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

Tuesday: 10:00-12:00am, or contact Mrs. Maggie Burton for appointments.  

Further information

Biography

I grew up in a small village by the Grand Canal in the countryside of Suzhou, China. I went to Hangzhou to study at Zhejiang University in 1984, where I  received the B.Sc., M.Sc., and Ph.D. degrees, all in automatic control. 

I started my career in 1991 as an Associate Lecturer in the Electrical Engineering Department, Zhejiang University and became an Associate Professor there in 1996.  I was awarded a Scholarship from the Ministry of Education of China and went to Germany in1996 as a Visiting Researcher with the Lehrstuhl fuer Theoretische Biologie (chaired by Prof Dr Werner von Seelen), Institut fuer Neuroinformatik, Ruhr-Universitaet Bochum, where I was offered a full position as a wissenschaftlicher Mitarbeiter in 1997. From July 1998 to June 1999, I was a postdoctoral associate at the Department of Industrial Engineering, Rutgers, the State University of New Jersey, New Brunswick, NJ, participating in a DARPA project located at AlliedSignal, Morristown, NJ. In July 1999, I joined the Future Technology Research Division,  Honda R&D Europe, Offenbach, Germany, where I completed my Dr.-Ing. degree from Ruhr-Universitaet Bochum in November 2001. From January 2003 to May 2010, I was a Principal Scientist and Project Leader at Honda Research Institute Europe, responsible for research on fundamentals of evolution and learning. Between 2008 and 2010, I was also a Scientific Coordinator at the Research Institute for Cognition and Robotics (CoR-Lab), Bielefeld University, Germany.   

In June 2010, I moved to UK to take up a Chair in Computational Intelligence at the University of Surrey, heading the Nature-Inspired Computing and Engineering (NICE) research group. I am also Visiting Professor at the University of Science and Technology of China (2009-2011) and Shenzhen Institute of Advanced Technology, CAS (2011-2013). My current research interests are to gain systems-level insights into evolution, learning and development in biology using computational techniques, and to solve complex real-world problems with bio-inspired methodologies.

I currently serve as an Associate Editor of BioSystems, International Journal of Fuzzy Systems, the IEEE Transactions on Neural Networks, IEEE Transactions on Cybernetics, IEEE Transactions on Nanobioscience, IEEE Computational Intelligence Magazine and Soft Computing Journal.  I am also an Editorial Board Member of several other international journals. I am a member of EPSRC Peer Review College since September 2012.

I was the founding General Co-Chair of the 2007, 2009, 2011 and 2013 IEEE Symposium on Computational Intelligence in Multi-Criterion Decision-Making (IEEE MCDM), and the 2011, 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (IEEE CIDUE). I am the General Chair of the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2012), and Program Chair of 2013 IEEE Congress on Evolutionary Computation.

I am an elected AdCom member of the IEEE Computational Intelligence Society, serving a three-year term (2012-2014). I am also a Distinguished Lecturer of the IEEE CIS DLP. I am presently chairing the Intelligent Systems Application Technical Committee, and a member of the Award Committee of the IEEE Computational Intelligence Society.

I am a Fellow of BCS, Senior Member of IEEE, and a member of INNS.

Personal homepage.

Honors and Awards

  • Fellow, BCS
  • Best Paper Award, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 2-5, 2010, Montreal, Canada
    Authors: Yaochu Jin and Jens Trommler
    Title: A fitness-independent evolvability measure for evolutionary developmental systems.
  • Best Student Paper Award, the IEEE Symposium on Foundations of Computational Intelligence, April 1-5, 2007, Honolulu, Hawaii
    Authors: Ingo Paenke (Student), Juergen Branke (co-supervisor), Yaochu Jin (co-supervisor)
    Title: On the influence of phenotype plasticity on the genotype diversity.
  • Distinguished Visiting Professor, College of Informatics, Yuan Ze University, Taiwan, ROC
  • Excellent Text Book Award, Zhejiang University, 1999
  • Science and Technology Progress Award from Zhejiang Province, China, 1996
  • Scholarship for Overseas Studying from The Ministry of Education of China, 1996
  • Science and Technology Progress Award from The Ministry of Education of China, 1995
  • Senior Member, IEEE

Invited Plenary / Keynote Talks and Invited Tutorials

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 behavior 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

Research Interests

My primary research interests lie in nature inspired computing and engineering, including the computational approach to a systems-level understanding of evolution, learning and development in biology, and bio-inspired approaches to solving engineering problems. Relevant research fields cover computational intelligence, computational systems biology and computational neuroscience.

Research Grants (since 06.2010):

  • EC FP7, "SWARM-ORGAN: A theoretical framework for swarms of GRN-controlled agents which display adaptive tissue-like organisation.", Grant (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)
  • 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

  • Dr Sohrab Saeb (Principal supervisor. Research topic: "Neural development under selection pressure", started 04/2012)

Ph.D. Students

  • 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 Chaoli Sun, Taiyuan Institute of Science and Technology, China (10/2012 - 03/2013)
  • Ayang Xiao, Visiting PhD student, Harbin Institute of Technology, China (01/2012 - 04/2013)

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 modeling of neural development; modeling of gene regulated synaptic, neuronal and homeostatic plasticity, developmental neural networks, uniform modeling 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 modeling 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 modeling 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 behavior recognition, medical image analysis, EEG signal classification, image forensics
  • Electric and process control and optimization, robotic control,  industrial automation, and data mining

Past Members:

  • Ricardo Cerri, Santander Visiting PhD student, University of Sao Paulo, Brazil (03/2012 -08/2012)
  • Dr Colin Bell (KTA Research Fellow, 09/2011-09/2012)
  • Prof. Xiaoyan Sun, China University of Mining and Technology (09/2011 - 02/2012)
  • Dr Daniel Bush (Research Fellow, 11/2010-10.2011)
  • Prof. Chuan-Kang Ting, National Chung-Cheng University, Taiwan (07/2011-08/2011)
  • Dr M. Govindarajan, 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 modeling 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 behaviors 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:

  • Intellas UK Ltd
  • HR Wallingford
  • Bosch Thermotechnology Ltd
  • Aero Optimal
  • Honda Europe

Publications

My verified Google Scholar Citation Profile: h-index = 34, i10-index = 80, sum of citations = 5424 (as of 12.03.2013)

According to Thomson Reuters ISI Web of Science: h-index = 21, number of cited articles=76, sum of citations = 1773 (as of 12.03.2013)

See also Microsoft Academic Search or 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

Journal Papers Under Revision / Review

Refereed Journal Papers (in English)

  1. A. Zhou, Y. Jin and Q. Zhang. A population prediction strategy for evolutionary dynamic multiobjective optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2013 (accepted)
  2. S. A. Thomas and Y. Jin. Evolving connectivity between genetic oscillators and switches using evolutionary algorithms. Journal of Bioinformatics and Computational Biology, 2013 (accepted)
  3. 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. 2012 (accepted)
  4. X. Sun, D. Gong, Y. Jin and S. Chen. A new surrogate-assisted interactive genetic algorithm with weighted semi-supervised learning. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 2012 (accepted)
  5. M.N. Le, Y.S. Ong, S. Menzel, Y. Jin, and B. Sendhoff. Evolution by adapting surrogates. Evolutionary Computation, 2012 (accepted)
  6. 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
  7. 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
  8. 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
  9. 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
  10. J. Yin, Y. Meng, Y. Jin. A developmental approach to reservoir computing. IEEE Transactions on Autonomous Mental Development, 4(4):273-289, 2012
  11. 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
  12. D. Bush and Y. Jin. Calcium control of hippocampal STDP. Journal of Computational Neuroscience. 33(3):495-514, 2012
  13. Y. Jin, H. Guo, Y. 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
  14. Hongliang Guo, Yaochu 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
  15. B. Inden, Y. Jin, R. Haschke, H. Ritter. Evolving neural fields for problems with large input and output spaces. Neural Networks, 28: 24-39, 2012
  16. M. N. Le, Y. S. Ong, Y. Jin and B. Sendhoff. Gene meets meme in computational intelligence: A theoretic modeling of symbiotic evolution. IEEE Computational Intelligence Magazine, 7(1):20-35, 2012
  17. Y. Meng, Y. Jin, J. Yin. Modeling activity-dependent plasticity for human behavior recognition. IEEE Transactions on Neural Networks, 22(12):1952-1966, 2011
  18. 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
  19. 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
  20. Y. Zheng, Y. Meng, Y. Jin. Object recognition using neural networks with bottom-up and top-down pathways. Neurocomputing, 74(17):3158-3169, 2011
  21. D. Bush, 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)
  22. Y. Jin. Surrogate-assisted evolutionary computation: Recent advances and future challenges. Swarm and Evolutionary Computation. 1(2):61-70, 2011 (Invited survey paper)
  23. 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)
  24. 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 
  25. 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
  26. 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
  27. Y. Jin and Y. Meng. Emergence of robust regulatory motifs from in silico evolution of sustained oscillation. BioSystems, 103(1): 38-44, 2011
  28. 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)
  29. 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
  30. T. Steiner, Y. Jin, and B. Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177, 2009
  31. 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
  32. 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
  33. 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
  34. 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)
  35. I. Paenke, Y. Jin, J. Branke. Balancing population and individual level of adaptation in changing environments. Adaptive Behavior, 17(2):153-174, 2009
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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
  42. 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
  43. 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
  44. Y. Jin and J. Branke. Evolutionary optimization in uncertain environments - A survey. IEEE Transactions on Evolutionary Computation, 9(3), 303-317, 2005
  45. 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
  46. 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
  47. Y. Jin. A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing, 9(1), 3-12, 2005
  48. M. Huesken, Y. Jin and B. Sendhoff. Structure optimization of neural networks for evolutionary design optimization. Soft Computing, 9(1), 21-28, 2005
  49. Y. Jin and B. Sendhoff, Extracting interpretable fuzzy rules from RBF networks. Neural Processing Letters, 17(2), 149-164, 2003
  50. 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
  51. Y. Jin. Fuzzy modeling 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)
  52. Y. Jin and B. Sendhoff. Knowledge incorporation into neural networks from fuzzy rules. Neural Processing Letters, 10(3), 231-242, 1999
  53. 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
  54. Y. Jin and W. von Seelen. Evaluating flexible fuzzy controllers via evolution strategies. Fuzzy Sets and Systems, 108, 243-252, 1999
  55. Y. Jin. Decentralized adaptive fuzzy control of robot manipulators. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 28(1), 47-57, 1998
  56. Y. Jin, J. Jiang and J. Zhu. Neural network based fuzzy identification and its applications to modeling and control of complex systems. IEEE Transactions on Systems, Man and Cybernetics, 25(6), 990-997, 1995
  57. 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. 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
  2. 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
  3. 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
  4. 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
  5. S. Gu and Y. Jin. Heterogeneous classifier ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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)
  13. 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
  14. 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
  15. 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
  16. 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
  17. 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
  18. 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
  19. 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
  20. 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
  21. 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
  22. 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
  23. 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)
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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)
  29. 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  )
  30. 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
  31. 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)
  32. 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
  33. 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  
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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)
  41. 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
  42. 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
  43. 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
  44. 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)
  45. 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
  46. 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
  47. N. Samways, Y. Jin, X. Yao, and B. Sendhoff. Toward a gene regulatory network model for evolving chemotaxis behavior. Congress on Evolutionary Computation, pp.2574-2581, Hong Kong, June 2008
  48. 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
  49. A. Zhou, Q. Zhang, Y. Jin, B. Sendhoff. Adaptive modeling strategy for continuous multi-objective optimization. Congress on Evolutionary Computation, pp.431-437 Singapore, September 2007
  50. 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)
  51. 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
  52. 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
  53. D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff. A study on meta-modeling techniques, ensembles and multi-surrogates in evolutionary computation. Genetic and Evolutionary Computation Conference, pp.1288-1295, July 8-11, 2007
  54. 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)
  55. 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
  56. 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
  57. D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff. Trusted evolutionary algorithms. Congress on Evolutionary Computation, pp.456-463, 2006
  58. L. Gräning, Y. Jin, B. Sendhoff. Generalization improvement in multi-objective learning. Int. Joint Conference in Neural Networks, pp.9893-9900, 2006
  59. Y. Jin, B. Sendhoff. Alleviating catastrophic forgetting via multi-objective learning. International Conference on Neural Networks, pp.6367-6374, 2006
  60. 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
  61. 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
  62. 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
  63. 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
  64. 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
  65. 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
  66. 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
  67. 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
  68. 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
  69. 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
  70. 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
  71. 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
  72. 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
  73. 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
  74. 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
  75. 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
  76. 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
  77. 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
  78. 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
  79. 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
  80. 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
  81. 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)
  82. Y. Jin. Fitness approximation in evolutionary computation - A survey. In: Genetic and Evolutionary Computation Conference, pp.1105-1112, New York, July 2002
  83. 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
  84. 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
  85. 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
  86. 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
  87. 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
  88. 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
  89. 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
  90. 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
  91. 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
  92. 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 modeling 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

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, Universite Paris Sud, 2012 (Student Ilya Loshchilov, Supervisor: Prof Marc Schoenauer)
  2. Ph.D. thesis, RMIT University, Australia, 2012 (Student: Robert Carrese, Supervisor: Dr Jon Watmuff)
  3. Ph.D. thesis, Brunel University, 2012 (Student: Sameera Alshayji, Supervisor: Prof Zidong Wang) 
  4. Ph.D. thesis, Universidad de Málaga, Spain, 2012 (Student: Jose D. Fernandez Rodriguez, Supervisor: Prof Francisco J. Vico)
  5. PhD thesis, University of Exeter, 2012 (Student: Andrew Clark, Supervisor: Prof Richard Everson)
  6. PhD thesis, Nanyang Technological University, 2012 (Student: Xianshun Chen, Supervisor: Prof Yew Soon Ong)
  7. PhD thesis, University of Manchester, 2012 (Student: Richard Allmendinger, Supervisor: Dr Joshua Knowles)
  8. PhD thesis, Birkbeck, University of London, 2011 (Student: Tony Lewis, Supervisor: Prof George Magoulas)
  9. PhD thesis, La Trobe University, Australia, 2011 (Student: Xi Li, Supervisor: Prof Dianhui Wang)
  10. PhD thesis, University of Leicester, 2011 (Student: Imtiaz Korejo, Supervisor: Dr Shengxiang Yang)
  11. PhD thesis, Gwangju Institute of Science and Technology, Korea, 2011 (Student: Sanghoun Oh, Supervisor: Prof. Moongu Jeon)
  12. PhD thesis, University of Dortmund, Germany, 2011 (Student: Boris Naujoks, Supervisor: Prof. Guenther Rudolph)
  13. PhD thesis, Department of Management Engineering, Technical University of Denmark, 2011 (Student: J.-F. Dupuis, Supervisor: Prof. Zhun Fan)
  14. PhD thesis, School of Computer Science, University of Birmingham, UK, 2011 (Student: Trung Thanh Nguyen, Supervisor: Prof. Xin Yao)
  15. PhD thesis, Department of Computer Science, University of Leicester, UK, 2011 (Student: Changhe Li, Supervisor: Dr Shengxiang Yang)
  16. PhD thesis, School of Computer Science and Information Technology, RMIT University, Australia, 2010 (Student: W.R.M.U.K. Wickramasinghe, Supervisor: Dr. Xiaodong Li)
  17. PhD thesis, Department of Electronics, The University of York, UK, 2010 (Student: Tuze Kuyucu, Supervisor: Prof. Andy Tyrrell)
  18. PhD thesis, Department of Computer Science and Engineering, Annamalai University, India, 2010 (Studenrt: M. Govindarajan, Supervisor: Prof. R.M. Chandrasekaran)
  19. PhD thesis, Section Computational Science, University of Amsterdam, The Netherlands, 2009 (Student: Yves Fomkong-Nanfack, Supervisor: Prof. Jaap Kaandorp)
  20. PhD thesis, School of Computer Science and Information Technology, RMIT University, Australia, 2008 (Student: Antony Iorio, Supervisor: Dr Xiaodong Li)
  21. 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)
  22. PhD thesis, School of Computer Science, University of Essex, UK, 2007 (Student: Hui Li, Supervisor: Prof. Qingfu Zhang)
  23. PhD thesis, School of Computer Science, Nanyang Technological University, Singapore, 2006 (Student: Zongzhao Zhou, Prof. Yew Soon Ong)
  24. 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

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