Dr. Rung-Tzuo Liaw 廖容佐

Assistant Professor

Computational Intelligence Lab

Department of Computer Science and Information Engineering

Fu Jen Catholic University, Taiwan
Office: Room 628, Divine Word Academic Highrise

Email: rtliaw_at_csie.fju.edu.tw

Phone: +886-(0)2-29053875

Education                                                                                            

u  PhD, Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan. (2017/07)

u  MS, Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan. (2012/06)

u  BS, Department of Psychology, National Taiwan University, Taiwan. (2009/06)

Research Interests                                                                                     

u  Evolutionary Computation

u  Evolutionary Multitasking and Transfer Learning

u  Evolutionary Learning and Data Mining

u  Data-driven Optimization and Surrogates

u  Multi-objective Optimization

Honors and Awards                                                                                    

u  Merit PhD Thesis Award, Taiwanese Association for Artificial Intelligence.

u  CEC’2017 Competition on Multitask Optimization First Runner Up.

u  Honorary Member of The Phi Tau Phi Scholastic Honor Society of the Republic of China 2014.

Teaching                                                                                             

u  Computer Programming (C and C++)

u  An Introduction to Computer Science

u  Operating System (in English)

u  Bio-inspired Computing

u  Metaheuristic Algorithms

Publications                                                                                         

Journal Papers

1.           R.-T. Liaw. A cooperative coevolution framework for evolutionary learning and instance selection. Swarm and Evolutionary Computation, 62:100840, 2021.

2.           R.-T. Liaw, and C.-K. Ting. Evolution of biocoenosis through symbiosis with fitness approximation for many-tasking optimization. Memetic Computing, 12(4): 399–417, 2020.

3.           C.-K. Ting, R.-T. Liaw, T.-C. Wang, and T.-P. Hong. Mining fuzzy association rules using a memetic algorithm based on structure representation. Memetic Computing, 10(1):15–28, 2018.

4.           F.-I. Chung, R.-T. Liaw, Z.-Y. Jhuang, S.-Y. Hung, and C.-K. Ting. A novel book recommendation system based on multi-level association mining. Journal of Library and Information Science Research, 13(1), 2018.

5.           C.-K. Ting, T.-C. Wang, R.-T. Liaw, and T.-P. Hong. Genetic algorithm with a structure-based representation for genetic-fuzzy data mining. Soft Computing, 21(11):2871–2882, 2017.

6.           C.-K. Ting, X.-L. Liao, Y.-H. Huang, and R.-T. Liaw. Multi-vehicle selective pickup and delivery using metaheuristic algorithms. Information Sciences, 406–407:146–169, 2017.

Conference Papers

1.           T.-C. Wang, and R.-T. Liaw. Multifactorial Genetic Fuzzy Data Mining for Building Membership Functions. In Proceedings of IEEE Congress on Evolutionary Computation, PP, 2020.

2.           T.-C. Wang, C.-Y. Lin, R.-T. Liaw, and C.-K. Ting. Empirical analysis of island model on large scale global optimization. In Proceedings of IEEE Congress on Evolutionary Computation, pages 342–349, 2019.

3.           R.-T. Liaw and C.-K. Ting. Evolutionary manytasking optimization based on symbiosis in biocoenosis. In Proceedings of The Thirty-Third AAAI Conference on Artificial Intelligence, 2019.

4.           R.-T. Liaw and C.-K. Ting. Incorporating fitness inheritance and k-nearest neighbors for evolutionary dynamic optimization. In Proceedings of IEEE Congress on Evolutionary Computation, pages 1345–1352, 2018.

5.           R.-T. Liaw and C.-K. Ting. Evolutionary many-tasking based on biocoenosis through symbiosis: A framework and benchmark problems. In Proceedings of IEEE Congress on Evolutionary Computation, pages 2266–2273, 2017.

6.           R.-T. Liaw, Y.-W. Chang, and C.-K. Ting. Solving the selective pickup and delivery problem using max-min ant system. In Proceedings of International Conference on Swarm Intelligence, pages 293–300, 2017.

7.           T.-C. Wang, R.-T. Liaw, and C.-K. Ting. MOEA/D using covariance matrix adaptation evolution strategy for complex multi-objective optimization problems. In Proceedings of IEEE Congress on Evolutionary Computation, pages 983–990, 2016.

8.           R.-T. Liaw and C.-K. Ting. Enhancing covariance matrix adaptation evolution strategy through fitness inheritance. In Proceedings of IEEE Congress on Evolutionary Computation, pages 1956–1963, 2016.

9.           C.-K. Ting, T.-C. Wang, and R.-T. Liaw. An efficient representation for genetic-fuzzy mining of association rules. In Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, volume 2, pages 599–612, 2015.

10.       C.-J. Lin, R.-T. Liaw, C.-C. Liao, and C.-K. Ting. Considering reputation in the selection strategy of genetic programming. In Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, volume 2, pages 533–542, 2015.

11.      R.-T. Liaw and C.-K. Ting. Effect of model complexity for estimation of distribution algorithm in nk landscapes. In Proceedings of IEEE Symposium on Foundations of Computational Intelligence, pages 76–83, 2013.

Professional Activities                                                                                 

Editorial Board Member, Memetic Computing, Springer (2020-)

Chair, IEEE CIS ISATC Intelligent Network Systems Task Force (2021-)

Chair, Special Session on Evolutionary Computation in Intelligent Transportation Systems (CEC 2019)

Co-chair, Special Session on Intelligent Transportation and Logistics Networks (WCCI 2018)