Publications

Publications

Please visit Google Scholar DBLP, ResearchGate, or Dr Kumar's full vita  for more complete information.

(links to articles are currently being updated; thank you for your patience.) 

2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 earlier 

 

 

2019

 

2018

Classifying Multivariate Time Series by Learning Sequence-level Discriminative Patterns 
G. Nayak , V. Mithal , X. Jia , and V. Kumar 
Proceedings of the 2018 SIAM International Conference on Data Mining, May 2018, doi:10.1137/1.9781611975321.29 (link)

Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework 
V. Mithal , G. Nayak , A. Khandelwal , V. Kumar , R. Nemani , and N. Oza 
Remote Sensing 2018, 10(1), 69; doi:10.3390/rs10010069 (link)

A cautionary note on decadal sea level pressure predictions from GCMs 
S. Liess , P. Snyder , A. Kumar , and V. Kumar 
Advances in Climate Change Research Volume 9, Issue 1, March 2018, Pages 43-56, doi:10.1016/j.accre.2018.02.002 (link)

 

2017

Predict land covers with transition modeling and incremental learning 
X. Jia , A. Khandelwal , G. Nayak , J. Gerber , K. Carlson , P. West , and V. Kumar 
Proceedings of the 2017 SIAM International Conference on Data Mining, pp. 171-179. Society for Industrial and Applied Mathematics, 2017. DOI:10.1137/1.9781611974973.20. (link)

Incremental Dual-memory LSTM in Land Cover Prediction 
X. Jia , A. Khandelwal , G. Nayak , J. Gerber , K. Carlson , P. West , and V. Kumar 
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 867-876. ACM, 2017 (link)

Joint Sparse Auto-encoder: A Semi-supervised Spatio-temporal Approach in Mapping Large-scale Croplands 
X. Jia , A. Khandelwal , A. Karpatne , and V. Kumar 
Big Data (Big Data), 2017 IEEE International Conference on. IEEE, 2017 (link)

An approach for global monitoring of surface water extent variations in reservoirs using MODIS data 
A. Khandelwal , A. Karpatne , M.E. Marlier , J. Kim , D.P. Lettenmaier , and V. Kumar 
Remote Sensing of Environment (2017) doi: 10.1016/j.rse.2017.05.039(link)

RAPT: Rare Class Prediction in Absence of True Labels 
V. Mithal , G. Nayak , A. Khandelwal , V. Kumar , N. Oza , and R. Nemani 
IEEE Transactions on Knowledge and Data Engineering 29, no. 11 (2017): 2484-2497 (link)

Monitoring Dynamics of Water Bodies at Global Scale using Remote Sensing Data: Opportunities, Challenges and New Research Directions
A. Khandelwal, A. Karpatne, and V. Kumar
Workshop on Mining Big Data in Climate and Environment (MBDCE 2017), 17th SIAM International Conference on Data Mining (SDM 2017) (link)

Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data 
A. Karpatne , G. Atluri , J. Faghmous , M. Steinbach , A. Banerjee , A. Ganguly , S. Shekhar , N. Samatova , and V. Kumar 
IEEE Transactions on Knowledge and Data Engineering. PP (99) DOI: 10.1109/TKDE.2017.2720168 (link)

A Teleconnection between the West Siberian Plain and the ENSO Region
S. Liess, S. Agrawal, S. Chatterjee, and V. Kumar
Journal of Climate, Volume 30, Issue 1, pp. 301-315. 2017 DOI:10.1175/JCLI-D-15-0884.1 (link)

 

2016

Learning large-scale plantation mapping from imperfect annotators 
X. Jia, A. Khandelwal, J. Gerber, K. Carlson, P. West, and V. Kumar
2016 IEEE International Conference on Big Data (Big Data)  DOI: 10.1109/BigData.2016.7840723 (link)

Identifying dynamic changes with noisy labels in spatial-temporal data: A study on large-scale water monitoring application
X. Jia, X. Chen, A. Karpatne, and V. Kumar
2016 IEEE International Conference on Big Data (Big Data) DOI: 10.1109/BigData.2016.7840738(link)

Mapping Burned Areas in Tropical forests using MODIS data
V. Mithal, G. Nayak, A. Khandelwal, R. Nemani, V. Kumar, and N. Oza
September 2016. (link)

A General Framework to Increase the Robustness of Model-based Change Point Detection Algorithms to Outliers and Noise
X. Chen, Y. Yao, S. Shi, V. Kumar, S. Chatterjee, and J. Faghmous
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016. DOI: 10.1137/1.9781611974348.19 (link)

Causality-Guided Feature Selection
M. Chaudhary, D. Gonzalez II, G. Bello, M. Angus, D. Desai, S. Harenberg, P. Doraiswamy, F. Semazzi, V. Kumar, and N. Samatova
International Conference on Advanced Data Mining and Applications (ADMA) 2016. DOI: 10.1007/978-3-319-49586-6_26 (link)

Monitoring Land-Cover Changes: A Machine-Learning Perspective
A. Karpatne, Z. Jiang, R. Vatsavai, S. Shekhar, and V. Kumar
IEEE Geoscience and Remote Sensing Magazine 4(2): 8-21. 2016. DOI: 10.1109/MGRS.2016.2528038 (link)

Global monitoring of inland water dynamics: State-of-the-art, challenges, and opportunities
A. Karpatne, A. Khandelwal, X. Chen, V. Mithal, J.H. Faghmous, and V. Kumar
K. Morik, J. Lässig, and K. Kersting, Eds. Computational Sustainability, Springer. 2016. DOI: 10.1007/978-3-319-31858-5_7 (link)

Exploring the Predictability of 30-Day Extreme Precipitation Occurence using a Global SST-SLP Correlation Network
M. Lu, U. Lall, J. Kawale, S. Liess, and V. Kumar
February 2016. DOI: 10.1175/JCLI-D-14-00452.1(link)

 

2015

Evaluation of Global Climate Models Based on Global Impacts of ENSO
S. Agrawal, T. Rehberger, S. Liess, G. Atluri, and V. Kumar
Machine Learning and Data Mining Approaches to Climate Science, Springer pp 101-109. 2015. DOI: 10.1007/978-3-319-17220-0_10 (link)

Computing and Climate 
J. Faghmous, V. Kumar, and S. Shekhar
Computing in Science and Engineering 17(6): 6-8, 2015. DOI: 10.1109/MCSE.2015.114 (link)

Patent: Automated mapping of land cover using sequences of aerial imagery 
S. Boriah, A. Khandelwal, V. Mithal, V. Kumar, and K. Steinhaeuser
February 2015 (link)

Tripoles: A New Class of Climate Teleconnections 
G. Atluri, S. Agrawal, S. Liess, V. Kumar, and S. Chatterjee
November 2015 (link)

Unsupervised Method for Water Surface Extent Monitoring Using Remote Sensing Data 
X. Chen, A. Khandelwal, S. Shi, J. Faghmous, S. Boriah, and V. Kumar
Machine Learning and Data Mining Approaches to Climate Science, Springer pp 51-58. 2015. DOI: 10.1007/978-3-319-17220-0_5 (link)

Evaluation of Global Climate Models Based on Global Impacts of ENSO 
S. Agrawal, T. Rehberger, S. Liess, G. Atluri, and V. Kumar
Machine Learning and Data Mining Approaches to Climate Science, Springer pp 101-109. 2015. (link)

A Daily Global Mesoscale Ocean Eddy Dataset from Satellite Altimetry
J. H. Faghmous, I. Frenger, Y. Yao, R. Warmka, A. Lindell, and V. Kumar
Scientific Data, Nature Publishing Group, 2. 2015. (link)

Post Classification Label Refinement Using Implicit Ordering Constraint Among Data Instances
A. Khandelwal, V. Mithal, and V. Kumar
International Conference on Data Mining (ICDM 2015), Atlantic City, NJ. November 14-17, 2015. (pdf)

Adaptive Heterogeneous Ensemble Learning Using the Context of Test Instances.
A. Karpatne and V. Kumar
International Conference on Data Mining (ICDM 2015), Atlantic City, NJ. November 14-17, 2015. (pdf)

Online change point detection for remote sensing time series
X. Chen, Y. Yao, S. Shi, V. Kumar, and J. Faghmous
Fifth International Workshop on Climate Informatics, Boulder, CO. September 24- 25, 2015. (pdf)

Understanding Dominant Factors for Precipitation over the Great Lakes Region
S. Chatterjee, V. Kumar, A. Banerjee, and S. Liess
5th International Workshop on Climate Informatics, September 24-25 2015. (pdf)

Clustering Dynamic Spatio-Temporal Patterns in the Presence of Noise and Missing Data
X. Chen, J. H. Faghmous, A. Khandelwal, and V. Kumar
24th International Joint Conference on Artificial Intelligence (IJCAI-15). Buenos Aires, Argentina. July 25-31, 2015. (pdf)

Ensemble learning methods for binary classification with multi-modality within the classes.
A. Karpatne, A. Khandelwal, and V. Kumar
Proceedings of the SIAM International Conference on Data Mining (SDM 2015). pp. 730-738. Vancouver, Canada. April 30-May 2, 2015. (pdf)

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall 
D. L. González, M. Angus, I. K. Tetteh, G. A. Bello, K. Padmanabhan, S. V. Pendse, S. Srinivas, J. Yu, F. Semazzi, V. Kumar, and N. F. Samatova
Nonlinear Processes in Geophysics Discussions 1: pp. 479-517. January 13, 2015. (link)

 

2014

Different Modes of Variability over the Tasman Sea: Implications for Regional Climate
S. Liess, A. Kumar, P. Snyder, J. Kawale, K. Steinhaeuser, F. Semazzi, A. Ganguly, N. Samatova, and V. Kumar
Journal of Climate, 27(22): pp. 8466-8486. 2014. (link)

On the Data-driven Inference of Causal Networks: Examining the relationship between global Sea Surface Temperatures and Sahel Rainfall
D. Gonzalez , I. Tetteh , M. Angus, S. Pendse , S. Srinivas , P. Kanchana, F. Semnazzi , V. Kumar , and N. Samatova
The Third International Workshop on Climate Informatics- NCAR (pdf)

Online Discovery of Group Level Events in Time Series
X. C. Chen , A. Mueen , V. K. Narayanan, N. Karampatziakis , G. Bansal , and V. Kumar
Proceedings of the 2014 SIAM International Conference on Data Mining (pdf)

Predictive Learning in the Presence of Heterogeneity and Limited Training Data 
A. Karpatne , A. Khandelwal , Shyam Boriah, and V. Kumar
Proceedings of the 2014 SIAM International Conference on Data Mining (link)

Spatio-temporal Consistency for Autonomous Dynamic Object Identification in Continuous Spatio-Temporal Fields 
J. H. Faghmous , H. Nguyen , M. Le, and V. Kumar
Twenty-Eighth Conference on Artificial Intelligence (AAAI). Quebec, Canada (link)

Toward enhanced understanding and projections of climate extremes using physics-guided data mining techniques. 
A. Ganguly, E. Kodra, A. Banerjee , S. Boriah , S. Chatterjee, A. Choudhary, D. Das, J. Faghmous, P. Ganguli, S. Ghosh, K. Hayhoe, C., Hays, W. Hendrix, Q. Fu, D. Kumar, V. Kumar, S. Liess, R. Mawalagedara, V. Mithal, R. Oglesby, K. Salvi, P. Snyder, K. Steinhaeuser, D. Wang, and D. Wuebbles
Nonlinear Processes in Geophysics (pdf)

State-of-the-art, challenges, and opportunities for data-driven research. 
J. H. Faghmous and V. Kumar
J. Lässig, K. Kersting, and K. Morik, Eds. Computational Sustainability Springer

 

2013

Multiple Hypothesis Object Tracking For Unsupervised Self-Learning: An Ocean Eddy Tracking Application
J. Faghmous , M. Uluyol , L. Styles , M. Le , V. Mithal, , S. Boriah , and V. Kumar 
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (pdf)

A Parameter-Free Spatio-Temporal Pattern Mining Model to Catalog Global Ocean Dynamics 
J. Faghmous, M. Le, M. Uluyol, V. Kumar, and S. Chatterjee
2013 IEEE 13th International Conference on Data Mining (link)

Spatio-Temporal Data Mining for Climate Data: Advances, Challenges, and Opportunities
J. Faghmous and V. Kumar
Advances in Data Mining, W. Chu, Editor, 2013 (pdf)

Contextual Time Series Change Detection
X. C. Chen, , K. Steinhaeuser, S. Boriah, S. Chatterjee, and V. Kumar
13th SIAM International Conference on Data Mining (SDM 2013), Austin, Texas, USA, May 2-4, 2013 (pdf)

Change Detection from Temporal Sequences of Class Labels: Application to Land Cover Change Mapping
V. Mithal, Khandelwal, S. Boriah, K. Steinhaeuser, and V. Kumar
13th SIAM International Conference on Data Mining (SDM 2013), Austin, Texas, USA, May 2-4, 2013 (pdf)

Automatic Detection and Correction of Multi-class Classification Errors Using System Whole-part Relationships
Z. Chen, J. Jenkins, J. Rao, A. Choudhary, F. Semazzi, A. V. Melechko, V. Kumar, and N. F. Samatova
13th SIAM International Conference on Data Mining (SDM 2013), Austin, Texas, USA, May 2-4, 2013 (pdf)

A graph-based approach to find teleconnections in climate data 
J. Kawale, S. Liess, A. Kumar, M. Steinbach, P. Snyder, V. Kumar, A.R. Ganguly, N.F. Samatova, and F. Semazzi
Statistical Analysis and Data Mining, online publication April 2013, doi: 10.1002/sam.11181 (link)

Earth Science Applications of Sensor Data
A. Karpatne, J. Faghmous, J. Kawale, L. Styles, M. Blank, V. Mithal, X. Chen, A. Khandelwal, S. Boriah, K. Steinhaeuser, M. Steinbach, V. Kumar, and S. Liess
Managing and Mining Sensor Data, C. C. Aggarwal (Ed.), Springer, 505-530, January 15, 2013, ISBN:9781461463085 (link)

 

2012

Hierarchical Classifier-Regression Ensemble for Multi-Phase Non-Linear Dynamic System Response Prediction: Application to Climate Analysis
D. L. Gonzalez, Z. Chen, I. K. Tetteh, T. Pansombut, F. Semazzi, V. Kumar, A.V. Melechko, and N. F. Samatova
2012 IEEE 12th International Conference on Data Mining (ICDM), pp. 781-788, December 10, 2012. Brussels, Belgium (link)

A New Data Mining Framework for Forest Fire Mapping
X.C. Chen, A. Karpatne, Y. Chamber, V. Mithal, M. Lau, K. Steinhaeuser, S. Boriah, M. Steinbach, V. Kumar, C. S. Potter, S. A. Klooster, T. Abraham, J.D. Stanley, and J. C. Castilla-Rubio
CIDU 2012: Proceedings of the IEEE Conference on Intelligent Data Understanding, pages 104-111, October,2012 (link)

A Novel and Scalable Spatio-Temporal Technique for Ocean Eddy Monitoring
J. H. Faghmous, Y. Chamber, S. Boriah, S. Liess, F. Vikebo, M. dos Santos Mesquita, and V. Kumar
AAAI 2012: AAAI Conference on Artificial Intelligence, July 2012 (link)

On the path to sustainable, scalable, energy-efficient data analytics: Challenges, future directions
S. Lakshminarasimhan, P. Kumar, W.-K. Liao, A. N. Choudhary, V. Kumar, and N. F. Samatova
2012 International Green Computing Conference (IGCC), pages 1 - 6, 4-8 June 2012 (link)

Toward Data-driven,Semi-automatic Inference of Phenomenological Physical Models: Application to Eastern Sahel Rainfall
S.V. Pendse, I.K. Tetteh, F. Semazzi, V. Kumar, and N.F. Samatova
SIAM International Conference on Data Mining (SDM), April 26-28, 2012 (link)

 

2011

Data Guided Discovery of Dynamic Climate Dipoles
J. Kawale, S. Liess, A. Kumar, A. Ganguly, M. Steinbach, N. Samatova, F. Semazzi, P. Snyder, and and V. Kumar
NASA Conference on Intelligent Data Understanding, October 19-21, 2011 (pdf)

Anomaly construction in Climate data: Issues and Challenges
J. Kawale, S. Chatterjee, A. Kumar, S. Liess, M. Steinbach, and and V. Kumar
NASA Conference on Intelligent Data Understanding, October 19-21, 2011 (pdf)

Monitoring Global Forest Cover Using Data Mining
V. Mithal, A. Garg, S. Boriah, M. Steinbach, V. Kumar, C. Potter, S. Klooster, and J.-C. Castilla-Rubio
ACM Transactions on Intelligent Systems and Technology, Volume 2, Number 4, 2011 (pdf | link)

Classification of Emerging Extreme Event Tracks in Multi-Variate Spatio-Temporal Physical Systems Using Dynamic Network Structures: Application to Hurricane Track Prediction
H. Sencan, Z. Chen, W. Hendrix, T. Pansombut, F. Semazzi, A. Choudhary, V. Kumar, N.F. Samatova, and A. Melechko
Proceedings of the 22nd International Joint Conference on Artificial Intelligence, July 16-22, 2011 (link)

Discovering Dynamic Dipoles in Climate Data
J. Kawale, M. Steinbach, and V. Kumar
SIAM International Conference on Data Mining (SDM), April 28-30, 2011 (pdf)

 

2010

A Knowledge Discovery Strategy for Relating Sea Surface Temperatures to Frequencies of Tropical Storms and Generating Predictions of Hurricanes Under 21st-Century Global Warming Scenarios
C. Race, M. Steinbach, A. Ganguly, F. Semazzi, and V. Kumar
Proceedings of Annual Conference on Intelligent Data Understanding (CIDU), October, 2010 (pdf)

A Comparative Study of Algorithms for Land Cover Change
S. Boriah, V. Mithal, A. Garg, V. Kumar, M. Steinbach, C. Potter, and S. Klooster
Proceedings of Annual Conference on Intelligent Data Understanding (CIDU), October, 2010, 175-188 (pdf)

2009 and earlier

 

 

Addtional links, outdated, but publications by topic: 

 

Software Packages

METIS/ParMETIS/hMETIS - Serial and Parallel Graph Partitioning Libraries 
 

PSPASES - A Scalable Parallel Direct Solver Library for Sparse SPD Systems