Publications

Selected Recent Publications.

• Joshua DeOliveira, Walter Gerych, and Elke Rundensteiner. The Surprising Effectiveness of Infinite-Width NTKs for Characterizing and Improving Model Training. AAAI 2025.
• Joshua DeOliveira, Walter Gerych, and Elke Rundensteiner. GAN Stabilization Under Practical Training Assumptions. 2024 IEEE International Conference on Big Data, 2024. Full Paper.
• Dongyu Zhang, Ruofan Hu, Dandan Tao, Hao Feng, and Elke Rundensteiner. LLM-based Hierarchical Label Annotation for Foodborne Illness Detection on Social Media. IEEE BigData 2024, 10th Special Session on Intelligent Data Mining
• Avantika Shrestha, ML Tlachac, Ricardo Flores, Kevin Hickey, and Elke Rundensteiner. Multi-task Learning with Pre-trained Language Models for Mental Illness Screening. 9th IEEE Special Session on Machine Learning on Big Data (MLBD 2024), IEEE Big Data 2024
• Rebecca Lopez, Avantika Shrestha, Kevin Hickey, Xingtong Guo, ML Tlachac, Shichao Liu, and Elke Rundensteiner. Screening Students for Stress Using Fitbit Data. The 4th International Workshop on Multi-Modal Medical Data Analysis", 2024 IEEE International Conference on Big Data (IEEE BigData 2024)
• Oluseun Olulana, Kathleen Cachel, Fabricio Murai, Elke Rundensteiner. Hidden or Inferred: Fair Learning-To-Rank With Unknown Demographics. AAAI Conference on AI, Ethics, and Society (AIES 2024)
• Harriet Sibitenda, Ruofan Hu, Elke Rundensteiner, Awa Diattara, Assitan Traore, and Cheikh Ba. Leveraging LLMs for Integrated Sentiment and Topic Analysis on African Social Media. ICMLA 2024, Deep Learning and Applications Special Session
• Harriet Sibitenda, Awa Diattara, Assitan Traore, Ruofan Hu, Dongyu Zhang, Elke Rundensteiner, and Cheikh Ba. Extracting Semantic Topics about Development in Africa from Social Media. IEEE Access 2024
• Simeon Krastev, Aukkawut Ammartayakun, Kewal Jayshankar Mishra, Harika Koduri, Eric Schuman, Drew Morris, Yuan Feng, Sai Supreeth Reddy Bandi, Chun-Kit Ngan, Andrew Yeung, Jason Li, Nigel Ko, Fatemeh Emdad, and Elke Rundensteiner. META: Deep Learning Pipeline for Detecting Anomalies on Multimodal Vibration Sewage Treatment Plant Data. Int Conf on Neural Computation Theory and Applications 2024
• Dennis M. Hofmann, Peter M. VanNostrand, Lei Ma, Huayi Zhang, Joshua C. DeOliveira, Lei Cao, and Elke A. Rundensteiner. Agree to Disagree: Robust Anomaly Detection with Noisy Labels. ACM SIGMOD 2025
• Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Belisha Genin, Randy Huang, and Elke A. Rundensteiner. Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions. Demonstration Paper, VLDB 2024
• Lei Ma. Lei Cao, Peter VanNostrand, Dennis Hofmann, Su Yao, and Elke Rundensteiner. Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data. ACM SIGMOD 2025
• Mallak Alkhathlan, Kathleen Cachel, Hilson Shrestha, Lane Harrison, and Elke Rundensteiner. Balancing Act: Evaluating People's Perceptions of Fair Ranking Metrics. FAccT 2024
• Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, and Elke A. Rundensteiner Actionable Recourse for Automated Decisions: Examining the Effects of Counterfactual Explanation Type and Presentation on Lay User Understanding. FAccT 2024
• Kathleen Cachel and Elke Rundensteiner. PreFAIR: Combining Partial Preferences for Fair Consensus Decision-Making. FAccT 2024
• Dongyu Zhang, Ruofan Hu, and Elke Rundensteiner. CoLafier: Collaborative Noisy Label Purifier With LID Guidance. SIAM International Conference on Data Mining. SDM 2024.
• Jidapa Thadajarassiri, Walter Gerych, Xiangnan Kong, and Elke Rundensteiner. Amalgamating Multi-Task Models with Heterogeneous Architectures. AAAI 2024.
• Ricardo Flores, Avantika Shrestha, ML Tlachac, and Elke Rundensteiner. DeepScreen: Boosting Depression Screening Performance with an Auxiliary Task. Special Session on Machine Learning on Big Data (MLBD) in IEEE BigData 2023.
• Ricardo Flores, Avantika Shrestha, and Elke Rundensteiner. Multi-Task Learning Using Facial Features for Mental Health Screening. Special Session on HealthCare Data in IEEE BigData 2023.
• Ruofan Hu, Dongyu Zhang, Dandan Tao, Huayi Zhang, Hao Feng, and Elke Rundensteiner. UCE-FID: Using Large Unlabeled, Medium Crowdsourced-Labeled, and Small Expert-Labeled Tweets for Foodborne Illness Detection. Special Session on Machine Learning on Big Data (MLBD) in IEEE BigData 2023.
• Walter Gerych, Kevin Hickey, Thomas Hartvigsen, Luke Buquicchio, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Emmanuel Agu, and Elke Rundensteiner. Stabilizing Adversarial Training for Generative Networks. Special Session on Machine Learning on Big Data (MLBD) IEEE BigData 2023.
• Walter Gerych, Kevin Hickey, Luke Buquicchio, Kavin Chandrasekaran, Abdulaziz Alajaji, Elke Rundensteiner, and Emmanuel Agu. Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes. NeurIPS 2023.
• Peter M. VanNostrand, Huayi Zhang, Dennis Hofmann, and Elke Rundensteiner. FACET: Robust Counterfactual Explanation Analytics. ACM SIGMOD 2023.
• Kathleen Cachel and Elke Rundensteiner. Fair&Share: Fast and Fair Multi-Criteria Selections. ACM CIKM 2023. Full Paper.
• Biao Yin, Nicholas Josselyn, Ziming Zhang, Elke Rundensteiner, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, and James Snyder. MOSS: AI Platform for Discovery of Corrosion-Resistant Materials. ACM CIKM 2023. Demonstration Paper.
• Kathleen Cachel and Elke Rundensteiner. Fairer Together: Mitigating Disparate Exposure in Kemeny Rank Aggregation. FAccT 2023.
• Hilson Shresta, Kathleen Cachel, Mallak Alkhathlan, Elke Rundensteiner and Lane Harrison. Help or Hinder? Evaluating the Impact of Fairness Metrics and Algorithms in Visualizations for Consensus Ranking. FAccT 2023.
• Jida Thadajarassiri, Tom Hartvigsen, Walter Gerych, Xiangnan Kong and Elke Rundensteiner. Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer. AAAI 2023.