Rudy SETIONO

Associate Professor
Assistant Dean, Undergraduate Studies

Ph.D. (Computer Science, University of Wisconsin-Madison)
M.Sc. (Computer Science, University of Wisconsin-Madison)
B.Sc. (Computer Science, Eastern Michigan University)
COM2-04-13
651 66297

Research Areas

  • Data Science & Business Analytics

Research Interests

  • Nonlinear Optimization
  • Data Mining
  • Neural Networks
  • Unconstrained optimization
  • Neural network construction and pruning
  • Rule extraction from neural networks and its applications

Profile

Dr. Rudy Setiono is Associate Professor in the School of Computing at the National University of Singapore. He received a B.S. degree in Computer Science (1984) from Eastern Michigan University, and M.S. (1986) and Ph.D. degrees (1990) in Computer Science from the University of Wisconsin-Madison. Since August 1990, he has been with the National University of Singapore. Dr. Setiono's research interests include unconstrained optimization, neural network construction and pruning, and rule extraction from neural networks and its applications. He has published in reputable international journals such as SIAM Journal on Control and Optimization, European Journal of Operational Research, Journal of Optimization Theory and Applications, IEEE Transactions on Neural Networks, IEEE Transactions on Data and Knowledge Engineering, IEEE Transactions on Systems, Man, and Cybernetics, Neural Computation, Neurocomputing, and Connection Science.

Current Projects

  • Application of neural networks in business

Selected Publications

  • Y. Hayashi, R. Setiono and A. Azcarraga. Neural network training and rule extraction with augmented discretized input, Neurocomputing, accepted for publication.

  • R. Setiono, A. Azcarraga and Y. Hayashi. Using sample selection to improve accuracy and simplicity of rules extracted from neural networks for credit scoring applications, International Journal of Computational Intelligence and Applications,  Vol. 14, No. 4, pages 1550021-1-20, 2015.

  • A. Azcarraga, A. Caronongan, R. Setiono and S. Manalili. Validating the stable clustering of songs in a structured 3D SOM.  In Proceedings of IJCNN 2016, International Joint Conference on Neural Networks, Vancouver, Canada, July 2016.

  • R. Setiono. Determining relevant variables and interactions in credit scoring data with neural network pruning and rule extraction. In Proceedings of the 45th  International Decision Sciences Institute Conference, Tampa, USA, November 2014.

  • A. Azcarraga, P. Tensuan and R. Setiono. Tagging  documents using neural networks based on local word features. In Proceedings of IJCNN 2014, International Joint Conference on Neural Networks, Beijing, China, July 2014, pages 724-731. 

  • R. Setiono, A. Azcarraga, and Y. Hayashi. MofN rule extraction from neural networks trained with discretized input. In  Proceedings of IJCNN 2014, International Joint Conference on Neural Networks,  Beijing, China, July 2014, pages 1079-1086.  

  • J. Hartanto and   R. Setiono. Combining Chi2 discretization and neural networks for efffective predictive analytics. In Proceedings of the 44th  International Decision Sciences Institute Conference, Baltimore, USA, November 2013. 

  • A. Azcarraga,  Y. Hayashi and R. Setiono. Credit scoring using  neural networks with augmented discretized inputs. In Proceedings of the 12th International Decision Sciences Institute Conference, Bali, Indonesia, July 2013, pages 1412-1426. 

  • A. Azcarraga,  C. Enriquez, Y. Hayashi and R. Setiono. Using neural network for visualizing poverty. In Proceedings of the 12th  International Decision Sciences Institute Conference, Bali, Indonesia, July 2013, pages 1005-1023. 

Awards & Honours

Teaching (2019/2020)

  • BT4240: Machine Learning for Predictive Data Analytics
  • IS5152: Decision Making Technologies
  • BT2101: Decision Making Methods and Tools