I am Puja Saha, M.A.Sc. candidate in Computer Engineering (CGPA: 3.93/4.00) at the University of Guelph, with a Bachelor’s degree in Biomedical Engineering (CGPA: 3.68/4.00). My research interests lie in model architecture adaptation, decentralized machine learning, optimization, and multimodal AI for diverse applications. Currently, I am doing research on decentralized AI for medical image analysis
I am actively seeking PhD/internship opportunities where I can apply my knowledge to contribute to advancing machine learning methodologies for impactful applications and grow.
- Programming: Python, MATLAB, C
- Frameworks and Tools: PyTorch, NVFLARE, MONAI, PySpark, TensorFlow, Flower, LangChain, OpenCV, Scikit-learn, NiBabel
- Technologies: Federated Learning, Cloud Computing (GCP, AWS, Compute Canada), Git
- Operating Systems: Linux, macOS, Windows
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Multiclass Semantic Segmentation:
Developed a PyTorch-based solution for segmenting kidney and tumor regions in CT scans, achieving Dice scores of 91.03% (kidney) and 62.82% (tumor).
GitHub Repository -
Medical Chatbot:
Built a retrieval-augmented generation-based chatbot trained on PubMed data, achieving high context precision and answer accuracy.
GitHub Repository -
Job Market Analysis and Salary Prediction:
Conducted big data exploratory analysis and built a salary prediction model using PySpark, achieving a prediction RMSE of ~$10K.
GitHub Repository -
Human Pose Estimation:
Designed a CNN-based regression model for human pose estimation, achieving an MSE of 0.0878.
GitHub Repository