Hello, I am Sneha Paul. Currently, I am a Ph.D. Candidate at the Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada. I am supervised by Dr. Zachary Patterson and Dr. Nizar Bouguila, and my research focuses on 3D computer vision involving Point Clouds in unsupervised settings.

I have published papers in renowned places, such as CVPR, ECCV. I am experienced in Python and different libraries (e.g., PyTorch, Scikit-learn, and NumPy), model design, training, and deployment. I also have 2 years of academic teaching experience. I am honoured to receive several awards and scholarships throughout my academic journey.

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	Point Cloud as a Foreign Language for Multi-modal Large Language Model Sneha Paul, Zachary Patterson, Nizar Bouguila Conference on Computer Vision and Pattern Recognition (CVPR 2026) ArXiv TLDR: We introduce a lightweight, trainable tokenizer that projects point clouds into an LLM's input space, enabling multi-modal large language models to natively understand 3D point cloud data.
	An Adapter-free Fine-tuning Approach for Tuning 3D Foundation Models Sneha Paul, Zachary Patterson, Nizar Bouguila International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2026) ArXiv TLDR: An adapter-free approach for fine-tuning 3D foundation models (e.g., Point-MAE) that avoids extra parameters while achieving competitive performance.
	Improving 3D Semi-supervised Learning by Effectively Utilizing All Unlabelled Data Sneha Paul, Zachary Patterson, Nizar Bouguila European Conference on Computer Vision (ECCV 2024) Paper | ArXiv TLDR: A semi-supervised framework for 3D point cloud learning that effectively leverages all unlabelled data to boost performance on downstream tasks.
	FishSegSSL: A Semi-supervised Semantic Segmentation Framework for Fish-eye Images Sneha Paul, Zachary Patterson, Nizar Bouguila Journal of Imaging, 2024 Paper TLDR: A semi-supervised semantic segmentation framework tailored for fish-eye camera images, addressing the challenges of large-FoV distortion in autonomous driving scenarios.
	Semi-supervised Semantic Segmentation on Vehicle-mounted Fish-eye Camera Images Sneha Paul, Zachary Patterson, Nizar Bouguila Transportation Research Board 103rd Annual Meeting (TRB 2024) 🏆 Best Paper Award PDF TLDR: A semi-supervised semantic segmentation approach for vehicle-mounted fish-eye camera images, leveraging unlabelled driving data to improve performance under wide-FoV distortions.
	CrossMoCo: Multi-modal Momentum Contrastive Learning for Point Cloud Sneha Paul, Zachary Patterson, Nizar Bouguila 20th Conference on Robots and Vision (CRV 2023) Paper TLDR: A multi-modal momentum contrastive learning method that learns rich 3D point cloud representations by leveraging cross-modal consistency between point clouds and other modalities.
	A Multi-layer Perceptron-based Two-stream Fusion Model for 3D Point Cloud Classification Sneha Paul, Zachary Patterson, Nizar Bouguila The Visual Computer Journal, 2023 Paper
	Semantic Segmentation Using Transfer Learning on Fisheye Images Sneha Paul, Zachary Patterson, Nizar Bouguila 22nd International Conference on Machine Learning and Applications (ICMLA 2023) Paper
	Improved Training for 3D Point Cloud Classification Sneha Paul, Zachary Patterson, Nizar Bouguila IAPR Joint International Workshops on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition (S+SSPR 2022) Paper
	Forecasting the Average Temperature Rise in Bangladesh: A Time Series Analysis Sneha Paul, Shuvendu Roy Journal of Engineering Science, 11(1), 83-91 PDF
	Land-Use Detection Using Residual Convolutional Neural Network Shuvendu Roy, Sneha Paul 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT 2019)

Reviewing

1. British Machine Vision Conference (BMVC), 2025
2. Computer Vision and Pattern Recognition (CVPR), 2025
3. International Conference on Learning Representations (ICLR), 2025
4. European Conference on Computer Vision (ECCV), 2024
5. International Conference on Machine Learning and Applications (ICMLA), 2023
6. International Conference on Robots and Vision (CRV), 2023
7. Pattern Recognition (Journal)
8. IEEE Transactions on Industrial Informatics (TII)
9. IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
10. Engineering Applications of Artificial Intelligence

1. Best Paper Award, TRB AED30 Information Systems and Technology Committee — Transportation Research Board 103rd Annual Meeting, Washington DC, Jan 2024
2. CIRRELT Doctoral Excellence Scholarship, Centre interuniversitaire de recherche sur les réseaux d'entreprise, la logistique et le transport, Jan 2024
3. Concordia University International Tuition Award Excellence, 2023
4. Concordia University Graduate Studies Conference and Exposition Award, 2022, 2023
5. CIRRELT Masters' Excellence Scholarship, Jan 2022
6. University Gold Medal (selected) — Upcoming Convocation Ceremony, KUET
7. Dean's Award for Excellent Performance, KUET, 2016, 2018, 2019
8. Academic Scholarship, KUET, 2015–2019