Publications

Selected Recent Publications.

• 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.
• Nikola Grozdani, America Muñoz, Alexander Pietrick, Ricardo Flores, Avantika Shrestha, Xingtong Guo, Shichao Liu and Elke Rundensteiner. Wearable Wellness: Depression Screening via Fitbit Data Collected During COVID-19 Pandemic. IEEE MIT Undergraduate Research Technology Conference (URTC) 2023. (REU Project Paper)
• 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.
• Dandan Tao, Ruofan Hu, Dongyu Zhang, Jasmine Laber, Anne Lapsley, Timothy Kwan, Liam Rathke, Elke Rundensteiner, Hao Feng. A Novel Foodborne Illness Detection and Web Application Tool Based on Social Media. Journal on Food Engineering and Technology Applications of Artificial Intelligence in Food Industry, MDPI 2023.
• 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.
• Liang Zhang, Noura Alghamdi, Huayi Zhang, Mohamed Y. Eltabakh, and Elke A. Rundensteiner. PARROT: Pattern-Based Correlation Exploitation in Big Partitioned Data Series. VLDB Journal, 1-24, 2022
• ML Tlachac, Walter Gerych, Kratika Agrawal, Benjamin Litterer, Nicholas Jurovich, Saitheeraj Thatigotla, Jidapa Thadajarassiri, and Elke Rundensteiner. Text Generation to Aid Depression Detection: A Comparative Study of Conditional Sequence Generative Adversarial Networks. 2022 IEEE International Conference on Big Data
• Nicholas Josselyn, Biao Yin, Ziming Zhang, and Elke Rundensteiner. An Empirical Study of Domain Adaptation: Are We Really Learning Transferable Representations? 2022 IEEE International Conference on Big Data
• Joshua DeOliveira, Walter Gerych, Aruzhan Koshkarova, Elke Rundensteiner, and Emmanuel Agu. HAR-CTGAN: A Mobile Sensor Data Generation Tool for Human Activity Recognition. 2022 IEEE International Conference on Big Data
• Nicholas Josselyn, Biao Yin, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, James Snyder, Ziming Zhang, and Elke Rundensteiner. Transferring indoor corrosion image assessment models to outdoor images via domain adaptation. 21st IEEE International Conference on Machine Learning and Applications, 2022.
• Avantika Shrestha, ML Tlachac, Ricardo Flores, Elke Rundensteiner. BERT Variants for Depression Screening with Typed and Transcribed Responses. WellComp Workshop, ACM UbiComp 2022.
• Ricardo Flores, ML Tlachac, Avantika Shrestha, Elke Rundensteiner. AudiFace: Multimodal Deep Learning For Depression Screening, Temporal Facial Features for Depression Screening. MHSI workshop, ACM UbiComp 2022.
• Ramesh Doddaiah, Prathyush Parvatharaju, Elke Rundensteiner, and Thomas Hartvigsen. Class-Specific Explainability for Deep Time Series Classifiers. IEEE Conf on Data Mining (ICDM), 2022
• ML Tlachac, Avantika Shrestha, Mahum Shah, Benjamin Litterer, and Elke A. Rundensteiner. Automated Construction of Lexicons to Improve Depression Screening with Text Messages. IEEE Journal of Biomedical and Health Informatics (J-BHI), 2022.
• Lei Cao, Yizhou Yan, Samuel Madden, and Elke Rundensteiner. AutoOD: Automatic Outlier Detection. ACM SIGMOD 2022.
• Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu and Elke Rundensteiner. Robust Recurrent Classifier Chains For Multi-Label Learning With Missing Labels. ACM CIKM'2022.
• Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong and Elke Rundensteiner. Stop&Hop: Early Classification of Irregular Time Series. ACM CIKM'2022.
• ML Tlachac, Miranda Reisch, Brittany Lewis, Ricardo Flores, Lane Harrison, and Elke Rundensteiner. Impact Assessment of Stereotype Threat on Mobile Depression Screening using Bayesian Estimation. Healthcare Analytics, Elsevier Publisher, 2022.
• Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner. AudiFace: Multimodal Deep Learning For Depression Screening. Machine Learning for Healthcare (MLHC), 2022.
• Mallak Alkhathlan, ML Tlachac, Lane Harrison and Elke Rundensteiner. Improving Image Accessibility by Combining Haptic and Auditory Feedback. ASSETS'2022.
• Ricardo Flores, ML Tlachac and Elke A. Rundensteiner. Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning. 2022 ACM International Conference on Information Technology for Social Good (GoodIT 2022).
• Hilson Shrestha, Kathleen Cachel, Mallak Alkhathlan, Elke A Rundensteiner and Lane Harrison. FairFuse: Interactive Visual Support for Fair Consensus Ranking. IEEE VIS, short paper, 2022.