基本信息
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Career Trajectory
Bio
Dr. Oommen has done research in the general areas of Artificial Intelligence for more than 40 years. In the fields of Stochastic Learning and Learning Automata (LA), he has pioneered the field of Discretized LA. Some of the fastest and most accurate LA are due to the work done by him and his co-authors. Research in these fields earned him his elevation to be a Fellow of the IEEE. In the area of Statistical Pattern Recognition (PR) he has pioneered the theory and applications of the so-called Anti-Bayesian paradigm of PR. Together with his co-authors, he also introduced the science and art of Chaotic PR. His work in using Dependence Trees to achieve PR is also well recorded. In the area of Syntactic PR, his award-winning algorithm has attained the optimal and information theoretic bound, and this earned him his elevation to be a Fellow of the IAPR. Within the field of Neural Networks (NNs), he has worked extensively with the Kohonen’s NN, and has demonstrated how one can merge the structure of the NN and its topology. Besides these, he has also worked in the general fields of AI, intelligent game playing, and LA-based data compression.
Research Interests
Papers共 477 篇Author StatisticsCo-AuthorSimilar Experts
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期刊级别
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IEEE transactions on neural networks and learning systemsno. 6 (2024): 8278-8292
Pattern Analysis and Applicationsno. 2 (2023): 751-772
Inf. Sci. (2023)
Springer handbookspp.233-250, (2023)
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KNOWLEDGE ENGINEERING REVIEW (2023)
Honoring Professor Mohammad S. Obaidatpp.33-52, (2022)
AI 2021: ADVANCES IN ARTIFICIAL INTELLIGENCE (2022): 507-518
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Author Statistics
#Papers: 472
#Citation: 6981
H-Index: 39
G-Index: 62
Sociability: 6
Diversity: 3
Activity: 21
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