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Theses by Dr. Gursel Serpen

List of selected theses and dissertations supervised by Dr. Gursel Serpen.

MS Theses & Projects

  • Dustin Baumgartner, Thesis Title: A New Ensemble Design Based on Global-Local Learners, In Progress.
  • Santhosh Pathical, Thesis Title: Feature Space Partitioning for High-Dimensional Data Sets for Improved Performance within Ensemble Learning Context, In Progress.
  • Michael J. Riesen, Project Title: Development of A Bayesian Belief Network Query Tool and Automatic Query Generation for the NCVS Data, December 2007.
  • Mike Orra, Project Title: Instantiating a Knowledge Based Artificial Neural Network based on PIOPED Criteria and Prediction of Retail Sales Trends with Artificial Neural Networks Using Economic Indicators, January 2006.
  • Mike Orra, Project Title: Prediction of Retail Sales Trends with Artificial Neural Networks Using Economic Indicators, May 2005.
  • Sasha Kozorez, Project Title: Theoretical and Empirical Explorations of Simultaneous Recurrent Neural Network Dynamics, March 2004.
  • Mahesh Sabhnani, Thesis Title: Development of An Intrusion Detection System Through Machine Learning and Rule Based Algorithms for Networked Computing, August 2002.
  • Rama Iyer, Thesis Title: Lung Outline Reconstruction for Ventilation-Perfusion Images Towards PIOPED-Compliant Feature Extraction, August 2001.
  • Yifeng Xu, Thesis Title: Dynamic System Analysis of Simultaneous Recurrent Neural Network", August 2001.
  • Vishvanath Acharya, Thesis Title: Fuzzy Inference System for Diagnosis of Pulmonary Embolism Using V/Q Scans", May 2000.

Undergraduate Research Projects & Honors Thesis

  • Abdul Dakkak, Project Title: Optimization of Operational Aspects of Wireless Sensor Networks in Analogy with Artificial Neural Networks, In Progress
  • Joel Corra, NSF-REU Research Project Title: Training Simultaneous Recurrent Neural Network with A Non-recurrent Learning Algorithm, August 2001.
  • Jeff Geib, NSF-REU Research Project Title: Simultaneous Recurrent Neural Networks for Large Scale Optimization, August 2000.
  • Jason Bechtel, Honors Thesis Title: Authentication Using A Neural Network to Identify Users by Typing Characteristics, August 2000.

List of Selected Publications by Dr. Gursel Serpen.

  • G. Serpen, D. K. Tekkedil, and M. Orra, "A Knowledge Based Artificial Neural Network Classifier for Pulmonary Embolism Diagnosis," Computers in Biology and Medicine, 2008 Feb; 38(2):204-220.
  • G. Serpen, "Hopfield Network as Static Optimizer: Learning the Weights and Eliminating the Guesswork," Neural Processing Letters, 2008 Feb; 27(1):1-15.
  • G. Serpen and A. Patwardhan, "Enhancing Computational Promise of Neural Optimization for Graph-Theoretic Problems in Real-Time Environment," Dynamics of Continuous, Discrete, and Impulsive Systems, Part A Suppl., Advances in Neural Networks, Vol. 14(S1), pp. 168-176, 2007.
  • G. Serpen and M. Sabhnani, "Measuring Similarity in Feature Space of Knowledge Entailed by Two Separate Rule Sets," Knowledge Based Systems, Vol. 19, pp. 67-76, 2006.
  • G. Serpen, "A Heuristic and Its Mathematical Analogue within Artificial Neural Network Adaptation Context," Neural Network World, Vol. 2/05, pp. 129-136, 2005.
  • G. Serpen and Y. Xu, "Theoretical Exploration on Local Stability of Simultaneous Recurrent Neural Network for Static Combinatorial Optimization," Neural Information Processing – Letters and Reviews, Vol. 2, No. 2, pp. 39-46, 2004.
  • G. Serpen, "Managing Spatio-Temporal Complexity in Hopfield Neural Network Simulations for Large-Scale Static Optimization," Mathematics and Computers in Simulation, pp. 279-293, 2004.
  • M. Sabhnani and G. Serpen, "On Failure of Machine Learning Algorithms for Detecting Misuse in KDD Intrusion Detection Data Set", Intelligent Data Analysis, Vol. 8, No. 4, pp. 403-415, 2004.
  • G. Serpen and Y. Xu, "Training Simultaneous Recurrent Neural Network with Non-recurrent Backpropagation Algorithm," Neural Computing and Applications, Vol. 12, No. 1, pp. 1-9, 2003.
  • G. Serpen and Y. Xu, "Weight Initialization for Simultaneous Recurrent Neural Network Trained with A Fixed-Point Learning Algorithm," Neural Processing Letters, Vol. 17, No. 1, pp. 33-41, 2003.
  • G. Serpen, R. Iyer, H. Elsamaloty, and I. Parsai, "Automated Lung Outline Reconstruction in Ventilation-Perfusion Scans Using Principal Component Analysis Techniques," Computers in Biology and Medicine, Vol. 33, pp. 119-142, 2003.
Last Updated: 2/9/17