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Associate Professor


Education : Ph.D. (University of California Davis)

Professor Nair obtained her Ph.D. in Computer Science from the University of California, Davis; after a B.Tech in Aerospace Engineering from IIT-Madras and an M.S. in Computational Engineering from Mississippi State University. Prior to joining IIITB, she worked as a scientific programmer at Enthought Inc. Austin and as a research associate at Texas Advanced Computing Center, the University of Texas at Austin. Her areas of interest are spatial data analysis, visualization, computer vision, scientific computing, computer graphics, computational topology, high performance computing.

She leads the  Graphics-Visualization-Computing Lab at IIITB. She is also the core team member of the E-Health Research Center at IIITB. 

[Curriculum Vitae][Graphics-Visualization-Computing Lab][E-Health Research Center]

Spatial big data analytics (multivariate/tensor/network data modeling and visual analytics) with a focus on applications in earth observations (LiDAR point clouds, ocean data, flood susceptibility maps), biological networks (genomic, brain), chart image processing (bar, line, scatterplot, sunburst, etc.) and survey data pertaining to population health and public health.

  • Best Paper Award Nomination, 14th International Conference on Knowledge Discovery and Information Retrieval (KDIR), INSTICC, 2022
  • Membership Grade Elevation to ACM Senior Member, 2022
  • Best Paper Award Nomination, 3rd International Conference on Deep Learning Theory and Applications (DeLTA), INSTICC, 2022
  • Best Associate Editor, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE, 2021
  • Best Paper Award Nomination, 1st International Conference on Image Processing and Vision Engineering (IMPROVE), INSTICC, 2021
  • Best Paper Award, 2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS), IEEE, 2020
  • Intel India Research Fellowship (for MS student, with a travel grant for faculty), Intel India, 2019-20
  • Best Paper Award Nomination, 12th International Joint Conference on Computer Vision, Imaging, and Computer Graphics Theory and Applications (VISIGRAPP (3: IVAPP)), INSTICC, 2017
  • Early Career Research Award, Science and Engineering Board, Govt. of India, 2017-20
  • Membership Grade Elevation to IEEE Senior Member, 2016
  • International Travel Grant for Young Scientists, Department of Science and Technology, Govt. of India, 2012


Selected publications: [complete list of publications - HTML, pdf][Topic-wise list][Supervised Masters/PhD Theses]

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.

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. 

J. Sreevalsan-Nair, Co-Association Matrices in Ensemble Clustering: Diverse Applications and Extensions, Preprint available at SSRN, May 2023. 

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. 

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. 

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. 

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. 

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.

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.

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.

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.

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, pp 1-14, 2021. 

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,” in Proceedings of the 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, 2021, pp. 1880–1886. 

S. Singh, and J. Sreevalsan-Nair,  “Adaptive Multiscale Feature Extraction in a Distributed System for Semantic Classification of Airborne LiDAR Point Clouds,” IEEE Geoscience and Remote Sensing Letters, July 2021. 

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

J. Sreevalsan-Nair, A. Jindal, and B. Kumari, ``Contour Extraction in Buildings in Airborne LiDAR Point Clouds Using Multi-scale Local Geometric Descriptors and Visual Analytics,'' in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 11(7), pp 2320-2335, June 2018. 

K. Lukose, S. Agarwal, V. N. Rao, and J. Sreevalsan-Nair, ``Design Study for Creating Pathfinder: A Visualization Tool for Generating Software Test Plans Using Model Based Testing,'' in the Proceedings of the 13th International Joint Conference on Computer Vision, Imaging, and Computer Graphics Theory and Applications (VISIGRAPP 2018), vol 3: IVAPP, SCITEPRESS, pp. 289-300, 2018. 

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 B. Kumari, ``Local Geometric Descriptors for Multi-Scale Probabilistic Point Classification of Airborne LiDAR Point Clouds,'' in ``Modeling, Analysis and Visualization of Anisotropy,'' Mathematics and Visualization Series, Springer, Cham, pp 175-200, October 2017. (from Proceedings of Dagstuhl Seminar 16142) 

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.

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. 

B. Kumari, and J. Sreevalsan-Nair, ``An interactive visual analytic tool for semantic classification of 3D urban LiDAR point cloud,'' In Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems 2015 (p. 73:1--73:4), ACM. 



[Odd Semester (Aug-Dec)]

  • CS732: Data Visualization
  • CS714: Advanced Computer Graphics (co-instructed with Prof. T. K. Srikanth)
  • DT107: Application Development for a Connected Society

[Even Semester (Jan-May)]

  • CS606: Computer Graphics (co-instructed with Prof. T. K. Srikanth)
  • CS762: Advanced Data Visualization
  • AI724: Spatio-temporal Statistical Techniques for Data Analysis (co-instructed with Dr. Ramesh Kestur)

[Past Courses]

  • Programming II (co-instructed with Prof. T. K. Srikanth, I taught the C++ module)
  • Operating systems (co-instructed with Prof. Shrisha Rao)
  • GEN601: Scientific Computing


  • (07/2021 – 05/2022), (Completed), “Vehicle LiDAR Point Cloud Processing and Analysis,” Ignitarium Technology Solutions Pvt. Ltd., (INR 3,50,000).
  • (02/2020 – 02/2023), (Completed), “Data Analysis of Split Questionnaire for Conducting Surveys for Population Studies Using Novel Statistical Measures and Visualizations,” Mathematical Research Impact Centric Support (MATRICS) fixed grant scheme, Science and Engineering Research Board (SERB), Government of India, (INR 6,60,000).
  • (08/2019 – 07/2020), (Completed), “Uncertainty Analysis of LiDAR Point Clouds in Autonomous Driving”, Intel India Research Fellowship, Intel India, (INR 8,00,000).
  • (06/2018-06/2020, and 6-month extension), (Completed), “Visual Analytics of Population Health Surveys,” IBM Shared University Grant, (INR 19,55,000).
  • (07/2017 – 06/2019), (Completed), “Visual Analytics of Public Health Data,” Foundations of Research in Health Systems (FRHS), India, (INR 10,00,000).
  • (05/2017 – 05/2020, and 4-month extension), (Completed), “Tensor Modeling and Visualization of Three-dimensional Geospatial Datasets,” Early Career Research Award (ECRA), Science and Engineering Research Board (SERB), Government of India, (INR 14,83,900).
  • (01/2016 – 06/2017), (Completed), “Visual Analytics for Early Detection of Child Malnutrition,” Foundations of Research in Health Systems (FRHS), India, (INR 10,00,000).
  • (08/2014 – 07/2017), (Completed), “Interactive Three-dimensional Visualization of Large-scale ARGO Data,” Indian National Center for Ocean Information Services (INCOIS), Ministry of Earth Sciences, Government of India, (INR 40,30,000).
  • (01/2014 – 12/2014), (Completed), “Visualization of Security Analytics,” EMC2 -RSA Center of Excellence, (INR 10,00,000).
  • (08/2012-08/2014, and 6-month extension), (Completed), “LAN-based Interactive Three-dimensional Visualization of LiDAR Point Cloud Data,” Natural Resources Data Management System (NRDMS) program (currently, National Geospatial Programme (NGP)), Department of Science and Technology (DST), Government of India, (INR 32,25,000).
  • 2023 IEEE India Geoscience and Remote Sensing Symposium (InGARSS 2023) General Chair URL
  • IEEE TCSVT Associate Editor (2021-) URL
  • IEEE GRSS Bangalore Section Chair (2021-) URL