Professor Yaochu Jin

Chair in Computational Intelligence

Qualifications: BSc MSc PhD Dr.-Ing. FBCS SMIEEE MINNS

Email:
Phone: Work: 01483 68 6037
Room no: 35 BB 02

Office hours

Monday: 12:00-14:00pm

Further information

Biography

In the news: A BBC interview on SWARM-ORGAN.

I am Professor of Computational Intelligence, Head of the Nature Inspired Computing and Engineering (NICE) group, Director of PGR, Department of Computing, University of Surrey. I obtained the BSc, MSc and PhD degrees from Zhejiang University, Hangzhou, China and the Dr.-Ing. from Ruhr-University Bochum, Germany.

I am a Distinguished Lecturer of IEEE and Vice President for Technical Activities of the IEEE Computational Intelligence Society. I am an Associate Editor of  IEEE Transactions on Cybernetics, IEEE Transactions on Nanobioscience, IEEE Computational Intelligence Magazine, Soft Computing Journal (Springer), BioSystems (Elsevier) and International Journal of Fuzzy Systems. I am also an Editorial Board Member of the Evolutionary Computation Journal (MIT Press). I am a past Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man and Cybernetics, Part C, Applications and Reviews, and the IEEE Transactions on Control Systems Technology.

I am a Member of EPSRC Peer Review College and EPSRC ICT Responsive Mode Panel, a Panel Member of EC FP7 FET/HBP grants, a Panel Review Member of Academy of Finland and a Reviewer of VQR (Research Assessment), Italy.

I am the Founding General Co-Chair of the IEEE Symposium on Computational Intelligence in Big Data, IEEE Symposium on Computational Intelligence in Multi-Criterion Decision-Making (IEEE MCDM), IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (IEEE CIDUE). I was General Chair of 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2012) and Program Chair of 2013 IEEE Congress on Evolutionary Computation.

Research Interests

I am particularly interested in nature-inspired, real-world driven problem-solving. Related research topics range from big data driven evolutionary optimization, surrogate-assisted evolutionary optimization, robust and dynamic optimization,  multi-objective optimization, to machine learning, in particular multi-objective knowledge extraction and data mining, semi-supervised and active learning, ensemble learning and deep reservoir learning. Current application areas include evolutionary design optimization, e.g., wing high-lift systems, fuselage of aircraft, turbine engines, vehicles; decision support systems, such as natural gas terminal design, intelligent heating systems design, energy management in buildings; image processing and image identification; process optimization and control, including steel-making and continuous casting, and control of multi-level carbon fibre stretching processes.        

My science-driven research interests lie in interdisciplinary areas that bridge the gap between computational intelligence and machine learning, computational neuroscience, and computational biology. My current main topics include evolutionary developmental systems, computational modeling of neural plasticity, morphogenetic swarm robots, bioinformatics, in particular reconstruction of biological gene regulatory networks. 

Highly motived students interested in doing a PhD at Surrey are encouraged to contact me by Email. If you intend to apply for a PhD scholarship, please submit your PhD application by the end of March in each calendar year for the October entry. Note that a minimum of 6.5 is required for overall IELTS and all single items.

如果你有兴趣申请萨里大学的博士生奖学金,请在每年的3月31日前申请10月份博士入学。萨里大学要求雅思(IELTS)平均成绩不低于6.5, 单项不低于6.5。 除了优良的学习成绩外, 如已经发表过高质量的论文将大大提高申请奖学金的成功率。欢迎通过Email咨询。 

Research Grants (since 06.2010):

  • State Key Laboratory of Software Engineering, Nanjing University, China, "Surrogate-assisted evolutionary optimisation using active semi-supervised learning" (PI, KFKT2013A05, CNY 40,000, 03.2013-03.2015)
  • EC FP7, "SWARM-ORGAN: A theoretical framework for swarms of GRN-controlled agents which display adaptive tissue-like organisation.", (PI, Grant Agreement No. 601062, €523,571 to Surrey, €2,221,000 in total, 03.2013-08.2016)
  • EPSRC, "Sparse multi-way digital signal processing approach for detection of deep medial temporal discharges from scalp EEG" (Co-I, £390,000, 01.2013-06.2015, PI: Dr Saeid Sanei, in collaboration with King's College London)
  • Honda Research Institute Europe, "Surrogate-assisted evolutionary many-objective optimisation" (PI, £116,733, 01.2013 - 12.2015)
  • State Key Laboratory of Synthetical Automation of Process Industry, Northeastern University, China, "Modeling and dynamic multi-objective optimisation of complex industrial processes" (PI, CNY 300,000, 08.2012-07.2014)
  • Santander Doctoral Student Award, "Evolutionary methods for generating hierarchical and multi-label classifiers", (PI, £ 5,000, 03-08.2012)
  • EPSRC KTA grant, "Optimisation of CFRP Stiffened Panels of Aircraft" (PI, in collaboration with Prof. Andrew Crocombe, GR/T10101/01, £51,112.  Industrial partner: Aero Optimal Ltd, 09.2011 - 08.2012)
  • EPSRC CASE Award: "Copyright protection and forensics of bootleg museum images" (PI, No. 10001560;  £ 89,500, Industrial Partner: Intellas UK Ltd, 01.2011-06.2014)
  • Start-up grant, Department of Computing, University of Surrey (PI, 11.2010-10.2012)

I also obtained two EPSRC DTC programs, one EPSRC DTG program and two PhD programs funded by the department of Computing.

Research Fellows, Ph.D./EngD Students, and Academic Visitors

I am the principal supervisor of the following research fellows, Ph.D. and academic visitors:

Research Fellows

  • Chaoli Sun, Research Fellow. Funded by EC FP7 SWARM-ORGAN (09/2014 -)

Ph.D. Students

  • Ataollah Ramezan Shirazi (07/2013 - ), Topic: Morphogenetic self-organisation of collective systems. Funded by EC FP7 SWARM-ORGAN. 
  • Ran Cheng (01/2013 - ), Topic: "Model-based evolutionary many-objective optimisation". Funded by Honda Research Institute Europe
  • Mohd Hanif Yusoff (04/2012 - ), Topic: "Semi-supervised learning for echo-state machines". Funded by the Malaysian government.
  • Shenkai Gu (10/2011 - ) Topic: "Semi-supervised learning for BCI-based game control".  Partly funded by the Department of Computing.
  • Tameera Rahman (10/2011- ) Topic: "Predicting suitable vaccines for foot-and-mouth disease virus based on genetic sequence". Jointly funded by the Department of Computing and FHMS.
  • Spencer Thomas (03/2011 - ) Topic: "Reconstruction of global regulatory networks governing the production of the production of antibiotics in Streptomyces bacteria".  Funded by EPSRC DTC.
  • Christopher Smith (03/2011 -) Topic: "Efficient evolutionary multi-objective optimisation of synthetic jet for active flow control". Funded by EPSRC DTC.
  • Joseph Chrol-Cannon (07/2011 - ) Topic: "Modeling neural plasticity for spatiotemporal pattern recognition". Funded by EPSRC DTG
  • Wissam Albukhanajer (01/2011 - ) Topic: "Fast and robust feature extraction for detection of bootlegged museum images". Funded by EPSRC and Intellas UK Ltd.

I am a Co-Supervisor of the following EngD students:

  • Michael Rustell (05/2011 - ) Topic: "Knowledge extraction and development of decision support systems for conceptual design of sustainable liquified nitrogen gas terminals". Funded by EPSRC and HR Wallingford Ltd.
  • Craig Brown (09/2011 -)  Topic: "Intelligent heat solutions: Concepts and strategies for product development". Funded by EPSRC and Bosch Thermotechnology

I am the secondary supervisor of a few other Ph.D. students.

Academic Visitors

  • Prof Songdong Xue, Taiyuan University of Science and Technology, China 
  • Prof Yan Wu, Xidian University, China

Main Research Topics

Computational Intelligence (CI)

Computational and Cognitive Neuroscience (CCN)

  • Evolutionary developmental neurocomputing: Understanding neural organization in evolution of primitive nervous systems through brain-body co-development; computational modelling of neural development; modelling of gene regulated synaptic, neuronal and homeostatic plasticity, developmental neural networks, uniform modelling of plasticity, autonomous learning through brain-body evolutionary co-development
  • Reservoir computing: Liquid state machines, echo state networks, plasticity and connectivity, memory capacity. input encoding
  • Computational cognitive neuroscience: Memory organization, top-down and bottom-up pathways in neural information processing, semi-supervised learning, brain machine interface

Computational Systems Biology and Bioinformatics (CSBB)

  • Computational modelling of gene regulation and cellular mechanisms underlying biological morphogenesis and signal transduction
  • Evolvability and robustness analysis of gene regulatory networks; in silico synthesis of gene regulatory dynamics
  • Mathematical modelling of biological systems and machine learning for analysis of biological data

Real-World Applications of CI, CSBB and CCN

  • Complex engineering optimisation: Multidisciplinary multi-objective aerodynamic design optimization, micro heat exchanger optimization, vehicle design and optimization, design of fuselage of aircraft, steel-making and continuous casting process, decision-making and decision support
  • Morphogenetic robotics, evolutionary developmental robotics, autonomous robotic systems, bio-inspired self-organization of collective engineered systems, morphogenetic design
  • Spatiotemporal pattern recognition, such as human behaviour recognition, medical image analysis, EEG signal classification, image forensics
  • Electric and process control and optimization, robotic control,  industrial automation, and data mining

Past Members:

  • Amiram Moshainov, Academic Visitor, Tel Aviv University, Israel (09?2013 - 08/2014)
  • Mr Kaname Narukawa, Honda Research Institute Europe, Germany (
  • Prof Xingyi Zhang, Academic Visitor, Anhui University, China (08/2013 - 08/2014)
  • Dr Hyondong Oh, Research Fellow. Funded by EC FP7 SWARM-ORGAN (04/2013 - 08/2014)
  • Ms Xin-Lan Liao, Visiting PD student, National Chung Cheng University, Taiwan, R.O.C. (09/2013 - 02/2014)
  • Dr Borys Wrobel,  Academic visitor, Polish Academy of Sciences and Adam Mickiewicz University in Poznan, Poland (06/2013-08/2013)
  • Prof Chaoli Sun,Visiting Academic Researcher, Taiyuan University of Science and Technology, China (10/2012 - 03/2013)
  • Ayang Xiao, Visiting PhD student, Harbin Institute of Technology, China (01/2012 - 04/2013)
  • Dr Sohrab Saeb, Postdoc Research Fellow (04/2012 - 04/2013)
  • Ricardo Cerri, Santander Visiting PhD student, University of Sao Paulo, Brazil (03/2012 -08/2012)
  • Dr Colin Bell, KTA Postdoc Research Fellow (09/2011-09/2012)
  • Prof. Xiaoyan Sun, Visiting Academic Researcher, China University of Mining and Technology (09/2011 - 02/2012)
  • Dr Daniel Bush, Postdoc Research Fellow (11/2010-10.2011)
  • Prof. Chuan-Kang Ting, Visiting Academic Researcher, National Chung-Cheng University, Taiwan (07/2011-08/2011)
  • Dr M. Govindarajan, Visiting Academic Researcher, Annamalai University, India (05/2011-06/2011)

Postdocs, Ph.D. and M.Sc. / Diplom Students Co-Supervised at Honda (2001-2010)

  • Postdoctoral associate, Tobias Luksch, “Robust humanoid robot object grasping and manipulation under uncertainty using evolutionary algorithms”, In collaboration with Technical University of Kaiserslauten (02/2010 - 05/2010)
  • Ph.D. student, Daniel Botman, “Genetic and cellular mechanisms for modelling controlled growth”. In collaboration with University of Amsterdam, The Netherlands (03/2010 - 05/2010)
  • Visiting Ph.D. student, Sanghoun Oh, “Evolutionary optimization of multi-modal constrained optimization problems through dynamicalization”, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea (08/2009 - 01/2010)
  • Ph.D. student, Hongliang Guo, “A hierarchical gene regulatory network for generating robust emerging behaviours for interacting collective systems”. In collaboration with Stevens Institute of Technology, Hoboken, USA (04/2009 - 05/2010)
  • Postdoctoral associate, Benjamin Inden, “Co-evolution of neural control and body plan for object grasping”. In coo-operation with the CoR-Lab Graduate School, Bielefeld University, Germany (06/2008 - 05/2010)
  • Ph.D. student, Andrea Finke, “Brain-machine interface for Asimo control”. In collaboration with the CoR-Lab Graduate School, Bielefeld University, Germany (02/2008 - 05/2010)
  • Ph.D. student, Heiko Lex, “Cognitive systems in motor adaptation”. In collaboration with the CoR-Lab Graduate School, Bielefeld University, Germany (06/2008 - 06/2010)
  • Ph.D. student Le-Minh Nghia, “Model-based approaches to large-scale, highly constrained multi-objective design optimization”. In collaboration with Nanyang Technological University, Singapore (10/2008 - 05/2010)
  • Ph.D. student, Lisa Schramm, “Co-evolution of nervous systems and morphology”. In collaboration with Fachgebiet Regelungstheorie und Robotik, TU Darmstadt, Germany (09/2007 - 05/2010)
  • Ph.D. student, Till Steiner, “Evolutionary development for system design”. In collaboration with Bielefeld University, Germany (09/2006 - 05/2010)
  • Ph.D. student, Ben Jones, “Major transitions in evolution of primary nervous systems”. In collaboration with School of Computer Science, University of Birmingham, UK (completed in 10/2009)
  • Ph.D. student, Neale Samways, “Co-evolution of functional and regulatory genes in DNA”. In collaboration with School of Computer Science, University of Birmingham, UK (completed in 02/2009 )
  • Postdoctoral associate, Breanna Studenka, “Cognitive planning in manual action”. In collaboration with the CoR-Lab Graduate School, Bielefeld University, Germany (completed in 09/2009)
  • Diploma student, Christine Becker, “Analysis and Modeling of the glycolysis of Saccharomyces cerevisiae”. In collaboration with Fachbereich Biologie, TU Darmstadt (completed in 08/2009)
  • Master student, Liuquan Yang, “Efficient CFD based design optimization using differential recurrent neural networks”. In collaboration with Cranfield University, UK (completed in 06/2009)
  • Diplom student, Jens Trommler, “Evolvability of evolutionary developmental systems”, In collaboration with Fachgebiet Regelungstheorie und Robotik, TU Darmstadt, Germany (completed in 02/2009)
  • Ph.D. student Dudy Lim, “Evolutionary optimization for computationally expensive problems”. In collaboration with Nanyang Technological University, Singapore (completed in 11/2008)
  • Ph.D. student, Aimin Zhou, “Modeling regularity in estimation of distribution algorithms for multi-objective optimization”. In collaboration with Department of Computing and Electronics Systems, University of Essex, UK (completed in 12/2008)
  • Ph.D. student, Ingo Paenke, “Interactions of evolution and learning”. In collaboration with Institut für Angewandte Informatik und Formelle Beschreibung (AIFB), University of Karlsruhe (completed in 02/2008)
  • Master student, Rob Veldkamp, “Evolution and memory”. In collaboration with Vrije University of Amsterdam (completed in 10/2007)
  • Master student, Michal Kowalczykiewicz, “Recurrent neural networks for approximation of computational fluid dynamics (CFD) simulations”. In collaboration with School of Engineering, Cranfield University, UK (completed in 05/2007)
  • Diplom student, Robin Gruna, “Analysis of redundant genotype-phenotype mapping”. In collaboration with Institut für Angewandte Informatik und Formelle Beschreibung (AIFB), University of Karlsruhe (completed in 10/2007
  • Diplom student, Lisa Schramm, “A model for nervous system development controlled by a gene regulatory network“, In collaboration with Fachgebiet Regelungstheorie und Robotik, TU Darmstadt (completed in 09/2007)
  • Diplom student, Lars Gräning, “Evolutionary multi-objective approach to analysis of ROC of neural classifiers”. In collaboration with FG Neuroinformatik und Kognitive Robotik, TU Ilmenau (completed in 01/2006)
  • Ph.D. student, Tatsuya Okabe, “Evolutionary multi-objective optimization”. In collaboration with Technische Fakultät, Universität Bielefeld (completed in 12/2004)
  • Diplom student, Ingo Paenke, Evolutionary search for robust solutions. In collaboration with Institut für Angewandte Informatik und Formelle Beschreibung (AIFB), University of Karlsruhe (completed in 05/2004)

Research Collaborations

Academic collaborators at Surrey:

Industrial Collaborators:

  • HR Wallingford
  • Bosch Thermotechnology Ltd
  • Honda Research Institute Europe
  • Airbus
  • QinetiQ
  • Intellas UK Ltd
  • Aero Optimal
  • Animal Health Research Institute

Publications

My verified Google Scholar Citation Profile: h-index = 41, i10-index =102, sum of citations = 7232 (as of 28.07.2014)

According to Thomson Reuters ISI Web of Science: h-index = 22, sum of citations = 2202 (as of 28.07.2014)

See also Research Gate, Publications Sorted by Year or DBLP Computer Science Bibliography

Authored Books

  1. Y. Jin. Evolutionary Developmental Systems -- Analysis, Synthesis and Applications of Gene Regulatory Network Models. Springer (To appear)
  2. Y. Jin.  Advanced Fuzzy Systems Design and Applications. Springer, 2003
  3. Y. Jin and J. Wang. Intelligent Control: Theory and Applications, Henan Science and Technology Publishing House, Zhengzhou, China, 1997 (in Chinese)

Edited Books / Conference Proceedings

  1. Y. Meng and Y. Jin. Bio-inspired Self-organizing Robotic Systems. Springer, 2011
  2. Y. Jin and L. Wang (Editors). Fuzzy Systems in Bioinformatics and Computational Biology. Springer, Berlin Heidelberg, 2009
  3. S. Yang, Y.S. Ong, and Y. Jin (Editors). Evolutionary Computation in Dynamic and Uncertain Environments. Springer, Berlin Heidelberg, 2007
  4. Y. Jin (editor). Multi-Objective Machine Learning. Springer, Berlin Heidelberg. 2006
  5. L. Wang and Y. Jin (editors), 2005 International Conference on Fuzzy Systems and Knowledge Discovery. LNAI 3613, LNAI 3614, Springer, August 2005
  6. F. Rothlauf, J.Branke, S. Codnoni, D.W. Corne, R. Drechsler, Y. Jin, P. Machado, E. Marchiori, J. Romerero, G.D. Smith,  G. Squillero (editors). Applications of Evolutionary Computing. LNCS 3449, Springer, March 2005
  7. Y. Jin (editor). Knowledge Incorporation in Evolutionary Computation. Springer, 2005
  8. G. Raidl, S. Cagnoni, J. Branke, D.W. Corne, R. Drechsler, Y. Jin, C.G. Johnson, P. Machado,  E. Marchiori, F. Rothlauf, G.D. Smith, G. Squillero (editors). Applications of Evolutionary Computing. LNCS 3005, Springer, April 2004

Refereed Journal Papers (in English)

  1. W. A. Albukhanajer, J. A. Briffa and Y. Jin. Evolutionary multi-objective image feature extraction in the presence of noise. IEEE Transactions on Cybernetics, 2014 (accepted)
  2. R. Cheng and Y. Jin. A social learning particle swarm optimization algorithm for scalable optimization. Information Sciences, 2014 (accepted)
  3. Z.-H. Zhou, N. V. Chawla, Y. Jin, and G. J. Williams. Big data opportunities and challenges: Discussions from data analytics perspectives. IEEE Computational Intelligence Magazine, 2014 (accepted) A draft here
  4. J. Chrol-Cannon and Y. Jin. On the correlation between reservoir metrics and performance for time series classification under the influence of synaptic plasticity. PLOS ONE, DOI: 10.1371/journal.pone.0101792, July 10, 2014.
  5. C. Smith and Y. Jin. Evolutionary multi-objective generation of recurrent neural network ensembles for time series prediction. Neurocomputing, 2014 (accepted)
  6. J. Chrol-Cannon and Y. Jin. Computational modeling of neural plasticity for self-organization of neural networks. BioSystems, 2014 (accepted)
  7. C. Sun, Y. Jin, J. Zeng and Y. Yu. A two-layer surrogate-assisted particle swarm optimization algorithm. Soft Computing, 2014 (accepted)
  8. T. Zhang, Y. Jin, Y. Ding and K. Hao. A cytokine network inspired cooperative control system for multi-stage stretching processes in fiber production. Soft Computing, 2014 (accepted)
  9. R. Cheng and Y. Jin. A competitive swarm optimizer for large scale optimization. IEEE Transactions on Cybernetics, 2014 (accepted). Download the c code here.
  10. X. Zhang, Y. Tian, R. Cheng, and Y. Jin. An efficient approach to non-dominated sorting for evolutionary multi-objective optimization. IEEE Transactions on Evolutionary Computation, 2014 (accepted) Download the Matlab code of ENS_SS, ENS_BS and NSGA-II with ENS.
  11. S. A. Thomas and Y. Jin. Reconstructing biological gene regulatory networks: Where optimization meets big data. Evolutionary Intelligence, 7:29-47, 2014
  12. A. Zhou, Y. Jin and Q. Zhang. A population prediction strategy for evolutionary dynamic multiobjective optimization. IEEE Transactions on Cybernetics, 44(1):40-53, 2014
  13. J. Chen, Y. Ding, Y. Jin, and K. Hao. A synergetic immune clonal selection algorithm based multi-objective optimization method for carbon fibre drawing process. Fibers and Polymer, 4(10): 1722-1730, 2013
  14. S. A. Thomas and Y. Jin. Evolving connectivity between genetic oscillators and switches using evolutionary algorithms. Journal of Bioinformatics and Computational Biology, Vol. 11, No. 3, 1341001, 2013
  15. B. Inden, Y. Jin, R. Haschke, H. Ritter, B. Sendhoff. An examination of different fitness and novelty based selection methods for the evolution of neural networks. Soft Computing, 17(5): 753-767, 2013
  16. X. Sun, D. Gong, Y. Jin and S. Chen. A new surrogate-assisted interactive genetic algorithm with weighted semi-supervised learning. IEEE Transactions on Cybernetics, 43(2):685-698, 2013
  17. M.N. Le, Y.S. Ong, S. Menzel, Y. Jin, and B. Sendhoff. Evolution by adapting surrogates. Evolutionary Computation, 21(2):313-340, 2013
  18. Y. Jin, K. Tang, X. Yu, B. Senhoff and X. Yao. A framework for finding robust optimal solutions over time. Memetic Computing, 5(1):3-18, 2013
  19. C. Sun, J. Zeng, J. Pan, S. Xue, Y. Jin. A new fitness estimation strategy for particle swarm optimization. Information Sciences, 221:355-370, 2013
  20. G. Jia, Y. Wang, Z. Cai and Y. Jin. An improved (mu+lambda) constrained differential evolution for constrained optimization. Information Sciences, 222:302-322, 2013
  21. Y. Meng, H. Guo and Y. Jin. A morphogenetic approach to flexible and robust shape formation for swarm robotic systems. Robotics and Autonomous Systems, 61(1):25-38, 2013
  22. J. Yin, Y. Meng and Y. Jin. A developmental approach to reservoir computing. IEEE Transactions on Autonomous Mental Development, 4(4):273-289, 2012
  23. L. Schramm, Y. Jin, and B. Sendhoff. Evolutionary Synthesis and Analysis of a Gene Regulatory Network for Dynamically Stable Growth and Regeneration. Artificial Life, 18(4):425-444, 2012
  24. D. Bush and Y. Jin. Calcium control of hippocampal STDP. Journal of Computational Neuroscience. 33(3):495-514, 2012
  25. Y. Jin, H. Guo andY. Meng. A hierarchical gene regulatory network for adaptive multi-robot pattern formation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(3):805-816, 2012
  26. Hongliang Guo, Y. Jin, and Yan Meng. A morphogenetic framework for self-organized multi-robot pattern formation and boundary coverage. ACM Transactions on Autonomous and Adaptive Systems, Volume 7, Issue 1, Article No. 15, April 2012. doi:10.1145/2168260.2168275
  27. B. Inden, Y. Jin, R. Haschke and H. Ritter. Evolving neural fields for problems with large input and output spaces. Neural Networks, 28: 24-39, 2012
  28. M. N. Le, Y. S. Ong, Y. Jin and B. Sendhoff. A unified framework for symbiosis of evolutionary mechanisms with application to water clusters potential model design. IEEE Computational Intelligence Magazine, 7(1):20-35, 2012
  29. Y. Meng, Y. Jin and J. Yin. Modeling activity-dependent plasticity for human behaviour recognition. IEEE Transactions on Neural Networks, 22(12):1952-1966, 2011
  30. S. Oh, Y. Jin and M. Jeon. Approximate models for constraint functions in evolutionary constrained optimization. International Journal of Innovative Computing, Information and Control, 7(11):6585-6603, 2011
  31. E. Gehrmann, Ch. Gläßer, Y. Jin, B. Sendhoff, B. Drossel and K. Hamacher. The robustness of glycolysis in yeast to internal and external noise. Physical Review E, 84(2): 021913, 2011
  32. Y. Zheng, Y. Meng and Y. Jin. Object recognition using a bio-inspired neuron model with bottom-up and top-down pathways. Neurocomputing, 74(17):3158-3169, 2011
  33. D. Bush and Y. Jin. A unified computational model of the genetic regulatory networks underlying synaptic, intrinsic and homeostatic plasticity. BMC Neuroscience, 12 (Suppl 1):P161, 2011 (Conference Abstract)
  34. Y. Jin. Surrogate-assisted evolutionary computation: Recent advances and future challenges. Swarm and Evolutionary Computation. 1(2):61-70, 2011 (Invited survey paper)
  35. L. Tang, T. Peto, J. Goh, Y. Jin, C. Chuluunkhuu. Filtering Normal Diabetic Retinopathy Images through Evolutionary Computation. European Journal of Ophthalmology, 21(3): 347-348, 2011 (Conference abstract)
  36. M. Liu, S. Zhang and Y. Jin. Multi-sensor optimal H∞ fusion filters for delayed nonlinear intelligent systems based on a unified model. Neural Networks, 24(3):280-290, 2011 
  37. Y. Jin and Y. Meng. Morphogenetic robotics: An emerging new field in developmental robotics. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(2):145-160, 2011
  38. Y. Meng, Y. Zheng, and Y. Jin. Autonomous self-reconfiguration of modular robots by evolving a hierarchical mechanochemical model. IEEE Computational Intelligence Magazine, 6(1):43-54, 2011
  39. Y. Jin and Y. Meng. Emergence of robust regulatory motifs from in silico evolution of sustained oscillation. BioSystems, 103(1): 38-44, 2011
  40. Y. Meng, Y. Jin: Distributed Multi-Agent Systems for a Collective Construction Task based on Virtual Swarm Intelligence. International Journal of Swarm Intelligence Research, 1(2): 58-79 (2010)
  41. D. Lim, Y. Jin, Y.-S. Ong, and B. Sendhoff. Generalizing surrogate-assisted evolutionary computation.IEEE Transactions on Evolutionary Computation, 14(3):329-355, 2010
  42. T. Steiner, Y. Jin, and B. Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177, 2009
  43. H. Guo, Y. Meng, and Y. Jin. A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network. BioSystems, 98(3):193-203, 2009
  44. M.N. Le, Y. S. Ong, Y. Jin, and B. Sendhoff. Lamarckian memetic algorithms: Local optimum and connectivity structure analysis. Memetic Computing, 1(3):1795-190, 2009
  45. A. Zhou, Q. Zhang, Y. Jin. Approximating the set of Pareto-optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm. IEEE Transactions on Evolutionary Computation, 13(5): 1167-1189, 2009
  46. Y. Jin and B. Sendhoff. A systems approach to evolutionary multi-objective structural optimization. IEEE Computational Intelligence Magazine, 4(3):62-76, 2009 (Invited feature article)
  47. I. Paenke, Y. Jin, J. Branke. Balancing population and individual level of adaptation in changing environments. Adaptive Behavior, 17(2):153-174, 2009
  48. M. Meeter, R. Veldkamp, Y. Jin. Multiple memory stores and operant conditioning: A rationale for memory's complexity. Brain and Cognition, 69(1):200-208, 2009
  49. Y. Jin, R. Grunar, and B. Sendhoff. Pareto analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009
  50. Y. Jin and B. Sendhoff. Pareto-based multi-objective machine learning: An overview and case studies. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 38(3):397-415, 2008
  51. Q. Zhang, A. Zhou, Y. Jin. RM-MEDA: A regularity model-based multiobjective estimation of distribution algorithm. IEEE Transactions on Evolutionary Computation. 12(1):41-63, 2008
  52. D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff, B.-S. Lee. Efficient hierarchical parallel genetic algorithms using grid computing.  Future Generation Computer Systems. 23(4):658-670, 2007
  53. D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff, and B. S. Lee. Adaptive inverse multi-objective robust evolutionary design optimization. Genetic Programming and Evolvable Machines. 7(4), 383-404, 2007
  54. I. Paenke, J. Branke, and Y. Jin. Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation. IEEE Transactions on Evolutionary Computation, 10(4), 405-420, 2006
  55. K. Foli, T. Okabe, M. Olhofer, Y. Jin, and B. Sendhoff. Optimization of micro heat exchanger: CFD, analytical approach and multi-objective evolutionary algorithms. International Journal of Heat and Mass Transfer. 49, 1090-1099, 2006
  56. Y. Jin and J. Branke. Evolutionary optimization in uncertain environments - A survey. IEEE Transactions on Evolutionary Computation, 9(3), 303-317, 2005
  57. H. Wang, S. Kwong, Y. Jin, W. Wei and K. Man. Agent-based evolutionary approach to interpretable rule-based knowledge extraction. IEEE Transactions Systems, Man, and Cybernetics, Part C, 29(2), 143-155, 2005
  58. H. Wang, S. Kwong, Y. Jin, W. Wei and K. Man. A multi-objective hierarchical genetic algorithm for interpretable rule-based knowledge extraction. Fuzzy Sets and Systems, 149(1), 149-186, 2005
  59. Y. Jin. A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing, 9(1), 3-12, 2005
  60. M. Huesken, Y. Jin and B. Sendhoff. Structure optimization of neural networks for evolutionary design optimization. Soft Computing, 9(1), 21-28, 2005
  61. Y. Jin and B. Sendhoff, Extracting interpretable fuzzy rules from RBF networks. Neural Processing Letters, 17(2), 149-164, 2003
  62. Y. Jin, M. Olhofer and B. Sendhoff. A framework for evolutionary optimization with approximate fitness functions. IEEE Transactions on Evolutionary Computation, 6(5), 481-494, 2002
  63. Y. Jin. Fuzzy modelling of high-dimensional systems: Complexity reduction and interpretability improvement. IEEE Transactions on Fuzzy Systems, 8(2), 212-221, 2000 (Highly cited article according to ISI Thomson)
  64. Y. Jin and B. Sendhoff. Knowledge incorporation into neural networks from fuzzy rules. Neural Processing Letters, 10(3), 231-242, 1999
  65. Y. Jin, W. von Seelen and B. Sendhoff. On generating FC3 fuzzy rule systems from data using evolution strategies. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 29(6), 829-845, 1999
  66. Y. Jin and W. von Seelen. Evaluating flexible fuzzy controllers via evolution strategies. Fuzzy Sets and Systems, 108, 243-252, 1999
  67. Y. Jin. Decentralized adaptive fuzzy control of robot manipulators. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 28(1), 47-57, 1998
  68. Y. Jin, J. Jiang and J. Zhu. Neural network based fuzzy identification and its applications to modelling and control of complex systems. IEEE Transactions on Systems, Man and Cybernetics, 25(6), 990-997, 1995
  69. Y. Jin, J. Zhu and J. Jiang. Adaptive fuzzy identification with applications. International Journal of Systems Science, 6(2), 197-212, 1995

Peer-Reviewed Conference Papers

  1. S. Gu and Y. Jin. Generating diverse and accurate classifier ensembles using multi-objective optimization. IEEE Symposium Series on Computational Intelligence, December 9-12, 2014, Orlando, Florida, USA
  2. M.-H. Yusoff and Y. Jin. Modeling neural plasticity in Echo State Networks for time series prediction. 2014 UK Workshop on Computational Intelligence, Bradford, UK, 8 - 10 September 2014
  3. H. Oh and Y. Jin. Adaptive swarm robot region coverage using gene regulatory networks. Advances in Autonomous Robotics Systems, Lecture Notes in Computer Science, Volume 8717, pp 197-208, 2014
  4. A. Ramezan Shirazi, H. Oh and Y. Jin. Morphogenetic self-organization of collective movement without directional sensing. Advances in Autonomous Robotics Systems, Lecture Notes in Computer Science, Volume 8717, pp 139-150, 2014
  5. C. Qian, Y. Yu, Y. Jin and Z.-H. Zhou. On the effectiveness of sampling for evolutionary optimization in noisy environments. Parallel Problem Solving from Nature, September 13-17, 2014 Ljubljana, Slovenia
  6. T. Liu, C. Sun, J. Zeng and Y. Jin. Similarity- and reliability-assisted fitness estimation for particle swarm optimization of expensive problems. IEEE Congress on Evolutionary Computation, July 2014
  7. R. Cheng and Y. Jin. Demonstrator selection in a social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014
  8. H. Oh and Y. Jin. Evolving hierarchical gene regulatory networks for morphogenetic pattern formation of swarm robotics.  IEEE Congress on Evolutionary Computation, July 2014
  9. W. A. Albukhanajer, Y. Jin and Johann A. Briffa. Neural network ensembles for image identification using Pareto-optimal features.  IEEE Congress on Evolutionary Computation, July 2014
  10. C. Smith, J. Doherty and Y. Jin. Multi-objective evolutionary recurrent neural network ensemble for prediction of computational fluid dynamic simulations. IEEE Congress on Evolutionary Computation, July 2014
  11. L. Zhuang, K. Tang and Y. Jin. Metamodel assisted mixed-integer evolution strategies based on Kendall rank correlation coefficient. The 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'2013). October 20-23, 2013, Hefei, China
  12. R. Cheng and Y. Jin. On the competition mechanism of the competitive particle swarm optimizer. UK Workshop on Computational Intelligence, September 9-11, 2013
  13. S. A. Thomas, Y. Jin, E. Laing and C. P. Smith. Reconstructing regulatory networks in Streptomyces using evolutionary algorithms. UK Workshop on Computational Intelligence, September 9-11, 2013
  14. R. Cheng, C. Sun and Y. Jin. A multi-swarm evolutionary framework based on a feedback mechanism. In: IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23 2013
  15. A. Xiao, B. Wang and Y. Jin. Evolutionary truss layout optimization using the vectorized structure approach. In: IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23 201
  16. J. Lu, B. Li, and Y. Jin. An evolution strategy assisted by an ensemble of local Gaussian process models. In: Genetic and Evolutionary Computation Conference, Amsterdam, The Netherlands, 6-10 July 2013
  17. C. Smith, J. Doherty, and Y. Jin. Recurrent neural network ensembles for convergence prediction in surrogate-assisted evolutionary optimisation. IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, part of the IEEE Symposium Series on Computational Intelligence, Singapore, 16-19 April 2013
  18. C. Sun, J. Zeng, J. Pan and Y. Jin. Similarity based evolution control for fitness estimation in particle swarm optimisation. IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, part of the IEEE Symposium Series on Computational Intelligence, Singapore, 16-19 April 2013
  19. S. A. Thomas and Y. Jin. Single and multi-objective in silico evolution of tunable genetic oscillators. The 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), Sheffield, UK, March 2013
  20. W. A. Albukhanajer, Y. Jin, J. A. Bri ffa, and G. Williams. A comparative study of multi-objective evolutionary Trace Transform algorithms for robust feature extraction. The 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), 19-22 March 2013, Sheffield, UK
  21. S. Gu and Y. Jin. Heterogeneous classifier ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012
  22. W. Albukhanajer, Y. Jin, J. Briffa and G. Williams. Evolutionary multi-objective optimization of Trace transform for invariant feature extraction. 2012 IEEE Congress on Evolutionary Computation, Brisbane, Australia, June 2012
  23. J. Chrol-Cannon, A. Gruning and Y. Jin. The emergence of polychronous groups under varying input patterns, plasticity rules and network connectivities. 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 2012
  24. S. Thomas and Y. Jin. Combining genetic oscillators and switches using evolutionary algorithms. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, USA, May 2012
  25. L. Schramm, Y. Jin and B. Sendhoff. Quantitative analysis of redundancy in evolution of developmental systems. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, USA, May 2012
  26. B. Inden, Y. Jin, R. Haschke, and H. Ritter. Evolution of multisensory integration in large neural fields. Artificial Evolution, 24-26 October 2011, Angers, France
  27. B. Inden, Y. Jin, R. Haschke and H. Ritter. Exploiting inherent regularity in control of multilegged robot locomotion by evolving neural fields. Third World Congress on Nature and Biologically Inspired Computing (NaBIC2011), October 19-21, 2011, Salamanca University, Spain
  28. D. Bush and Y. Jin. A unified computational model of the genetic regulatory networks underlying synaptic, intrinsic and homeostatic plasticity. 2011 International Conference on Wiring the Brain: Making Connections, April 12-15, 2011, County Wicklow, Ireland (oral presentation, not peer-reviewed)
  29. L. Schramm, Y. Jin, and B. Sendhoff. Redundancy Creates Opportunity in Developmental Representations. 2011 IEEE Symposium on Artificial Life, Paris, France, April 11-15, 2011
  30. H. Guo, Y. Meng, and Y. Jin. Swarm robot pattern formation using a morphogenetic multi-cellular based self-organization algorithm. 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China, May 9-13, 2011
  31. Y. Meng, Y. Zhang, A. Sampath, Y. Jin, and B. Sendhoff. Cross-ball: A new morphogenetic self-reconfigurable modular robot. 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China, May 9-13, 2011
  32. J. Goh, L. Tang, L. Al Turk, Y. Jin, G. Saleh, A Combined Particle Swarm Optimisation and Genetic Algorithm for Context Analysis of Medical Images. In: 4th International Conference on Health Informatics. Rome, Italy, 26-29, January, 2011
  33. Y. Jin, Y. Meng and H. Guo. A Morphogenetic Self-Organization Algorithm for Swarm Robotic Systems using Relative Position Information. UK Workshop on Computational Intelligence (UKCI), Colchester, UK, September 2010
  34. L. Schramm, V. Valente Martins, Y. Jin, B. Sendhoff. Analysis of gene regulatory network motifs in evolutionary development of multi-cellular organisms. Artificial Life XII, Odense, Denmark, August 2010
  35. Y. Meng, Y. Zheng and Y. Jin. A Morphogenetic Approach to Self-Reconfigurable Modular Robots using a Hybrid Hierarchical Gene Regulatory Network. Artificial Life XII, Odense, Denmark, August 2010
  36. B. Jones, Y. Jin, B. Sendhoff, and X. Yao. Emerged optimal distribution of computational workload in the evolution of an undulatory animat. The 11th International Conference on Simulation of Adaptive Behaviors (SAB 2010), August 24-28, 2010
  37. Y. Jin, S. Oh and M. Jeon. Incremental approximation of nonlinear constraint functions for evolutionary constrained optimization. Congress on Evolutionary Computation, pp.2966-2973, Barcelona, July 2010
  38. X. Yu, Y. Jin, K. Tang, and X. Yao. Robust optimization over time -- A new perspective on dynamic optimization problems. Congress on Evolutionary Computation, pp. 3998-4003, Barcelona, July 2010
  39. Y. Meng, Y. Jin, J. Yin, and M. Conforth. Human activity detection using spiking neural networks regulated by a gene regulatory network. Int. Joint Conference on Neural Networks, pp.2232-2237, Barcelona, July 2010 (Best paper nomination)
  40. H. Guo, Y. Meng, and Y. Jin. Analysis of local communication load in shape formation of a distributed morphogenetic swarm robotic system. Congress on Evolutionary Computation, pp.1117-1124, Barcelona, July 2010
  41. Y. Zheng, Y. Meng and Y. Jin. Fusing bottom-up and top-down pathways in neural networks for visual object recognition. Int. Joint Conference on Neural Networks, pp. 2064-2031, Barcelona, July 2010
  42. T. Steiner, B. Sendhoff, and Y. Jin. Evolving heterochrony for cellular differentiation using vector field embryogeny. Genetic and Evolutionary Computation Conference, pp.571-578, Portland, July 2010
  43. B. Inden, Y. Jin, R. Haschke, H. Ritter. NEATfields: Evolution of neural fields for visual discrimination and multiple pole balancing tasks. Genetic and Evolutionary Computation Conference, pp.645-646, Portland, 2010
  44. H. Lex, M. Weigelt, Y. Jin, and T. Schack. Visuo-motor adaptation relies on kinesthetic representation of movement directions. North American Society for Psychology of Sport and Physical Activity (NASPSPA) Conference, Tucson, AZ, June 10-12, 2010 (abstract published in Journal of Sport & Exercise Psychology, 32, 100-101)
  45. Y. Jin and J. Trommler. A fitness-independent evolvability measure for evolutionary developmental systems. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp.69-76, Montreal, Canada, May 2-5 2010 ( Best Paper Award  )
  46. A. Finke, Y. Jin, H. Ritter. A P300 based brain-robot interface for shaping human-robot interaction. Bernstein Conference on Computational Neuroscience, Frankfurt, September 2009. doi: 10.3389/conf.neuro.10.2009.14.108
  47. B. Jones, Y. Jin, B. Sendhoff, and X. Yao. The evolutionary emergence of neural organization in a hydra-like animat. Bernstein Conference on Computational Neuroscience, Frankfurt, September 2009 (poster presentation)
  48. B. Jones, Y. Jin, B. Sendhoff, and X. Yao. The effect of proprioceptive feedback on the distribution of sensory information in a model of an undulating organism. 10th European Conference on Artificial Life, Budapest, September 2009
  49. L. Schramm, Y. Jin, Bernhard Sendhoff. Emerged coupling of motor control and morphological development in evolution of multi-cellular animates. 10th European Conference on Artificial Life, Budapest, September 2009  
  50. Y. Jin, Y. Meng, and B. Sendhoff. Evolvability and robustness of in silico evolution of gene regulatory dynamics. In: Foundations of Systems Biology in Engineering. Omnipress, pages 68-71, 2009
  51. Y. Jin, H. Guo and Y. Meng. Robustness analysis and failure recovery of a bio-inspired self-organizing multi-robot system. In: Third IEEE International Conference on Self-Adaptive and Self-organizing Systems. IEEE Press, pages 154-164, 2009
  52. T. Steiner, J. Trommler, M. Brenn, Y. Jin, and B. Sendhoff. Global shape with morphogen gradients and motile polarized cells. Congress on Evolutionary Computation, pp.2225-2232, May 2009, Trondheim, Norway
  53. Y. Jin, Y. Meng, B. Sendhoff. Influence of regulation logic on the easiness of evolving sustained oscillation for gene regulatory networks. IEEE ALIFE, pp.61-68, March 30 - April 1, 2009, Nashville, TN, USA
  54. H. Guo, Y. Meng, Y. Jin. Self-adaptive multi-robot construction using gene regulatory networks. IEEE ALIFE, pp. 53-60, March 30 - April 1, 2009, Nashville, TN, USA
  55. Y. Jin, R. Gruna, I. Paenke, B. Sendhoff. Multi-objective optimization of robustness and innovation in redundant genetic representations. IEEE MCDM, pp.38-45, March 30 - April 1, 2009, Nashville, TN, USA 2009
  56. Y. Jin, L. Schramm, and B. Sendhoff. A gene regulatory model for the development of primitive nervous systems. INNS-NNN Symposia on Modeling the Brain and Nervous Systems, LNCS 5506, pp.48-55, 2009 (Best paper nomination)
  57. B. Jones, Y. Jin, X. Yao, and B. Sendhoff. Evolution of neural organization in a Hydra-like animat. 15th Int. Conf. on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP’08), LNCS 5506, pp. 216-223, 2009
  58. D. Lim, Y.-S. Ong, Y. Jin, and B. Sendhoff. Evolutionary optimization with dynamic fidelity computational models. International Conference on Intelligent Computing, pp.235-242, September 15-18, 2008, Shanghai, China
  59. B. Jones, Y. Jin, B. Sendhoff, and X. Yao. Evolving functional symmetry in a three dimensional model of an elongated organism. Artificial Life IX, Winchester, UK, pp.305-312, August 2008
  60. T. Steiner, Y. Jin and B. Sendhoff. A cellular model for evolutionary development of lightweight materials with an inner structure. Genetic and Evolutionary Computation Conference, pp.851-858, Atlanta, July 2008 (Best paper nomination)
  61. Y. Cao, Y. Jin, M. Kowalczykiewicz and B. Sendhoff. Prediction of convergence dynamics of design performance using differential recurrent neural networks. International Joint Conference on Neural Networks, pp.529-534, Hong Kong, June 2008
  62. A. Zhou, Q. Zhang, Y. Jin and B. Sendhoff. Combination of EDA and DE for continuous bi-objective optimization. Congress on Evolutionary Computation, pp.1447-1454, Hong Kong, June 2008
  63. N. Samways, Y. Jin, X. Yao, and B. Sendhoff. Toward a gene regulatory network model for evolving chemotaxis behaviour. Congress on Evolutionary Computation, pp.2574-2581, Hong Kong, June 2008
  64. Y. Jin, B. Sendhoff. Evolving in silico bistable and oscillatory dynamics for gene regulatory network motifs. Congress on Evolutionary Computation, pp.386-391,Hong Kong, June 2008
  65. A. Zhou, Q. Zhang, Y. Jin, B. Sendhoff. Adaptive modelling strategy for continuous multi-objective optimization. Congress on Evolutionary Computation, pp.431-437 Singapore, September 2007
  66. T. Steiner, L. Schramm, Y. Jin, Bernhard Sendhoff. Emergence of feedback in artificial gene regulatory networks. Congress on Evolutionary Computation, pp.867-874, September 2007 (Best paper 10 finalist)
  67. Y. Jin, R.Wen, B. Sendhoff. Evolutionary multi-objective optimization of spiking neural networks. International Conference on Artificial Neural Networks, LNCS 4668, pp. 370-379, 2007
  68. A. Zhou, Q. Zhang, Y. Jin, B. Sendhoff, E. Tsang, Global multi-objective optimization via estimation of distribution with biased initialization and crossover. Genetic and Evolutionary Computation Conference, pp.617—623, July 8-11, 2007
  69. D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff. A study on meta-modelling techniques, ensembles and multi-surrogates in evolutionary computation. Genetic and Evolutionary Computation Conference, pp.1288-1295, July 8-11, 2007
  70. I. Paenke, J. Branke, and Y. Jin. On the influence of phenotype plasticity on genotype diversity. 2007 IEEE Symposium on Foundations of Computational Intelligence, pp.33-40, April 1-4, 2007, Honolulu, Hawaii, 2007 (Best student paper)
  71. A. Zhou, Y. Jin, Q. Zhang, B. Sendhoff, E. Tsang. Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization. The Fourth International Conference on Evolutionary Multi-Criterion Optimization. Pp. 832-846, LNCS 4403, Springer, 2007
  72. Zhou, Q. Zhang, Y. Jin, B. Sendhoff, E. Tsang. Modeling the population distribution in multi-objective optimization by generative topographic mapping. Parallel Problem Solving from Nature, LNCS 4193, pp.443-452, 2006
  73. D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff. Trusted evolutionary algorithms. Congress on Evolutionary Computation, pp.456-463, 2006
  74. L. Gräning, Y. Jin, B. Sendhoff. Generalization improvement in multi-objective learning. Int. Joint Conference in Neural Networks, pp.9893-9900, 2006
  75. Y. Jin, B. Sendhoff. Alleviating catastrophic forgetting via multi-objective learning. International Conference on Neural Networks, pp.6367-6374, 2006
  76. A. Zhou, Y. Jin, Q. Zhang, B. Sendhoff, E. Tsang. Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion. Congress on Evolutionary Computation, pp.3234-3240, 2006
  77. A. Zhou, Q. Zhang, Y. Jin, E. Tsang, T. Okabe. A model-based evolutionary algorithm for bi-objective optimization. Congress on Evolutionary Computation, pp.2568-2575, Edinburgh, September 2005
  78. V. Khare, X. Yao, B. Sendhoff, Y. Jin, and H. Wersing. Co-evolutionary modular neural networks for automatic problem decomposition. Congress on Evolutionary Computation, pp.2691-2698, Edinburgh, September 2005
  79. T. Okabe, Y. Jin, and B. Sendhoff. Theoretical comparisons of search dynamics of genetic algorithms and evolution strategies. Congress on Evolutionary Computation, pp.382-389, Edinburgh, September 2005
  80. T. Okabe, Y. Jin, and B. Sendhoff. A new approach to dynamics analysis of genetic algorithms without selection. Congress on Evolutionary Computation, pp.374-381, Edinburgh, September 2005
  81. Y. Jin, M. Olhofer, and B. Sendhoff. On evolutionary optimization of large problems with small populations. Int. Conf. on Natural Computation. LNCS 3611,  pp.1145-1154, Springer, Changsha, China, 2005
  82. L. Gräning, Y. Jin, B. Sendhoff. Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study. European Symposium on Artificial Neural Networks. pp.273-278, Bruges, April 2005
  83. Y. Jin, B. Sendhoff, and E. Körner. Evolutionary multi-objective optimization for simultaneous generation of signal-type and symbol-type representations. The Third International Conference on Evolutionary Multi-Criterion Optimization. LNCS 3410, pp.752-766, Springer, Guanajuato, Mexico, March 9-11, 2005
  84. T. Okabe, Y. Jin, M. Olhofer, and B. Sendhoff. On test functions for evolutionary multi-objective optimization. Parallel Problem Solving from Nature, VIII, LNCS 3242, Springer, pp.792-802, September 2004
  85. T. Okabe, Y. Jin, B. Sendhoff and M. Olhofer. Voronoi-based estimation of distribution algorithm for multi-objective optimization. Congress Evolutionary Computation, pp. 1594-1602, Portland, 2004
  86. Y. Jin, T. Okabe and B. Sendhoff. Neural network regularization and ensembling using multi-objective evolutionary algorithms. Congress on Evolutionary Computation, pp.1-8, Portland, 2004
  87. Y. Jin and B. Sendhoff. Reducing fitness evaluations using clustering techniques and neural network ensembles. Genetic and Evolutionary Computation Conference. LNCS 3102, Springer, pp. 688-699, Seattle, 2004
  88. Y. Jin and B. Sendhoff. Constructing dynamic test problems using the multi-objective optimization concept. In: Applications of Evolutionary Computing. LNCS 3005, pp.525-536, Springer, 2004
  89. Y. Jin and B. Sendhoff. Connectedness, regularity and the success of local search in evolutionary multi-objective optimization. In: Congress on Evolutionary Computation, Vol.3, pp.1910-1917, 2003
  90. L. Willmes, Th. Bäck, Y. Jin and B. Sendhoff. Comparing neural networks and kriging in fitness approximation in evolutionary optimization. Congress on Evolutionary Computation, Vol.1, pp.663-670, 2003
  91. T. Okabe, Y. Jin and B. Sendhoff. A critical survey of performance indices for multi-objective optimization. Congress on Evolutionary Computation, pp.878-885, 2003
  92. T. Okabe, K. Foli, M. Olhofer, Y. Jin and B. Sendhoff. Comparative studies on micro heat exchanger optimization. In: Congress on Evolutionary Computation, Vol.1, pp.647-654, 2003
  93. T. Okabe, Y. Jin and B. Sendhoff. Evolutionary multi-objective optimization with a hybrid representation. In: Congress on Evolutionary Computation, Vol.4, pp. 2262-2269, 2003
  94. Y. Jin, T. Okabe and B. Sendhoff. Solving three-objective optimization problems using evolutionary dynamic weighted aggregation: Results and analysis. In: Genetic and Evolutionary Computation Conference, pp.636, Chicago, 2003
  95. Y. Jin and B. Sendhoff. Trade-off between performance and robustness: An evolutionary multi-objective approach. In: The Second International Conference on Evolutionary Multi-criteria Optimization. LNCS 2632, Springer, pp.237-251, Faro, 2003
  96. Y. Jin and B. Sendhoff. Fuzzy preference incorporation into evolutionary multi-objective optimization. In: Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution and Learning, Vol.1, pp.26-30, Singapore, Nov. 2002
  97. T. Okabe, Y. Jin, B. Sendhoff. On the dynamics of multi-objective optimization. In: Genetic and Evolutionary Computation Conference, pp. 247-256, New York, July 2002 (Best paper nomination)
  98. Y. Jin. Fitness approximation in evolutionary computation - A survey. In: Genetic and Evolutionary Computation Conference, pp.1105-1112, New York, July 2002
  99. Y. Jin and B. Sendhoff. Incorporation of fuzzy preferences into evolutionary multiobjective optimization. In: Proceedings of Genetic and Evolutionary Computation Conference, pp.683, New York, July 2002
  100. Y. Jin, M. Olhofer and B. Sendhoff. Managing approximate models in evolutionary aerodynamic design optimization. In: Congress on Evolutionary Computation, vol.1, pp.592-599. Seoul, Korea, May 2001
  101. M. Olhofer, Y. Jin and B. Sendhoff. Adaptive encoding for aerodynamic shape optimization using evolution strategies. In: Congress on Evolutionary Computation, vol.1, pp.576-583, Seoul, Korea, May 2001
  102. Y. Jin, M. Olhofer and B. Sendhoff. Dynamic weighted aggregation for evolutionary multi-objective optimization: Why does it work and how? In: Genetic and Evolutionary Computation Conference, pp.1042-1049, San Francisco, 2001
  103. Y. Jin, T. Okabe and B. Sendhoff. Adapting weighted aggregation for multi-objective evolution strategies. In: The First International Conference on Evolutionary Multi-criterion Optimization. LNCS 1993, Springer, pp.96-110, Zurich, Switzerland, March 7-9, 2001
  104. Y. Jin, M. Olhofer and B. Sendhoff. On evolutionary optimization with approximate fitness functions. In: The Genetic and Evolutionary Computation Conference, Las Vegas, Nevada, USA. pp.786- 793, July 10-12, 2000
  105. A. Buczak, Y. Jin, H. Darabi and M. Jafari. Genetic algorithm based sensor network optimization for target tracking. Intelligent Engineering Systems through Artificial Neural Networks, Vol. 9, pp.349-354, 1999
  106. R. Burne, A. Buczak, Y. Jin, V. Jamalabad, I. Kadar and E. Eadan. A self-organizing, cooperative sensor network for remote surveillance: Current results. SPIE Proceedings of Unattended Ground Sensor Technologies and Applications, Vol.3713, pp.238-248, 1999
  107. Y. Jin, W. von Seelen and B. Sendhoff. An approach to rule-based knowledge extraction. In: IEEE International Conference on Fuzzy Systems, Anchorage, Alaska, pp.1188-1193, 1998
  108. Y. Jin, J. Zhu and J. Jiang. Fuzzy linearization of nonlinear systems. In: IEEE International Conference on Fuzzy Systems, pp.1688-1672, Orlando, Florida, USA, 1994

Refereed Journal Papers (in Chinese)

  1. Y. Jin, J.P. Jiang. Performance analysis of fuzzy controllers based on genetic algorithms. Pattern Recognition and Artificial Intelligence 10(1):75-80, 1997 (in Chinese)
  2. Y. Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings of Chinese Society of Electrical Engineering. 16(3):201-204, 1996 (in Chinese)
  3. Y. Jin and J.P. Jiang. Optimization of fuzzy control rules by means of genetic algorithms. Control and Decision, 11(6):672-676, 1996 (in Chinese)
  4. Y. Jin, J. Zhu. Neural network based fuzzy modelling and its simulation techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)
  5. Y. Jin, J.P. Jiang. Neuro-fuzzy control of robot manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)
  6. Y. Jin, J.P. Jiang. A neural network model with applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)
  7. Y. Jin, J.P. Jiang. Fuzzy logic integrated multivariable adaptive neuro-control. Information and Control, 23(4):223-228, 1994 (in Chinese)
  8. Y. Jin, J. Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Electronics Technology, 4:35-40, 1994 (in Chinese)
  9. Y. Jin, J. Zhu and J.P. Jiang. State estimation and adaptive control of multivariable systems using fuzzy logic and neural networks. AMSE Advances in Modeling and Analysis, 43(2), 1994
  10. Y. Jin, X. Shen. Two-level hierarchical intelligent fuzzy control of servo systems. Journal of Zhejiang University, 28(6):644-654, 1994 (in Chinese)
  11. Y. Jin, J.P. Jiang. Adaptive fuzzy prediction with application to weather forecast. Pattern Recognition and Artificial Intelligence, 6(4):283-290, 1993 (in Chinese)
  12. Y. Jin, J.P. Jiang. Neural network based non-linear feedback control. Journal of Zhejiang University, 27, 1993 (in Chinese)
  13. Y. Jin, J.P. Jiang. Fuzzy logic integrated variable structure control of a class of nonlinear systems. Control and Decision, 7(1):36-40, 1992 (in Chinese)
  14. Y. Jin, J.P. Jiang. Artificial neural networks in robot control- A survey. Robot, 14(6):54-58, 1992 (in Chinese)

Non-Refereed Journal Publications

  1. Y. Jin, Y. Meng. Guest Editorial Special Issue on Evolutionary and Developmental Robotics, IEEE Computational Intelligence Magazine, August 2010
  2. Y. Jin, J. Hallinan, Guest editorial: Special section on evolving gene regulatory networks, BioSystems, 98(3), pages vi-vii, 2009
  3. S. Yang, Y.-S. Ong, and Y. Jin. Guest editorial: Special issue on evolutionary computation in dynamic and uncertain environments. Genetic Programming and Evolvable Machines. 7(4):292--294, 2006
  4. J. Branke, Y. Jin. Guest editorial: Special issue on evolutionary computation in the presence of uncertainty. IEEE Transactions on Evolutionary Computation. 10(4):377--379, 2006
  5. Y. Jin, K. Rasheed and S. Louis. Guest editorial: Special issue on approximation and learning in evolutionary computation, Soft Computing, 9(1), 1-2, 2005
  6. Y. Jin. Guest editorial: Special issue on knowledge extraction and incorporation in evolutionary computation. IEEE Transactions Systems, Man, and Cybernetics, Part C: Applications and Reviews, 35(2), 129-130, 2005
  7. S. Kwong and Y. Jin. Guest editorial: Special issue on soft computing techniques in intelligent vehicle systems. IEEE Transactions on Industrial Electronics , 50(1), 2-3, 2003
  8. M. Olhofer, T. Arima, Y. Jin, T. Sonoda and B. Sendhoff. Optimization of transonic gas turbine blades with evolution strategies. Honda R&D Technical Review, 14(1), 203-216, 2002

Invited / Contributed Book Chapters

  1. Y. Jin and B. Sendhoff. Fuzzy logic in evolving in silico oscillatory dynamics for gene regulatory networks. In: Y. Jin and L. Wang. Fuzzy Systems in Bioinformatics and Computational Biology, Springer, 2009
  2. T. Steiner, Y. Jin, L. Schramm, and Bernhard Sendhoff. Dynamic links and evolutionary history in simulated gene regulatory networks. In: S. Das et al (eds.), Computational Methodologies in Gene Regulatory Networks, 2009
  3. Y. Jin, A. Zhou, Q. Zhang. Modeling regularity to improve the scalability of model-based multi-objective optimization algorithms. Multi-Objective Problem Solving from Nature, J. Knowles, D. Corne, K. Deb (Editors), pp.331-355, Springer, 2008
  4. Y. Jin, B. Sendhoff and E. Körner, Multi-objective learning of neural networks for interpretable rule extraction. In: Multi-objective Evolutionary Algorithms for Knowledge Discovery from Data Bases, A. Ghosh (Editor), pp.71-90, Springer, 2008
  5. D. Lim, Y.-S. Ong, M.-H. Lim, and Y. Jin. Single/multi-objective inverse robust evolutionary design methodology in the presence of uncertainty. In: S. Yang, Y.S. Ong, and Y. Jin(eds.) Evolutionary Computation in Dynamic and Uncertain Environments, pp.437-455, Springer, March 2007
  6. L. Graening, Y. Jin, and B. Sendhoff. Individual-based management of meta-models for evolutionary optimization with applications to three-dimensional blade optimization. In: S. Yang, Y.S. Ong, and Y. Jin(eds.) Evolutionary Computation in Dynamic and Uncertain Environments, pp.225-249, Springer, March 2007
  7. Y. Jin, B. Sendhoff, E. Körner. Simultaneous generation of accurate and interpretable neural network classifiers. In: Multi-Objective Machine Learning, Y. Jin (ed.), pp.281-300, Springer, Berlin Heidelberg, 2006
  8. Y. Jin, M. Huesken, M. Olhofer and B. Sendhoff. Neural networks for fitness approximation in evolutionary optimization. Knowledge Incorporation in Evolutionary Computation. Y. Jin (ed.), pp.281-306, Springer, Berlin Heidelberg, 2005
  9. Y. Jin. Evolutionary multi-objective approach to construction of neural network ensembles. In: Applications of Multi-objective Evolutionary Algorithms, C. Coello et al (eds.), pp.653-672, World Scientific, 2004
  10. Y. Jin. Interpretability improvement of RBF-based neuro-fuzzy systems using regularized learning. Interpretability Issues in Fuzzy-Rule-Based Modeling, J. Casillas et al (eds.), pp.605-619, Springer, 2003
  11. Y. Jin. Generating distinguishable, complete, consistent and compact fuzzy systems using evolutionary algorithms. Accuracy Improvements in  Modeling, J. Casillas et al (eds.), pp.100-118, Springer, 2003
  12. Y. Jin and J. Jiang. Techniques in Neural Network Based Fuzzy Identification and Their Application in Control of Complex Systems,  Fuzzy Theory Systems, Vol.1, C. T. Leondes (ed.), Chapter 5, pp.112-118, Academic Press, San Diego, 1999

Granted Patents

  1. Combining model-based and genetics-based offspring generation for mulit-objective optimization using a convergence criterion, US Patent No 7739206, 2010
  2. Fuzzy preferences in multi-objective optimization (MOO), US Patent No 7383236, 2008 / Japan Patent No 433510, 2009
  3. Estimation of distribution algorithm (EDA). US Patent No 7428514, 2008
  4. Multi-objective optimization, US Patent No 7363280, 2008
  5. Reduction of fitness evaluations using clustering techniques and neural network ensembles. European Patent No 1557788 / US Patent No 7363281, 2008
  6. Approximate fitness functions. US Patent No 7043462, 2006

Teaching

    • COMM040: Evolutionary Computation and Artificial Development (MSc, Autumn Semester, 2012 - )
    • COM3013: Computational Intelligence (Undergraduate, Autumn semester, 2010 - )
    • COM2016: Professional Studies (Undergraduate, Autumn semester, 2011)
    • COM2030: Advanced Algorithms (Undergraduate, Autumn semester, shared, 2011)
    • COMM028: Technologies and Application Schedule (MSc, Spring semester, shared, 2010-2011)

Departmental Duties

  • Director, Postgraduate Study by Research
  • Member, Research Management Committee
  • Member, MSc Teaching Management Committee

Member, FEPS Faculty International Relations Committee

  • International Coordinator 
  • Member of Policy and Strategy Group Committee 
  • Academic Integrity Officer 
  • Industry Placement Visiting Tutor
  • MSc Admission Tutor (10.2010 - 05.2012)
  • Seminar Series Organizer (09.2010 - 08.2011)

Grant Reviewer, Referee and External PhD Examiner

External PhD Examiner

  1. Ph.D. thesis, Robert Gordon University, 2014
  2. Ph.D. thesis, Bielefeld University, 2014
  3. Ph.D. thesis, University of Sheffield, 2013 (Student: Rui Wang, Supervisor: Prof Peter Fleming, Dr Robin Purshouse)
  4. Ph.D. thesis, University of Bradford, 2013
  5. Ph.D. thesis, University of Oxford, 2013 (Student: Zhenyu Wang, Supervisor: Dr V. Palade) 
  6. Ph.D. thesis, Hong Kong Polytechnic University, 2013 (Student: Yihong Zhang, Supervisor: Prof C.W. Yuen)  
  7. Ph.D. thesis, Universite Paris Sud, 2012 (Student: Ilya Loshchilov, Supervisor: Prof Marc Schoenauer)
  8. Ph.D. thesis, RMIT University, Australia, 2012 (Student: Robert Carrese, Supervisor: Dr Jon Watmuff)
  9. Ph.D. thesis, Brunel University, 2012 (Student: Sameera Alshayji, Supervisor: Prof Zidong Wang) 
  10. Ph.D. thesis, Universidad de Málaga, Spain, 2012 (Student: Jose D. Fernandez Rodriguez, Supervisor: Prof Francisco J. Vico)
  11. PhD thesis, University of Exeter, 2012 (Student: Andrew Clark, Supervisor: Prof Richard Everson)
  12. PhD thesis, Nanyang Technological University, 2012 (Student: Xianshun Chen, Supervisor: Prof Yew Soon Ong)
  13. PhD thesis, University of Manchester, 2012 (Student: Richard Allmendinger, Supervisor: Dr Joshua Knowles)
  14. PhD thesis, Birkbeck, University of London, 2011 (Student: Tony Lewis, Supervisor: Prof George Magoulas)
  15. PhD thesis, La Trobe University, Australia, 2011 (Student: Xi Li, Supervisor: Prof Dianhui Wang)
  16. PhD thesis, University of Leicester, 2011 (Student: Imtiaz Korejo, Supervisor: Dr Shengxiang Yang)
  17. PhD thesis, Gwangju Institute of Science and Technology, Korea, 2011 (Student: Sanghoun Oh, Supervisor: Prof. Moongu Jeon)
  18. PhD thesis, University of Dortmund, Germany, 2011 (Student: Boris Naujoks, Supervisor: Prof. Guenther Rudolph)
  19. PhD thesis, Department of Management Engineering, Technical University of Denmark, 2011 (Student: J.-F. Dupuis, Supervisor: Prof. Zhun Fan)
  20. PhD thesis, School of Computer Science, University of Birmingham, UK, 2011 (Student: Trung Thanh Nguyen, Supervisor: Prof. Xin Yao)
  21. PhD thesis, Department of Computer Science, University of Leicester, UK, 2011 (Student: Changhe Li, Supervisor: Dr Shengxiang Yang)
  22. PhD thesis, School of Computer Science and Information Technology, RMIT University, Australia, 2010 (Student: W.R.M.U.K. Wickramasinghe, Supervisor: Dr. Xiaodong Li)
  23. PhD thesis, Department of Electronics, The University of York, UK, 2010 (Student: Tuze Kuyucu, Supervisor: Prof. Andy Tyrrell)
  24. PhD thesis, Department of Computer Science and Engineering, Annamalai University, India, 2010 (Studenrt: M. Govindarajan, Supervisor: Prof. R.M. Chandrasekaran)
  25. PhD thesis, Section Computational Science, University of Amsterdam, The Netherlands, 2009 (Student: Yves Fomkong-Nanfack, Supervisor: Prof. Jaap Kaandorp)
  26. PhD thesis, School of Computer Science and Information Technology, RMIT University, Australia, 2008 (Student: Antony Iorio, Supervisor: Dr Xiaodong Li)
  27. PhD thesis, Department of Informatics and Systems, Universidad de las Palmas de Grand Canaria, Spain, 2008 (Student: Daniel E. Salazar Aponte, Supervisor: Prof. Blas Galván)
  28. PhD thesis, School of Computer Science, University of Essex, UK, 2007 (Student: Hui Li, Supervisor: Prof. Qingfu Zhang)
  29. PhD thesis, School of Computer Science, Nanyang Technological University, Singapore, 2006 (Student: Zongzhao Zhou, Prof. Yew Soon Ong)
  30. PhD thesis, Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 2005 (Student: Pawan K. S. Nain, Prof. Kalyanmoy Deb)

Grant Reviewer

  • Review Panel, Academy of Finland, 2013
  • Review Panel, EU FP7 FET, 2013
  • Royal Academy of Engineer, 2012
  • DAAD, Germany, 2012
  • Marsden Fund, New Zealand, 2012
  • Italy VQR 2012
  • Killam Research Fellowship, Canada Council , 2012
  • Netherlands Organization for Scientific Research, 2011
  • EPSRC, UK, 2011
  • Research Promotion Foundation, Cyprus, 2011
  • The EUROCORES Programme "EuroBioSAS", European Science Foundation, 2010
  • Visiting Professorship Application, the Leverhulme Trust, 2010
  • Netherlands Organization for Scientific Research, 2003

Referee

  • Promotion to Full Professorship, University of Kansas, 2011
  • Promotion to Full Professorship, Zhejiang University, 2010
  • Young Scientist Award, Singapore National Academy of Science (SNAS)
  • Research Award of ASEA Brown Boveri (ABB), 2003

Editorships, Conference Chairs and Professional Services

Editorships

Main Conference Activities

Main Professional Services

Keynotes and Invited Talks

Invited Plenary / Keynote Talks and Invited Tutorials

  • Invited keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", The 19th International Conference on Automation and Computing, September 13-14, 2013, Uxbridge, UK
  • Invited Keynote, "Evolutionary dynamic optimization: To track or not to track, and how to track?" IEEE Symposium Series on Computational Intelligence, April 16-19 2013, Singapore
  • Invited summer school course, "Evolutionary optimisation of expensive problems." 22nd Jyvaskyla Summer School, University of Jyvaskyla, Finland, 13-17 August 2012
  • Invited Keynote, 10th Workshop on Bioinformatics and 5th Symposium of the Polish Bioinformatics Society, 25 – 27 May 2012, Gdańsk, Poland
  • Invited keynote, "Surrogate-assisted evolutionary optimization: Past, present and future", Learning and Intelligent Optimization Conference (LION 6),  January 16-20, 2011, Paris, France
  • Invited keynote, "Morphogenetic self-organization of swarm robotic systems for robust boundary coverage and target tracking", The 7th International Conference on Computational Intelligence and Security, December 3-4, 2011, Sanya, Hainan, China
  • Invited keynote, "Self-organisation of neural systems - An evolutionary and developmental perspective", DeveLeaNN Workshop, October 27-28, 2011, Paris, France
  • Invited Keynote, "Computational modelling, analysis and synthesis of gene regulatory networks", Workshop on Computational Methods in Bioinformatics, October 19, 2011, Salerno, Italy
  • Invited keynote, "Morphogenetic self-organization of collective systems. Organic Computing Workshop, The 8th International Conference on Autonomic Computing, Karlsruhe, Germany, June 14-18, 2011
  • Invited tutorial, "A systems approach to aerodynamic design optimization", Learning and Intelligent OptimizatioN (LION 5), Jan. 17-21, 2011, Rome, Italy
  • Plenary talk, "Morphogenetic robotics", World Congress on Nature and Biologically Inspired Computing, Kitakyushu, Japan, December 15-17, 2010
  • Plenary talk, "Analysis and Synthesis of Gene Regulatory Networks and Their Application to Morphogenetic Robotics", International Conference on Computational Systems Biology and Bioinformatics, Bangkok, Thailand, November 4-5, 2010
  • Plenary talk, "Multi-objective machine learning",  The 2010 International Workshop on Nature Inspired Computation and Application , October 23-27, 2010, Hefei, China
  • Keynote talk, "A fitness-independent evolvability measure for evolutionary developmental systems",  7th International Symposium on Networks in Bioinformatics, Amsterdam, the Netherlands, April 22-23, 2010
  • Semi-plenary talk, "Computational modelling of gene regulatory networks: Analysis, synthesis and applications", 15th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP 2008), November 25-28, 2008, Auckland, New Zealand
  • Keynote talk, "Efficient evolutionary algorithms for complex engineering design", Adaptive Computing in Design and Manufacturing, April 29th-30th 2008, Bristol, UK
  • Keynote talk, "Pareto-optimality is everywhere: From engineering design, machine learning to biological systems", Genetic and Evolving Fuzzy Systems, 4 - 7 March, 2008, Witten-Bommerholz, Germany
  • Plenary talk, "Pareto-based multi-objective machine learning", Hybrid Intelligent Systems, Sept. 17-19, 2007, Kaiserslautern, Germany

Other Invited Talks

  • Invited Seminar, "A systems approach to evolutionary optimisation of complex engineering problems.", Department of Mathematical Information technology , University of Jyvaskyla, Finland, 16.08.2012
  • Invited talk, "Morphogenetic self-organisation of robotic systems." Social Robotics lab, National University of Singapore, 05.06.2012
  • Invited talk, "Modeling activity-dependent neural plasticity in liquid state machines for spatiotemporal pattern recognition." School of Computer Engineering, Nanyang Technological University, Singapore, 03.06.2012
  • Invited speech, Biology + Computing = ?? A Joint Meeting of the CSE:SEABIS Group and the ModAbs Group, Sponsored by SICSA, University of Stirling, UK, 21st May 2012
  • Invited talk, "Self-organization of neural systems – An evolutionary and developmental perspective", School of Computing, Robert Gordon University, 24 February, 2012
  • Invited seminar, Department of Information Systems and Computing, Brunel University, 22 February, 2012
  • Invited talk, "Morphogenetic robotics", Robot Intelligence Technology Lab, KAIST, Republic of Korea, December 16, 2011
  • Invitd talk, "Morphogenetic robotics",  College of Engineering, Seoul National University, Republic of Korea, December 15, 2011
  • Invited talk, "Modeling neural plasticity for human behaviour recognition", School of Computer Science, Nanjing University, April 26, 2011
  • Invited talk, "Dynamicalization - Manipulated Changes of Constraints for Efficient Optimization of Constrained Problems", Bridging The Gap: Workshop 7, Dynamic Optimisation in an Uncertain World: Challenges and State-of-the-Art , University of Birmingham, 24th February, 2011
  • Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", The Centre for Computational Statistics and Machine Learning, University College London, January 27, 2011
  • Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", Department of Control Science and Engineering, Huazhong University of Science and Technology, 31st December, 2010    
  • Invited talk, "A systems approach to multi-objective optimization of complex systems", Department of Automation, Tsinghua University, 29th December, 2010
  • Invited talk, "Analysis, synthesis and applications of gene regulatory networks models", School of Engineering, Mathematics and Physical Sciences, University of Exeter, 10th November, 2010
  • Invited talk, International Workshop on Nature Inspired Computation and Applications, Oct. 23-27, 2010, Hefei, China
  • Invited speaker, EU ICT FET Action Workshop on EVOBODY: new Principles of Unbound Embodied Evolution. Sept. 23, 2010, Malta
  • Invited talk, "Morphogenetic self-organization of collective systems", COST Action IC0806: Intelligent Monitoring, Control and Security of Critical Infrastructure Systems, Second Action Workshop, May 17-18, 2010, Budapest, Hungary
  • Invited talk, "Analysis and synthesis of gene regulatory networks and their application to morphogenetic robotics", Laboratory for Systems Theory and Automatic Control, Otto-von-Guericke University of Magdeburg, January 26, 2010
  • Invited talk, "Evolutionary multi-objective optimization of expensive problems using surrogate ensembles", Special Session on "Evolutionary Multi-Objective Optimizationation" organized by J. Branke, the 23rd European Conference on Operational Research, July 6-8 2009, Bonn, Germany
  • Invited talk, "Analysis, synthesis and applications of gene regulatory network", Colloquium, Faculty of Science, University of Amsterdam, February 13, 2009
  • Invited talk, "Brain-body co-evolution toward understanding major transitions in evolution of primitive nervous systems", INNS-NNN Symposia (New directions in Neural Networks) on Modelling the Brain and Nervous Systems, 24-25 November 2008, Auckland, NZ
  • Invited talk, "Pareto analysis of evolutionary and learning systems", The 2008 International Workshop on Nature Inspired Computation and Applications, May 27-29,2008, Hefei, China
  • Invited talk (together with B. Sendhoff), "Towards multi-objective system optimization", EMO 2007, March 8, Matsushima, Japan
  • Invited talk, "Scalable model-based multi-objective optimization", Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Dec. 13-17, 2006, Schloss Dagstuhl, Wadern, Germany
  • Invited talk, "Modeling regularity in multi-objective optimization", PPSN Workshop on Multi-Objective problem Solving from Nature, Sep. 9, 2006, Reykjavik
  • Invited talk, "Multi-objective machine learning", School of Computer Science, University of Birmingham, February 18, 2006
  • Invited talk, "Research on evolution and learning at HRI-EU", Kanpur Genetic Algorithm Lab , Indian Institute of Technology, Kanpur, India, July 6, 2005
  • Invited talk on "Hybrid representations for evolutionary multi-objective optimization", Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Schloss Dagstuhl, Germany, Nov. 8-12, 2004
  • Invited talk, "Aerodynamic optimization using evolutionary algorithms", Track on EC in Industry, GECCO'04, Seattle, July 2004
  • Invited talk on "Ein auf evolutionaerer Mehrzieloptimierung basierender Ansatz zur Regularisierung neuronaler Netze" (A method for neural network regularization based on evolutionary multi-objective optimization), Fachbereich Informatik, Lehrstuhl Systemanalyse (Prof. Dr. Hans-Paul Schwefel), University of Dortmund, Germany, March 1, 2004
  • Invited talk on "Rethinking multi-objective evolutionary algorithms", Dagstuhl Seminar on Theory of Evolutionary Algorithms, Schloss Dagstuhl, Germany, Feb. 15-20, 2004
  • Invited talk on "Dynamic weighted aggregation: from multi-objective optimization to dynamic optimum tracking". AIFB, University of Karlsruhe, Karlsruhe, Germany, Nov. 28, 2003
  • Invited talk on "Evolutionary multi-objective optimization: Methods, analysis and applications". The Industrial Engineering and Management Department, Yuan-Ze University, Chung-Li, Taiwan, ROC, Nov. 4-10, 2002

 

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