• Journals
    1. Extracting Deep Phenotypes for Chronic Kidney Disease using Electronic Health Records. Duc Thanh Anh Luong, Dinh Tran, Varun Chandola, Chet Fox, Wilson Pace, Joseph Vassalotti, Jennifer Carroll, Miriam Dickinson, Matthew Withiam-Leitch, Nikhil Satchindanand, Min Yang, and Craig Smail. eGems - Generating Evidence & Methods to Improve Patient Outcomes, To Appear, 2016.
    2. Rumor Tagging in Crisis Microblogs: A Case of Boston Bombings. Rohit Valecha, Ankit Sultania, Varun Chandola, Manish Agrawal and Raghav Rao.Transactions on Information Systems, Under Review, 2015.
    3. A Reference Based Analysis Framework for Understanding Anomaly Detection Techniques for Symbolic Sequences. Varun Chandola, Varun Mithal and Vipin Kumar. Data Mining and Knowledge Discovery, Springer. 2014.
    4. Image Based Characterization of Formal and Informal Neighborhoods in an Urban Landscape. Jordan Grasser, Anil Cheriyadat, Ranga R. Vatsavai, Varun Chandola, Jordan Long, and Edward Bright. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2012.
    5. GX-Means: A model-based divide and merge algorithm for geospatial image clustering. Ranga R. Vatsavai, Christopher T. Symons, Varun Chandola, and Goo Jun. Procedia Computer Science. 2011.
    6. A Scalable Gaussian Process Analysis Algorithm for Biomass Monitoring. Varun Chandola and Ranga R. Vatsavai. Statistical Analysis and Data Mining. 2011.
    7. Anomaly Detection for Discrete Sequences - A Survey. Varun Chandola, Arindam Banerjee, and Vipin Kumar. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2011.
    8. Anomaly Detection - A Survey. Varun Chandola, Arindam Banerjee, and Vipin Kumar. ACM Computing Surveys (CSUR). 2009.
    9. Summarization - Compressing Data into an Informative Representation. Varun Chandola and Vipin Kumar. Knowledge And Information Systems Journal (KAIS). 2007.
  • Conferences
    1. Hospital Readmission Prediction - Applying Hierarchical Sparsity Norms for Interpretable Models. Jialiang Jiang, Sharon Hewner, and Varun Chandola, To Appear in the Proceedings of the Machine Learning and Data Mining Conference (MLDM), 2016
    2. Modeling Graphs Using a Mixture of Kronecker Models. Suchismit Mahapatra and Varun Chandola. Proceedings of the 3rd IEEE International Conference on Big Data, 2015.
    3. Surface Reconstruction from Intensity Image using Illumination Model based Morphable Modeling. Zhi Yang and Varun Chandola. Proceedings of 10th International Conference on Computer Vision Systems (ICVS), 2015.
    4. Bringing Big Data from Space to Desktop. Varun Chandola and Patrick Hogan. Proceedings of the 2014 conference on Big Data from Space (BiDS'14), 2014.
    5. Knowledge Discovery from Massive Healthcare Claims Data. Varun Chandola, Sreenivas R. Sukumar, and Jack C. Schryver. Proceedings of the 19th International ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2013.
    6. Large Scale Remote Sensing Data Mining for Biomass Monitoring: Recent Advances and Future Challenges. Ranga R. Vatsavai, Varun Chandola, and Budhendra Bhaduri. Proceedings of 7th International Conference on Geographic Information Science (GIScience). 2012.
    7. iGlobe: An Interactive Visualization and Analysis Framework for Geospatial Data. Varun Chandola, Budhendra Bhaduri, and Ranga R. Vatsavai. Proceedings of 2nd International Conference and Exhibition on Computing for Geospatial Research and Application (COM.Geo), 2011.
    8. Machine Learning Approaches for High-resolution Urban Land Cover Classification. Ranga R. Vatsavai, Varun Chandola, Anil Cheriyadat, Edward Bright, Bhaduri Budhendra, and Jordan Grasser. Proceedings of 2nd International Conference and Exhibition on Computing for Geospatial Research and Application (COM.Geo), 2011.
    9. Rapid Damage Assessment using High-resolution Remote Sensing Imagery: Tools and Techniques. Ranga R. Vatsavai, Mark Tuttle, Budhendra Bhaduri, Edward Bright, Anil Cheriyadat, and Varun Chandola. Presented at International Geoscience and Remote Sensing Symposium (IGARSS), 2011.
    10. A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series. Varun Chandola and Ranga R. Vatsavai. Proceedings of SIAM International Conference on Data Mining (SDM), 2011.
    11. Multi-temporal Remote Sensing Image Classification - A Multi-view Approach. Varun Chandola and Ranga R. Vatsavai. Proceedings of NASA Conference on Intelligent Data Understanding, 2010.
    12. Scalable Time Series Change Detection for Biomass Monitoring Using Gaussian Process. Varun Chandola and Ranga R. Vatsavai. Proceedings of NASA Conference on Intelligent Data Understanding (CIDU), 2010. ( Selected as one of the top 6 best papers at the conference.)
    13. A Framework for Exploring Categorical Data. Varun Chandola, Shyam Boriah, and Vipin Kumar. Proceedings of 2009 SIAM Data Mining Conference, 2009.
    14. Comparative Evaluation of Anomaly Detection Techniques for Sequence Data. Varun Chandola, Varun Mithal, and Vipin Kumar. Proceedings of 8th International Conference on Data Mining (ICDM), 2008.
    15. Similarity Measures for Categorical Data: A Comparative Evaluation, Shyam Boriah, Varun Chandola and Vipin Kumar. Proceedings of 8th SIAM Data Mining Conference (SDM), 2008.
    16. Summarization - Compressing Data into an Informative Representation. Varun Chandola and Vipin Kumar. Proceedings of 5th International Conference on Data Mining (ICDM), 2005. (Awarded one of the top 3 best student papers at the conference).
  • Workshop papers
    1. Exploiting Hierarchy in Disease Codes - A Healthcare Application of Tree Structured Sparsity-Inducing Norms. Jialiang Jiang, Sharon Hewner, and Varun Chandola, Presented at the SDM-DMMH Workshop, 2016
    2. Ettu: Analyzing Query Intents in Corporate Databases. Gökhan Kul, Duc Thanh Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu Upadhyaya, ERMIS 2016
    3. A Big Data Approach to Rumor Mitigation in Twitter Microblog: A Case of Boston Bombings. Rohit Valecha, Ankit Sultania, Varun Chandola, Manish Agrawal and H. Raghav Rao. Proceedings of the 13th Workshop on e-Business (WeB), 2015.
    4. Development of a computational and data-enabled science and engineering Ph.D. program. Paul T. Bauman, Varun Chandola, Abani Patra and Matthew Jones Proceedings of SC EduHPC Workshop, 2014.
    5. Spatiotemporal Data Mining in the Era of Big Spatial Data: Algorithms and Applications. Ranga R. Vatsavai, Varun Chandola, Scott Klasky, Auroop Ganguly, Anthony Stefanidis, Shashi Shekhar. Proceedings of 1st International Workshop on Analytics for Big Geospatial Data (BigSpatial), 2012.
    6. Implementing a Gaussian Process Learning Algorithm in Mixed Parallel Environment. Varun Chandola and Ranga R. Vatsavai. Proceedings of Super computing (SC) Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), 2011.
    7. Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data. Varun Chandola, Dafeng Hui, Lianhong Gu, and Ranga R. Vatsavai. Proceedings of 1st ICDM Workshop on Knowledge Discovery from Climate Data: Prediction, Extremes, and Impacts, 2010.
    8. An In Depth Scalability Analysis of a Gaussian Process Training Algorithm. Varun Chandola and Ranga R. Vatsavai. Proceedings of Super Computing (SC) Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), 2010.
    9. Scalable Hyper-parameter Estimation for Gaussian Process Based Time Series Analysis. Varun Chandola and Ranga R. Vatsavai. Proceedings of 4th SIGKDD Workshop on Large-scale Data Mining: Theory and Applications (LDMTA), 2010.
    10. A Reference Based Analysis Framework for Analyzing System Call Traces. Varun Chandola, Shyam Boriah, and Vipin Kumar. Proceedings of 6th Annual Cyber Security and Information Intelligence Research Workshop (CSIIRW), 2010.
    11. DDDAS/ITR: A Data Mining and Exploration Middleware for Grid and Distributed Computing. Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric Eilertson, Levent Ertoz, Gyorgy Simon, Seonho Kim, and Jinoh Kim. Proceedings of Workshop on Dynamic Data Driven Application Systems - DDDAS, 2007.
  • Edited Proceedings
    1. Third ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial). Varun Chandola and Ranga Raju Vatsavai. Workshop Proceedings, 22nd International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2014), 2014.
    2. Second ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial). Varun Chandola and Ranga Raju Vatsavai. Workshop Proceedings, 21st International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2013), 2013.
    3. First ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial). Varun Chandola and Ranga Raju Vatsavai. Workshop Proceedings, 20th International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2012), 2012.
    4. Fifth International Conference on Knowledge Discovery from Sensor Data (Sensor-KDD’11). Varun Chandola, Olufemi Omitaomu, Auroop Ganguly, Ranga R. Vatsavai, Joao Gama, Mohamed Gaber, and Nitesh Chawla [Proceedings Editors and Workshop Organizers] Workshop Proceedings, 17th International Conference on Knowledge Discovery and Data Mining (KDD), 2011.
    5. Fourth International Conference on Knowledge Discovery from Sensor Data (Sensor-KDD’10). Varun Chandola, Olufemi Omitaomu, Auroop Ganguly, Ranga R. Vatsavai, Joao Gama, Mohamed Gaber, and Nitesh Chawla [Proceedings Editors and Workshop Organizers] Workshop Proceedings, 16th International Conference on Knowledge Discovery and Data Mining (KDD), 2010.
  • Invited Articles
    1. Virtualization of Evolving Power Grid. Olufemi Omitaomu, Varun Chandola, and Alexander Sorokine. IEEE Smart Grid Newsletter, 2012. (Included in the IEEE Smart Grid Compendium tagged Smart Grid: The Next Decade.)
    2. Knowledge discovery from sensor data (SensorKDD). Varun Chandola, Olufemi Omitaomu, Auroop Ganguly, Ranga R. Vatsavai, Nitesh Chawla, Joao Gama, and Mohamed Gaber. SIGKDD Explorations Newsletter, 2011.
  • Book Chapters
    1. Analyzing Big Spatial and Big Spatiotemporal Data: A Case Study of Methods and Applications. Varun Chandola, Ranga R. Vatsavai, Devashish Kumar, and Auroop Ganguly. Big Data Analytics, eds. Vijay Raghavan, Calyumpadi R. Rao and Venu Govindaraju, Elsevier Publications, 2015.
    2. Fraud Detection in Healthcare. Varun Chandola, Sreenivas R. Sukumar, and Jack C. Schryver. Healthcare Data Analytics, eds. Chandan Reddy and Charu Aggarwal, 2014.
    3. Data Analysis for Real Time Identification of Grid Disruptions. Varun Chandola, Omitaomu Olufemi and Steve N. Fernandez. Computational Intelligent Data Analysis for Sustainable Development, eds. Ting Yu, Nitesh Chawla, and Simeon Simoff, Taylor and Francis, 2012.
    4. Data Mining for Cyber Security. Varun Chandola, Eric Eilertson, Levent Ertoz, Gyorgy Simon and Vipin Kumar. Data Warehousing and Data Mining Techniques for Computer Security, ed. Anoop Singhal, Springer, 2006.
  • Technical Reports
    1. Non-parametric Depth Estimation for Images from a Single Reference Depth. Zhi Yang and Varun Chandola. UB CSE Technical Report 2014-01. 2014.
    2. Knowledge Discovery from Massive Healthcare Claims Data. Varun Chandola, Sukumar R.~Sreenivas, Jack Schryver. ORNL Technical Report ORNL/TM-2013/83. 2013.
    3. Detecting Anomalies in a Time Series Database. Varun Chandola, Deepthi Cheboli, and Vipin Kumar. CS Technical Report 09-004, Computer Science Department, University of Minnesota. 2009.
    4. Understanding Anomaly Detection Techniques for Symbolic Sequences. Varun Chandola, Varun Mithal, and Vipin Kumar. CS Technical Report 09-001, Computer Science Department, University of Minnesota. 2009.
    5. Understanding Categorical Similarity Measures for Outlier Detection. Varun Chandola, Shyam Boriah, and Vipin Kumar. CS Technical Report 08-008, Computer Science Department, University of Minnesota. 2008.
    6. A Multi-Step Framework for Detecting Attack Scenarios. Mark Shaneck, Varun Chandola, Haiyang Liu, Changho Choi, Gyorgy Simon, Eric Eilertson, Yongdae Kim, Zhi-li Zhang, Jaideep Srivastava, and Vipin Kumar. CS Technical Report 06-004, Computer Science Department, University of Minnesota. 2008.