| 2026 | ICCS | A Two-Stream CNN Framework for Spatiotemporally Resolved NO | Adam Bloom, Zhen Qu, Ranga Raju Vatsavai |
| 2026 | PAKDD | Physics-Guided Knowledge Graphs for Verifiable Wildfire Prediction. | Nahed Abu Zaid, Ranga Raju Vatsavai |
| 2025 | ICDM | Enhancing LLM Dialogue with Graph-Based Context, Style, and Sentiment Integration. | Mayur Prakash Gotmare, Ranga Raju Vatsavai |
| 2025 | ICDM | Efficient Multi-Domain Instance Segmentation with Modular Shared-Head Routing. | Rohit Sriram, Ranga Raju Vatsavai |
| 2025 | PAKDD | CoMAC: Conversational Agent for Multi-source Auxiliary Context with Sparse and Symmetric Latent Interactions. | Junfeng Liu, Christopher T. Symons, Ranga Raju Vatsavai |
| 2024 | ICDM | A Deep Learning Based Cloud Imputation Framework. | Harshitaa Yarramsetti, Kritika Javali, Mukund Logasundar, Richard Li, Ranga Raju Vatsavai |
| 2023 | ICDM | Context Retrieval via Normalized Contextual Latent Interaction for Conversational Agent. | Junfeng Liu, Zhuocheng Mei, Kewen Peng, Ranga Raju Vatsavai |
| 2023 | IGARSS | Novel Deep Learning Framework for Imputing Holes in Orthorectified VHR Images. | Sai Venkata Vinay Kumar Samudrala, Yifan Zhao, Ranga Raju Vatsavai |
| 2023 | ICTAI | Persona-Coded Poly-Encoder: Persona-Guided Multi-Stream Conversational Sentence Scoring. | Junfeng Liu, Christopher T. Symons, Ranga Raju Vatsavai |
| 2022 | ICDM | Persona-Based Conversational AI: State of the Art and Challenges. | Junfeng Liu, Christopher T. Symons, Ranga Raju Vatsavai |
| 2022 | ICMLA | Real-Time Change Detection At the Edge. | Krishna Karthik Gadiraju, Zexi Chen, Bharathkumar Ramachandra, Ranga Raju Vatsavai |
| 2022 | ICMLA | Multi-stream Deep Residual Network for Cloud Imputation Using Multi-resolution Remote Sensing Imagery. | Yifan Zhao, Xian Yang, Ranga Raju Vatsavai |
| 2022 | ICPR | Deep Residual Network with Multi-Image Attention for Imputing Under Clouds in Satellite Imagery. | Xian Yang, Yifan Zhao, Ranga Raju Vatsavai |
| 2020 | ICPR | Local Clustering with Mean Teacher for Semi-supervised learning. | Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra, Tianfu Wu, Ranga Raju Vatsavai |
| 2020 | KDD | Multimodal Deep Learning Based Crop Classification Using Multispectral and Multitemporal Satellite Imagery. | Krishna Karthik Gadiraju, Bharathkumar Ramachandra, Zexi Chen, Ranga Raju Vatsavai |
| 2020 | WACV | Learning a distance function with a Siamese network to localize anomalies in videos. | Bharathkumar Ramachandra, Michael J. Jones, Ranga Raju Vatsavai |
| 2019 | ICDM | Evaluating Performance of Deep Neural Networks for Crop Classification and Complex Facility Recognition. | Krishna Karthik Gadiraju, Bharathkumar Ramachandra, Ranga Raju Vatsavai |
| 2019 | ICMLA | Scalable Data Parallel Approaches to Anomaly Detection in Climate Data using Gaussian Processes. | Krishna Karthik Gadiraju, Bharathkumar Ramachandra, Ashwin Shashidharan, Benjamin Dutton, Ranga Raju Vatsavai |
| 2019 | IGARSS | Scaling Deep Learning Based Crop Classification on Modern Intel Xeon Processors. | Bharathkumar Ramachandra, Krishna Karthik Gadiraju, Ranga Raju Vatsavai, Jaime Puente |
| 2019 | IGARSS | Classification Performance Evaluation of Deep Learning Architectures for Complex Object Based Facility Recognition. | Krishna Karthik Gadiraju, Bharathkumar Ramachandra, Ranga Raju Vatsavai |
| 2018 | ICDM | Machine Learning Approaches for Slum Detection Using Very High Resolution Satellite Images. | Krishna Karthik Gadiraju, Ranga Raju Vatsavai, Nikhil Kaza, Eric Wibbels, Anirudh Krishna |
| 2017 | BigData | Parallel Processing over Spatial-Temporal Datasets from Geo, Bio, Climate and Social Science Communities: A Research Roadmap. | Sushil K. Prasad, Danial Aghajarian, Michael McDermott, Dhara Shah, Mohamed F. Mokbel, Satish Puri, Sergio J. Rey, Shashi Shekhar, Yiqun Xe, Ranga Raju Vatsavai, Fusheng Wang, Yanhui Liang, Hoang Vo, Shaowen Wang |
| 2017 | IGARSS | Hierarchical change detection framework for biomass monitoring. | Zexi Chen, Bharathkumar Ramachandra, Ranga Raju Vatsavai |
| 2017 | IGARSS | Semi-supervised deep generative models for change detection in very high resolution imagery. | Clayton Connors, Ranga Raju Vatsavai |
| 2017 | SC | In Situ Summarization with VTK-m. | David C. Thompson, Sbastien Jourdain, Andrew C. Bauer, Berk Geveci, Robert Maynard, Ranga Raju Vatsavai, Patrick O'Leary |
| 2016 | BigData | A Scalable Probabilistic Change Detection Algorithm for Very High Resolution (VHR) Satellite Imagery. | Seokyong Hong, Ranga Raju Vatsavai |
| 2016 | HPDC | Evaluation of Pattern Matching Workloads in Graph Analysis Systems. | Seokyong Hong, Sangkeun Lee, Seung-Hwan Lim, Sreenivas R. Sukumar, Ranga Raju Vatsavai |
| 2016 | ICCS | Sliding Window-based Probabilistic Change Detection for Remote-sensed Images. | Seokyong Hong, Ranga Raju Vatsavai |
| 2016 | ICCS | Detecting Extreme Events in Gridded Climate Data. | Bharathkumar Ramachandra, Krishna Karthik Gadiraju, Ranga Raju Vatsavai, Dale P. Kaiser, Thomas P. Karnowski |
| 2015 | BigData | A Scalable Complex Pattern Mining Framework for Global Settlement Mapping. | Ranga Raju Vatsavai |
| 2015 | KDD | Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery. | Manu Sethi, Yupeng Yan, Anand Rangarajan, Ranga Raju Vatsavai, Sanjay Ranka |
| 2013 | ICDM | Multi-sensor Remote Sensing Image Change Detection: An Evaluation of Similarity Measures. | Karthik Ganesan Pillai, Ranga Raju Vatsavai |
| 2013 | KDD | Gaussian multiple instance learning approach for mapping the slums of the world using very high resolution imagery. | Ranga Raju Vatsavai |
| 2012 | ICDM | Rapid Damage eXplorer (RDX): A Probabilistic Framework for Learning Changes from Bitemporal Images. | Ranga Raju Vatsavai |
| 2012 | ICDM | A Data Mining Framework for Monitoring Nuclear Facilities. | Ranga Raju Vatsavai |
| 2012 | ICMLA | Bias Selection Using Task-Targeted Random Subspaces for Robust Application of Graph-Based Semi-supervised Learning. | Christopher T. Symons, Ranga Raju Vatsavai, Goo Jun, Itamar Arel |
| 2012 | SC | Scalable Multi-Instance Learning Approach for Mapping the Slums of the World. | Ranga Raju Vatsavai |
| 2011 | ICDM | High-Resolution Urban Image Classification Using Extended Features. | Ranga Raju Vatsavai |
| 2011 | IGARSS | Design of benchmark imagery for validating facility annotation algorithms. | Randy S. Roberts, Paul A. Pope, Ranga Raju Vatsavai, Ming Jiang, Lloyd F. Arrowood, Timothy G. Trucano, Shaun S. Gleason, Anil M. Cheriyadat, Alex Sorokine, Aggelos K. Katsaggelos, Thrasyvoulos N. Pappas, Lucinda R. Gaines, Lawrence K. Chilton |
| 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 | IGARSS | Verification & validation of a semantic image tagging framework via generation of geospatial imagery ground truth. | Shaun S. Gleason, Mesfin Dema, Hamed Sari-Sarraf, Anil M. Cheriyadat, Ranga Raju Vatsavai, Regina Ferrell |
| 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 |
| 2010 | ICDM | Unsupervised Semantic Labeling Framework for Identification of Complex Facilities in High-Resolution Remote Sensing Images. | Ranga Raju Vatsavai, Anil M. Cheriyadat, Shaun S. Gleason |
| 2010 | IGARSS | Geospatial image mining for nuclear proliferation detection: Challenges and new opportunities. | Ranga Raju Vatsavai, Budhendra L. Bhaduri, Anil M. Cheriyadat, Lloyd F. Arrowood, Eddie A. Bright, Shaun S. Gleason, Carl Diegert, Aggelos K. Katsaggelos, Thrasos N. Pappas, Reid B. Porter, Jim Bollinger, Barry Chen, Ryan Hohimer |
| 2010 | IGARSS | Semantic information extraction from multispectral geospatial imagery via a flexible framework. | Shaun S. Gleason, Regina Ferrell, Anil M. Cheriyadat, Ranga Raju Vatsavai, Soumya De |
| 2009 | ICCS | Incremental Clustering Algorithm for Earth Science Data Mining. | Ranga Raju Vatsavai |
| 2009 | ICDM | Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes. | Goo Jun, Ranga Raju Vatsavai, Joydeep Ghosh |
| 2009 | KDD | Phenological event detection from multitemporal image data. | Ranga Raju Vatsavai |
| 2008 | ICDM | A Semi-supervised Learning Algorithm for Recognizing Sub-classes. | Ranga Raju Vatsavai, Shashi Shekhar, Budhendra L. Bhaduri |
| 2008 | IGARSS | Multisource Data Classification using a Hybrid Semi-Supervised Learning Scheme. | Ranga Raju Vatsavai, Budhendra L. Badhuri, Shashi Shekhar, Thomas E. Burk |
| 2008 | ICTAI | Sub-class Recognition from Aggregate Class Labels: Preliminary Results. | Ranga Raju Vatsavai, Shashi Shekhar, Budhendra L. Bhaduri |
| 2008 | SSPR | A Learning Scheme for Recognizing Sub-classes from Model Trained on Aggregate Classes. | Ranga Raju Vatsavai, Shashi Shekhar, Budhendra L. Bhaduri |
| 2007 | ICDM | A Hybrid Classification Scheme for Mining Multisource Geospatial Data. | Ranga Raju Vatsavai, Budhendra L. Bhaduri |
| 2006 | EDBT | Improving DB2 Performance Expert - A Generic Analysis Framework. | Laurent Mignet, Jayanta Basak, Manish Bhide, Prasan Roy, Sourashis Roy, Vibhuti S. Sengar, Ranga Raju Vatsavai, Michael Reichert, Torsten Steinbach, D. V. S. Ravikant, Soujanya Vadapalli |
| 2005 | ICTAI | A Semi-Supervised Learning Method for Remote Sensing Data Mining. | Ranga Raju Vatsavai, Shashi Shekhar, Thomas E. Burk |
| 2001 | SSDBM | An efficient query strategy for integrated Remote Sensing and inventory (Spatial) Databases. | Ranga Raju Vatsavai, Thomas E. Burk, Shashi Shekhar, Mark H. Hansen |