Publications
B. B. Desai, Y. A. Rajapur, A. Mundayatt, and J. Sreevalsan-Nair, CityAQVis: Integrated ML-Visualization Sandbox Tool for Pollutant Estimation in Urban Regions Using Multi-Source Data (Software Article), Under editorial hold at arXiv Preprints, 2025.
A. Mundayatt and J. Sreevalsan-Nair, Large-scale hazard susceptibility mapping using machine learning and deep learning techniques, (accepted) as the Graduate Forum, the Sixth Indian Symposium on Machine Learning (IndoML 2025), 2025.
K. K. Htay and J. Sreevalsan-Nair, “Attention- and Uncertainty-based Enhancements to U-Net Model for Semantic Segmentation of Aerial Imagery for Land Cover Classification,” (accepted) in the IEEE International Conference on Robotics and Mechatronics, IEEE, 2025.
V. S. Bitra, R. R. Vangimalla, and J. Sreevalsan-Nair, “Network-based Diseasome Construction from Multi-omics Data and RadTrix Visualization,” IEEE Transactions on Computational Biology and Bioinformatics (to appear), 2025. https://doi.org/10.1109/TCBBIO.2025.3599771
J. Sreevalsan-Nair, A. Mundayatt, B. Gnanaraj, A. Thomas, N. C. Kumar, G. G. Sabhahit, S. Joshi, and T. K. Srikanth, “Mental Healthcare in the Times of Climate Change Action and Data Science,” in Data-Driven Insights and Analytics for Measurable Sustainable Development Goals, Elsevier, 2025, pp. 59-82. https://doi.org/10.1016/B978-0-443-33044-5.00010-3. [Online]. Available: Elsevier webpage
K. Sama, J. Sreevalsan-Nair, S. Choudhary, S. Nagendra, P. V. Reddy, A. Cohen, U. M. Mehta, and J. Torous, “mindLAMPVis as a Co-designed Clinician-facing Data Visualization Portal to Integrate Clinical Observations from Digital Phenotyping in Schizophrenia: User-centered Design Process and Pilot Implementation,” JMIR Formative Research, vol. 9:e70073, 2025, PMID: 40493647; Preprint at https://preprints.jmir.org/preprint/70073 DOI: https://doi.org/10.2916/70073 [Online]. Available: https://formative.jmir.org/2025/1/e70073
S. Kothari, S. Murali, S. Kothari, U. Verma, and J. Sreevalsan-Nair, Adversarial Robustness of Deep Learning Models for Inland Water Body Segmentation from SAR Images, arXiv Preprints, 2025. [Online]. Available: https://arxiv.org/abs/2505.01884
R. N. Laveti, J. Sreevalsan-Nair, and T. Srikanth, “EAMF: An Entropy-enhanced Attention-based Ensemble Metric Few-Shot Learning for MRI Image Classification,” in Proceedings of the 2025 47th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (accepted), IEEE, 2025.
B. Gnanaraj, S. Manivasagam, and J. Sreevalsan-Nair, “To the Point: From Dynamic Heatmap Video to Gaze Points,” in Proceedings of the 2025 Symposium on Eye Tracking Research and Applications, ser. ETRA ’25, New York, NY, USA: ACM, 2025. https://doi.org/10.1145/3715669.3725873
J. Sreevalsan-Nair, “Data-Driven Framework for Enhanced Flash Flood Preparedness and Building Urban Resilience,” in Proceedings of the 2025 IEEE Bangalore Humanitarian Technology Conference (B-HTC), pp 1-6, IEEE, 2025. https://doi.org/10.1109/B-HTC64616.2025.11116113
J. Sreevalsan-Nair and A. Mundayatt, Evolution of Data-driven Single- and Multi-Hazard Susceptibility Mapping and Emergence of Deep Learning Methods, arXiv Preprints, 2025. [Online]. Available: https://arxiv.org/abs/2502.09045
V. Arora, S. Gupta, A. Kudupu, A. Priyadarshi, A. Mundayatt, and J. Sreevalsan-Nair, CCESAR: Coastline Classification-Extraction From SAR Images Using CNN-U-Net Combination, arXiv Preprints, 2025. [Online].
Available: https://arxiv.org/abs/2501.12384
V. Jaisankar and J. Sreevalsan-Nair, “SuP-SLiP: Subsampled Processing of Large-scale Static LIDAR Point Clouds,” in Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data, ser. GeoSearch ’24, ACM, 2024, 40–47. (doi)(URL)
D. Katkoria, J. Sreevalsan-Nair, M. Sati, and S. Karunakaran, “WBF-ODAL: Weighted Boxes Fusion for 3D Object Detection from Automotive LiDAR Point Clouds,” in Proceedings of 2024 International Conference on Vehicular Technology and Transportation System (ICVTTS), IEEE, 2024, 1–6, Best Paper Award.(doi)(URL)
P. Nileshbhai Butani, J. Sreevalsan-Nair, and N. Kamat, “CMA: An End-to-End System for Reverse Engineering
Choropleth Map Images,” IEEE Geoscience and Remote Sensing Letters, vol. 21, pp. 1–5, 2024, also
presented in the GRSL Special Stream at the 37th Conference on Graphics, Patterns and Images (SIBGRAPI
2024). (doi)(URL)
A. Moreira, F. Bovolo, A. Plaza, and J. Sreevalsan-Nair, “44th IEEE International Geoscience and Remote Sensing Symposium - IGARSS 2024, Athens, Greece, 7-12 July, 2024 Impressions of the First Days,” IEEE Geoscience and Remote Sensing Magazine, vol. 12, no. 3, pp. 149–161, 2024. (doi)
F. Bovolo, J. Sreevalsan-Nair, A. Plaza, H. Yu, and A. Moreira, “GRSS Awards Presented at the IGARSS 2024 Banquet,” IEEE Geoscience and Remote Sensing Magazine, vol. 12, no. 3, pp. 161–170, 2024. (doi)
J. Sreevalsan-Nair, A. Kiran, A. Bhattacharya, B. D. Sagar, G. KN, U. Verma, K. Lanka, and S. K. Meher, “InGARSS 2023 in Bangalore: Striking a Balance,” IEEE Geoscience and Remote Sensing Magazine, vol. 12, no. 3, pp. 180–187, 2024. (doi)
S. Mathai, P. Krishnan, and J. Sreevalsan Nair, “Understanding Graphical Literacy Using School Students’ Comprehension Strategies,” Contemporary Education Dialogue, pp. 1–35, 2024. (doi)
D. Katkoria, J. Sreevalsan-Nair, M. Sati, and S. Karunakaran, “ME-ODAL: Mixture-of-Experts Ensemble of CNN Models for 3D Object Detection from Automotive LiDAR Point Clouds,”in Deep Learning Theory and
Applications, 5th International Conference DeLTA 2024, Dijon, France, July 10-11, 2024, Proceedings, Part II,
CCIS, vol. 2172, Springer Cham, 2024, pp. 279–300. (doi)(URL)
A. Mundayatt and J. Sreevalsan-Nair, “Scaling up Study Area Size in Flood Susceptibility Mapping,” in Proceedings of 2024 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (accepted), IEEE, 2024.
L. S. Liang, J. Sreevalsan-Nair, and B. S. D. Sagar, “Multispectral Data Mining: A Focus on Remote Sensing Satellite Images,” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1522, October 2023. (doi)(eprint)
J. Sreevalsan-Nair, A. Mubayi, J. Chhabra, R. R. Vangimalla, and P. R. Ghogale, “Evaluating Early Pandemic Response through Length-of-Stay Analysis of Case Logs and Epidemiological Modeling: A Case Study of Singapore in Early 2020,” Computational and Mathematical Biophysics, vol. 11, no. 1, p. 20 230 104, October 2023. (doi)(open access)
P. Rastogi, K. Singh, and J. Sreevalsan-Nair, “SunburstChartAnalyzer: Hierarchical Data Retrieval from Images of Sunburst Charts for Tree Visualization,” in Computer Graphics & Visual Computing (CGVC), P. Vangorp and D. Hunter, Eds., The Eurographics Association, 2023, pp. 97–101, ISBN: 978-3-03868-231-8. (doi)
L.-T. Tay and J. Sreevalsan-Nair, “Disaster Susceptibility Analysis in Remote Sensing,” in Cognitive Sensing Technologies and Applications, G. R. Sinha, B. Subudhi, C.-P. Fan, and H. Nisar, Eds., Stevenage, UK: Institute of Engineering and Technology (IET), 2023 (doi)(url).
D. Katkoria and J. Sreevalsan-Nair, “Evaluating and Improving RoSELS for Road Surface Extraction from 3D Automotive LiDAR Point Cloud Sequences,” in Deep Learning Theory and Applications: Revised Selected Papers from Third International Conference DeLTA 2022, Portugal, Chapter 6, CCIS volume 1858, Springer Cham, 2023. (doi) (book-link)
B. Gnanaraj and J. Sreevalsan-Nair, “EyeExplore: An Interactive Visualization Tool for Eye-Tracking Data for Novel Stimulus-Based Analysis,” in Proceedings of the 2023 Symposium on Eye Tracking Research and Applications, ser. ETRA ’23, Tubingen, Germany: ACM, 2023. (doi)
J. Sreevalsan-Nair, Co-Association Matrices in Ensemble Clustering: Diverse Applications and Extensions, Preprint available at SSRN, May 2023. (url)
H. Ravindra and J. Sreevalsan-Nair, “A Methodology for Integrating Population Health Surveys Using Spatial Statistics and Visualizations for Cross-sectional Analysis,” SN Computer Science, vol. 4, no. 224, pp. 1–19, 2023. (full-text view) (doi)
S. Singh and J. Sreevalsan-Nair, “Visual Exploration of LiDAR Point Clouds,” in Advances in Scalable and Intelligent Geospatial Analytics: Challenges and Applications, Chapter 12, K. Kurte, S. Durbha, J. Sanyal, L. Yang, S. Chaudhari, U. Bhangale, and U. Bharambe, Eds., Florida, USA: CRC Press, 2023, p. 19. (doi)
J. Sreevalsan-Nair, “On Metavisualization and Properties of Visualization,” in Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Vol 3, IVAPP, INSTICC, SciTePress, 2023, pp. 230–239, ISBN: 978-989-758-634-7. (doi)
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