Satchidananda Dehuri (Ph.D. (Computer Science))

1 Satchidananda Dehuri ( (Computer Science)) PERSONALINFORMATIONDOB: 15thJune 1976 SEX: Male PASSPORT NO.: G5389112 NATIONALITY: IndianCORRESPONDENCE ADDRESSS atchidananda Dehuri ,Reader,Department of Information and Communication Technology,Fakir Mohan University, Vyasa Vihar, Januganj,Balsore-756019, ORISSA, : TEL:+91-6843-2-62229 MOBILE:+91-96683-21964 Email: Satchidananda Dehuri ,Reader and HeadDepartment of Information and Communication Technology,Director,Instrumentation Maintenance Facility Center,Software Development Cell,Center of Distance and Continuing Education,Fakir Mohan University, Vyasa Vihar, Januganj,Balasore-756019, ORISSA, Doctorin Engineering Sciences, Yonsei University, SOUTH KOREA, Computer Science, Utkal University, INDIA, TITLE: Application of Parallel Processing Techniques to Data Warehousingand Mining ,under the guidance of Prof. Rajib Mall, IIT of Technology(First Class with Honors) in Computer Science, School ofMathematics Statistics & Computer Science, Utkal University, INDIA, TITLE: Multi-objective Evolutionary Algorithms for Rule Generation inData Mining ,completed from Machine Intelligence Unit, Indian Statistical Institute under theGuidance of Prof.

2 Ashish Travel Supportfrom Department of Science and Technology, INDIAto participate in GECCO 2011 at Dublin, Scientist Awardfrom Department of Science and Technology, Orissa Bi-gyan Academy, Govt. of ORISSA for the year Doctoral Fellowshipreceived from University of Algarve, FARO Portugal Scholarwith Fellowship in Center for Theoretical Studies, Indian Instituteof Technology Kharagpur, INDIA, Scientistwith Fellowship during the period 20th May to 20th June inCenter for Soft Computing Research, Indian Statistical Institute, Kolkata, Scientistwith Fellowship during the period 20th May to 20th July inCenter for Soft Computing Research, Indian Statistical Institute, Kolkata, Opportunities for Young Scientist in Chosen Area of Science andTechnology (BOYSCAST) awarded by Department of Science and Technology,Govt. of India for the Period 20th March 2008 to 20th March Project titled Knowledge Extraction Using Fuzzy Genetic Approach fromMeteorological Data from DRDO, ITR Chandipur.

3 Duration 2011-2012, ContractNo. RD/P-11/ITER-025, (INR:5,00,000).UGC Minor Research Project titled Application of Biologically Inspired Methods inFinancial Modeling . Duration 2011-2013, Sanction No.: 40-472/2011(SR), (INR:1,20,000).Fast Track project titled Multi-objective Fuzzy Swarm Intelligent System for Intru-sion Detection from Department of Science and Technology, 2011, (INR:13,00,000).TEACHINGRESEARCHINTEREST D esign and Analysis of Algorithms, Data Structure, Evolutionary and Non-EvolutionaryAlgorithm for Pattern Recognition, Relational Database, Data Mining and DataWarehousing, Theory of Computation and Programming Languages C, C++, DataMining for Bioinformatics, Graph Algorithms, Swarm Intelligence and Neural ofPhilosophy(Completed)Particle Swarm Optimization for Multi-objective Problems by Madhabananda Dasin KIIT University, Orissa, Sankar Prasad Mishra has submitted thesis on Parallel Single and Multi-objective Genetic Algorithms in F. M. University, Vyasa Vihar, Balasore, Orissa, ofPhilosophy(In Progress)Mr.

4 Harihar Kalia is working on Multi-objective Fuzzy Genetic Rule Mining in University, Vyasa Vihar, Balasore, Orissa, Bijaya Kumar Nanda is working on Ant Colony Based Data Mining in F. , Vyasa vihar, Balasore, ORISSA, Arbind Panda is working on Data Mining Tools and Techniques for Bioinfor-matics in F. M. University, Vyasa Vihar, Balasore, Orissa, Choudhury Sanjeeb Kumar Dash is working on Evolving Neural Networks forData Mining in F. M. University, Vyasa Vihar, Balasore, Orissa, Ashok Panda is working on Web Mining and its Application to E-commerce in Berhampur University, Bhanja Bihar, Orissa, publications in DBLP ( ley/db/indices/a-tree/d/ ).Book ChapterM. Das and S. Dehuri , Particle Swarm Optimization for Single and Multi-objectiveClassification Problem , In V. K. Mago, et al. (Eds.), Cross Disciplinary Applica-tions of Artificial Intelligence and Pattern Recognition: Advancing Technologies, IGIG lobal, 2011 (Accepted).S. Dehuri , S. Ghosh, and C.

5 A. C. Coello, An Introduction to Swarm Intelligence forMulti-objective Problems in Data Mining , Coello, S. Dehuri and S. Ghosh(Eds.) Swarm Intelligence for Multi-objective Problems in Data Mining, Springer-Verlag, Berlin/Heidelberg, Dehuri and Cho, A Theoretical and Empirical Study of Functional LinkNeural Networks (FLANNs) for Classification. In: M. Zhang (Eds.) Artificial HigherOrder Neural Networks for Computer Science and Engineering: Trends for EmergingApplications, IGI Global, Dehuri , Coello, Cho and A. Ghosh, A Discrete Swarm for Multi-objective Problems in Polynomial Neural Network for Classification: Data MiningPerspective. In: Coello, S. Dehuri and S. Ghosh (Eds.) Swarm Intelligencefor Multi-objective Problems in Data Mining, Springer-Verlag, Berlin/Heidelberg, Dehuri , S. Ghosh, and A. Ghosh, Genetic Algorithms for Optimization of Multi-objectives in Knowledge Discovery from Large Databases , (Eds.) A. Ghosh, , and S. Ghosh, Multi-objective Evolutionary Algorithms for Knowledge Dis-covery from Databases, Springer Berlin/Heidelberg, pp.

6 1-22, B. Misra, S. Dehuri , B. K. Panigrahi, and A. K. Nayak (Eds.), Computational In-telligence in Sensor Networks, Studies in Computational Intelligence Series, Springer-Verlag/Heidelberg, 2011 (In Press).S. Dehuri , M. R. Patra, B. B. Misra, and A. k. Jagadev (Eds.), Intelligent Tech-niques in Recommendation System: Contextual Advancements and New Methods,IGI Global, USA, 2011 (In Press).S. Dehuri , Cho and S. Ghosh (Eds.), Integration of Swarm Intelligence andArtificial Neural Networks, World Scientific Press, Dehuri and Cho (Eds.), Knowledge Mining Using Intelligent Agents, ImperialCollege Press, Peng Lim, Lakhmi C. Jain, and S. Dehuri (Eds.), Innovations in Swarm Intel-ligence, Springer-Verlag, A. Coello Coello, S. Dehuri , and S. Ghosh (Eds.), Swarm Intelligence forMulti-objective Problems in Data Mining, Springer-Verlag, Ghosh, S. Dehuri , S. Ghosh (Eds.), Multi-Objective Evolutionary Algorithms forKnowledge Discovery in Databases, Springer-Verlag, Ghosh, S.

7 Dehuri , and A. Panda, Soft Computing, India Tech, New Delhi, Dehuri , Jagadev, and Rath, An Introduction to Object Oriented Pro-gramming through C++, Published by PHI, New Delhi, INDIA, Dehuri , Rath, Das, An Introduction to Dos and Linux Commands withShell Programming, Published by ECT, Bhubaneswar, Dehuri and Rajib Mall, Application of Parallel Processing to DataWarehousing and Mining: Application and Challenges, VDM Verlag Dr. Muller,ISBN:978-3-639-09848-8, , S., A Novel Learning Scheme for Chebyshev Functional Link Neural Net-works , Advances in Artificial Neural Systems, vol. 2011, , , , B. S. P., Dehuri , S., Mall, R., and Ghosh, A., Parallel Single and Mul-tiple Objectives Genetic Algorithms: A Survey , International Journal of AppliedEvolutionary Computation, , , 58, , M., Roy, R., Dehuri , S., and Cho, , A New Approach to Associative Classi-fication based on Binary Multi-objective Particle Swarm Optimization , InternationalJournal of Applied Meta-heuristic Computing, , , pp.

8 51 73, , B. S. P. and Dehuri , S., A Survey of Parallel Single and Multi-objectiveGenetic Algorithms , IUP Journal of Computer Science, , , , 87, , B. S. P. and Dehuri , S., Parallel Computing Environments: A Review ,IETE Journal of Technical Review, , , , , H., Dehuri , S., and Ghosh, A., Multi-objective Fuzzy Classification Rule Min-ing Using Genetic Algorithms: A Survey , IUP Journal of Information Technology,vol. VII, ,pp7 34, , S., Misra, B. B., Ghosh, A., Cho, , A Condensed Polynomial Neu-ral Network for Classification Using Swarm Intelligence , Applied Soft computingJournal, , , 2011. (SCIE, )Pradhan, L., Dehuri , S., Mahapatro, B. B., and Panda, A. K., A Study of Compu-tational Intelligence in Agriculture , CSI Communications, vol. 34, no. 7, , , L., Mohapatro, B. B., Panda, A. K., and Dehuri , S. Bridging the digitalDivide and a Comprehensible Model to Develop Handy E-government in developingCountries , CSI Communications, vol. 34, no.

9 3, pp. 35-40, , P. and Mishra, B. S. P. and Dehuri , S., A Multi-objective Genetic Algo-rithms for Solving Vehicle Routing Problem , International Journal of InformationTechnology & Knowledge Management, , , , S. and Cho, , Evolutionary Optimized Features in Functional LinkArtificial Neural Network for Classification , Expert Systems with Applications: anInternational Journal, , , pp. 4379-4391, 2010 (SCI), IF= , S., Jagadev, A. K., Dehuri , S., Mall, R., A Survey on Feature Selection Meth-ods , International Journal on Computer Engineering and Information Technology(IJCEIT), vol. 3, no. 4, pp. 6-12, , S., Cho, , A Hybrid Genetic Based Functional Link Artificial NeuralNetwork with a Statistical Comparison of Classifiers over Multiple Datasets , Neu-ral Computing and Applications, Springer, , , , 2009 (SCIE),IF= , S., Jagadev, A. K., Dehuri , S., Mall, R, Knowledge Discovery from Bio-medicalData Using a Hybrid PSO/Bayesian Classifier , Technia: International Journal ofComputing Science and Communication Technologies, vol.

10 2, no. 1, pp. 364-371, , S., Cho, S. B., A Comprehensive Survey on Functional Link Neural Networksand an Adaptive PSOBP learning for CFLNN , Neural Computing and Applications,Springer, , , pp. 187-205, 2009, (SCIE), IF= , S., Das, M. N., Jagadev, A. K., Ghosh, A., Application of Parallel GeneticAlgorithms for Attribute Selection in Knowledge Discovery in Databases , Interna-tional Journal of Computing and Information Technology (IJCIT), 2009 (Accepted). Dehuri , S., Cho, , Multi-criterion Pareto based particle swarm optimized poly-nomial neural network for classification: A Review and State-of-the-Art. ComputerScience Review, Elsevier Science, vol. 3, no. 1, pp. 19-40, , L., Mohapatra, B. B., Dehuri , S., Panda, A. K., Enhancement of E-readiness Ranking of a Nation by Solving Multiple Campaign Assignment ProblemUsing Differential Evolution. International Journal of Electronic Finance, Inder-science, vol. 3, , pp. 77-95, , S., Ghosh, A. and Cho, , Particle swarm optimized polynomial neuralnetwork for classification: A Multi-objective View.