| 2022 | ICCS | Classifying Anomalous Members in a Collection of Multivariate Time Series Data Using Large Deviations Principle: An Application to COVID-19 Data. | Sreelekha Guggilam, Varun Chandola, Abani K. Patra |
| 2022 | ICCS | ChemTab: A Physics Guided Chemistry Modeling Framework. | Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola |
| 2021 | ICMLA | From images in the wild to video-informed image classification. | Marc Bhlen, Raunaq Jain, Wawan Sujarwo, Varun Chandola |
| 2021 | SSDBM | Graph-based Strategy for Establishing Morphology Similarity. | Namit Juneja, Jaroslaw Zola, Varun Chandola, Olga Wodo |
| 2019 | ICCS | Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data. | Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra |
| 2018 | TrustCom | Detecting Data Leakage from Databases on Android Apps with Concept Drift. | Gkhan Kul, Shambhu J. Upadhyaya, Varun Chandola |
| 2017 | CLUSTER | Tracking System Behavior from Resource Usage Data. | Niyazi Sorkunlu, Varun Chandola, Abani K. Patra |
| 2017 | SDM | Error Metrics for Learning Reliable Manifolds from Streaming Data. | Frank Schoeneman, Suchismit Mahapatra, Varun Chandola, Nils Napp, Jaroslaw Zola |
| 2016 | WWW | Ettu: Analyzing Query Intents in Corporate Databases. | Gkhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya |
| 2015 | ICVS | Surface Reconstruction from Intensity Image Using Illumination Model Based Morphable Modeling. | Zhi Yang, Varun Chandola |
| 2014 | SC | Development of a computational and data-enabled science and engineering Ph.D. program. | Paul T. Bauman, Varun Chandola, Abani K. Patra, Matthew D. Jones |
| 2013 | KDD | Knowledge discovery from massive healthcare claims data. | Varun Chandola, Sreenivas R. Sukumar, Jack C. Schryver |
| 2011 | IGARSS | Rapid damage assessment using high-resolution remote sensing imagery: Tools and techniques. | Ranga Raju Vatsavai, Mark A. Tuttle, Budhendra L. Bhaduri, Edward Bright, Anil M. Cheriyadat, Varun Chandola, Jordan Graesser |
| 2011 | SC | Implementing a gaussian process learning algorithm in mixed parallel environment. | Varun Chandola, Ranga Raju Vatsavai |
| 2011 | SDM | A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series. | Varun Chandola, Ranga Raju Vatsavai |
| 2010 | ICDM | Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data. | Varun Chandola, Dafeng Hui, Lianhong Gu, Budhendra L. Bhaduri, Ranga Raju Vatsavai |
| 2009 | SDM | A Framework for Exploring Categorical Data. | Varun Chandola, Shyam Boriah, Vipin Kumar |
| 2008 | ICDM | Comparative Evaluation of Anomaly Detection Techniques for Sequence Data. | Varun Chandola, Varun Mithal, Vipin Kumar |
| 2008 | SDM | Similarity Measures for Categorical Data: A Comparative Evaluation. | Shyam Boriah, Varun Chandola, Vipin Kumar |
| 2007 | ICCS | DDDAS/ITR: A Data Mining and Exploration Middleware for Grid and Distributed Computing. | Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric Eilertson, Levent Ertz, Gyrgy J. Simon, Seonho Kim, Jinoh Kim |
| 2005 | ICDM | Summarization - Compressing Data into an Informative Representation. | Varun Chandola, Vipin Kumar |