Dr. Vasant Honavar
Vasant Honavar, Ph.D. is
Professor and Edward Frymoyer Chair of Information Sciences and Technology;
Associate Director, Institute for Cyberscience;
Professor of Genomics and Bioinformatics;
Professor of Neuroscience;
Faculty Member, The Huck Institutes of the Life Sciences;
Penn State University.
Vasant’s research interests are:
Artificial Intelligence: Intelligent agent architectures, Multi-agent organizations, Inter-agent interaction, and Multi-agent coordination, Logical, probabilistic, and decision-theoretic knowledge representation and inference, Neural architectures for knowledge representation and inference, Computational models of perception and action.
Bioinformatics, Computational Molecular Biology, and Computational Systems Biology: Data-driven discovery of macromolecular sequence-structure-function-interaction-expression relationships, identification of sequence and structural correlates of protein-protein, protein-RNA, and protein-DNA interactions, protein sub-cellular localization, automated protein structure and function annotation, modeling and inference of genetic regulatory networks from gene expression (micro-array, proteomics) data, modeling and inference of signal transduction and metabolic pathways.
Data Mining: Design, analysis, implementation, and evaluation of algorithms and software for data-driven knowledge acquisition, data and knowledge visualization, and collaborative scientific discovery from semantically heterogeneous, distributed data and knowledge sources, Applications to data-driven knowledge acquisition tasks in bioinformatics, medical informatics, geo-informatics, environmental informatics, chemo-informatics, security informatics, social informatics, critical national infrastructure (communication networks, energy networks) e-government, e-commerce, and e-science.
Machine Learning: Statistical, information theoretic, linguistic and structural approaches to machine learning, Learning and refinement of bayesian networks, causal networks, decision networks, neural networks, support vector machines, kernel classifiers,, multi-relational models, language models (n-grams, grammars, automata), Learning classifiers from attribute value taxonomies and partially specified data; Learning attribute value taxonomies from data; Learning classifiers from sequential and spatial data; Learning relationships from multi-modal data (e.g., text, images), Learning classifiers from distributed data, multi-relational data, and semantically heterogeneous data; Incremental learning, Ensemble methods, multi-agent learning, selected topics in computational learning theory.
Semantic Web: Ontology-based user and query-centric approaches to information integration and acquisition of sufficient statistics for learning from data under different access and resource constraints from heterogeneous, distributed, autonomous, ubiquitous information sources, sensor networks, peer-to peer networks; description logics, collaborative ontology design, ontology tools, ontology-extended information sources, ontology-extended workflow components, ontology-extended agents and services, semantic workflow composition.
Other Topics of Interest: Biological Computation, Evolutionary, Cellular and Neural Computation, Complex Adaptive Systems, Sensory systems and behavior evolution, Language evolution, Mimetic evolution; Computational Semiotics. Origins and use of signs, emergence of semantics; Computational organization theory; Computational Neuroscience; Computational models of creativity, Computational models of discovery.
Vasant is co-editor-in-chief of the Journal of Cognitive Systems Research and a member of the Editorial Board of the Machine Learning Journal, the International Journal of Information and Computer Security, and the International Journal of Data Mining and Bioinformatics.
He has served on the program committees of several major conferences in artificial intelligence, data mining, and bioinformatics including the International Conference on Machine Learning (ICML), ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), IEEE Conference on Data Mining (ICDM), IEEE Conference on Tools With Artificial Intelligence (ICTAI), the National Conference on Artificial Intelligence (AAAI), ACM/IEEE Conference on Intelligent Agent Technology (IAT), Intelligent Systems in Molecular Biology (ISMB), IEEE Conference on Bioinformatics and Bioengineering (BIBE), IEEE Conference on Bioinformatics and Biomedicine (BIBM), and the Workshop on Algorithms in Bioinformatics (WABI).
Vasant coedited Advances in the Evolutionary Synthesis of Intelligent Agents, Artificial Intelligence and Neural Networks: Steps Toward Principled Integration, and Grammatical Inference: 4th International Colloquium, ICGI-98, Ames, Iowa, USA, July 12–14, 1998, Proceedings (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence), and coauthored Striking Similarities in Diverse Telomerase Proteins Revealed by Combining Structure Prediction and Machine Learning Approaches and Evolutionary Design of Neural Architectures A Preliminary Taxonomy and Guide to Literature. Read the full list of his publications!
Vasant earned his M.S. in Computer Science from the University of Wisconsin-Madison in 1989 and his Ph.D. in Computer Science from the University of Wisconsin-Madison in 1990. He also earned a B.E. in Electronics Engineering from Bangalore University, India, and a M.S. in Electrical and Computer Engineering from Drexel University.