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;
all at
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.