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Abid Hasan
MEng student in Electrical Engineering (Intelligent Systems) at McGill University, focused on machine learning, multimodal AI, computer vision, and retrieval-augmented systems.
I build practical ML systems and research-driven prototypes across multimodal retrieval, visual question answering, representation learning, OOD detection, and scientific data modeling.
What I work on
- Machine learning and deep learning systems
- Multimodal AI and vision language models
- Representation learning and data driven modeling
- Robust and reliable machine learning
- Retrieval systems and downstream LLM fine tuning
Highlights
- Built a multimodal RAG system for visual question answering with SigLIP and CLIP-based retrieval.
- Developed and evaluated models for dopamine fluorescence classification in Parkinson’s disease research.
- Proposed a zero-shot multimodal approach for out-of-distribution segmentation.
- Trained ML models on 2M+ wave-height samples from 47 buoys across the USA and Canada.
Quick links
- Email: abid.hasan@mail.mcgill.ca
- GitHub: github.com/abidhasan03
- LinkedIn: linkedin.com/in/abid-hasan3
