YAO, Xin    Department Head



Room 908, Building A7, Nanshan i-Park

Research Area:

Neural Computation; Evolutionary Computation; Machine Learning; Big Data Analytics; Intelligent Optimisation; Smart Logistic, etc.

Educational Background

◆ 1985-1990,University of Science and Technology of China,PhD

◆ 1982-1985,North China Institute of Computing Technology,M.S.

◆ 1978-1982,University of Science and Technology of China,B.S.

Professional Experience

2016-: Chair Professor of Computer Science and Engineering Department, Southern University of Science and Technology, Shenzhen, China

1999-2016: Chair (Professor) of Computer Science, University of Birmingham, UK

1992-1999: Lecturer, Senior Lecturer, and Associate Professor, School of Computer Science, University College, University of New South Wales, Australian Defence Force Academy, Canberra, Australia

1991-1992: Postdoctoral Research Fellow (Level B), CSIRO Division of Building, Construction, and Engineering, Melbourne, Australia

1990-1991: Postdoctoral Fellow, Australian National University, Canberra, Australia

Honors & Awards

Fellow of IEEE (since 2003)

National Distinguished Scholar

2013 IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award

Royal Society Wolfson Research Merit Award holder (since 2012)

Thomson Reuters - 2016 Highly Cited Researcher

2017 IEEE CIS Meritorious Service Award

2001 IEEE Donald G. Fink Prize Paper Award

2011 IEEE Transactions on Neural Networks Outstanding Paper Award

2017/2016/2010 IEEE Transactions on Evolutionary Computation Outstanding Paper Award

31 October 2013: The Hsue-Shen Tsien International Distinguished Scientists Lecturer, Chinese Association of Automation, Beijing, China.

2 November 2010: Distinguished "Leon the Mathematician" Lecturer, Department of Informatics, Aristotle University of Thessaloniki, Greece.

Sterling Hou Lecturer, University of Missouri - Columbia, Columbia, MO 65211, USA, 28 October 2005.

Selected Publication

1. M. Li, X. Yao(2019). Quality Evaluation of Solution Sets in Multiobjective Optimisation: A Survey. ACM Computing Surveys (CSUR), 52(2), 26.

2. D. Yazdani, M. N. Omidvar, T. T. Nguyen, J. Branke, X. Yao(2019). Scaling Up Dynamic Optimization Problems: A Divide-and-Conquer Approach. IEEE Transactions on Evolutionary Computation.

3. E. Fernandes, A. {de Carvalho}, X. Yao (2019). Ensemble of Classifiers based on MultiObjective Genetic Sampling for Imbalanced Data. IEEE Transactions on Knowledge and Data Engineering.

4. C. Wang, C. Xu, X. Yao, D. Tao(2019). Evolutionary generative adversarial networks. IEEE Transactions on Evolutionary Computation.

5. C. He, L. Li, Y. Tian, X. Zhang, R. Cheng, Y. Jin,X. Yao (2019). Accelerating Large-scale Multi-objective Optimization via Problem Reformulation. IEEE Transactions on Evolutionary Computation.

6. B. Kazimipour, M.N. Omidvar, A.K. Qin, X. Li,X. Yao (2019). Bandit-based cooperative coevolution for tackling contribution imbalance in large-scale optimization problems. Applied Soft Computing, 76, 265-281.

7. S. Wang, L. L. Minku, N. Chawla, X. Yao (2019). Learning in the Presence of Class Imbalance and Concept Drift. Neurocomputing.

8. L. Song, L.L. Minku and X. Yao (2019). Software Effort Interval Prediction via Bayesian Inference and Synthetic Bootstrap Resampling. ACM Transactions on Software Engineering and Methodology (TOSEM), 28(1), 5.

9. M. Li, X. Yao (2019, March). An empirical investigation of the optimality and monotonicity properties of multiobjective archiving methods. In International Conference on Evolutionary Multi-Criterion Optimization (pp. 15-26). Springer, Cham.

10.Y. Sun, K. Tang, Z. Zhu,X. Yao (2018). Concept drift adaptation by exploiting historical knowledge. IEEE transactions on neural networks and learning systems, (99), 1-11.

11.X. Lu, S. Menzel, K. Tang, X. Yao (2018). Cooperative co-evolution-based design optimization: a concurrent engineering perspective. IEEE Transactions on Evolutionary Computation, 22(2), 173-188.

12.R. Cheng, M. Li, K. Li, X. Yao (2018). Evolutionary Multiobjective Optimization-Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection. IEEE Transactions on Evolutionary Computation, 22(5), 692-706.

13.K. Li, R. Chen, G. Min, X. Yao (2018). Integration of preferences in decomposition multiobjective optimization. IEEE transactions on cybernetics, (99), 1-12.

14.T. Chen, K. Li, R. Bahsoon, X. Yao (2018). FEMOSAA: Feature-Guided and Knee-Driven Multi-Objective Optimization for Self-Adaptive Software. ACM Transactions on Software Engineering and Methodology (TOSEM), 27(2), 5.

15.T. Chen, R. Bahsoon, X. Yao (2018). A survey and taxonomy of self-aware and self-adaptive cloud autoscaling systems. ACM Computing Surveys (CSUR), 51(3), 61.

16.R. G. F. Soares, H. Chen,X. Yao (2018). Efficient cluster-based boosting for semisupervised classification. IEEE transactions on neural networks and learning systems, (99), 1-14.

17.Y. Li, B. Jiang, H. Chen, X. Yao (2018). Symbolic Sequence Classification in the Fractal Space. IEEE Transactions on Emerging Topics in Computational Intelligence.

18.K. Li, R. Chen, G. Fu,X. Yao (2018). Two-archive evolutionary algorithm for constrained multi-objective optimization. IEEE Transactions on Evolutionary Computation.

19.K. Li, R. Chen, D. Savic,X. Yao (2018). Interactive Decomposition Multi-Objective Optimisation via Progressively Learned Value Functions. IEEE Transactions on Fuzzy Systems.

20.R. Cheng, M. N. Omidvar, A. H. Gandomi, B. Sendhoff, S. Menzel,X. Yao (2018). Solving Incremental Optimization Problems via Cooperative Coevolution. IEEE Transactions on Evolutionary Computation.

21.Z. Su, G. Zhang, F. Yue, L. Chang, J. Jiang,X. Yao (2018). SNR-Constrained Heuristics for Optimizing the Scaling Parameter of Robust Audio Watermarking. IEEE Transactions on Multimedia, 20(10), 2631-2644.

22.H. Chen, B. Jiang,X. Yao (2018). Semisupervised Negative Correlation Learning. IEEE transactions on neural networks and learning systems, (99), 1-14.

23.M. Wang, B. Li, G. Zhang,X. Yao (2018). Population Evolvability: Dynamic Fitness Landscape Analysis for Population-Based Metaheuristic Algorithms. IEEE Transactions on Evolutionary Computation, 22(4), 550-563.

24.P. Yang, K. Tang,X. Yao (2018). Turning high-dimensional optimization into computationally expensive optimization. IEEE Transactions on Evolutionary Computation, 22(1), 143-156.

25.S. Wang, L. L. Minku,X. Yao (2018). A systematic study of online class imbalance learning with concept drift. IEEE transactions on neural networks and learning systems, (99), 1-20.

26.Z. Gong, H. Chen, B. Yuan,X. Yao (2018). Multiobjective Learning in the Model Space for Time Series Classification. IEEE transactions on cybernetics, (99), 1-15.

27.R. Cheng, C. He, Y. Jin,X. Yao (2018). Model-based evolutionary algorithms: a short survey. Complex & Intelligent Systems, 4(4), 283-292.

28.L. Song, L. L. Minku, X. Yao (2018, October). A novel automated approach for software effort estimation based on data augmentation. In Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering(pp. 468-479). ACM.

29.C. Qian, C. Bian, Y. Yu, K. Tang, X. Yao (2018, July). Analysis of noisy evolutionary optimization when sampling fails. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 1507-1514). ACM.

30.D. Yazdani, J. Branke, M. N. Omidvar, T. T. Nguyen, X. Yao (2018, July). Changing or keeping solutions in dynamic optimization problems with switching costs. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 1095-1102). ACM.

31.T. Chen, M. Li, X. Yao (2018, July). On the effects of seeding strategies: A case for search-based multi-objective service composition. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 1419-1426). ACM.

32.M. Li, T. Chen, X. Yao (2018, May). A Critical Review of" A Practical Guide to Select Quality Indicators for Assessing Pareto-Based Search Algorithms in Search-Based Software Engineering": Essay on Quality Indicator Selection for SBSE. In 2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER) (pp. 17-20). IEEE.

33.S. Shi, Y. Chen, X. Yao (2018, May). Computing-Inspired Detection of Multiple Cancers. In 2018 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.

34.C. Qian, Y. Zhang, K. Tang, X. Yao (2018, April). On multiset selection with size constraints. In Thirty-Second AAAI Conference on Artificial Intelligence.

35.T. Chen, R. Bahsoon, S. Wang, X. Yao (2018, March). To Adapt or Not to Adapt?: Technical Debt and Learning Driven Self-Adaptation for Managing Runtime Performance. In Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering (pp. 48-55). ACM.

36.M. Li, L. Zhen, X. Yao (2017). How to read many-objective solution sets in parallel coordinates [educational forum. IEEE Computational Intelligence Magazine, 12(4), 88-100.

37.M. N. Omidvar, M. Yang Y. Mei, X. Li and X. Yao (2017). DG2: A faster and more accurate differential grouping for large-scale black-box optimization. IEEE Transactions on Evolutionary Computation, 21(6), 929-942.

38.Y. Chen, S. Shi,X. Yao, T. Nakano (2017). Touchable computing: Computing-inspired bio-detection. IEEE transactions on nanobioscience, 16(8), 810-821.

39.M. Yang, M. N. Omidvar, C. Li, X. Li, Z. Cai, B. Kazimipour, X. Yao (2017). Efficient resource allocation in cooperative co-evolution for large-scale global optimization. IEEE Transactions on Evolutionary Computation, 21(4), 493-505.

40.G. Zhang, Z. Su, M. Li, F. Yue, J. Jiang,X. Yao (2017). Constraint handling in NSGA-II for solving optimal testing resource allocation problems. IEEE Transactions on Reliability, 66(4), 1193-1212.

41.B. Jiang, H. Chen, B. Yuan,X. Yao (2017). Scalable graph-based semi-supervised learning through sparse Bayesian model. IEEE Transactions on Knowledge and Data Engineering, 29(12), 2758-2771.

42.B. Yuan, H. Chen, X. Yao (2017). Optimal relay placement for lifetime maximization in wireless underground sensor networks. Information Sciences, 418, 463-479.

43.G. Zhang, Z. Su, M. Li, M. Qi, J. Jiang,X. Yao (2017). A Task-Oriented Heuristic for Repairing Infeasible Solutions to Overlapping Coalition Structure Generation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, (99), 1-17.

44.L. Zhang, K. Tang, X. Yao (2017). Log-normality and skewness of estimated state/action values in reinforcement learning. In Advances in Neural Information Processing Systems (pp. 1804-1814).

45.R. G. F. Soares, H. Chen,X. Yao (2017). A cluster-based semisupervised ensemble for multiclass classification. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(6), 408-420.

46.R. Cheng, M. Li, Y. Tian, X. Zhang, S. Yang, Y. Jin,X. Yao (2017). A benchmark test suite for evolutionary many-objective optimization. Complex & Intelligent Systems, 3(1), 67-81.

47.L. Zhen,M. Li, R. Cheng, D. Peng, X. Yao (2017, November). Adjusting parallel coordinates for investigating multi-objective search. In Asia-Pacific Conference on Simulated Evolution and Learning (pp. 224-235). Springer, Cham.

48.H. K. Singh, X. Yao (2017, November). Improvement of Reference Points for Decomposition Based Multi-objective Evolutionary Algorithms. In Asia-Pacific Conference on Simulated Evolution and Learning (pp. 284-296). Springer, Cham.

49.P. T. Thuong, N. X. Hoai,X. Yao (2017, July). Combining conformal prediction and genetic programming for symbolic interval regression. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 1001-1008). ACM.

50.Y. Chen, S. Shi, X. Yao, T. Nakano, P. Kosmas (2017, July). Touchable computation: Computing-inspired bio-detection. In 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (pp. 1-5). IEEE.

51.J. Chen, M. N. Omidvar, M. Azad, X. Yao (2017, June). Knowledge-based particle swarm optimization for PID controller tuning. In 2017 IEEE Congress on Evolutionary Computation (CEC) (pp. 1819-1826). IEEE.

52.R. Cheng, M. Li, X. Yao (2017, June). Parallel peaks: A visualization method for benchmark studies of multimodal optimization. In 2017 IEEE Congress on Evolutionary Computation (CEC) (pp. 263-270). IEEE.

53.I. L. Yen, F. Bastani, Y. Huang, Y. Zhang, X. Yao (2017, June). SaaS for automated job performance appraisals using service technologies and big data analytics. In 2017 IEEE International Conference on Web Services (ICWS) (pp. 412-419). IEEE.