Dr. Jiju Poovvancheri
Saint Mary’s University, Halifax, Canada. Director of the Graphics & Spatial Computing Lab. Previously a postdoctoral researcher at the Graphics Lab, University of Victoria, and the Geospatial Intelligence Lab, University of Calgary; PhD from Indian Institute of Technology (IIT) Madras with Prof. Ramanathan Muthuganapathy, and a Master’s from National Institute of Technology (NIT) Surathkal, Karnataka.
Research
My research lies at the intersection of 3D computer vision, computer graphics, geometric learning, and spatial computing, with a focus on scalable, learning-based algorithms for understanding and modelling large-scale 3D environments. Motivated by challenges in urban, environmental, and planetary sensing, my work emphasizes a principled integration of geometry, topology, and machine learning for robust perception from 3D data.
A central theme is the analysis of point clouds acquired from LiDAR and RGB-D sensors. Rather than treating 3D data as unstructured input, I design methods that leverage spatial data structures, geometric priors, and topological representations to improve the scalability, generalization, and interpretability of learning-based models. The broader goal is next-generation 3D spatial intelligence for digital twins, urban modelling and simulation, autonomous perception, and environmental monitoring — grounded in solid geometric and algorithmic foundations.
Point cloud learning
Representation learning for large-scale LiDAR and RGB-D data.
Semantic reconstruction
Surface reconstruction and scene understanding in complex urban environments.
Spatial data structures
Hierarchical representations for efficient 3D computation.
Topological deep learning
Topology-aware sampling, feature learning, and structural regularization.
Join the lab
Funded positions are available at the PhD, MSc, and BSc levels for motivated students who want to work on hard problems in graphics, vision, and geometric learning. See the open positions on the team page, then email Show email with your CV and transcripts.
Professional activities
Editorial
- Associate Editor, IEEE Access 2019–
- Guest Editor, Remote Sensing — 3D Semantic Modeling of Urban Scenes from Point Clouds (I & II)
- Guest Editor, Remote Sensing — Deep Learning based 3D Scene Understanding from LiDAR
- Guest Editor, Sensors — LiDAR based Virtual City Creation
Committees & service
- Program Committee — NeurIPS 2026, CVPR 2026/25, ICCV 2025, ECCV 2026/24, CRV, USM3D, ISVC
- Session Chair — Urban: Computational Methods, SAR & Infrastructure (posters), IEEE IGARSS 2026
- Session Chair — 3D Data Construction, Processing and Evaluation (posters), IEEE IGARSS 2023
- NSERC CS Scholarship Committee 2022–25
- Science Atlantic CS Committee 2023–2025
- AARMS CRG Scientific Machine Learning 2021–
- IEEE GRSS Image Analysis & Data Fusion 2023–
Reviewer — journals
- IEEE TPAMI · IEEE TIP · IEEE TGRS · IEEE T-ITS
- Computer Vision & Image Understanding (CVIU)
- Image & Vision Computing (IVC)
- Computer Graphics Forum (CGF) · Computers & Graphics
Reviewer — conferences
- NeurIPS · CVPR · ICCV · ECCV · WACV · BMVC
- CRV · ISVC · INDOOR3D · SIBGRAPI · ISPRS Congress
Funding agencies
- NSERC Discovery Grant · MITACS Accelerate
Memberships
Contact
Office: MN130, McNally North
Department of Mathematics & Computing Science
Saint Mary’s University
923 Robie Street, Halifax, NS, Canada B3H 3C3
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+1 902 420 5787