| 2026 | ACL | SQL-Trail: Multi-Turn Reinforcement Learning with Interleaved Feedback for Text-to-SQL. | Harper Hua, Zhen Han, Zhengyuan Shen, Meng-Chieh Lee, Sheng Guan, Qi Zhu, Sullam Jeoung, Yueyan Chen, Yunfei Bai, Shuai Wang, Vassilis N. Ioannidis, Huzefa Rangwala |
| 2026 | ACL | BoundRL: Efficient Token-level Structured Text Segmentation through Reinforced Boundary Generation. | Haoyuan Li, Zhengyuan Shen, Sullam Jeoung, Yueyan Chen, Jiayu Li, Qi Zhu, Shuai Wang, Vassilis N. Ioannidis, Huzefa Rangwala |
| 2026 | ACL | When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors. | Yuqing Yang, Qi Zhu, Zhen Han, Boran Han, Zhengyuan Shen, Shuai Wang, Vassilis N. Ioannidis, Huzefa Rangwala |
| 2025 | ACL | HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases. | Meng-Chieh Lee, Qi Zhu, Costas Mavromatis, Zhen Han, Soji Adeshina, Vassilis N. Ioannidis, Huzefa Rangwala, Christos Faloutsos |
| 2025 | AISTATS | DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification. | Xiaoxue Han, Huzefa Rangwala, Yue Ning |
| 2025 | EMNLP | BYOKG-RAG: Multi-Strategy Graph Retrieval for Knowledge Graph Question Answering. | Costas Mavromatis, Soji Adeshina, Vassilis N. Ioannidis, Zhen Han, Qi Zhu, Ian Robinson, Bryan Thompson, Huzefa Rangwala, George Karypis |
| 2025 | ICDE | Featpilot: Automatic Feature Augmentation on Tabular Data. | Jiaming Liang, Chuan Lei, Xiao Qin, Jiani Zhang, Asterios Katsifodimos, Christos Faloutsos, Huzefa Rangwala |
| 2025 | ICLR | AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. | Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala |
| 2025 | ICLR | AutoG: Towards automatic graph construction from tabular data. | Zhikai Chen, Han Xie, Jian Zhang, Xiang Song, Jiliang Tang, Huzefa Rangwala, George Karypis |
| 2025 | ICLR | Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling, and Zero-Shot Transfer. | Zihan Pengmei, Zhengyuan Shen, Zichen Wang, Marcus D. Collins, Huzefa Rangwala |
| 2025 | ICML | Protein Structure Tokenization: Benchmarking and New Recipe. | Xinyu Yuan, Zichen Wang, Marcus D. Collins, Huzefa Rangwala |
| 2025 | KDD | SKnow-LLM Workshop: Structured Knowledge for Large Language Models. | Qi Zhu, Xiusi Chen, Yu Zhang, Soji Adeshina, Costas Mavromatis, Zhen Han, Vassilis N. Ioannidis, Leman Akoglu, Danai Koutra, Huzefa Rangwala |
| 2025 | KDD | Hierarchical Lexical Graph for Enhanced Multi-Hop Retrieval. | Abdellah Ghassel, Ian Robinson, Gabriel Tanase, Hal Cooper, Bryan Thompson, Zhen Han, Vassilis N. Ioannidis, Soji Adeshina, Huzefa Rangwala |
| 2025 | NAACL | PolyJoin: Semantic Multi-key Joinable Table Search in Data Lakes. | Xuming Hu, Chuan Lei, Xiao Qin, Asterios Katsifodimos, Christos Faloutsos, Huzefa Rangwala |
| 2025 | NAACL | DiscoverGPT: Multi-task Fine-tuning Large Language Model for Related Table Discovery. | Xuming Hu, Xiao Qin, Chuan Lei, Asterios Katsifodimos, Zhengyuan Shen, Balasubramaniam Srinivasan, Huzefa Rangwala |
| 2024 | EMNLP | CoverICL: Selective Annotation for In-Context Learning via Active Graph Coverage. | Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen, Jiani Zhang, Huzefa Rangwala, Christos Faloutsos, George Karypis |
| 2024 | ICDE | DATALORE: Can a Large Language Model Find All Lost Scrolls in a Data Repository? | Yuze Lou, Chuan Lei, Xiao Qin, Zichen Wang, Christos Faloutsos, Rishita Anubhai, Huzefa Rangwala |
| 2024 | ICLR | BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs. | Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai |
| 2024 | ICLR | OpenTab: Advancing Large Language Models as Open-domain Table Reasoners. | Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis |
| 2024 | ICLR | Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space. | Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis |
| 2024 | KDD | GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications. | Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis |
| 2023 | EMNLP | NameGuess: Column Name Expansion for Tabular Data. | Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis |
| 2023 | KDD | Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls". | Mia C. Mayer, Muhammad Bilal Zafar, Luca Franceschi, Huzefa Rangwala |
| 2023 | PAKDD | Estimating the Risk of Individual Discrimination of Classifiers. | Jonathan Vasquez, Xavier Gitiaux, Huzefa Rangwala |
| 2022 | ICDM | Causality Enhanced Societal Event Forecasting With Heterogeneous Graph Learning. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2022 | IJCAI | SoFaiR: Single Shot Fair Representation Learning. | Xavier Gitiaux, Huzefa Rangwala |
| 2022 | KDD | Robust Event Forecasting with Spatiotemporal Confounder Learning. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2022 | KDD | Graph Neural Networks in Life Sciences: Opportunities and Solutions. | Zichen Wang, Vassilis N. Ioannidis, Huzefa Rangwala, Tatsuya Arai, Ryan Brand, Mufei Li, Yohei Nakayama |
| 2022 | LAK | FairEd: A Systematic Fairness Analysis Approach Applied in a Higher Educational Context. | Jonathan Vasquez Verdugo, Xavier Gitiaux, Cesar Ortega, Huzefa Rangwala |
| 2021 | AAAI | Fair Representations by Compression. | Xavier Gitiaux, Huzefa Rangwala |
| 2021 | AISTATS | Learning Smooth and Fair Representations. | Xavier Gitiaux, Huzefa Rangwala |
| 2021 | ASSETS | WLA4ND: a Wearable Dataset of Learning Activities for Young Adults with Neurodiversity to Provide Support in Education. | Hui Zheng, Pattiya Mahapasuthanon, Yujing Chen, Huzefa Rangwala, Anya S. Evmenova, Vivian Genaro Motti |
| 2021 | CIKM | Understanding Event Predictions via Contextualized Multilevel Feature Learning. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2021 | EDM | Using Course Evaluations and Student Data to Predict Computer Science Student Success. | Anlan Du, Alexandra Plukis, Huzefa Rangwala |
| 2021 | EDM | Synthetic Embedding-based Data Generation Methods for Student Performance. | Dom Huh, Huzefa Rangwala |
| 2021 | FIE | Using Role-Plays to Improve Ethical Understanding of Algorithms Among Computing Students. | Ashish Hingle, Huzefa Rangwala, Aditya Johri, Alex Monea |
| 2021 | WACV | Hand Pose Guided 3D Pooling for Word-level Sign Language Recognition. | Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Huzefa Rangwala, Jana Koseck |
| 2021 | SC | FedAT: a high-performance and communication-efficient federated learning system with asynchronous tiers. | Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala |
| 2020 | AAAI | American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract). | Yuanqi Du, Nguyen Dang, Riley Wilkerson, Parth H. Pathak, Huzefa Rangwala, Jana Kosecka |
| 2020 | CIKM | Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction. | Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning |
| 2020 | DSAA | Body Pose and Deep Hand-shape Feature Based American Sign Language Recognition. | Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Koseck, Huzefa Rangwala |
| 2020 | EDM | Using online text books and in-class quizzes to predict in class performance. | Noah Hunt-Isaak, Peter Cherniavsky, Mark Snyder, Huzefa Rangwala |
| 2020 | EDM | Towards Fair Educational Data Mining: A Case Study on Detecting At-risk Students. | Qian Hu, Huzefa Rangwala |
| 2020 | ICDM | Metric-Free Individual Fairness with Cooperative Contextual Bandits. | Qian Hu, Huzefa Rangwala |
| 2020 | IJCNN | Federated Multi-task Learning with Hierarchical Attention for Sensor Data Analytics. | Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala |
| 2020 | KDD | Dynamic Knowledge Graph based Multi-Event Forecasting. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2020 | KDD | Attention Realignment and Pseudo-Labelling for Interpretable Cross-Lingual Classification of Crisis Tweets. | Jitin Krishnan, Hemant Purohit, Huzefa Rangwala |
| 2020 | SECON | Expressive ASL Recognition using Millimeter-wave Wireless Signals. | Panneer Selvam Santhalingam, Yuanqi Du, Riley Wilkerson, Al Amin Hosain, Ding Zhang, Parth H. Pathak, Huzefa Rangwala, Raja S. Kushalnagar |
| 2019 | DSAA | Sign Language Recognition Analysis using Multimodal Data. | Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Koseck, Huzefa Rangwala |
| 2019 | DSAA | Grade Prediction with Neural Collaborative Filtering. | Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala |
| 2019 | EDM | Academic Performance Estimation with Attention-based Graph Convolutional Networks. | Qian Hu, Huzefa Rangwala |
| 2019 | EDM | Grade Prediction Based on Cumulative Knowledge and Co-taken Courses. | Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala |
| 2019 | IJCAI | mdfa: Multi-Differential Fairness Auditor for Black Box Classifiers. | Xavier Gitiaux, Huzefa Rangwala |
| 2019 | ICSE | Guiding testing effort using mutant utility. | Justin Alvin, Bob Kurtz, Paul Ammann, Huzefa Rangwala, Ren Just |
| 2019 | KDD | Tutorial: Are You My Neighbor?: Bringing Order to Neighbor Computing Problems. | David C. Anastasiu, Huzefa Rangwala, Andrea Tagarelli |
| 2019 | KDD | Learning Dynamic Context Graphs for Predicting Social Events. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2019 | KDD | Spatio-temporal Event Forecasting and Precursor Identification. | Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu, Huzefa Rangwala |
| 2019 | LAK | Reliable Deep Grade Prediction with Uncertainty Estimation. | Qian Hu, Huzefa Rangwala |
| 2019 | WWW | Event Detection using Hierarchical Multi-Aspect Attention. | Sneha Mehta, Mohammad Raihanul Islam, Huzefa Rangwala, Naren Ramakrishnan |
| 2018 | AIED | Early Identification of At-Risk Students Using Iterative Logistic Regression. | Li Zhang, Huzefa Rangwala |
| 2018 | LAK | Running out of STEM: a comparative study across STEM majors of college students at-risk of dropping out early. | Yujing Chen, Aditya Johri, Huzefa Rangwala |
| 2018 | PAKDD | Course-Specific Markovian Models for Grade Prediction. | Qian Hu, Huzefa Rangwala |
| 2018 | SDM | STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. | Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan |
| 2018 | SDM | ALE: Additive Latent Effect Models for Grade Prediction. | Zhiyun Ren, Xia Ning, Huzefa Rangwala |
| 2017 | DSAA | Enriching Course-Specific Regression Models with Content Features for Grade Prediction. | Qian Hu, Agoritsa Polyzou, George Karypis, Huzefa Rangwala |
| 2017 | EDM | Grade Prediction with Temporal Course-wise Influence. | Zhiyun Ren, Xia Ning, Huzefa Rangwala |
| 2017 | ICDM | IterativE Grammar-Based Framework for Discovering Variable-Length Time Series Motifs. | Yifeng Gao, Jessica Lin, Huzefa Rangwala |
| 2017 | ICMLA | Integrated Framework for Improving Large-Scale Hierarchical Classification. | Azad Naik, Huzefa Rangwala |
| 2017 | RecSys | A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. | Yue Ning, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan |
| 2016 | CIKM | A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events. | Wei Wang, Yue Ning, Huzefa Rangwala, Naren Ramakrishnan |
| 2016 | DSAA | Inconsistent Node Flattening for Improving Top-Down Hierarchical Classification. | Azad Naik, Huzefa Rangwala |
| 2016 | EDM | Predicting Performance on MOOC Assessments using Multi-Regression Models. | Zhiyun Ren, Huzefa Rangwala, Aditya Johri |
| 2016 | EDM | Next-Term Student Performance Prediction: A Recommender Systems Approach. | Mack Sweeney, Jaime Lester, Huzefa Rangwala, Aditya Johri |
| 2016 | ICMLA | Iterative Grammar-Based Framework for Discovering Variable-Length Time Series Motifs. | Yifeng Gao, Jessica Lin, Huzefa Rangwala |
| 2016 | KDD | Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. | Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan |
| 2016 | SIGCSE | Using Learning Analytics to Trace Academic Trajectories of CS and IT Students to Better Understanding Successful Pathways to Graduation (Abstract Only). | Omaima Almatrafi, Huzefa Rangwala, Aditya Johri, Jaime Lester |
| 2015 | DSAA | A ranking-based approach for hierarchical classification. | Azad Naik, Huzefa Rangwala |
| 2015 | ICDM | Predicting Clinical Phenotype Using OTU-Based Metagenome Representation. | Nathan LaPierre, Huzefa Rangwala |
| 2015 | ICER | What Are We Teaching?: Automated Evaluation of CS Curricula Content Using Topic Modeling. | Jean Michel Rouly, Huzefa Rangwala, Aditya Johri |
| 2015 | ICMLA | Predicting New Friendships in Social Networks. | Anvardh Nanduri, Huzefa Rangwala |
| 2015 | ICMLA | A Machine Learning Approach to False Alarm Detection for Critical Arrhythmia Alarms. | Xing Wang, Yifeng Gao, Jessica Lin, Huzefa Rangwala, Ranjeev Mittu |
| 2015 | ICTAI | Recommending Temporally Relevant News Content from Implicit Feedback Data. | Nikhil Muralidhar, Huzefa Rangwala, Eui-Hong Sam Han |
| 2015 | SAC | Approximate block coordinate descent for large scale hierarchical classification. | Anveshi Charuvaka, Huzefa Rangwala |
| 2015 | SDM | Predicting Preference Tags to Improve Item Recommendation. | Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi |
| 2014 | CIDM | Convex multi-task relationship learning using hinge loss. | Anveshi Charuvaka, Huzefa Rangwala |
| 2013 | IJCAI | Protein Function Prediction by Integrating Multiple Kernels. | Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang |
| 2013 | ICTAI | Classifying Documents within Multiple Hierarchical Datasets Using Multi-task Learning. | Azad Naik, Anveshi Charuvaka, Huzefa Rangwala |
| 2013 | SDM | Joint Segmentation and Clustering in Text Corpuses. | Samuel J. Blasiak, Huzefa Rangwala, Sithu Sudarsan |
| 2013 | SDM | MC-MinH: Metagenome Clustering using Minwise based Hashing. | Huzefa Rangwala, Zeehasham Rasheed |
| 2012 | ICDM | Multi-task Learning for Classifying Proteins Using Dual Hierarchies. | Anveshi Charuvaka, Huzefa Rangwala |
| 2012 | ICMLA | Multi-label Collective Classification Using Adaptive Neighborhoods. | Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi |
| 2012 | KDD | Transductive multi-label ensemble classification for protein function prediction. | Guo-Xian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang, Zhiwen Yu |
| 2012 | PAKDD | Feature Enriched Nonparametric Bayesian Co-clustering. | Pu Wang, Carlotta Domeniconi, Huzefa Rangwala, Kathryn B. Laskey |
| 2012 | SDM | Beam Methods for the Profile Hidden Markov Model. | Samuel J. Blasiak, Huzefa Rangwala, Kathryn B. Laskey |
| 2012 | SDM | Efficient Clustering of Metagenomic Sequences using Locality Sensitive Hashing. | Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbar |
| 2011 | HPCC | GPU-Euler: Sequence Assembly Using GPGPU. | Syed Faraz Mahmood, Huzefa Rangwala |
| 2011 | ICMLA | Analysis of Microbiome Data across Inflammatory Bowel Disease Patients. | Nuttachat Wisittipanit, Huzefa Rangwala, Patrick Gillevet |
| 2011 | IJCAI | A Hidden Markov Model Variant for Sequence Classification. | Sam Blasiak, Huzefa Rangwala |
| 2010 | ICWSM | Co-Participation Networks Using Comment Information. | Huzefa Rangwala, Salman Jamali |
| 2009 | PAKDD | A Kernel Framework for Protein Residue Annotation. | Huzefa Rangwala, Christopher Kauffman, George Karypis |
| 2008 | APBC | fRMSDAlign: Protein Sequence Alignment Using Predicted Local Structure Information for Pairs with Low Sequence Identity. | Huzefa Rangwala, George Karypis |
| 2005 | AMIA | Feature Mining for Prediction of Degree of Liver Fibrosis. | Benjamin W. Mayer, Huzefa Rangwala, Rohit Gupta, Jaideep Srivastava, George Karypis, Vipin Kumar, Piet C. de Groen |