Theme: Population Studies/Healthcare

The preprints of these papers are available at ResearchGate.

2025:

B. Gnanaraj, and J. Sreevalsan-Nair, Cognitive Load Estimation and Analysis Using Eye Tracking in Mental Health Care Application, presented at the Doctoral Colloquium, Pattern Recognition and Machine Intelligence (PReMI’25) Conference, 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, vol. 22, no. 6, pp 3550-3556, 2025. https://doi.org/10.1109/TCBBIO.2025.3599771 

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 

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), IEEE, 2025. https://doi.org/10.1109/EMBC58623.2025.11251527 

2024:

S. Mathai, P. Krishnan, and J. Sreevalsan Nair, “Understanding Graphical Literacy Using School Students’ Comprehension Strategies,” Contemporary Education Dialogue, pp. 1–35, 2024. (doi)

2023:

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)

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)

2022:

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, INSTICC, SciTePress, 2022, pp 63--74. ISBN : 978-989-758-614-9. (doi). (Best Paper Award Nomination)

H. Ravindra and J. Sreevalsan-Nair, Spatial and Visual Analytics for Grouped Analysis of Population Survey Data, presented at the doctoral research workshop at the 26th International Conference on Information Visualization IV2022, July 2022.

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, IEEE, 2022, pp. 432–441. (doi) 

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).

S. Agarwal, F. Beck, U. Ghosh, and J. Sreevalsan-Nair, CiteVis: Visual Analysis of Overlapping Citation Intents as Dynamic Sets, accepted for poster presentation at the 15th IEEE Pacific Visualization Symposium (PacificVis) 2022, April 2022.

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, V. Sridhar, Ed., 1st ed., Routledge India, 2022, ch. 8, ISBN: 9780367536534. (doi)

2021:

R. R. Vangimalla and J. Sreevalsan-Nair, “HCNM: Heterogeneous Correlation Network Model for Multi-level Integrative Study of Multi-omics Data for Cancer Subtype Prediction,” in Proceedings of the 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, 2021, pp. 1880–1886. (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, ISBN: 9780367536534. (doi)

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)

2020:

A. Jakher, and J. Sreevalsan-Nair, “Community Detection in Migration Flow Networks,” accepted for oral presentation at the Urban Complex Systems 2020, a satellite event at the annual Conference on Complex Systems 2020 (CCS 2020), December 9-10, 2020.

R. R. Vangimalla and J. Sreevalsan-Nair, “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, October 2020. (doi); preprint at bioRxiv (2020), February 2020.(doi)

U. M. Mehta, D. Shadakshari, P. Vani, S. S. Naik, Kiran Raj V., R. R. Vangimalla, Y. C. J. Reddy, J. Sreevalsan-Nair, and R. D. Bharath, "Case Report: Obsessive compulsive disorder in posterior cerebellar infarction - illustrating clinical and functional connectivity modulation using MRI-informed transcranial magnetic stimulation,"  Wellcome Open Research 2020, 5:189. (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 a poster in NetBio COSI at the 28th Conference on Intelligent Systems for Molecular Biology (ISMB), July 2020. (abstract)(doi)(doi for additional oral presentation)

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 a poster in COVID-19 COSI at the 28th Conference on Intelligent Systems for Molecular Biology (ISMB), July 2020. (abstract)(doi)(doi for additional oral presentation)

J. Sreevalsan-Nair, R. R. Vangimalla, and P. R. Ghogale, “Estimation of Length of In-Hospital Stay Using Demographic Data of the First 1000 COVID-19 Patients in Singapore,” medRxiv (2020), April 2020. (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. (pdf with correction in axis labels in Fig. 2(i))(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)(researchgate)

2019:

R. R. Vangimalla, and J. Sreevalsan-Nair, "RadTrix: A Composite Hybrid Visualization for Unbalanced Bipartite Graphs in Biological Datasets," accepted as a poster in the 9th Eurographics Workshop on Visual Computing for Biology and Medicine, September 2019. (conference-proceedings)

2017:

J. Sreevalsan-Nair, N. Murthy, S. Agarwal, R. R. Vangimalla, and S. Ramesh, ``Collaborative Design of Visual Analytics Techniques for Survey Data for Community-based Research in Public Health,'' (accepted as poster) in the 8th Workshop on Visual Analytics in Healthcare, affiliated with IEEE VIS 2017. 

J. Sreevalsan-Nair, and S. Agarwal, ``NodeTrix-CommunityHierarchy: Techniques for Finding Hierarchical Communities for Visual Analytics of Small-world Networks,'' in the Proceedings of 12th International Joint Conference on Computer Vision, Imaging, and Computer Graphics Theory and Applications (VISIGRAPP 2017), vol 3: IVAPP, pp 140-151, SCITEPRESS, 2017. (doi)(Best Paper Award Nomination)

S. Agarwal, A. Tomar, and J. Sreevalsan-Nair, ``NodeTrix-Multiplex: Visual Analytics of Multiplex Small World Networks,'' in Complex Networks & Their Applications V, Studies in Computational Intelligence, vol. 693, pp 579-591, Springer International Publishing, 2017. (doi)

2016:

J. Sreevalsan-Nair, ``A Survey of Requirements of Multivariate Data and its Visualizations for Analysis of Child Malnutrition in India,'' Data Science Communications, vol. 1, IIITB Press, 1--26, October 2016. 

2013:

S. Parveen, and J. Sreevalsan-Nair, ``Visualization of Small World Networks Using Similarity Matrices,'' in the Proceedings of the Second International Conference on Big Data Analytics, Lecture Notes in Computer Science, Volume 8302, 2013, pp 151-170, Springer. (doi)