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Evaluating Differences in Insights from Interactive Dimensionality Reduction Visualizations Through Complexity and Vocabulary

Mia Taylor, Lata Kodali, Leanna House, Chris North: Evaluating Differences in Insights from Interactive Dimensionality Reduction Visualizations Through Complexity and Vocabulary. VISIGRAPP (3: IVAPP) 2023: 158-165

Mixed Multi-Model Semantic Interaction for Graph-based Narrative Visualizations

Brian Felipe Keith Norambuena, Tanushree Mitra, Chris North: Mixed Multi-Model Semantic Interaction for Graph-based Narrative Visualizations. IUI 2023: 866-888

Reflecting on the Scalable Adaptive Graphics Environment Team’s 20-Year Translational Research Endeavor in Digital Collaboration Tools

Sindhura Kommu

Sindhura Kommu is a master’s degree student in the Department of Computer Science. She is advised by Xuan Yang. Her research interests lie in the domain of multimodal ML for healthcare applications and her current work focuses on multi-omics Large Language Models for bio-medicine.  

Abhijit Sarkar

Abhijit Sarkar is a senior research associate within the Division of Data and Analytics at the Virginia Tech Transportation Institute (VTTI) and affiliate faculty at the Sanghani Center.  At present, he leads the Computer Vision and Machine Learning team at VTTI. His research mainly focuses in the intersection of artificial intelligence and transportation research with […]

Overcoming Barriers to Skill Injection in Language Modeling: Case Study in Arithmetic

Scrutinizing Shipment Records To Thwart Illegal Timber Trade

Innovations in Neural Data-to-text Generation

Lessons from Deep Learning applied to Scholarly Information Extraction: What Works, What Doesn’t, and Future Directions

Efficient Generative Wireless Anomaly Detection for Next Generation Networks

G. Rathinavel, N. Muralidhar, N. Ramakrishnan and T. O’Shea, “Efficient Generative Wireless Anomaly Detection for Next Generation Networks,” MILCOM 2022 – 2022 IEEE Military Communications Conference (MILCOM), Rockville, MD, USA, 2022, pp. 594-599, doi: 10.1109/MILCOM55135.2022.10017520.