Publications

Recent publications (2019-):
  • S. C. Daggubati, J. Sreevalsan-Nair, and K. Dadhich, “BarChartAnalyzer: Data Extraction and Summarization of Bar Charts from Images,” SN Computer Science, 3(500), 1–19, 2022. (full-text view) (doi)
  • J. Sreevalsan-Nair and A. Jakher, “CAP-DSDN: Node Co-association Prediction in Communities in Dynamic Sparse Directed Networks and a Case Study of Migration Flow,” in Proceedings of the 14th International Conference on Knowledge Discovery and Information Retrieval (accepted), INSTICC, SciTePress, 2022.
    (Best Paper Award Nomination)
  • H. Ravindra and J. Sreevalsan-Nair, "Composition of Geospatial Visualizations for Scale-aware Views of Multiple Outcome Variables in Population Surveys," in Proceedings of the 26th International Conference on Information Visualization IV2022 - AIMH track - Visualization and Artificial Intelligence for Medicine, Healthcare, and Social Good (to appear), GraphicsLink, July 2022.
  • R. R. Vangimalla and J. Sreevalsan-Nair, “Communities and Cliques in Functional Brain Network Using Multiscale Consensus Approach,” IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), vol. 30, pp. 1951–1960, 2022 (doi).
  • D. Katkoria and J. Sreevalsan-Nair, “RoSELS: Road Surface Extraction for 3D Automotive LiDAR Point Cloud
    Sequence,” in Proceedings of the 3rd International Conference on Deep Learning Theory and Applications (DeLTA), INSTICC, SciTePress, 2022, 55–67. ISBN : 978-989-758-584-5. (doi). (Best Paper Award Nomination)
  • S. C. Daggubati and J. Sreevalsan-Nair, “ACCirO: A System for Analyzing and Digitizing Images of Charts
    with Circular Objects,” in Computational Science – ICCS 2022, Proceedings of the 22 nd International Conference, Part III, chapter 50, Cham: Springer International Publishing, 2022, pp. 605–612. (doi)
  • S. Agarwal, F. Beck, U. Ghosh, and J. Sreevalsan-Nair, "CiteVis: Visual Analysis of Overlapping Citation Intents as Dynamic Sets," poster presentation at the 15th IEEE Pacific Visualization Symposium (PacificVis) 2022, April 2022.
  • J. Sreevalsan-Nair, K. Dadhich, and S. C. Daggubati, "Tensor Fields for Data Extraction from Chart Images: Bar Charts and Scatter Plots," in Topological Methods in Data Analysis and Visualization VI, Ingrid Hotz, Talha Bin Masood, Filip Sadlo, and Julien Tierny (Eds.). Springer, Cham, 2021, pp 219-241. (doi).Preprint at arXiv (2020), October 2020, https://arxiv.org/abs/2010.02319
  • J. Sreevalsan-Nair, "Normal Distribution,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022.(doi)
  • J. Sreevalsan-Nair, P. Mohapatra, and S. Singh, “IMGD: Image-based Multiscale Global Descriptors of Airborne LIDAR Point Clouds Used for Comparative Analysis,” in Smart Tools and Apps in Graphics (STAG 2021) - Eurographics Italian Chapter Conference, P. Frosini, D. Giorgi, S. Melzi, and E. Rodolá, Eds., The Eurographics Association, October 2021, pp 61--72, ISBN: 978-3-03868-165-6.(doi)
  • R. Thangavel and J. Sreevalsan-Nair, “CV4FEE: Flood Extent Estimation Using Consensus Voting in Ensemble of Methods for Change Detection in Sentinel-1 GRD SAR Images,” in 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR 2021), IEEE, 2021, pp 1--6.(doi)
  • A. C. Victor and J. Sreevalsan-Nair, “Building 3D Virtual Worlds from Monocular Images of Urban Road Traffic Scenes,” in International Symposium on Visual Computing (ISVC 2021), Part II, Lecture Notes in Computer Science LNCS 13018, Bebis, George et al., Springer Nature Switzerland AG, October 2021. (doi)(Easychair preprint)
  • J. Sreevalsan-Nair, "K-Means Clustering,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022.(doi)
  • J. Sreevalsan-Nair, "Virtual Globe,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022.(doi)
  • J. Sreevalsan-Nair, "K-Nearest Neighbors,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022. (doi)
  • J. Sreevalsan-Nair, "Minimum Entropy Deconvolution,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022. (doi)
  • R. R. Vangimalla and J. Sreevalsan-Nair, “HCNM: Heterogenous Correlation Network Model for Multi-level Integrative Study of Multi-omics Data for Cancer Subtype Prediction,” (accepted) in the Proceedings of the 43rd International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), November 2021.
  • Singh, S., and Sreevalsan-Nair, J., “Adaptive Multiscale Feature Extraction in a Distributed System for Semantic Classification of Airborne LiDAR Point Clouds,” IEEE Geoscience and Remote Sensing Letters (Early Access), July 2021. (doi)(preprint)
  • J. Sreevalsan-Nair, "Data Visualization,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022. (doi)
  • J. Sreevalsan-Nair, “Multiscaling,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022. (doi)
  • J. Sreevalsan-Nair, “LiDAR,” in Earth Sciences Series, Encyclopedia of Mathematical Geosciences (accepted), B. S. D. Sagar, Q. Cheng, J. McKinley, and F. Agterberg, Eds., Springer International Publishing, 2022. (doi)
  • V. Sridhar, J. Sreevalsan-Nair, P. R. Ghogale, and R. R. Vangimalla, “Sharing and Use of Non-Personal Health Information: Case of the COVID-19 Pandemic,” in Data Centric Living: Algorithms, Digitization and Regulation (in press), V. Sridhar, Ed., 1st ed., Routledge India, 2022, ch. 8, ISBN : 9780367536534. (doi)
  • K. Dadhich, S. C. Daggubati, and J. Sreevalsan-Nair, "ScatterPlotAnalyzer: Digitizing Images of Charts Using Tensor-based Computational Model" in International Conference on Computational Science, Computational Science -- ICCS 2021, Part V, Lecture Notes in Computer Science, volume 12746, M. Paszynski, D. Kranzlmüller, V. V. Krzhizhanovskaya, and P. M. Dongarra Jack J. and Sloot, Eds., Cham: Springer International Publishing, 2021, pp. 70–83, ISBN : 978-3-030-77977-1. (doi)(preprint)
  • K. Dadhich, S. C. Daggubati, and J. Sreevalsan-Nair, "BarChartAnalyzer: Digitizing Images of Bar Charts," in the Proceedings of the International Conference on Image Processing and Vision Engineering (IMPROVE 2021), pp 17--28, April 2021. (doi) (preprint) (Best Paper Award Nomination)
  • H. Ravindra, and J. Sreevalsan-Nair, "Integrating Population Surveys Using Spatial Visual Analytics: A Case Study on Nutrition and Health Indicators of Children under Five in India," in the Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2021), pp 203--213, April 2021, SCITEPRESS. (doi)(preprint)
  • S. Singh, and J. Sreevalsan-Nair, "A Distributed System for Optimal Scale Feature Extraction and Semantic Classification of Airborne LiDAR Point Clouds," in Distributed Computing and Internet Technology, Proceedings of the 17th International Conference on Distributed Computing and Internet Technology (ICDCIT), January 2021, Sequence Number 18, Lecture Notes in Computer Science, Springer International Publishing. (doi)(preprint)
  • Jakher, A., and Sreevalsan-Nair, J., “Community Detection in Migration Flow Networks,” accepted for oral presentation at the Urban Complex Sysems 2020, a satellite event at the annual Conference on Complex Systems 2020 (CCS 2020), December 9-10, 2020.
  • R. R. Vangimalla and Sreevalsan-Nair J. “Comparing Community Detection Methods in Brain Functional Connectivity Networks,” in Balusamy S., Dudin A.N., Graña M., Mohideen A.K., Sreelaja N.K., Malar B. (eds) Computational Intelligence, Cyber Security and Computational Models. Models and Techniques for Intelligent Systems and Automation. ICC3 2019. Communications in Computer and Information Science, vol 1213. Springer, Singapore. (doi); preprint in bioRxiv (2020), February 2020, (doi).
  • S. Singh, and J. Sreevalsan-Nair, “A Distributed System for Multiscale Feature Extraction and Semantic Classification of Large-scale LiDAR Point Clouds,” to appear in the Proceedings of the 2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS), pp 74-77, December 2020. (doi) (preprint) (Best Paper Award)
  • J. Sreevalsan-Nair and P. Mohapatra, “Influence of Aleatoric Uncertainty on Semantic Classification of Airborne LiDAR Point Clouds: A Case Study with Random Forest Classifier Using Multiscale Features”, to appear in the Proceedings of the 2020 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2020), pp 1066-1070, September 2020. (doi)(preprint)
  • Mehta, U. M., Shadakshari, D., Vani P., Naik, S. K., Kiran Raj, V., Vangimalla, R. R., Reddy, Y. C. J., Sreevalsan-Nair, J., and Bharath, R. D. “Case Report: Obsessive compulsive disorder in posterior cerebellar infarction - illustrating clinical and functional connectivity modulation using MRI-informed transcranial magnetic stimulation,” [version 2; peer review: 2 approved]. Wellcome Open Res 2020, 5:189. (doi)
  • R. R. Vangimalla and J. Sreevalsan-Nair, “A Multiscale Consensus Method Using Factor Analysis to Extract Modular Regions in the Functional Brain Network,” in the Proceedings of the 42nd Annual Conferences of the IEEE Engineering in Medicine and Biology Society, pp 2824-2828, July 2020. (doi)(preprint with correction in axis labels in Fig 2(i))
  • J. Sreevalsan-Nair, R. R. Vangimalla, and P. R. Ghogale, “Influence of COVID-19 Transmission Stages and Demographics on Length of In-Hospital Stay in Singapore for the First 1000 Patients,” accepted as poster at the COVID-19 track at the 28 th Conference on Intelligent Systems for Molecular Biology (ISMB 2020), July 2020. (doi)
  • R. R. Vangimalla, and J. Sreevalsan-Nair, “Construction and Visualization of Diseasome of Lung Diseases Associated with COVID-19 from Co-association Networks of Multi-omics Data,” accepted as poster at the NetBio COSI track at the 28 th Conference on Intelligent Systems for Molecular Biology (ISMB 2020), July 2020. (doi)
  • R. R. Vangimalla, and J. Sreevalsan-Nair, “Consensus Methods for Network Analysis of Biomedical Data: Case Studies on Brain Functional Connectivity Network and Gene-Gene Association Networks,” presented at the doctoral colloquium at the 4th International Conference on Computational Intelligence and Networks (CINE 2020), February 2020. (pdf)
  • A. C. Victor, and J. Sreevalsan-Nair, “Scene Editing Using Synthesis of Three-Dimensional Virtual Worlds From Monocular Images of Urban Road Traffic Scenes,” accepted for spotlight session and as poster at the ACM SIGGRAPH European Conference on Visual Media Production (CVMP), December 2019. (pdf)(conference-proceedings)
  • R. R. Vangimalla, and J. Sreevalsan-Nair, “RadTrix: A Composite Hybrid Visualization for Unbalanced Bipartite Graphs in Biological Datasets,” accepted as poster in the 9th Eurographics Workshop on Visual Computing for Biology and Medicine, September 2019. (pdf)(conference-proceedings)

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J. Sreevalsan-Nair, K. Dadhich, and S. C. Daggubati, "Tensor Fields for Data Extraction from Chart Images: Bar Charts and Scatter Plots," in Topological Methods in Data Analysis and Visualization VI, Ingrid Hotz, Talha Bin Masood, Filip Sadlo, and Julien Tierny (Eds.). Springer, Cham, 2021, pp 219-241. (doi). Preprint at arXiv (2020), October 2020, https://arxiv.org/abs/2010.02319