Year-wise Grouping of
GVCL Publications
Consolidated
List
[Back
to the publications page]
2024:
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
(accepted),
2024.
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
(GeoSearch
2024)
(accepted),
2024, pp. 1–8.
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
IEEE
International
Conference on
Vehicular
Technology and
Transportation
System
(ICVTTS) 2024
(to appear in
IEEExplore),
IEEE, 2024,
Best Paper
Award.
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, to be
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)
J.
Sreevalsan-Nair and A. Mundayatt,
“Evolution of Data-driven Single-
and Multi-Hazard Susceptibility
Mapping and Emergence of Deep
Learning Methods,” IOP Conference
Series: Earth and Environmental
Science (accepted), April 2024.
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.
[Back
to Consolidated List]
2023:
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)
[Back to
Consolidated List]
2022:
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,
“Interpolation,”
in
Encyclopedia
of
Mathematical
Geosciences,
Encyclopedia
of Earth
Sciences
Series, B. S.
Daya Sagar, Q.
Cheng, J.
McKinley, and
F. Agterberg,
Eds., Cham:
Springer
International
Publishing,
2022. (doi)
J.
Sreevalsan-Nair,
“Eigenvalues
and
Eigenvectors,”
in
Encyclopedia
of
Mathematical
Geosciences,
Encyclopedia
of Earth
Sciences
Series, B. S.
Daya Sagar, Q.
Cheng, J.
McKinley, and
F. Agterberg,
Eds., Cham:
Springer
International
Publishing,
2022. (doi)
J.
Sreevalsan-Nair,
“Independent
Component
Analysis,” in
Encyclopedia
of
Mathematical
Geosciences,
Encyclopedia
of Earth
Sciences
Series, B. S.
Daya Sagar, Q.
Cheng, J.
McKinley, and
F. Agterberg,
Eds., Cham:
Springer
International
Publishing,
2022. (doi)
J.
Sreevalsan-Nair, “Laplace
Transform," in
Encyclopedia of
Mathematical
Geosciences,
Encyclopedia of Earth
Sciences Series, B. S.
Daya Sagar, Q. Cheng,
J. McKinley, and F.
Agterberg, Eds., Cham:
Springer International
Publishing, 2022. (doi)
J.
Sreevalsan-Nair,
“Expectation-Maximization
Algorithm,” in
Encyclopedia
of
Mathematical
Geosciences,
Encyclopedia
of Earth
Sciences
Series, B. S.
Daya Sagar, Q.
Cheng, J.
McKinley, and
F. Agterberg,
Eds., Cham:
Springer
International
Publishing,
2022. (doi)
J.
Sreevalsan-Nair, “Simulated
Annealing,” in
Encyclopedia of
Mathematical
Geosciences,
Encyclopedia of Earth
Sciences Series, B. S.
Daya Sagar, Q. Cheng,
J. McKinley, and F.
Agterberg, Eds., Cham:
Springer International
Publishing, 2022. (doi)
J.
Sreevalsan-Nair,
“K-Medoids,”
in
Encyclopedia
of
Mathematical
Geosciences,
Encyclopedia
of Earth
Sciences
Series, B. S.
Daya Sagar, Q.
Cheng, J.
McKinley, and
F. Agterberg,
Eds., Cham:
Springer
International
Publishing,
2022. (doi)
J.
Sreevalsan-Nair, “Fuzzy
C-Means Clustering,"
in Encyclopedia of
Mathematical
Geosciences,
Encyclopedia of Earth
Sciences Series, B. S.
Daya Sagar, Q. Cheng,
J. McKinley, and F.
Agterberg, Eds., Cham:
Springer International
Publishing, 2022. (doi)
J.
Sreevalsan-Nair, “Proximity
Regression,” in
Encyclopedia of
Mathematical
Geosciences,
Encyclopedia of Earth
Sciences Series, B. S.
Daya Sagar, Q. Cheng,
J. McKinley, and F.
Agterberg, Eds., Cham:
Springer International
Publishing, 2022. (doi)
J.
Sreevalsan-Nair,
“Normal
Distribution,” in
Encyclopedia of
Mathematical
Geosciences,
Encyclopedia of Earth
Sciences Series, B. S.
Daya Sagar, Q. Cheng, J.
McKinley, and F.
Agterberg, Eds., Cham:
Springer International
Publishing, 2022. (doi)
J.
Sreevalsan-Nair,
“Virtual
Globe,” in Encyclopedia
of Mathematical
Geosciences,
Encyclopedia of Earth
Sciences Series, B. S.
Daya Sagar, Q. Cheng, J.
McKinley, and F.
Agterberg, Eds., Cham:
Springer International
Publishing, 2022. (doi)
J.
Sreevalsan-Nair,
“K-Means
Clustering,” in
Encyclopedia of
Mathematical
Geosciences,
Encyclopedia of Earth
Sciences Series, B. S.
Daya Sagar, Q. Cheng, J.
McKinley, and F.
Agterberg, Eds., Cham:
Springer International
Publishing, 2022. (doi)
J. Sreevalsan-Nair, “K-Nearest Neighbors,” in
Encyclopedia of Mathematical Geosciences,
Encyclopedia of Earth Sciences Series, B. S.
Daya Sagar, Q. Cheng, J. McKinley, and F.
Agterberg, Eds., Cham: Springer International
Publishing, 2022. (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,
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, July 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).
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, pp 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 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,
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)
[Back to
Consolidated List]
2021:
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, 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, pp 1-14, 2021. (doi)(Easychair
preprint)
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. (doi)
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. (doi)(preprint)
J. Sreevalsan-Nair, “Maximum Likelihood,” in
Encyclopedia of Mathematical Geosciences, Encyclopedia of
Earth Sciences Series, B. S. Daya Sagar, Q. Cheng, J.
McKinley, and F. Agterberg, Eds., Cham: 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)
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, 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, SCITEPRESS. (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)
[Back to
Consolidated List]
2020:
A. Jakher, and J. Sreevalsan-Nair,
“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 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)
S. Singh, and J. Sreevalsan-Nair, "A
Distributed System for Multiscale Feature Extraction and Semantic
Classification of Airborne LiDAR Point Clouds," accepted at the
IEEE International India Geoscience and Remote Sensing Symposium
(InGARSS) 2020, pp 74-77, December 2020. (doi)(pdf)
(Best Paper Award)
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 in
NetBio COSI at
the 28th
Conference on
Intelligent
Systems for
Molecular
Biology
(ISMB), July
2020. (abstract)(doi)
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 in
COVID-19 COSI
at the 28th
Conference on
Intelligent
Systems for
Molecular
Biology
(ISMB), July
2020. (abstract)(doi)
J.
Sreevalsan-Nair, and P. Mohapatra, “Augmented Semantic
Signatures of Airborne LiDAR Point Clouds for Comparison,”
in arXiv (2020), May 2020, https://arxiv.org/abs/2005.02152
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)
J. Sreevalsan-Nair and P. Mohapatra,
“Influence of Aleatoric Uncertainty on Semantic Classification
of Air-borne LiDAR Point Clouds: A Case Study with Random Forest
Classifier Using Multiscale Features”, accepted in the
Proceedings of the 2020 IEEE International Geoscience and Remote
Sensing Symposium (IGARSS 2020), pp 1066-1070, September 2020. (doi)(pdf)
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)
[Back to
Consolidated List]
2019:
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 poster
at the ACM SIGGRAPH European Conference on Visual Media
Production (CVMP) on 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. (conference-proceedings)(pdf)(poster-pdf)
2018:
J. Sreevalsan-Nair, "Visual Analytics of 3D
Airborne LiDAR Point Clouds in Urban Regions," in Sarda, N.,
Acharya, P., Sen, S. (eds) Geospatial Infrastructure,
Applications and Technologies: India Case Studies, pp 313-325,
Springer Singapore, November 2018. (doi)(pdf)
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. (doi)(pdf)
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. (doi)(pdf)
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. (pdf)
J. Sreevalsan-Nair, and A. Jindal, ``Using Gradients and Tensor
Voting in 3D Local Geometric Descriptors for Feature Detection in
Airborne LiDAR Point Clouds in Urban Regions,'' in the Proceedings
of the 2017 IEEE International Geoscience and Remote Sensing
Symposium (IGARSS 2017), July 2017. (doi)(pdf)
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) (doi)(pdf)
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)(pdf)
(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)(pdf)
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. (pdf)
2015:
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. (doi)(pdf)
2014:
B. Kumari, A.Ashe, and J. Sreevalsan-Nair, ``Remote Interactive
Visualization of Parallel Implementation of Structural Feature
Extraction of Three-dimensional Lidar Point Cloud,'' in the
Proceedings of the Third International Conference on Big Data
Analytics, Lecture Notes in Computer Science (LNCS) Series, Vol.
8883, 2014, pp 129-132, Springer. (doi)(pdf)
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)(pdf)
2012:
A. Narayan, J. Sreevalsan-Nair, K.
Gaither, and B. Hamann,``Isosurface Extraction from Hybrid
Unstructured Grids Containing Pentahedral Elements,'' Kraus, M.,
Laramee, R.S., Battiato, S., de Campos, T., Jurie, F., Kato, Z.
and Raducanu, B., eds., Proceedings of International Conference on
Information Visualization Theory and Applications 2012
(GRAPP/IVAPP 2012), 660-669. (doi)(pdf)
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