoning, while continuing to sharpen my skills through impactful collaborations.
- 4 years' experience
- Joined May 2026
Industry experience
- Software & Internet
- Healthcare
- Life Sciences
- Education
- Media & Entertainment
Work experience
Developed deep learning pipelines for early accident anticipation using YOLO and CLIP models; optimized performance and secured 1st Place at the Taiwan AI Safety Challenge (IEEE AVSS 2025). Designed lightweight multi-granularity AI architectures for micro-action recognition, balancing accuracy and efficiency; research submitted to IEEE Transactions on Multimedia (under review). Built a multi-modal diagnostic AI system integrating clinical and imaging data using CNNs, achieving 90% AUC for Liver Fibrosis classification.
Maintained and extended a large-scale production platform (Canon Canada), integrating third-party APIs and implementing feature improvements to keep services scalable and reliable. Collaborated closely with cross-functional teams (QA, product, international clients) through design discussions, issue triage, and delivery reviews.
Developed analytical dashboards for a factory management platform, visualizing complex industrial data using React and TypeScript.
Education
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