Shakib Khan
Data Scientist @Roche
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WORK HISTORY
Data Scientist @Roche
Mississauga, ON, CA
Used - to analyze whole slide images in digital pathology, improving accuracy and efficiency with scalable and effective graph techniques. Compared the performance of - like, on digital pathology datasets, benchmarking their results against graph-based approaches. Successfully combined the advanced () with graph neural networks, achieving an 80% average precision on whole slide image datasets. Applied to capture spatial relationships between distant patches in whole slide images, improving the analysis and classification of complex patterns. Built a graph training pipeline using and used to generate graphs from image patches for effective model training.
EDUCATION
Concordia University
Masters of Applied Science, Graph Neural Network, Computer Vision, Natural Language Processing
North South University
Bachelor of Science - BS, Computer Science & Engineering
ABOUT SHAKIB KHAN
With, I specialize in and, focusing on enhancing the performance and scalability of vision and graph-based applications. My expertise includes fine-tuning state-of-the-art models, building robust pipelines, and leveraging advanced techniques to solve complex real-world problems.Previously, I worked as a, where I contributed to developing vision applications for O. In addition, I designed and implemented Graph Neural Network (GNN) models for, tackling challenges in data irregularities and uncovering hidden patterns.Beyond my technical contributions, I have hands-on experience integrating foundation models into large-scale systems, optimizing model performance for specialized tasks, and working with tools such as, and. My passion lies in bridging the gap between cutting-edge research and practical implementation, making AI solutions impactful and efficient.
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