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Main Campus
2008 Nitschke Hall
Mail Stop 308
2801 W. Bancroft St.
Toledo, OH 43606-3390
Phone: (419) 530-8140
Fax: (419) 530-8146

Dr. Gursel Serpen

serpen

Associate Professor

Contact Information

EECS Department
The University of Toledo
Toledo,OH 43606 
Tel: (419) 530-8158 
Office: NI 2027 
E-mail: gursel.serpen@utoledo.edu 

Recent Courses

  • EECS 6/8360-Knowledge Based Systems
  • EECS 6/8370-Artificial Neural Nets
  • EECS 4/5740-Artificial Intelligence
  • EECS 4/5750-Machine Learning
  • EECS 4010/4020-Senior Design I & II
  • EECS 3100-Microsystem Design
  • EECS 2110-Computer Architecture and Organization
  • EECS 1100-Digital Logic Design

Research Interests:

Intelligent and adaptive systems (wireless sensor networks), Design and development of "smart/intelligent algorithms, rule based systems, and agents" (knowledge based systems), Empirical model development through input/output data for blackbox systems or processes (machine learning), Classifier development through empirical means (learning from data) (pattern recognition, neural net and machine learning), Probabilistic knowledge base/inferencing model construction from data (Bayesian belief network), Hybrid intelligent systems for regression (linear and nonlinear) and classification: ensembles, Computation complexity analysis and management of algorithms (space and time cost of algorithms), Design and development of intelligent algorithms for real-time and/or distributed environments

Biography

Dr. Serpen received a Ph. D. in Electrical Engineering (with specialization in computer engineering) from the Old Dominion University, Norfolk, Virginia in 1992. He worked as an application and senior software engineer for Integrated Systems, Inc. (acquired by WindRiver Systems, Inc in late 90s) of Santa Clara, California between 1992 and 1993. He joined the Computer Science and Engineering Department at the University of Toledo as a faculty member in 1993. He has been serving as a faculty member with the Electrical Engineering and Computer Science Department at the University of Toledo.

Recent Publications

  • J. Li, and G. Serpen, "Adaptive and Intelligent Wireless Sensor Networks through Neural Networks: An Illustration for Sensor Network Infrastructure Adaptation", Applied Intelligence, pp. 1-20, 2016
  • G. Serpen, L. Liu, "Parallel and distributed neurocomputing with wireless sensor networks", Neurocomputing (2015),Volume 173, pp. 1169-1182, 2016
  • G. Serpen and C. Dou, "Automated Robotic Parking Systems: Real-Time, Concurrent and Multi-Robot Path Planning in Dynamic Environments", Applied Intelligence, Vol. 42, pp. 231-251, 2015
  • F. Assaad and G. Serpen, "Transformation based Score Fusion Algorithm for Multi-modal Biometric User Authentication through Ensemble Classification", Procedia Computer Science, Vol. 61, pp. 410-415, 2015
  • J. Debnath and G. Serpen, "Real-Time Optimal Scheduling of a Group of Elevators in a Multi-Story Robotic Fully-Automated Parking Structure", Procedia Computer Science, Vol. 61, pp. 507-514, 2015
  • G. Serpen and Z. Gao, "Complexity analysis of multilayer perceptron neural network embedded into a wireless sensor network", Procedia Computer Science, Vol. 36, pp. 192-197, 2014
  • G. Serpen and Z. Gao, "Empirical Model Development for Message Delay and Drop in Wireless Sensor Networks", Procedia Computer Science, Vol. 36, pp. 353-358, 2014
  • D. Baumgartner and G. Serpen, "Performance of global-local hybrid ensemble versus boosting and bagging ensembles", Machine Learning and Cybernetics, Springer Berlin/Heidelberg, Volume 4, Issue 4, pp 301-317, 2013
  • D. Baumgartner and G. Serpen, "A Design Heuristic for Hybrid Classification Ensembles in Machine Learning", Intelligent Data Analysis. Vol. 16, No. 2, pp. 233-246, 2012
  • S. Pathical and G. Serpen, "Hybrid random subsample classifier ensemble for high dimensional data sets", Hybrid Intelligent Systems, Vol. 9, No. 2, pp. 91-103, 2012
  • S. Shepard, A. McSweeny, G. Serpen, and A. Fedorov, "Exploiting mid-range DNA patterns for sequence classification: binary abstraction Markov models", Nucleic Acids Research, Vol. 40. No. 11, pp. 4754-4764, 2012
  • J. Sangtani and G. Serpen, "Composition of Optimal Service Workflows with Quality-of-Service Enabled Multi-Criteria Uniform Cost Search Algorithm", Systems and Service-Oriented Engineering, Vol. 3, pp. 1-25, 2012
Last Updated: 4/13/17