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个人简介
Honavar's current research and teaching interests include Artificial Intelligence, Machine Learning, Bioinformatics, Big Data Analytics, Computational Molecular Biology, Data Mining, Discovery Informatics, Information Integration, Knowledge Representation and Inference, Semantic Technologies, Social Informatics, Security Informatics, and Health Informatics. Honavar has led research projects funded by NSF, NIH, and USDA that have resulted in foundational research contributions (documented in over 250 peer-reviewed publications) in Scalable approaches to building predictive models from large, distributed, semantically disparate data (big data); Constructing predictive models from sequence, image, text, multi-relational, graph-structured data; Eliciting causal information from multiple sources of observational and experimental data; Selective sharing of knowledge across disparate knowledge bases; Representing and reasoning about preferences; Composing complex services from components; and Applications in bioinformatics and computational biology (especially analysis and prediction of protein-protein, protein-DNA, and protein-RNA interactions and interfaces, B-cell and T-cell epitopes, post-translational modifications), Social network Informatics, Health Informatics, Energy Informatics, Security Informatics, and related areas.
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AAAI 2024no. 12 (2024): 13736-13743
Sleep health (2024)
arxiv(2024)
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arxiv(2024)
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Weijieying Ren,Vasant G Honavar
Proceedings of the 2024 SIAM International Conference on Data Mining (SDM)pp.163-171, (2024)
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