| 2026 | ACL | The Personalization Trap: How User Memory Alters Emotional Reasoning in LLMs. | Xi Fang, Weijie Xu, Yuchong Zhang, Scott Nickleach, Stephanie Eckman, Chandan K. Reddy |
| 2026 | ACL | MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Training. | Taicheng Guo, Hai Wang, Chaochun Liu, Mohsen Golalikhani, Xin Chen, Xiangliang Zhang, Chandan K. Reddy |
| 2025 | AAAI | Evolutionary Large Language Model for Automated Feature Transformation. | Nanxu Gong, Chandan K. Reddy, Wangyang Ying, Haifeng Chen, Yanjie Fu |
| 2025 | AAAI | Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges. | Chandan K. Reddy, Parshin Shojaee |
| 2025 | ACL | Mitigating Selection Bias with Node Pruning and Auxiliary Options. | Hyeong Kyu Choi, Weijie Xu, Chi Xue, Stephanie Eckman, Chandan K. Reddy |
| 2025 | EMNLP | Sycophancy Mitigation Through Reinforcement Learning with Uncertainty-Aware Adaptive Reasoning Trajectories. | Mohammad Beigi, Ying Shen, Parshin Shojaee, Qifan Wang, Zichao Wang, Chandan K. Reddy, Ming Jin, Lifu Huang |
| 2025 | ICLR | LLM-SR: Scientific Equation Discovery via Programming with Large Language Models. | Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani, Chandan K. Reddy |
| 2025 | ICML | LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models. | Parshin Shojaee, Ngoc-Hieu Nguyen, Kazem Meidani, Amir Barati Farimani, Khoa D. Doan, Chandan K. Reddy |
| 2025 | KDD | KDD Workshop on Evaluation and Trustworthiness of Agentic and Generative AI. | Yuan Ling, Shujing Dong, Zheng Chen, Yarong Feng, Sadid Hasan, George Karypis, Chandan K. Reddy |
| 2025 | NAACL | H-STAR: LLM-driven Hybrid SQL-Text Adaptive Reasoning on Tables. | Nikhil Abhyankar, Vivek Gupta, Dan Roth, Chandan K. Reddy |
| 2024 | ACL | ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation. | Akshita Jha, Vinodkumar Prabhakaran, Remi Denton, Sarah Laszlo, Shachi Dave, Rida Qadri, Chandan K. Reddy, Sunipa Dev |
| 2024 | ACL | Synthesizing Conversations from Unlabeled Documents using Automatic Response Segmentation. | Fanyou Wu, Weijie Xu, Chandan K. Reddy, Srinivasan Sengamedu |
| 2024 | ICLR | SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training. | Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, Amir Barati Farimani |
| 2024 | KDD | KDD workshop on Evaluation and Trustworthiness of Generative AI Models. | Yuan Ling, Shujing Dong, Yarong Feng, Zongyi Joe Liu, George Karypis, Chandan K. Reddy |
| 2024 | WWW | An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce. | Nurendra Choudhary, Edward W. Huang, Karthik Subbian, Chandan K. Reddy |
| 2023 | AAAI | CodeAttack: Code-Based Adversarial Attacks for Pre-trained Programming Language Models. | Akshita Jha, Chandan K. Reddy |
| 2023 | ACL | SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models. | Akshita Jha, Aida Mostafazadeh Davani, Chandan K. Reddy, Shachi Dave, Vinodkumar Prabhakaran, Sunipa Dev |
| 2023 | EACL | Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis. | Akshita Jha, Adithya Samavedhi, Vineeth Rakesh, Jaideep Chandrashekar, Chandan K. Reddy |
| 2023 | IJCAI | A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks. | Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K. Reddy |
| 2023 | KDD | International Workshop on Multimodal Learning - 2023 Theme: Multimodal Learning with Foundation Models. | Yuan Ling, Fanyou Wu, Shujing Dong, Yarong Feng, George Karypis, Chandan K. Reddy |
| 2022 | AAAI | Multilingual Code Snippets Training for Program Translation. | Ming Zhu, Karthik Suresh, Chandan K. Reddy |
| 2022 | ACCV | Unified Energy-Based Generative Network for Supervised Image Hashing. | Khoa D. Doan, Sarkhan Badirli, Chandan K. Reddy |
| 2022 | AMIA | An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury. | Amin Nayebi, Sindhu Tipirneni, Brandon Foreman, Chandan K. Reddy, Vignesh Subbian |
| 2022 | KDD | Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance. | Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Chandan K. Reddy |
| 2022 | KDD | Hyperbolic Neural Networks: Theory, Architectures and Applications. | Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy |
| 2022 | WWW | Accepted Tutorials at The Web Conference 2022. | Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lyu, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He |
| 2022 | WWW | GraphZoo: A Development Toolkit for Graph Neural Networks with Hyperbolic Geometries. | Anoushka Vyas, Nurendra Choudhary, Mehrdad Khatir, Chandan K. Reddy |
| 2022 | WSDM | ANTHEM: Attentive Hyperbolic Entity Model for Product Search. | Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy |
| 2021 | AAAI | A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection. | Tian Shi, Liuqing Li, Ping Wang, Chandan K. Reddy |
| 2021 | AMIA | Tracking the Evolution of COVID-19 via Temporal Comorbidity Analysis from Multi-Modal Data. | Sutanay Choudhury, Khushbu Agarwal, Colby Ham, Pritam Mukherjee, Siyi Tang, Sindhu Tipirneni, Veysel Kocaman, Suzanne Tamang, Robert Rallo, Chandan K. Reddy |
| 2021 | AMIA | Recurrent Neural Network based Time-Series Modeling for Long-term Prognosis Following Acute Traumatic Brain Injury. | Amin Nayebi, Sindhu Tipirneni, Brandon Foreman, Jonathan J. Ratcliff, Chandan K. Reddy, Vignesh Subbian |
| 2021 | IJCAI | Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare. | Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning |
| 2021 | KDD | Workshop on Data-Efficient Machine Learning (DeMaL). | Sumeet Katariya, Nikhil Rao, Chandan K. Reddy |
| 2021 | WWW | Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs. | Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy |
| 2021 | WWW | Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks. | Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, Chandan K. Reddy |
| 2021 | SIGIR | Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings. | Khoa D. Doan, Saurav Manchanda, Suchismit Mahapatra, Chandan K. Reddy |
| 2020 | AAAI | LATTE: Latent Type Modeling for Biomedical Entity Linking. | Ming Zhu, Busra Celikkaya, Parminder Bhatia, Chandan K. Reddy |
| 2020 | ACSAC | NoiseScope: Detecting Deepfake Images in a Blind Setting. | Jiameng Pu, Neal Mangaokar, Bolun Wang, Chandan K. Reddy, Bimal Viswanath |
| 2020 | EMNLP | Question Answering with Long Multiple-Span Answers. | Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, Chandan K. Reddy |
| 2020 | WWW | Efficient Implicit Unsupervised Text Hashing using Adversarial Autoencoder. | Khoa D. Doan, Chandan K. Reddy |
| 2020 | WWW | Text-to-SQL Generation for Question Answering on Electronic Medical Records. | Ping Wang, Tian Shi, Chandan K. Reddy |
| 2020 | WSDM | Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms. | Aman Ahuja, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy |
| 2019 | CIKM | Adversarial Factorization Autoencoder for Look-alike Modeling. | Khoa D. Doan, Pranjul Yadav, Chandan K. Reddy |
| 2019 | CIKM | Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts. | Tian Shi, Vineeth Rakesh, Suhang Wang, Chandan K. Reddy |
| 2019 | MICCAI | Active Learning Technique for Multimodal Brain Tumor Segmentation Using Limited Labeled Images. | Dhruv Sharma, Zahil Shanis, Chandan K. Reddy, Samuel Gerber, Andinet Enquobahrie |
| 2019 | NAACL | LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization. | Tian Shi, Ping Wang, Chandan K. Reddy |
| 2019 | PAKDD | Spatio-Temporal Event Detection from Multiple Data Sources. | Aman Ahuja, Ashish Baghudana, Wei Lu, Edward A. Fox, Chandan K. Reddy |
| 2019 | PAKDD | An Attentive Spatio-Temporal Neural Model for Successive Point of Interest Recommendation. | Khoa D. Doan, Guolei Yang, Chandan K. Reddy |
| 2019 | WWW | Discovering Product Defects and Solutions from Online User Generated Contents. | Xuan Zhang, Zhilei Qiao, Aman Ahuja, Weiguo Fan, Edward A. Fox, Chandan K. Reddy |
| 2019 | WWW | A Hierarchical Attention Retrieval Model for Healthcare Question Answering. | Ming Zhu, Aman Ahuja, Wei Wei, Chandan K. Reddy |
| 2019 | SDM | Deep Transfer Reinforcement Learning for Text Summarization. | Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy |
| 2018 | CIKM | Recurrent Spatio-Temporal Point Process for Check-in Time Prediction. | Guolei Yang, Ying Cai, Chandan K. Reddy |
| 2018 | IJCAI | Social Media based Simulation Models for Understanding Disease Dynamics. | Ting Hua, Chandan K. Reddy, Lei Zhang, Lijing Wang, Liang Zhao, Chang-Tien Lu, Naren Ramakrishnan |
| 2018 | IJCAI | Spatio-Temporal Check-in Time Prediction with Recurrent Neural Network based Survival Analysis. | Guolei Yang, Ying Cai, Chandan K. Reddy |
| 2018 | WWW | A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews. | Vineeth Rakesh, Weicong Ding, Aman Ahuja, Nikhil Rao, Yifan Sun, Chandan K. Reddy |
| 2018 | WWW | Short-Text Topic Modeling via Non-negative Matrix Factorization Enriched with Local Word-Context Correlations. | Tian Shi, Kyeongpil Kang, Jaegul Choo, Chandan K. Reddy |
| 2018 | SDM | STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. | Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan |
| 2017 | AAAI | PIVE: Per-Iteration Visualization Environment for Real-Time Interactions with Dimension Reduction and Clustering. | Hannah Kim, Jaegul Choo, Changhyun Lee, Hanseung Lee, Chandan K. Reddy, Haesun Park |
| 2017 | ICDM | A Probabilistic Geographical Aspect-Opinion Model for Geo-Tagged Microblogs. | Aman Ahuja, Wei Wei, Wei Lu, Kathleen M. Carley, Chandan K. Reddy |
| 2017 | IJCAI | Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization. | Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan K. Reddy |
| 2017 | ICWSM | How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation. | Vachik S. Dave, Mohammad Al Hasan, Chandan K. Reddy |
| 2017 | WSDM | Probabilistic Social Sequential Model for Tour Recommendation. | Vineeth Rakesh, Niranjan Jadhav, Alexander Kotov, Chandan K. Reddy |
| 2016 | CIKM | Survival Analysis based Framework for Early Prediction of Student Dropouts. | Sattar Ameri, Mahtab Jahanbani Fard, Ratna Babu Chinnam, Chandan K. Reddy |
| 2016 | CIKM | CRISP: Consensus Regularized Selection based Prediction. | Ping Wang, Karthik K. Padthe, Bhanukiran Vinzamuri, Chandan K. Reddy |
| 2016 | ICDM | Transfer Learning for Survival Analysis via Efficient L2, 1-Norm Regularized Cox Regression. | Yan Li, Lu Wang, Jie Wang, Jieping Ye, Chandan K. Reddy |
| 2016 | ICDM | L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization. | Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan K. Reddy |
| 2016 | ICDM | Feature Grouping Using Weighted l1 Norm for High-Dimensional Data. | Bhanukiran Vinzamuri, Karthik K. Padthe, Chandan K. Reddy |
| 2016 | KDD | A Multi-Task Learning Formulation for Survival Analysis. | Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy |
| 2016 | PAKDD | Early-Stage Event Prediction for Longitudinal Data. | Mahtab Jahanbani Fard, Sanjay Chawla, Chandan K. Reddy |
| 2016 | WSDM | Project Success Prediction in Crowdfunding Environments. | Yan Li, Vineeth Rakesh, Chandan K. Reddy |
| 2016 | WSDM | Probabilistic Group Recommendation Model for Crowdfunding Domains. | Vineeth Rakesh, Wang-Chien Lee, Chandan K. Reddy |
| 2016 | SDM | Regularized Weighted Linear Regression for High-dimensional Censored Data. | Yan Li, Bhanukiran Vinzamuri, Chandan K. Reddy |
| 2016 | SDM | Regularized Parametric Regression for High-dimensional Survival Analysis. | Yan Li, Kevin S. Xu, Chandan K. Reddy |
| 2015 | ECIR | Geographical Latent Variable Models for Microblog Retrieval. | Alexander Kotov, Vineeth Rakesh, Eugene Agichtein, Chandan K. Reddy |
| 2015 | ICWSM | Project Recommendation Using Heterogeneous Traits in Crowdfunding. | Vineeth Rakesh, Jaegul Choo, Chandan K. Reddy |
| 2015 | KDD | Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization. | Hannah Kim, Jaegul Choo, Jingu Kim, Chandan K. Reddy, Haesun Park |
| 2014 | CIKM | Active Learning based Survival Regression for Censored Data. | Bhanukiran Vinzamuri, Yan Li, Chandan K. Reddy |
| 2014 | ICWSM | Personalized Recommendation of Twitter Lists using Content and Network Information. | Vineeth Rakesh, Dilpreet Singh, Bhanukiran Vinzamuri, Chandan K. Reddy |
| 2014 | SDM | Multi-Task Clustering using Constrained Symmetric Non-Negative Matrix Factorization. | Samir Al-Stouhi, Chandan K. Reddy |
| 2013 | ICDM | Cox Regression with Correlation Based Regularization for Electronic Health Records. | Bhanukiran Vinzamuri, Chandan K. Reddy |
| 2013 | KDD | Big data analytics for healthcare. | Jimeng Sun, Chandan K. Reddy |
| 2012 | ICTAI | Label Space Transfer Learning. | Samir Al-Stouhi, Chandan K. Reddy, David E. Lanfear |
| 2012 | PAKDD | Exploiting Label Dependency for Hierarchical Multi-label Classification. | Noor Alaydie, Chandan K. Reddy, Farshad Fotouhi |
| 2012 | SDM | Query-based Biclustering using Formal Concept Analysis. | Faris Alqadah, Joel S. Bader, Rajul Anand, Chandan K. Reddy |
| 2011 | PAKDD | Graph-Based Clustering with Constraints. | Rajul Anand, Chandan K. Reddy |
| 2011 | SDM | A Generalized Framework for Mining Arbitrarily Positioned Overlapping Co-clusters. | Omar Odibat, Chandan K. Reddy |
| 2010 | CIKM | Robust prediction from multiple heterogeneous data sources with partial information. | Mohammad S. Aziz, Chandan K. Reddy |
| 2010 | ICDM | Parallelized Boosting with Map-Reduce. | Indranil Palit, Chandan K. Reddy |
| 2010 | KDD | Optimizing debt collections using constrained reinforcement learning. | Naoki Abe, Prem Melville, Cezar Pendus, Chandan K. Reddy, David L. Jensen, Vince P. Thomas, James J. Bennett, Gary F. Anderson, Brent R. Cooley, Melissa Kowalczyk, Mark Domick, Timothy Gardinier |
| 2010 | PAKDD | A Robust Seedless Algorithm for Correlation Clustering. | Mohammad S. Aziz, Chandan K. Reddy |
| 2010 | SDM | p-ISOMAP: An Efficient Parametric Update for ISOMAP for Visual Analytics. | Jaegul Choo, Chandan K. Reddy, Hanseung Lee, Haesun Park |
| 2009 | PAKDD | Multi-resolution Boosting for Classification and Regression Problems. | Chandan K. Reddy, Jin Hyeong Park |
| 2009 | SDM | Identifying Information-Rich Subspace Trends in High-Dimensional Data. | Snehal Pokharkar, Chandan K. Reddy |
| 2008 | BIBE | Retrieval and ranking of biomedical images using boosted haar features. | Chandan K. Reddy, Fahima A. Bhuyan |
| 2008 | ICPR | Component-wise parameter smoothing for learning mixture models. | Chandan K. Reddy, Bala Rajaratnam |
| 2008 | SSPR | Scale-Space Kernels for Additive Modeling. | Chandan K. Reddy, Jin Hyeong Park |
| 2007 | IJCNN | TRUST-TECH Based Neural Network Training. | Hsiao-Dong Chiang, Chandan K. Reddy |
| 2007 | KDD | Looking for Great Ideas: Analyzing the Innovation Jam. | Wojciech Gryc, Mary E. Helander, Richard D. Lawrence, Yan Liu, Claudia Perlich, Chandan K. Reddy, Saharon Rosset |
| 2006 | ICDM | Stability Region Based Expectation Maximization for Model-based Clustering. | Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratnam |
| 2005 | SAC | Finding saddle points using stability boundaries. | Chandan K. Reddy, Hsiao-Dong Chiang |
| 2004 | CVPR | Mobile Face Capture for Virtual Face Videos. | Chandan K. Reddy, George C. Stockman, Jannick P. Rolland, Frank A. Biocca |