In December 2024, our team published a paper at the IEEE Big Data 2024 conference: Hazelwood, D. J., D. Joshi, A. Samal, and L.-K. Soh (2024). Discovering Localized Drivers of Unrest Events using Clustering and XGBoost, Proceedings of the IEEE Conference on Big Data (IEEE Big Data 2024), December 15-18, Washington, DC, pp. 2958-2966.
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With former PhD student and former post-doctoral researcher Yi Liu, we publish a new journal paper “Integrating Textual and Visual Features to Generate Pseudo-Groundtruth for Enhancing Training of Machine Learning Models in Document Image Classification” at the Journal of Electronic Imaging. Our team has a paper accepted at UAI’2025. Congratulations to the team with Dr. Doshi’s group at University of Georgia and Dr. Eck’s group at Oberlin College, and the research students Daniel (U. Georgia) and Ceferino (U. Nebraska)! “MOHITO: Multi-Agent Reinforcement Learning Using Hypergraphs for Task-Open Systems” Congratulations to Ceferino Patino for winning the School of Computing’s Annual Outstanding Undergraduate Research Student Award for 2025! Professor Leen-Kiat Soh received NSF IUSE funding for the CS FUTURES project, together with an interdisciplinary team (Prof. Guy Trainin, Prof. Gwen Nugent, Prof. Wendy Smith, Prof. Brian Dorn, at UNL and UNO) and partners at Southeast Community College, Metropolitan Community College, and Western Nebraska Community College. The project officially started in September 2024. Congratulations to Praval Sharma! Praval successfully defended his Doctoral Dissertation on July 29, 2024! Welcome to Ceferino Patino, Tyler Billings, and Alireza Saleh Abadi to the IAMAS group. They are part of the OASYS project with University of Georgia and Oberlin College. Professor Soh and his collaborators Professors Adam Eck and Prashant Doshi have published a research article on agent decision making in open environments: Eck, A., L.-K. Soh, and P. Doshi (2023). Decision Making in Open Agent Systems, AI Magazine, pp. 1-16, https://doi.org/10.1002/aaai.12131. Video: https://www.youtube.com/watch?v=vQOK3YNeTDE The Computational Creativity Exercises team has published the final paper documenting their work on how student learn about CS. This paper is about the relationship between implicit intelligence beliefs and self-regulation of learning. Flanigan, A. E., M. Peteranetz, D. Shell, and L.-K. Soh (2023). Relationship between Implicit Intelligence Beliefs and Maladaptive Self-Regulation of Learning, ACM Transactions on Computing Education, 23(3):1-23, https://doi.org/10.1145/3595187 The Aida team that has worked on historical document analysis has published an article documenting our work: L.-K. Soh, E. Lorang, C. Pack, and Y. Liu (2023). Applying Image Analysis and Machine Learning to Historical Newspaper Collections, The American Historical Review, 128(3):1382-1389, September. |
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