Varun Chandola

100 papers A* 3A 4B 2C 4Misc 2Journal 46Unranked 25

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	2024 NSF CSSI-Cybertraining-SCIPE PI Meeting August 12 to 13, 2024, Charlotte, NC. CoRR Abani K. Patra, Mary P. Thomas, Elias Bou-Harb, Jeffrey C. Carver, Yuebin Guo, Ratnesh Kumar, Julien Langou, Guoyu Lu, Vivak Patel, Marianna Safronova, Isla Simpson, Dhruva Chakravorty, Jane Combs, Hantao Cui, Sushil K. Prasad, Adnan Rajib, Susan Rathbun, Erik Saule, Alan Sussman, Shaowen Wang, Sarina Zhe Zhang, Ben Brown, Varun Chandola, Daniel Crawford, Ian T. Foster, Dave Hart, Mike Heroux, Mary Ann Leung, Benjamin Lynch, Dan Negrut, D. K. Panda, Manish Parashar, Melissa Kline Struhl, George K. Thiruvathukal
2024	J	`jnl`	Learning manifolds from non-stationary streams. J. Big Data Suchismit Mahapatra, Varun Chandola
2024	B	`conf`	Resource Efficient Bayesian Optimization. CLOUD Namit Juneja, Varun Chandola, Jaroslaw Zola, Olga Wodo, Parth Desai
2023	J	`jnl`	Large Deviations Anomaly Detection (LAD) for collection of multivariate time series data: Applications to COVID-19 data. J. Comput. Sci. Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2023	J	`jnl`	Large Deviations for Accelerating Neural Networks Training. CoRR Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2023	J	`jnl`	Physics informed machine learning for chemistry tabulation. J. Comput. Sci. Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola
2023	—	`ed.`	Proceedings of the 11th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2023, Hamburg, Germany, 13 November 2023 BigSpatial@SIGSPATIAL Ashwin Shashidharan, Martin Werner, Krishna Karthik Gadiraju, Varun Chandola, Ranga Raju Vatsavai
2022	J	`jnl`	An Ensemble-Based Deep Framework for Estimating Thermo-Chemical State Variables from Flamelet Generated Manifolds. CoRR Amol Salunkhe, Georgios Georgalis, Abani K. Patra, Varun Chandola
2022	—	`conf`	ChemTab: A Physics Guided Chemistry Modeling Framework. ICCS (1) Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola
2022	J	`jnl`	ChemTab: A Physics Guided Chemistry Modeling Framework. CoRR Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola
2022	—	`conf`	Classifying Anomalous Members in a Collection of Multivariate Time Series Data Using Large Deviations Principle: An Application to COVID-19 Data. ICCS (1) Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2022	J	`jnl`	Geo-Adaptive Deep Spatio-Temporal predictive modeling for human mobility. CoRR Syed Mohammed Arshad Zaidi, Varun Chandola, Eun-Hye Enki Yoo
2022	—	`conf`	Mutual Information Scoring: Increasing Interpretability in Categorical Clustering Tasks with Applications to Child Welfare Data. SBP-BRiMS Pranav Sankhe, Seventy F. Hall, Melanie D. Sage, Maria Y. Rodriguez, Varun Chandola, Kenneth Joseph
2022	J	`jnl`	Mutual Information Scoring: Increasing Interpretability in Categorical Clustering Tasks with Applications to Child Welfare Data. CoRR Pranav Sankhe, Seventy F. Hall, Melanie D. Sage, Maria Y. Rodriguez, Varun Chandola, Kenneth Joseph
2022	J	`jnl`	Physics Informed Machine Learning for Chemistry Tabulation. CoRR Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola
2022	—	`ed.`	Proceedings of the 10th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2022, Seattle, Washington, 1 November 2022 BigSpatial@SIGSPATIAL Ashwin Shashidharan, Krishna Karthik Gadiraju, Varun Chandola, Ranga Raju Vatsavai
2022	J	`jnl`	The 10th ACM SIGSPATIAL International Workshop on Analytics for Big Spatial Data (BigSpatial 2022). ACM SIGSPATIAL Special Ashwin Shashidharan, Krishna Karthik Gadiraju, Ranga Raju Vatsavai, Varun Chandola
2022	J	`jnl`	Tracking clusters and anomalies in evolving data streams. Stat. Anal. Data Min. Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2021	J	`jnl`	Anomaly Detection for High-Dimensional Data Using Large Deviations Principle. CoRR Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2021	J	`jnl`	DST-Predict: Predicting Individual Mobility Patterns From Mobile Phone GPS Data. IEEE Access Syed Mohammed Arshad Zaidi, Varun Chandola, Eun-Hye Enki Yoo
2021	—	`conf`	Explainable Deep Learning for Readmission Prediction with Tree-GloVe Embedding. ICHI Jialiang Jiang, Sharon Hewner, Varun Chandola
2021	C	`conf`	From images in the wild to video-informed image classification. ICMLA Marc Böhlen, Raunaq Jain, Wawan Sujarwo, Varun Chandola
2021	J	`jnl`	From images in the wild to video-informed image classification. CoRR Marc Böhlen, Varun Chandola, Wawan Sujarwo, Raunaq Jain
2021	B	`conf`	Graph-based Strategy for Establishing Morphology Similarity. SSDBM Namit Juneja, Jaroslaw Zola, Varun Chandola, Olga Wodo
2020	—	`ed.`	BIGSPATIAL '20: Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2020, Seattle, WA, USA, November 3, 2020 BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai, Ashwin Shashidharan
2020	J	`jnl`	Learning Manifolds from Dynamic Process Data. Algorithms Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola
2020	J	`jnl`	The 9th ACM SIGSPATIAL International Workshop on Analytics for Big Spatial Data (BigSpatial 2020): November 3, 2020. ACM SIGSPATIAL Special Ashwin Shashidharan, Varun Chandola, Ranga Raju Vatsavai
2019	J	`jnl`	Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised). CoRR Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra
2019	—	`conf`	Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data. ICCS (4) Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra
2019	—	`conf`	Learning Deep Representations from Clinical Data for Chronic Kidney Disease. ICHI Duc Thanh Anh Luong, Varun Chandola
2019	—	`ed.`	Proceedings of the 8th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2019, Chicago, IL, USA, November 5th, 2019. BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai, Ashwin Shashidharan
2019	J	`jnl`	The Eighth ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data: Chicago, IL, USA - November 5, 2019. ACM SIGSPATIAL Special Ashwin Shashidharan, Varun Chandola, Ranga Raju Vatsavai
2019	—	`conf`	Tree-based Regularization for Interpretable Readmission Prediction. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering Jialiang Jiang, Sharon Hewner, Varun Chandola
2019	J	`jnl`	longSil: an Evaluation Metric to Assess Quality of Clustering Longitudinal Clinical Data. J. Heal. Informatics Res. Duc Thanh Anh Luong, Prerna Singh, Mahin Ramezani, Varun Chandola
2018	J	`jnl`	An Empirical Evaluation of Time-Aware LSTM Autoencoder on Chronic Kidney Disease. CoRR Duc Thanh Anh Luong, Varun Chandola
2018	—	`conf`	Detecting Data Leakage from Databases on Android Apps with Concept Drift. TrustCom/BigDataSE Gökhan Kul, Shambhu J. Upadhyaya, Varun Chandola
2018	J	`jnl`	Detecting Data Leakage from Databases on Android Apps with Concept Drift. CoRR Gökhan Kul, Shambhu J. Upadhyaya, Varun Chandola
2018	—	`conf`	Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes. IEEE BigData Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola
2018	J	`jnl`	Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes. CoRR Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola
2018	J	`jnl`	Hospital Readmission Prediction - Applying Hierarchical Sparsity Norms for Interpretable Models. CoRR Jialiang Jiang, Sharon Hewner, Varun Chandola
2018	J	`jnl`	Learning Manifolds from Non-stationary Streaming Data. CoRR Suchismit Mahapatra, Varun Chandola
2018	—	`ed.`	Proceedings of the 7th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2018, Seattle, WA, USA, November 6, 2018 BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai
2018	J	`jnl`	Query Log Compression for Workload Analytics. CoRR Ting Xie, Oliver Kennedy, Varun Chandola
2018	J	`jnl`	Query Log Compression for Workload Analytics. Proc. VLDB Endow. Ting Xie, Varun Chandola, Oliver Kennedy
2018	J	`jnl`	Similarity Metrics for SQL Query Clustering. IEEE Trans. Knowl. Data Eng. Gökhan Kul, Duc Thanh Anh Luong, Ting Xie, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya
2018	J	`jnl`	The seventh ACM SIGSPATIAL international workshop on analysis for big spatial data seattle, wa, USA - November 6, 2018. ACM SIGSPATIAL Special Varun Chandola, Ranga Raju Vatsavai
2018	—	`conf`	WebGIobe - A cloud-based geospatial analysis framework for interacting with climate data. BigSpatial@SIGSPATIAL Arun Sharma, Syed Mohammed Arshad Zaidi, Varun Chandola, Melissa R. Allen, Budhendra L. Bhaduri
2018	—	`conf`	dynamicMF: A Matrix Factorization Approach to Monitor Resource Usage in High Performance Computing Systems. IEEE BigData Niyazi Sorkunlu, Duc Thanh Anh Luong, Varun Chandola
2018	J	`jnl`	dynamicMF: A Matrix Factorization Approach to Monitor Resource Usage in High Performance Computing Systems. CoRR Niyazi Sorkunlu, Duc Thanh Anh Luong, Varun Chandola
2017	—	`conf`	A K-Means Approach to Clustering Disease Progressions. ICHI Duc Thanh Anh Luong, Varun Chandola
2017	—	`ch.`	Active Learning. Encyclopedia of Machine Learning and Data Mining Varun Chandola, Arindam Banerjee, Vipin Kumar
2017	—	`conf`	Automatic Extraction of Deep Phenotypes for Precision Medicine in Chronic Kidney Disease. DH Prerna Singh, Varun Chandola, Chester H. Fox
2017	A	`conf`	Error Metrics for Learning Reliable Manifolds from Streaming Data. SDM Frank Schoeneman, Suchismit Mahapatra, Varun Chandola, Nils Napp, Jaroslaw Zola
2017	J	`jnl`	Modeling Graphs Using a Mixture of Kronecker Models. CoRR Suchismit Mahapatra, Varun Chandola
2017	—	`ed.`	Proceedings of the 6th ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2017, Redondo Beach, CA, USA, November 7, 2017 BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai
2017	J	`jnl`	S-Isomap++: Multi Manifold Learning from Streaming Data. CoRR Suchismit Mahapatra, Varun Chandola
2017	—	`conf`	S-Isomap++: Multi manifold learning from streaming data. IEEE BigData Suchismit Mahapatra, Varun Chandola
2017	J	`jnl`	Server, server in the cloud. Who is the fairest in the crowd? CoRR Marc Böhlen, Varun Chandola, Amol Salunkhe
2017	J	`jnl`	The Sixth ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data: Redondo Beach, CA, USA - November 7, 2017. ACM SIGSPATIAL Special Varun Chandola, Ranga Raju Vatsavai
2017	C	`conf`	Tracking System Behavior from Resource Usage Data. CLUSTER Niyazi Sorkunlu, Varun Chandola, Abani K. Patra
2017	J	`jnl`	Tracking System Behaviour from Resource Usage Data. CoRR Niyazi Sorkunlu, Varun Chandola, Abani K. Patra
2016	—	`conf`	Ettu: Analyzing Query Intents in Corporate Databases. WWW (Companion Volume) Gökhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya
2016	J	`jnl`	Guest editorial: big spatial data. GeoInformatica Ranga Raju Vatsavai, Varun Chandola
2016	—	`ed.`	Proceedings of the 5th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2016, Burlingame, California, USA, October 31, 2016 BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai
2016	J	`jnl`	Summarizing Large Query Logs in Ettu. CoRR Gökhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya
2015	—	`ch.`	Fraud Detection in Healthcare. Healthcare Data Analytics Varun Chandola, Jack C. Schryver, Sreenivas R. Sukumar
2015	—	`conf`	Modeling graphs using a mixture of Kronecker models. IEEE BigData Suchismit Mahapatra, Varun Chandola
2015	—	`ed.`	Proceedings of the 4th International ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2015, Bellevue, WA, USA, November 3-6, 2015 BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai
2015	C	`conf`	Surface Reconstruction from Intensity Image Using Illumination Model Based Morphable Modeling. ICVS Zhi Yang, Varun Chandola
2015	J	`jnl`	The Third ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data Dallas, Texas, USA - November 4, 2014. ACM SIGSPATIAL Special Varun Chandola, Ranga Raju Vatsavai
2014	J	`jnl`	A reference based analysis framework for understanding anomaly detection techniques for symbolic sequences. Data Min. Knowl. Discov. Varun Chandola, Varun Mithal, Vipin Kumar
2014	J	`jnl`	BigSpatial-2013 workshop report: 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial-2013): Nov 5, 2013, Orlando, Florida, USA. ACM SIGSPATIAL Special Varun Chandola, Ranga Raju Vatsavai
2014	—	`conf`	Development of a computational and data-enabled science and engineering Ph.D. program. EduHPC@SC Paul T. Bauman, Varun Chandola, Abani K. Patra, Matthew D. Jones
2014	—	`ed.`	Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2014, Dallas, Texas, USA, November 4, 2014 BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai
2013	—	`ch.`	Data Analysis for Real- Time Identification of Grid Disruptions. Computational Intelligent Data Analysis for Sustainable Development Varun Chandola, Olufemi A. Omitaomu, Steven J. Fernandez
2013	A*	`conf`	Knowledge discovery from massive healthcare claims data. KDD Varun Chandola, Sreenivas R. Sukumar, Jack C. Schryver
2013	—	`ed.`	Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2013, Nov 4th, 2013, Orlando, FL, USA BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai
2012	J	`jnl`	Anomaly Detection for Discrete Sequences: A Survey. IEEE Trans. Knowl. Data Eng. Varun Chandola, Arindam Banerjee, Vipin Kumar
2012	J	`jnl`	Image Based Characterization of Formal and Informal Neighborhoods in an Urban Landscape. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Jordan Graesser, Anil M. Cheriyadat, Ranga Raju Vatsavai, Varun Chandola, Jordan Long, Eddie A. Bright
2012	—	`ed.`	Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2012, Redondo Beach, CA, USA, November 6, 2012 BigSpatial@SIGSPATIAL Varun Chandola, Ranga Raju Vatsavai, Chetan Gupta
2012	—	`conf`	Spatiotemporal data mining in the era of big spatial data: algorithms and applications. BigSpatial@SIGSPATIAL Ranga Raju Vatsavai, Auroop R. Ganguly, Varun Chandola, Anthony Stefanidis, Scott Klasky, Shashi Shekhar
2011	A	`conf`	A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series. SDM Varun Chandola, Ranga Raju Vatsavai
2011	J	`jnl`	A scalable gaussian process analysis algorithm for biomass monitoring. Stat. Anal. Data Min. Varun Chandola, Ranga Raju Vatsavai
2011	Misc	`conf`	GX-Means: A model-based divide and merge algorithm for geospatial image clustering. ICCS Ranga Raju Vatsavai, Christopher T. Symons, Varun Chandola, Goo Jun
2011	—	`conf`	Implementing a gaussian process learning algorithm in mixed parallel environment. ScalA@SC Varun Chandola, Ranga Raju Vatsavai
2011	—	`conf`	Machine learning approaches for high-resolution urban land cover classification: a comparative study. COM.Geo Ranga Raju Vatsavai, Eddie A. Bright, Varun Chandola, Budhendra L. Bhaduri, Anil M. Cheriyadat, Jordan Graesser
2011	C	`conf`	Rapid damage assessment using high-resolution remote sensing imagery: Tools and techniques. IGARSS Ranga Raju Vatsavai, Mark A. Tuttle, Budhendra L. Bhaduri, Edward Bright, Anil M. Cheriyadat, Varun Chandola, Jordan Graesser
2011	—	`conf`	iGlobe: an interactive visualization and analysis framework for geospatial data. COM.Geo Varun Chandola, Ranga Raju Vatsavai, Budhendra L. Bhaduri
2010	—	`conf`	A reference based analysis framework for analyzing system call traces. CSIIRW Varun Chandola, Shyam Boriah, Vipin Kumar
2010	J	`jnl`	Knowledge discovery from sensor data (SensorKDD). SIGKDD Explor. Varun Chandola, Olufemi A. Omitaomu, Auroop R. Ganguly, Ranga Raju Vatsavai, Nitesh V. Chawla, João Gama, Mohamed Medhat Gaber
2010	—	`conf`	Multi-temporal remote sensing image classification - A multi-view approach. CIDU Varun Chandola, Ranga Raju Vatsavai
2010	—	`conf`	Scalable Time Series Change Detection for Biomass Monitoring Using Gaussian Process. CIDU Varun Chandola, Ranga Raju Vatsavai
2010	—	`conf`	Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data. ICDM Workshops Varun Chandola, Dafeng Hui, Lianhong Gu, Budhendra L. Bhaduri, Ranga Raju Vatsavai
2009	A	`conf`	A Framework for Exploring Categorical Data. SDM Varun Chandola, Shyam Boriah, Vipin Kumar
2009	J	`jnl`	Anomaly detection: A survey. ACM Comput. Surv. Varun Chandola, Arindam Banerjee, Vipin Kumar
2008	A*	`conf`	Comparative Evaluation of Anomaly Detection Techniques for Sequence Data. ICDM Varun Chandola, Varun Mithal, Vipin Kumar
2008	A	`conf`	Similarity Measures for Categorical Data: A Comparative Evaluation. SDM Shyam Boriah, Varun Chandola, Vipin Kumar
2007	Misc	`conf`	DDDAS/ITR: A Data Mining and Exploration Middleware for Grid and Distributed Computing. International Conference on Computational Science (1) Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric Eilertson, Levent Ertöz, György J. Simon, Seonho Kim, Jinoh Kim
2007	J	`jnl`	Summarization - compressing data into an informative representation. Knowl. Inf. Syst. Varun Chandola, Vipin Kumar
2005	A*	`conf`	Summarization - Compressing Data into an Informative Representation. ICDM Varun Chandola, Vipin Kumar