Publications

2022

• Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, and Chandan K. Reddy, "ANTHEM: Attentive Hyperbolic Entity Model for Product Search", In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), Phoenix, AZ, February 2022. [pdf]
  

• Ming Zhu, Karthik Suresh, and Chandan K. Reddy, "Multilingual Code Snippets Training for Program Translation", In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Online, February 2022. [pdf]
  

• Tian Shi, Xuchao Zhang, Ping Wang, and Chandan K. Reddy, "Corpus-level and Concept-based Explanations for Interpretable Document Classification", ACM Transactions on Knowledge Discovery and Data Mining (TKDD), Vol.16, No.3, pp.48:1-17, June 2022. [pdf]
  

• Nurendra Choudhary, Charu C. Aggarwal, Karthik Subbian, and Chandan K. Reddy, "Self-supervised Short Text Modeling through Auxiliary Context Generation", ACM Transactions on Intelligent Systems and Technology (TIST), Vol.13, No.3, pp.1-21, June 2022. [pdf]
  

• Amirsina Torfi, Edward A. Fox, and Chandan K. Reddy, "Differentially Private Synthetic Medical Data Generation using Convolutional GANs", Information Sciences, Vol.586, pp.485-500, March 2022. [pdf]
  

• Sindhu Tipirneni, and Chandan K. Reddy, "Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series", ACM Transactions on Knowledge Discovery and Data Mining (TKDD), 2022. [pdf]
  

2021

• Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, and Chandan K. Reddy, "Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs", In Proceedings of the Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), Virtual Event, December 2021. [pdf]
  

• Amin Nayebi, Sindhu Tipirneni, Brandon Foreman, Jonathan Ratcliff, Chandan K Reddy, and Vignesh Subbian, "Recurrent Neural Network based Time-Series Modeling for Long-term Prognosis Following Acute Traumatic Brain Injury", In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA), Virtual Event, October 2021. [pdf]
  

• Ahmadreza Azizi, Ibrahim Asadullah Tahmid, Asim Waheed, Neal Mangaokar, Jiameng Pu, Mobin Javed, Chandan K. Reddy, and Bimal Viswanath, "T-Miner: A Generative Approach to Defend Against Trojan Attacks on Deep Text Models", USENIX Security, Vancouver, B.C., Canada, August 2021. [pdf]
  

• Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, and Yue Ning, "Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare", In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Virtual Event, August 2021. [pdf]
  

• Khoa D. Doan*, Saurav Manchanda*, Suchismit Mahapatra, and Chandan K. Reddy, "Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings", In Proceedings of the International ACM SIGIR conference on research and development in Information Retrieval (SIGIR), Virtual Event, July 2021. (* first two authors are equal contributors) [pdf]
  

• Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, and Chandan K. Reddy, "Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks", In Proceedings of The Web Conference (WWW), Online, April 2021. [pdf]
  

• Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, and Chandan K. Reddy, "Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs", In Proceedings of The Web Conference (WWW), Online, April 2021. [pdf]
  

• Tian Shi, Liuqing Li, Ping Wang, and Chandan K. Reddy, "A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection", In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Online, February 2021. [pdf]
  

• Dhruv Sharma, Sanjay Purushotham, and Chandan K Reddy, "MedFuseNet: An Attention-based Multimodal deep learning model for Visual Question Answering in the Medical Domain", Nature Scientific Reports, Vol.11, No.19826, October 2021. [pdf]
  

• Ping Wang, Tian Shi, and Chandan K. Reddy, "Tensor-based Temporal Multi-Task Survival Analysis", IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.33, No.9, pp.3311-3322, September 2021. [pdf]
  

• Tian Shi, Yaser Keneshloo, Naren Ramakrishnan, and Chandan K. Reddy, "Neural Abstractive Text Summarization with Sequence-to-Sequence Models", ACM / IMS Transactions on Data Science (TDS), Vol.2, No.1, pp.1-37, January 2021. [pdf]
  

• Sina Ehsani, Chandan K. Reddy, Brandon Foreman, Jonathan Ratcliff, and Vignesh Subbian, "Subspace Clustering of Physiological Data From Acute Traumatic Brain Injury Patients: Retrospective Analysis Based on the PROTECT III Trial", JMIR Biomedical Engineering, Vol.6, No.1, pp.e24698, January 2021. [pdf]
  

• Chang Lu, Chandan K. Reddy, and Yue Ning, "Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction", IEEE Transactions on Cybernetics, 2021. [pdf]
  

2020

• Jiameng Pu, Neal Mangaokar, Bolun Wang, Chandan K. Reddy, and Bimal Viswanath, "NoiseScope: Detecting Deepfake Images in a Blind Setting", In Proceedings of the Annual Computer Security Applications Conference (ACSAC), Online, December 2020. [pdf]
  

• Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, and Chandan K. Reddy, "Question Answering with Long Multiple-Span Answers", Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, November 2020. [pdf]
  

• Neal Mangaokar, Jiameng Pu, Parantapa Bhattacharya, Chandan K. Reddy, and Bimal Viswanath, "Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models", In Proceedings of the IEEE European Symposium on Security and Privacy (EuroS&P), Online, September 2020. [pdf]
  

• Ping Wang, Tian Shi, and Chandan K. Reddy, "Text-to-SQL Generation for Question Answering on Electronic Medical Records", In Proceedings of The Web Conference (WWW), Taipei, Taiwan, April 2020. [pdf]
  

• Khoa Doan, and Chandan K. Reddy, "Efficient Implicit Unsupervised Text Hashing using Adversarial Autoencoder", In Proceedings of The Web Conference (WWW), Taipei, Taiwan, April 2020. [pdf]
  

• Ming Zhu, Busra Celikkaya, Parminder Bhatia, and Chandan K. Reddy, "LATTE: Latent Type Modeling for Biomedical Entity Linking", In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), New York, NY, February 2020. [pdf]
  

• Aman Ahuja, Nikhil Rao, Sumeet Katariya, Karthik Subbian, and Chandan K Reddy, "Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms", In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), Houston, TX, February 2020. [pdf]
  

• Yaser Keneshloo, Tian Shi, Naren Ramakrishnan, and Chandan K. Reddy, "Deep Reinforcement Learning for Sequence-to-Sequence Models", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Vol.31, No.7, pp.2469-2489, July 2020. [pdf]
  

• Sina Dabiri, Nikola Marković, Kevin Heaslip, and Chandan K. Reddy, "A Deep Convolutional Neural Network based Approach for Vehicle Classification Using Large-Scale GPS Trajectory Data", Transportation Research Part C: Emerging Technologies (TRC), Vol.116, pp.102644, July 2020. [pdf]
  

• Sina Dabiri, Chang-Tien Lu, Kevin Heaslip, and Chandan K. Reddy, "Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data", IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.32, No.5, pp.1010-1023, May 2020. [pdf]
  

• Ting Hua, Chang-Tien Lu, Jaegul Choo, and Chandan K. Reddy, "Probabilistic Topic Modeling for Comparative Analysis of Document Collections", ACM Transactions on Knowledge Discovery and Data Mining (TKDD), Vol.14, No.2, pp.24:1-24:27, March 2020. [pdf]
  

2019

• Khoa D. Doan, Pranjul Yadav, and Chandan K. Reddy, "Adversarial Factorization Autoencoder for Look-alike Modeling", In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), Beijing, China, November 2019. [pdf]
  

• Tian Shi, Vineeth Rakesh, Suhang Wang, and Chandan K. Reddy, "Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts", In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), Beijing, China, November 2019. [pdf]
  

• Tian Shi, Ping Wang, and Chandan K. Reddy, "LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization", In Proceedings of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2019), Minneapolis, MN, June 2019. (demo) [pdf]
  

• Ming Zhu, Aman Ahuja, Wei Wei, and Chandan K. Reddy, "A Hierarchical Attention Retrieval Model for Healthcare Question Answering", In Proceedings of The Web Conference (WWW), San Francisco, CA, May 2019. [pdf]
  

• Yaser Keneshloo, Naren Ramakrishnan, and Chandan K. Reddy, "Deep Transfer Reinforcement Learning for Text Summarization", In Proceedings of SIAM International Conference on Data Mining (SDM), Calgary, Canada, May 2019. [pdf]
  

• Xuan Zhang, Zhilei Qiao, Aman Ahuja, Weiguo Fan, Edward Fox, and Chandan K. Reddy, "Discovering Product Defects and Solutions from Online User Generated Contents", In Proceedings of The Web Conference (WWW), San Francisco, CA, May 2019. [pdf]
  

• Aman Ahuja, Ashish Baghudana, Edward Fox, Wei Lu, and Chandan K. Reddy, "Spatio-Temporal Event Detection from Multiple Data Sources", In Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Macau, China, April 2019. [pdf]
  

• Khoa Doan, Guolei Yang, and Chandan K Reddy, "Attentive Spatio-Temporal Neural Model for Successive Point of Interest Recommendation", In Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Macau, China, April 2019. [pdf]
  

• Ping Wang, Yan Li and Chandan K. Reddy, "Machine Learning for Survival Analysis: A Survey", ACM Computing Surveys, Vol.51, No.6, pp.110, February 2019. [pdf]
  

2018

• Guolei Yang, Ying Cai and Chandan K. Reddy, "Recurrent Spatio-Temporal Point Process for Check-in Time Prediction", In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), Torino, Italy, October 2018. [pdf]
  

• Guolei Yang, Ying Cai and Chandan K. Reddy, "Spatio-Temporal Check-in Time Prediction with Recurrent Neural Network based Survival Analysis", In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, July 2018. [pdf]
  

• Ting Hua, Chandan K. Reddy, Lei Zhang, Lijing Wang, Liang Zhao, Chang-Tien Lu and Naren Ramakrishnan, "Social Media based Simulation Models for Understanding Disease Dynamics", In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, July 2018. [pdf]
  

• Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz and Naren Ramakrishnan, "STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting", In Proceedings of SIAM International Conference on Data Mining (SDM), San Diego, CA, May 2018. [pdf]
  

• Tian Shi, Kyeongpil Kang, Jaegul Choo and Chandan K. Reddy, "Short-Text Topic Modeling via Non-negative Matrix Factorization Enriched with Local Word-Context Correlations", In Proceedings of the International Conference on World Wide Web (WWW), Lyon, France, April 2018. [pdf]
  

• Vineeth Rakesh, Weicong Ding, Aman Ahuja, Nikhil Rao, Yifan Sun and Chandan K. Reddy, "A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews", In Proceedings of the International Conference on World Wide Web (WWW), Lyon, France, April 2018. [pdf]
  

• Vachik S. Dave, Mohammad Al Hasan, Baichuan Zhang, and Chandan K. Reddy, "Predicting Interval Time for Reciprocal Link Creation using Survival Analysis", Social Network Analysis and Mining (SNAM), Vol.8, No.1, pp.16, December 2018. [pdf]
  

• Sakyajit Bhattacharya, Vijay Huddar, Vaibhav Rajan, and Chandan K. Reddy, "A Dual Boundary Classifier for Predicting Acute Hypotensive Episodes in Critical Care", PLOS One, Vol.13, No.2, pp.e0193259, February 2018. [pdf]
  

• Sangho Suh, Sungbok Shin, Joonseok Lee, Chandan K. Reddy and Jaegul Choo, "Localized User-Driven Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization", Knowledge and Information Systems (KAIS), Vol.56, No.3, pp.503-531, September 2018. [pdf] Invited Paper
  

2017

• Aman Ahuja, Wei Wei, Wei Lu, Kathleen M. Carley and Chandan K. Reddy, "A Probabilistic Geographical Aspect-Opinion Model for Geo-tagged Microblogs", In Proceedings of the IEEE International Conference on Data Mining (ICDM), New Orleans, LA, November 2017. [pdf]
  

• Sangho Suh, Jaegul Choo, Joonseok Lee, and Chandan K. Reddy, "Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization", In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 2017. [pdf]
  

• Abhishek Sengupta, Prathosh AP, Satya Narayan Shukla, Vaibhav Rajan, and Chandan K Reddy, "Prediction and Imputation in Irregularly Sampled Clinical Time Series Data using Hierarchical Linear Dynamical Models", In Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), JeJu Island, South Korea, July 2017. [pdf]
  

• Vachik S. Dave, Mohammad Al Hasan, and Chandan K. Reddy, "How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation", In Proceedings of International AAAI Conference on Web and Social Media (ICWSM), Montréal, Canada, May 2017. [pdf]
  

• Vineeth Rakesh, Niranjan Jadhav, Alexander Kotov, and Chandan K. Reddy, "Probabilistic Social Sequential Model for Tour Recommendation", In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), Cambridge, UK, February 2017. [pdf]
  

• Hannah Kim, Jaegul Choo, Changhyun Lee, Hanseung Lee, Chandan K. Reddy, and Haesun Park, "PIVE: Per-Iteration Visualization Environment for Real-time Interactions with Dimension Reduction and Clustering", In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, February 2017. [pdf]
  

• Bhanukiran Vinzamuri, Yan Li and Chandan K. Reddy, "Pre-Processing Censored Survival Data Using Inverse Covariance Matrix Based Calibration", IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.29, No.10, pp.2111-2124, October 2017. [pdf]
  

2016

• Sangho Suh, Jaegul Choo, Joonseok Lee, and Chandan K. Reddy, "Boosted L-EnsNMF: Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization", In Proceedings of the IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, December 2016. Best Student Paper Award [pdf]
  

• Yan Li, Lu Wang, Jie Wang, Jieping Ye, and Chandan K. Reddy, "Transfer Learning for Survival Analysis via Efficient L2,1-norm Regularized Cox Regression", In Proceedings of the IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, December 2016. [pdf]
  

• Bhanukiran Vinzamuri, Karthik Padthe, and Chandan K. Reddy, "Feature Grouping using Weighted L1-norm for High-Dimensional Data", In Proceedings of the IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, December 2016. [pdf]
  

• Ping Wang, Karthik K. Padthe, Bhanukiran Vinzamuri, and Chandan K. Reddy, "CRISP: Consensus Regularized Selection based Prediction", In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), Indianapolis, IN, October 2016. [pdf]
  

• Sattar Ameri, Mahtab J. Fard, Ratna B. Chinnam and Chandan K. Reddy, "Survival Analysis based Framework for Early Prediction of Student Dropouts", In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), Indianapolis, IN, October 2016. [pdf]
  

• Yan Li, Jie Wang, Jieping Ye and Chandan K. Reddy, "A Multi-Task Learning Formulation for Survival Analysis", In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), San Francisco, CA, August 2016. [pdf]
  

• Yan Li, Kevin Xu, and Chandan K. Reddy, "Regularized Parametric Regression for High-dimensional Survival Analysis", In Proceedings of SIAM International Conference on Data Mining (SDM), Miami, FL, May 2016. [pdf]
  

• Yan Li, Bhanukiran Vinzamuri, and Chandan K. Reddy, "Regularized Weighted Linear Regression for High-dimensional Censored Data", In Proceedings of SIAM International Conference on Data Mining (SDM), Miami, FL, May 2016. [pdf]
  

• Mahtab J. Fard, Sanjay Chawla, and Chandan K. Reddy, "Early-Stage Event Prediction for Longitudinal Data", In Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Auckland, New Zealand, April 2016. [pdf]
  

• Vineeth Rakesh, Wang-Chien Lee, and Chandan K. Reddy, "Probabilistic Group Recommendation Model for Crowdfunding Domains", In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), San Francisco, CA, February 2016. [pdf]
  

• Yan Li, Vineeth Rakesh, and Chandan K. Reddy, "Project Success Prediction in Crowdfunding Environments", In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), San Francisco, CA, February 2016. [pdf]
  

• Mahtab J. Fard, Ping Wang, Sanjay Chawla, and Chandan K. Reddy, "A Bayesian Perspective on Early Stage Event Prediction in Longitudinal Data", IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.28, No.12, pp.3126-3139, December 2016. [pdf]
  

• Samir Al-Stouhi and Chandan K. Reddy, "Transfer Learning for Class Imbalance Problems with Inadequate Data", Knowledge and Information Systems (KAIS), Vol.48, No.1, pp.201-228, July 2016. [pdf]
  

• Jayanta K. Dutta, Bonny Banerjee and Chandan K. Reddy, "RODS: Rarity based Outlier Detection in a Sparse Coding Framework", IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.28, No.2, pp.483-495, February 2016. [pdf]
  

• Yan Li, Changxin Bai, and Chandan K. Reddy, "A Distributed Ensemble Approach for Mining Healthcare Data under Privacy Constraints", Information Sciences, Vol.330, pp.245-259, February 2016. [pdf]
  

• Vijay Huddar, Bapu Desiraju, Vaibhav Rajan, Sakyajit Bhattacharya, Shourya Roy, and Chandan K. Reddy, "Predicting Complications in Critical Care using Heterogeneous Clinical Data", IEEE Access, Vol.4, pp.7988-8001, 2016. [pdf] Invited Paper
  

2015

• Hannah Kim, Jaegul Choo, Jingu Kim, Chandan K. Reddy, and Haesun Park, "Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization", In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Sydney, Australia, August 2015. [pdf]
  

• Vineeth Rakesh, Jaegul Choo, and Chandan K Reddy, "Project Recommendation using Heterogeneous Traits in Crowdfunding", In Proceedings of International AAAI Conference on Web and Social Media (ICWSM), Oxford, UK, May 2015. [pdf]
  

• Alexander Kotov, Vineeth Rakesh, Eugene Agichtein and Chandan K. Reddy, "Geographical Latent Variable Models for Microblog Retrieval", In Proceedings of the European Conference on Information Retrieval (ECIR), Vienna, Austria, March 2015. [pdf]
  

• Jaegul Choo, Changhyun Lee, Chandan K. Reddy, and Haesun Park, "Weakly Supervised Nonnegative Matrix Factorization for User-Driven Clustering", Data Mining and Knowledge Discovery (DMKD), Vol.29, No.6, pp.1598-1621, November 2015. [pdf]
  

• Badri Padhukasahasram, Chandan K. Reddy, Albert M. Levin, Esteban G. Burchard and L. Keoki Williams, "Powerful Tests for Multi-Marker Association Analysis Using Ensemble Learning", PLoS ONE, Vol.10, No.11, pp.e0143489, November 2015. [pdf]
  

• Faris Alqadah, Chandan K. Reddy, Junling Hu and Hatim F. Alqadah , "Biclustering Neighborhood-based Collaborative Filtering Method for Top-n Recommender Systems", Knowledge and Information Systems (KAIS), Vol.44, No.2, pp.475-491, August 2015. [pdf]
  

• Yan Li, Bhanukiran Vinzamuri, and Chandan K. Reddy, "Constrained Elastic Net based Knowledge Transfer for Healthcare Information Exchange", Data Mining and Knowledge Discovery (DMKD), Vol.29, No.4, pp.1094-1112, July 2015. [pdf]
  

• Badri Padhukasahasram, Chandan K. Reddy, Yan Li, and David E. Lanfear, "Joint Impact of Clinical and Behavioral Variables on the Risk of Unplanned Readmission and Death after a Heart Failure Hospitalization", PLoS ONE, Vol.10, No.6, pp.e0129553, June 2015. [pdf]
  

• Chandan K. Reddy and Mohammad S. Aziz , "Predicting Gene Functions from Multiple Biological Sources using Novel Ensemble Methods", International Journal of Data Mining and Bioinformatics (IJDMB), Vol.12, No.2, pp.184-206, May 2015. [pdf]
  

• Adel Alaeddini, Kai Yang, Pamela Reeves, and Chandan K. Reddy, "A Hybrid Prediction Model for No-shows and Cancellations of Outpatient Appointments", IIE Transactions on Healthcare Systems Engineering (THSE), Vol.5, No.1, pp.14-32, March 2015. [pdf]
  

• Hannah Kim, Jaegul Choo, Chandan K. Reddy, and Haesun Park, "Doubly Supervised Embedding based on Class Labels and Intrinsic Clusters for High-dimensional Data Visualization", Neurocomputing, Vol.150, pp.570-582, February 2015. [pdf]
  

• Chandan K. Reddy and Charu C. Aggarwal (editors), "Healthcare Data Analytics", Chapman and Hall/CRC, 2015. [pdf] [e-book ] [Sample Chapters - Intro, EHR, Prediction, CDSS.]
  

2014

• Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Chandan K. Reddy, Barry L. Drake, and Haesun Park, "PIVE: Per-Iteration Visualization Environment for Supporting Real-time Interactions with Computational Methods", In Proceedings of IEEE Conference on Visual Analytics Science and Technology (VAST), Paris, France, November 2014. Best Poster Award [pdf]
  

• Bhanukiran Vinzamuri, Yan Li and Chandan K. Reddy, "Active Learning Based Survival Regression for Censored Data", In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), Shanghai, China, November 2014. [pdf]
  

• Vineeth Rakesh, Dilpreet Singh, Bhanukiran Vinzamuri, and Chandan K Reddy, "Personalized Recommendation of Twitter Lists using Content and Network Information", In Proceedings of International AAAI Conference on Weblogs and Social Media (ICWSM), Ann Arbor, MI, June 2014. [pdf]
  

• Samir Al-Stouhi and Chandan K. Reddy, "Multi-Task Clustering using Constrained Symmetric Non-Negative Matrix Factorization", In Proceedings of SIAM International Conference on Data Mining (SDM), Philadelphia, PA, April 2014. [pdf]
  

• Omar Odibat and Chandan K. Reddy, "Efficient Mining of Discriminative Co-clusters from Gene Expression Data", Knowledge and Information Systems (KAIS), Vol.41, No.3, pp.667-696, December 2014. [pdf]
  

• Dilpreet Singh and Chandan K. Reddy, "A Survey on Platforms for Big Data Analytics", Journal of Big Data, Vol.2, No.8, pp.1-20, October 2014. [pdf]
  

2013

• Bhanukiran Vinzamuri and Chandan K. Reddy, "Cox Regression with Correlation based Regularization for Electronic Health Records", In Proceedings of the IEEE International Conference on Data Mining (ICDM), Dallas, TX, December 2013. [pdf]
  

• Vineeth Rakesh, Chandan K. Reddy, Dilpreet Singh and Ramachandran MS, "Location-Specific Tweet Detection and Topic Summarization in Twitter", In Proceedings of the IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), Niagara Falls, Canada, August 2013. [pdf]
  

• Jaegul Choo, Changhyun Lee, Chandan K. Reddy, Haesun Park, "UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization", IEEE Transactions on Visualization and Computer Graphics (TVCG), Vol.19, No.12, pp.1992 - 2001, December 2013. [pdf]
  

• Asfar S. Azmi, Aliccia Bollig-Fischer, Bin Bao, Bum-Joon Park, Sun-Hye Lee, Gyu Yong-Song, Gregory Dyson, Chandan K. Reddy, Fazlul H. Sarkar, and Ramzi M. Mohammad. , "Systems Analysis Reveals a Transcriptional Reversal of the Mesenchymal Phenotype induced by SNAIL-inhibitor GN-25", BMC Systems Biology, Vol.7, No.1, pp.85, September 2013. [pdf]
  

• Chandan K. Reddy and Cristopher C. Yang , "Introduction to the Special Section on Intelligent Systems for Health Informatics", ACM Transactions on Intelligent Systems and Technology (TIST), Vol.4, No.4, pp.62:1--62:3, September 2013. [pdf]
  

• Charu C. Aggarwal and Chandan K. Reddy (editors), "Data Clustering: Algorithms and Applications", CRC Press, 2013. [Sample Chapters - Kmeans, Biology.]
  

2012

• Samir Al-Stouhi, Chandan K. Reddy, and David E. Lanfear, "Label Space Transfer Learning", IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Athens, Greece, November 2012. [pdf]
  

• Faris Alqadah, Joel S. Bader, Rajul Anand and Chandan K. Reddy, "Query-based Biclustering using Formal Concept Analysis", In Proceedings of SIAM International Conference on Data Mining (SDM), Anaheim, CA, April 2012. Best Paper Candidate (10 out of 362 submissions) [pdf]
  

• Noor Alaydie, Chandan K. Reddy and Farshad Fotouhi, "Exploiting Label Dependency for Hierarchical Multi-label Classification", In Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Kaula Lumpur, Malaysia, 2012. [pdf]
  

• Indranil Palit and Chandan K. Reddy, "Scalable and Parallel Boosting with MapReduce", IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.24, No.10, pp.1904-1916, October 2012. [pdf]
  

• Omar Odibat and Chandan K. Reddy, "Ranking Differential Hubs in Gene Co-expression Networks", Journal of Bioinformatics and Computational Biology (JBCB), Vol.10, No.1, pp.1240002, January 2012. [pdf]
  

• Gerard Miller, Melissa Weatherwax, Timothy Gardinier, Naoki Abe, Prem Melville, Cezar Pendus, Chandan K. Reddy, David Jensen, Vince Thomas, James Bennett, Gary Anderson, Brent Cooley, "Tax Collections Optimization for New York State", Interfaces, Vol.42, No.1, pp.74-84, January 2012. [pdf] Franz Edelman Special issue
  

2011

• Samir Al-Stouhi and Chandan K. Reddy, "Adaptive Boosting for Transfer Learning using Dynamic Updates", In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) , Athens, Greece, September 2011. [pdf]
  

• Rajul Anand and Chandan K. Reddy, "Constrained Logistic Regression for Discriminative Pattern Mining", In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Athens, Greece, September 2011. [pdf]
  

• Omar Odibat and Chandan K. Reddy, "Mining Differential Hubs in Homogenous Networks", In Proceedings of SIGKDD workshop on Mining and Learning with Graphs (MLG), San Diego, CA, August 2011. [pdf]
  

• Omar Odibat and Chandan K. Reddy, "Ranking Differential Genes in Co-expression Networks", In Proceedings of the ACM Conference on Bioinformatics and Computational Biology (BCB), Chicago, IL, August 2011. [pdf]
  

• Noor Alaydie, Chandan K. Reddy and Farshad Fotouhi, "A Bayesian Integration Model for Improved Gene Functional Inference from Heterogeneous Data Sources", In Proceedings of the ACM Conference on Bioinformatics and Computational Biology (BCB), Chicago, IL, August 2011. [pdf]
  

• Rajul Anand and Chandan K. Reddy, "Graph-based Clustering with Constraints", In Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Shenzhen,China, May 2011. [pdf]
  

• Omar Odibat and Chandan K. Reddy, "A Generalized Framework for Mining Arbitrarily Positioned Overlapping Co-clusters", In Proceedings of the SIAM International Conference on Data Mining (SDM), Phoenix, AZ, April 2011. [pdf]
  

• Chandan K. Reddy and Jin-Hyeong Park, "Multi-resolution Boosting for Classification and Regression Problems", Knowledge and Information Systems (KAIS), Vol.29, No.2, pp.435-456, November 2011. [pdf]
  

• Adel Alaeddini, Kai Yang, Chandan K Reddy and Susan Yu, "A Probabilistic Model for Predicting the Probability of No-Show in Hospital Appointments", Health Care Management Science (HCMS), Vol.14, No.2, pp.146-157, June 2011. [pdf]
  

2010

• Indranil Palit and Chandan K. Reddy, "Parallelized Boosting with Map-Reduce", In Proceedings of the ICDM 2010 Workshop on Large-scale Analytics for Complex Instrumented Systems (LACIS)., Sydney, Australia, December 2010. [pdf]
  

• Mohammad S. Aziz and Chandan K. Reddy, "Robust Prediction from Multiple Heterogeneous Data Sources with Partial Information", In Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM), Toronto, Canada, October 2010. short paper [pdf]
  

• Omar Odibat, Chandan K. Reddy and Craig N. Giroux, "Differential Biclustering for Gene Expression Analysis", In Proceedings of the ACM Conference on Bioinformatics and Computational Biology (BCB), Niagara Falls, NY, August 2010. [pdf]
  

• Noor Alaydie, Chandan K. Reddy and Farshad Fotouhi, "Hierarchical Multi-label Boosting for Gene Function Prediction", In Proceedings of the International Conference on Computational Systems Bioinformatics (CSB), Stanford, CA, August 2010. [pdf]
  

• Naoki Abe, Prem Melville, Cezar Pendus, Chandan K. Reddy , David L. Jensen et al., "Optimizing Debt Collections Using Constrained Reinforcement Learning", In Proceedings of the ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (KDD), Washington D.C., July 2010. Best Application Paper Award [pdf]
  

• Mohammad Aziz and Chandan K. Reddy , "A Robust Seedless Algorithm for Correlation Clustering", In Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Hyderabad, India, June 2010. [pdf]
  

• Jaegul Choo, Chandan K. Reddy, Hanseung Lee and Haesun Park, "p-ISOMAP: An Efficient Parametric Update for ISOMAP for Visual Analytics", In Proceedings of the SIAM International Conference on Data Mining (SDM), Columbus, OH, April 2010. [pdf]
  

• Chandan K. Reddy and Mohammad S. Aziz, "Modeling Local Non-linear Correlations using Subspace Principal Curves", Statistical Analysis and Data Mining (SADM), Vol.3, No.5, pp.332-349, October 2010. [pdf]
  

• Chandan K. Reddy and Bala Rajaratnam, "Learning Mixture Models via Component-wise Parameter Smoothing", Computational Statistics and Data Analysis (CSDA), Vol.54, No.3, pp.732-749, March 2010. [pdf]
  

• Colin A. Gross, Chandan K. Reddy and Frank B. Dazzo, "CMEIAS Color Segmentation: An Improved Computing Technology To Process Color Images for Quantitative Microbial Ecology Studies at Single-Cell Resolution", Microbial Ecology (ME), Vol.59, No.2, pp.400-414, February 2010. [pdf]
  

2009

• Indranil Palit, Chandan K. Reddy and Kendra Schwartz, "Differential Predictive Modeling for Racial Disparities in Breast Cancer", In Proceedings of IEEE International Conference on Bioinformatics and BioMedicine (BIBM), Washington DC, November 2009. [pdf]
  

• Snehal Pokharkar and Chandan K. Reddy , " Identifying Information-Rich Subspace Trends in High-Dimensional Data", In Proceedings of SIAM International Conference on Data Mining (SDM), Sparks, NV, April 2009. [pdf]
  

• Chandan K. Reddy and Jin-Hyeong Park, "Multi-Resolution Boosting for Classification and Regression", In Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Bangkok, Thailand, April 2009. [pdf]
  

• Yazhene Krishnaraj and Chandan K. Reddy "Protein Fold Recognition using Boosting algorithms", in Biological Data Mining , Jake Chen and Stefano Lonardi (eds.), Chapman & Hall/CRC Press, 2009.
  
  

• Hsiao-Dong Chiang, Jeng-Huei Chen and Chandan K. Reddy "Trust-Tech-Based Global Optimization Methodology for Nonlinear Programming", in Lectures on Global Optimization , Panos M. Pardalos and Thomas F. Coleman (eds.), American Mathematical Society, 2009.
  
  

2008

• Chandan K. Reddy and Bala Rajaratnam, "Component-wise Parameter Smoothing for Learning Mixture Models", In Proceedings of the International Conference on Pattern Recognition (ICPR), Tampa, FL, December 2008. [pdf]
  

• Yazhene Krishnaraj and Chandan K. Reddy, "Boosting methods for Protein Fold Recognition: An Empirical Comparison", In Proceedings of IEEE International Conference on BioInformatics and BioMedicine (BIBM) , Philadelphia, PA, November 2008. [pdf]
  

• Chandan K. Reddy, Snehal Pokharkar and Tin Kam Ho, "Generating Hypotheses of Trends in High-Dimensional Data Skeletons", In Proceedings of IEEE Symposium on Visual Analytics Science and Technology (VAST), Columbus, OH, October 2008. [pdf]
  

• Chandan K. Reddy and Fahima A. Bhuyan, "Retrieval and Ranking of Biomedical Images using Boosted Haar Features", In Proceedings of International Conference on BioInformatics and BioEngineering (BIBE), Athens, Greece, October 2008. [pdf]
  

• Chandan K. Reddy, Hsiao-Dong Chiang and Bala Rajaratnam, "TRUST-TECH based Expectation Maximization for Learning Finite Mixture Models", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol.30 , No.7, pp.1146-1157, July 2008. [pdf]
  

• Chandan K. Reddy and Bala Rajaratnam "Theory and Practice of Expectation Maximization Algorithm", in Encyclopedia of Data Warehousing and Mining , 2nd Edition, 2008.
  
  

2007

• Jin-Hyeong Park and Chandan K. Reddy, "Scale-space based boosting for weak regressors", In Proceedings of European Conference on Machine Learning, (ECML), Warsaw, Poland, September 2007. [pdf]
  

• Mary Helander, Rick Lawrence, Yan Liu, Claudia Perlich, Chandan Reddy and Saharon Rosset, "Looking for Great Ideas: Analyzing the Innovation Jam", In Proceedings of the ACM SIGKDD Workshop on Web Mining and Social Network Analysis (WEBSNAKDD), San Jose, CA, August 2007. [pdf]
  

• Hsiao-Dong Chiang and Chandan K. Reddy , "TRUST-TECH based Neural Network Training", International Joint Conference on Neural Networks (IJCNN), Orlando, FL, August 2007. [pdf]
  

• Chandan K. Reddy, Yao-Chung Weng and Hsiao-Dong Chiang "Neighborhood Profile Search for Motif Refinement", in Machine Learning for Bioinformatics , Yan-Qing Zhang and Jagath C. Rajapakse (eds.), John Wiley & Sons, 2007.
  
  

2006

• Chandan K. Reddy, Hsiao-Dong Chiang and Bala Rajarathnam, "Stability Region based Expectation Maximization for Model-based Clustering", In proceedings of the IEEE International Conference on Data Mining (ICDM), Hong Kong, December 2006. [pdf]
  

• Chandan K. Reddy, Yao-Chung Weng and Hsiao-Dong Chiang, "Motif Refinement using Hybrid Expectation Maximization based Neighborhood profile Search", In Proceedings of the 6th ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD), August 2006. [pdf]
  

• Chandan K. Reddy, Yao-Chung Weng and Hsiao-Dong Chiang, "Refining Motifs by improving Information Content Scores using Neighborhood Profile Search", BMC Algorithms for Molecular Biology, Vol.1, No.23, pp.1-14, November 2006. [pdf]
  

• Chandan K. Reddy and Hsiao-Dong Chiang, "A Stability Boundary based Method for Finding Saddle Points on Potential Energy Surfaces", Journal of Computational Biology, Vol.13, No.3, pp.745-766, April 2006. [pdf]