Prof Yaochu Jin | University of Surrey (2025)

Table of Contents
ResearchResearch interestsEvolutionary optimisationData driven evolutionary optimizationSurrogate-assisted evolutionary optimization and Bayesian optimization, transfer optimizationRobust and dynamic optimization, robustness over time, optimization in the presence of uncertaintyMulti-objective and many-objective optimizationLarge-scale optimization, federated optimizationMachine learningDeep learning, automated machine learning, neural architecture searchSecure and trustworthy machine learning, adversarial machine learning, privacy-preserving federated learning, learning over encrypted dataEvolutionary machine learning, multi-objective learningReal world applications include:Design optimization and control of complex systems, e.g., high-lift wing systems, fuselage of aircraft, turbine engines and vehicles, hybrid and electrical vehicles;Process optimization and control, including steel-making and continuous casting, and control of multi-level carbon fibre stretching processes; electric power transmission systemsImage identification, face recognition and human behaviour detectionHealthcare, bioinformatics and fintechMy 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 includeEvolutionary developmental systems (neural and morphological development, gene regulatory networks, brain-body co-evolution)Computational modelling of neural plasticity (computational modelling of plasticity, gene regulated plasticity in reservoir computing such as echo-state networks and liquid state machines)Morphogenetic robotics, including morphogenetic swarm and reconfigurable modular robotics. Research projects "Evolutionary Multi-objective Federated Learning" funded by industry (PI)The objective of this collaboration is to apply evolutionary optimization strategies to the multi-objective optimizationof federated recommendation system with minimal effect on the user’s experience of the mobile device. "Surrogate based runtime difference mitigation in asynchronous multi-disciplinary search tasks" funded by Honda Research Institute Europe (PI)Bayesian approaches to the optimization of complex systems have attracted much research in recent years and have achieved encouraging success. The project has mainly two aims: 1) Develop new training algorithms and new optimization methods that can deal with very low amount of training data for surrogate models and optimization evaluations. 2) Develop new infill criteria for Bayesian approaches to optimisation which integrate multiple models for estimating different criteria of a multi-objective problem or constraints. "Multi-source side information fusion assisted Bayesian optimization" funded by Royal Society (PI)In this project, we study multi-source side information fusion assisted Bayesian optimization models and algorithms. The aim of this study is to fully exploit the side information to reduce the number of computational times of expensive fitness functions, and, meanwhile, to accurately construct response surface in the parameter space for effectively searching and recognizing the global optimum. "Many-objective Bayesian optimization for vehicle dynamics" funded by Honda R&D Europe (PI)The project aims to improve digital development process for vehicle dynamics in the light of efficient many-objective optimization and smart visualization. "Multi-objective evolutionary methods for hierarchical and multi-label classification" funded by FAPESP SPRINT, Brazil (PI: Ricardo Cerri, Co-I: Yaochu Jin)FAPESP SPRINT,Surrey-PI, PI: Dr Ricardo Cerri, UFSCar, Brazil "Deep learning in mass spectrometry imaging" funded by EPSRC iCASE (PI)This project aims to develop new and innovative machine learning algorithms to analyse the data from the new 3D OrbiSIMS instrument (mass spectrometry) in a time and memory efficient manner. Current techniques limit the volume of data that can be analysed, and currently there are no methods to integrate the different modalities produced by the instrument. The 3D OrbiSIMS is the first of its kind and is involved in a large number of projects relating to antimicrobial resistance, cancer research, and material characterisation. The project offers a unique opportunity for candidates to contribute to a wide range of disciplines and impact a broad scientific base. "Preference learning in multi-objective decision making" funded by Honda (PI)This project investigates the current state of the art methods and algorithms relevant for decision making support systems. Focus points of the investigation are multi- and many-objective evolutionary optimization methods as well as non-evolutionary MCDM methods and methods from portfolio management in relation to decision making support systems in which user of a system are supported in the task of selecting solutions from a numerically identified Pareto front. "Data-driven surrogate-assisted evolutionary fluid dynamic optimization" funded by EPSRC (PI)This research proposal aims to permit the application of evolutionary algorithms, a class of global search metaheuristics, to fluid dynamic optimisation of highly complex industrial systems by exploiting surrogate models and modern machine learning techniques. "Decision support for complex multiobjective optimization problems (DeCoMo)" funded by Tekes (PI: Kaisa Miettinen, Finland Distinguished Professor: Yaochu Jin)Finland Distinguished Professor "A theoretical framework for swarms of GRN-controlled agents which display adaptive tissue-like organization - SWARM-ORGAN" funded by European Commission FP7 (PI)This project aims to use gene regulatory networks and morphogen gradients governing the biological development process for self-organizing large-scale swarm robots that can autonomously generating patterns for following and surrounding moving targets. "Surrogate-assisted evolutionary many-objective optimization" funded by Honda Research Institute Europe (PI)This project aims to address the main challenges in evolutionary many-objective optimisation using model-based techniques and surrogate-assisted evolutionary optimisation. "Optimisation of CFRP Stiffened Panels of Aircraft" funded by EPSRC KTA (PI)This project takes a detailed look at the design and use of materials in the aerospace industry, and will deliver a fully designed structure for use in aircraft design, and joins up a number of key themes in weight reduction, namely a reduction of fuel consumption and the knock-on environmental effects of this. It has been estimated that reduction in 1 Kg mass of the panel can lead to a saving of 1.5 to 2.million Euros based on today’s fuel prices. The project also pin-points the safety implications which must be taken into account when superseding already advanced aerospace composite materials. "Evolutionary methods for generating hierarchical and multi-label classifiers" funded by Santander (PI)Santander Doctoral Student Award "Copyright protection and forensics bootleg museum images" funded by EPSRC CASE (PI)Machine learning or pattern matching problem consists of two parts. Firstly, a set of features or statistics must be extracted from the object. The aim is to select features which include as much information relevant to the problem as possible, by avoiding unnecessary features. The second part is the classifier, like a support vector machine or artificial neural network. We will invest most of the time on feature extraction, because the features must be tailored to our particular problem of recognition. If the features are well-chosen, any classifier should be able to demonstrate some positive effect. Further work on the classifier design may improve results if the features are well-chosen, but may have no effect if they are properly not. AI-assisted Automatic Dental Disease Detection with Radiography funded by EPSRC Impact Acceleration Account (IAA) Projects Fund (PI:Yunpeng Li, Co-I: Yaochu Jin)The purpose aims to build a mobile phone app that empowers smartphones with Artificial Intelligence (AI) capability in firstly, correcting dental radiographic images to reduce errors for the viewer or prescriber, and secondly recognising normal anatomical structures and differentiate from subtle abnormalities. This project will provide a proof-of-concept study to incorporate AI into mobile devices to serve as a complementary method to help identify and classify dental diseases from digital radiographic images by improving the accuracy and diagnostic outcome "Efficient Evolutionary Neural Architecture Search for Human Face and Shape Recognition" funded by industry (PI)This project aims to develop computationally efficient, scalable, and powerful neural architecture search methods that are able to automatically generate deep neural network models best suited for a given problem at hand, in particular for human face and shape recognition. "Bayesian evolutionary optimization for electric drive" funded by Bosch (PI)This project aims to investigate the application of Bayesian optimization techniques to electric drive optimization with many objectives having various computational complexities. Research collaborationsAcademic collaborators:Dr Spencer Thomas, NPL, UKProf Tianyou Chai, Northeastern University, ChinaProf Kaisa Miettinen, University of Jyvaskyla, FinlandDr Mana Mahapatra, The Pirbright InstituteProf. Colin A. Smith and Dr Emma Laing, Department of Biological SciencesProf. Matthew Leach, CESProf. Soon-Thiam Khu, CESJohn Doherty, MES.Industrial collaborators:Huawei Research Institute, FinlandBosch, GermanyHonda R&D Europe, GermanyThe National Physical Laboratory, UKThe Pirbright Institute, UKHonda Research Institute Europe, GermanyValtra, FinlandFingrid, FinlandHR Wallingford, UKBosch Thermotechnology Ltd, UKAirbusQinetiQIntellas UK LtdAero OptimalSantander. Indicators of esteemIEEE Computational Intelligence Magazine Outstanding Paper Award, IEEE Computational Intelligence Society, 2020IEEE Transactions on Evolutionary Computation Outstanding Paper Award, IEEE Computational Intelligence Society, 2017Best Student Paper Award, IEEE Congress on Evolutionary Computation, June 5-8, 2017, San Sebastian, SpainIEEE Computational Intelligence Magazine Outstanding Paper Award, IEEE Computational Intelligence Society, 2016IEEE Computational Intelligence Magazine Outstanding Paper Award, IEEE Computational Intelligence Society, 2014Runner-up, Best Student Paper Award, IEEE Congress on Evolutionary Computation, July 2014, Beijing, ChinaBest Paper Award, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 2-5, 2010, Montreal, CanadaBest Student Paper Award(Student: I. Paenke, Supervisors: J. Branke, Y. Jin), IEEE Symposium on Foundations of Computational Intelligence, April 2007, Hawaii, USA Main conference activitiesSpecial Session Chair, 2014 IEEE World Congress on Computational Intelligence, July 6-11, 2014, Beijing, ChinaProgram Chair,2013 IEEE Congress on Evolutionary Computation, June 20-23, 2013, Cancu, MexicoGeneral Chair, 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 9-12, 2012, San Diego, USAArea Co-Chair,FUZZ-IEEE 2011, Taipei, Taiwan, June 27-30, 2011Program Co-Chair of International Workshop on Advanced Computational Intelligence, Oct. 19-21, 2011, Wuhan, ChinaIndustry Liaison, IJCNN 2011, San Jose, California, July 31 - August 5, 2011Co-Chair, IEEE Symposium on Computational Intelligence in Multi-Criterion Decision Making (MCDM 2011), part ofIEEE Symposium Series on Computational Intelligence, April 11-15, 2011, ParisCo-Chair, IEEE Symposium on Computational Intelligence in Industry (CII 2011), part ofIEEE Symposium Series on Computational Intelligence, April 11-15, 2011, ParisCo-Chair,IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE 2011), part ofIEEE Symposium Series on Computational Intelligence, April 11-15, 2011, ParisTutorials and Workshops Co-Chair, CEC 2010, Barcelona, Spain, July 18-23, 2010Program Chair-Industry,2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS'09), September, 2009, Istanbul, TurkeyProgram Co-Chair, IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (IEEE MCDM 2009), Part of SSCI 2009, March 30 - April 2, 2009, Nashville, TN, USATutorial Chair,2007 IEEE Congress on Evolutionary Computation, Singapore, Sept. 25-28, 2007Co-Chair,2007 IEEE Symposium on Multi-Criteria Decision-Making (IEEE MCDM 2007), Part of SSCI 2007, April 1-5, Honolulu, Hawaii, USAProgram Chair, The Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'05). Hunan, China, 27-29 August 2005Publicity Co-Chair, The Sixth International Conference on Intelligent Systems Design and Applications (ISDA2006), Jinan, China, Oct. 16-18, 2006.Main professional servicesAdCom Member,IEEE Computational Intelligence Society. Term 2012-2014Chair,Intelligent Systems Applications Technical Committee (ISATC), IEEE Computational Intelligence Society (2011 -)Management Committee Member, European Cooperation in Science and Technology (COST), Action IC0806: Intelligent Monitoring, Control, and Security of Critical Infrastructure Systems (2010)Chair,Industrial Liaison Subcommittee, IEEE Computational Intelligence Society (2010)Chair,Continuing Education Sub-Committee, IEEE Computational Intelligence Society (2009-2010)Member,Award Sub-Committee for Outstanding PhD Dissertation Award, IEEE Computational Intelligence Society (2009)Member,Evolutionary Computation Technical Committee, IEEE Computational Intelligence Society (2007 - )Member,Emergent Technologies Technical Committee, IEEE Computational Intelligence Society (2007 - 2010)Founding Chair, Task Force onEvolutionary Computation in Dynamic and Uncertain Environments,Evolutionary Computation Technical Committee, IEEE Computational Intelligence Society (2004 - 2010).Keynotes and invited talksInvited plenary / keynote talks and invited tutorialsInvited Keynote, “Scalable Model based Evolutionary Multi-objective Optimization”, 7th Joint International Conference on Computational Intelligence, Lisbon, Portugal, 12-14 November, 2015Invited Keynote, “Evolutionary optimization of complex systems in uncertain environments”, The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT) , June 30 - July 3 2015, Gijón, Asturias, SpainInvited Keynote, "Towards large-scale bio-inspired robot swarms", The 5th Joint International Conference on Swarm, Evolutionary and Memetic Computing", December 18-20, 2014, Bhubaneswar, Odisha, IndiaInvited Keynote, "Social and cellular swarm intelligence for scalable optimisation and swarm robot pattern formation", The 5th International Conference on Swarm Intelligence, October 17-19, 2014, Hefei, ChinaInvited Keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", 20th International Conference on Soft Computing (MENDEL'14), June 25-27, Brno, Czech RepublicInvited Keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", The 19th International Conference on Automation and Computing, September 13-14, 2013, Uxbridge, UKInvited Keynote, "Evolutionary dynamic optimization: To track or not to track, and how to track?" IEEE Symposium Series on Computational Intelligence, April 16-19 2013, SingaporeInvited summer school course, "Evolutionary optimisation of expensive problems." 22nd Jyvaskyla Summer School, University of Jyvaskyla, Finland, 13-17 August 2012Invited Keynote, 10th Workshop on Bioinformatics and 5th Symposium of the Polish Bioinformatics Society, 25 - 27 May 2012, Gdańsk, PolandInvited keynote, "Surrogate-assisted evolutionary optimization: Past, present and future", Learning and Intelligent Optimization Conference (LION 6), January 16-20, 2011, Paris, FranceInvited 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, ChinaInvited keynote, "Self-organisation of neural systems - An evolutionary and developmental perspective", DeveLeaNN Workshop, October 27-28, 2011, Paris, FranceInvited Keynote, "Computational modelling, analysis and synthesis of gene regulatory networks", Workshop on Computational Methods in Bioinformatics, October 19, 2011, Salerno, ItalyInvited keynote, "Morphogenetic self-organization of collective systems. Organic Computing Workshop, The 8th International Conference on Autonomic Computing, Karlsruhe, Germany, June 14-18, 2011Invited tutorial, "A systems approach to aerodynamic design optimization", Learning and Intelligent OptimizatioN (LION 5), Jan. 17-21, 2011, Rome, ItalyPlenary talk, "Morphogenetic robotics",World Congress on Nature and Biologically Inspired Computing, Kitakyushu, Japan, December 15-17, 2010Plenary 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, 2010Plenary talk, "Multi-objective machine learning",The 2010 International Workshop on Nature Inspired Computation and Application, October 23-27, 2010, Hefei, ChinaKeynote talk, "A fitness-independent evolvability measure for evolutionary developmental systems", 7th International Symposium on Networks in Bioinformatics, Amsterdam, the Netherlands, April 22-23, 2010Semi-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 ZealandKeynote talk, "Efficient evolutionary algorithms for complex engineering design", Adaptive Computing in Design and Manufacturing, April 29th-30th 2008, Bristol, UKKeynote talk, "Pareto-optimality is everywhere: From engineering design, machine learning to biological systems", Genetic and Evolving Fuzzy Systems, 4 - 7 March, 2008, Witten-Bommerholz, GermanyPlenary talk, "Pareto-based multi-objective machine learning",Hybrid Intelligent Systems, Sept. 17-19, 2007, Kaiserslautern, Germany.Other selected invited talksInvited Seminar, "Evolution of gene regulated cellular growth models for morphological development", Department of Computer Science, University of Oxford, January 31, 2014Invited Seminar, "A systems approach to evolutionary optimisation of complex engineering problems.", Department of Mathematical Information technology , University of Jyvaskyla, Finland, 16.08.2012Invited talk, "Morphogenetic self-organisation of robotic systems." Social Robotics lab, National University of Singapore, 05.06.2012Invited talk, "Modeling activity-dependent neural plasticity in liquid state machines for spatiotemporal pattern recognition." School of Computer Engineering, Nanyang Technological University, Singapore, 03.06.2012Invited speech,Biology + Computing = ??A Joint Meeting of the CSE:SEABIS Group and the ModAbs Group, Sponsored by SICSA, University of Stirling, UK, 21st May 2012Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", School of Computing, Robert Gordon University, 24 February, 2012Invited seminar, Department of Information Systems and Computing, Brunel University, 22 February, 2012Invited talk, "Morphogenetic robotics", Robot Intelligence Technology Lab, KAIST, Republic of Korea, December 16, 2011Invitd talk, "Morphogenetic robotics", College of Engineering, Seoul National University, Republic of Korea, December 15, 2011Invited talk, "Modeling neural plasticity for human behaviour recognition", School of Computer Science, Nanjing University, April 26, 2011Invited 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, 2011Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", The Centre for Computational Statistics and Machine Learning, University College London, January 27, 2011Invited 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, 2010Invited talk, "A systems approach to multi-objective optimization of complex systems", Department of Automation, Tsinghua University, 29th December, 2010Invited talk, "Analysis, synthesis and applications of gene regulatory networks models", School of Engineering, Mathematics and Physical Sciences, University of Exeter, 10th November, 2010Invited talk,International Workshop on Nature Inspired Computation and Applications, Oct. 23-27, 2010, Hefei, ChinaInvited speaker,EU ICT FET Action Workshop on EVOBODY: new Principles of Unbound Embodied Evolution. Sept. 23, 2010, MaltaInvited 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, HungaryInvited 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, 2010Invited talk, "Evolutionary multi-objective optimization of expensive problems using surrogate ensembles", Special Session on "Evolutionary Multi-Objective Optimization" organized by J. Branke, the 23rd European Conference on Operational Research, July 6-8 2009, Bonn, GermanyInvited talk, "Analysis, synthesis and applications of gene regulatory network", Colloquium, Faculty of Science, University of Amsterdam, February 13, 2009Invited 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, NZInvited talk, "Pareto analysis of evolutionary and learning systems",The 2008 International Workshop on Nature Inspired Computation and Applications, May 27-29,2008, Hefei, ChinaInvited talk (together with B. Sendhoff), "Towards multi-objective system optimization", EMO 2007, March 8, Matsushima, JapanInvited talk, "Scalable model-based multi-objective optimization", Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Dec. 13-17, 2006, Schloss Dagstuhl, Wadern, GermanyInvited talk, "Modeling regularity in multi-objective optimization", PPSN Workshop on Multi-Objective problem Solving from Nature, Sep. 9, 2006, ReykjavikInvited talk, "Multi-objective machine learning", School of Computer Science, University of Birmingham, February 18, 2006Invited talk, "Research on evolution and learning at HRI-EU",Kanpur Genetic Algorithm Lab, Indian Institute of Technology, Kanpur, India, July 6, 2005Invited talk on "Hybrid representations for evolutionary multi-objective optimization",Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Schloss Dagstuhl, Germany, Nov. 8-12, 2004Invited talk, "Aerodynamic optimization using evolutionary algorithms",Track on EC in Industry, GECCO'04, Seattle, July 2004Invited 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, 2004Invited talk on "Rethinking multi-objective evolutionary algorithms",Dagstuhl Seminar on Theory of Evolutionary Algorithms, Schloss Dagstuhl, Germany, Feb. 15-20, 2004Invited talk on "Dynamic weighted aggregation: from multi-objective optimization to dynamic optimum tracking".AIFB, University of Karlsruhe, Karlsruhe, Germany, Nov. 28, 2003Invited 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 Research projects Research collaborations Indicators of esteem Main conference activities Main professional services Keynotes and invited talks

Research

Research interests

  • Evolutionary optimisation
    • Data driven evolutionary optimization
    • Surrogate-assisted evolutionary optimization and Bayesian optimization, transfer optimization
    • Robust and dynamic optimization, robustness over time, optimization in the presence of uncertainty
    • Multi-objective and many-objective optimization
    • Large-scale optimization, federated optimization
  • Machine learning
    • Deep learning, automated machine learning, neural architecture search
    • Secure and trustworthy machine learning, adversarial machine learning, privacy-preserving federated learning, learning over encrypted data
    • Evolutionary machine learning, multi-objective learning
  • Real world applications include:
    • Design optimization and control of complex systems, e.g., high-lift wing systems, fuselage of aircraft, turbine engines and vehicles, hybrid and electrical vehicles;
    • Process optimization and control, including steel-making and continuous casting, and control of multi-level carbon fibre stretching processes; electric power transmission systems
    • Image identification, face recognition and human behaviour detection
    • Healthcare, bioinformatics and fintech

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 (neural and morphological development, gene regulatory networks, brain-body co-evolution)
  • Computational modelling of neural plasticity (computational modelling of plasticity, gene regulated plasticity in reservoir computing such as echo-state networks and liquid state machines)
  • Morphogenetic robotics, including morphogenetic swarm and reconfigurable modular robotics.

Research projects

"Evolutionary Multi-objective Federated Learning" funded by industry (PI)

The objective of this collaboration is to apply evolutionary optimization strategies to the multi-objective optimizationof federated recommendation system with minimal effect on the user’s experience of the mobile device.

"Surrogate based runtime difference mitigation in asynchronous multi-disciplinary search tasks" funded by Honda Research Institute Europe (PI)

Bayesian approaches to the optimization of complex systems have attracted much research in recent years and have achieved encouraging success. The project has mainly two aims: 1) Develop new training algorithms and new optimization methods that can deal with very low amount of training data for surrogate models and optimization evaluations. 2) Develop new infill criteria for Bayesian approaches to optimisation which integrate multiple models for estimating different criteria of a multi-objective problem or constraints.

"Multi-source side information fusion assisted Bayesian optimization" funded by Royal Society (PI)

In this project, we study multi-source side information fusion assisted Bayesian optimization models and algorithms. The aim of this study is to fully exploit the side information to reduce the number of computational times of expensive fitness functions, and, meanwhile, to accurately construct response surface in the parameter space for effectively searching and recognizing the global optimum.

"Many-objective Bayesian optimization for vehicle dynamics" funded by Honda R&D Europe (PI)

The project aims to improve digital development process for vehicle dynamics in the light of efficient many-objective optimization and smart visualization.

"Multi-objective evolutionary methods for hierarchical and multi-label classification" funded by FAPESP SPRINT, Brazil (PI: Ricardo Cerri, Co-I: Yaochu Jin)

FAPESP SPRINT,Surrey-PI, PI: Dr Ricardo Cerri, UFSCar, Brazil

"Deep learning in mass spectrometry imaging" funded by EPSRC iCASE (PI)

This project aims to develop new and innovative machine learning algorithms to analyse the data from the new 3D OrbiSIMS instrument (mass spectrometry) in a time and memory efficient manner. Current techniques limit the volume of data that can be analysed, and currently there are no methods to integrate the different modalities produced by the instrument. The 3D OrbiSIMS is the first of its kind and is involved in a large number of projects relating to antimicrobial resistance, cancer research, and material characterisation. The project offers a unique opportunity for candidates to contribute to a wide range of disciplines and impact a broad scientific base.

"Preference learning in multi-objective decision making" funded by Honda (PI)

This project investigates the current state of the art methods and algorithms relevant for decision making support systems. Focus points of the investigation are multi- and many-objective evolutionary optimization methods as well as non-evolutionary MCDM methods and methods from portfolio management in relation to decision making support systems in which user of a system are supported in the task of selecting solutions from a numerically identified Pareto front.

"Data-driven surrogate-assisted evolutionary fluid dynamic optimization" funded by EPSRC (PI)

This research proposal aims to permit the application of evolutionary algorithms, a class of global search metaheuristics, to fluid dynamic optimisation of highly complex industrial systems by exploiting surrogate models and modern machine learning techniques.

"Decision support for complex multiobjective optimization problems (DeCoMo)" funded by Tekes (PI: Kaisa Miettinen, Finland Distinguished Professor: Yaochu Jin)

Finland Distinguished Professor

"A theoretical framework for swarms of GRN-controlled agents which display adaptive tissue-like organization - SWARM-ORGAN" funded by European Commission FP7 (PI)

This project aims to use gene regulatory networks and morphogen gradients governing the biological development process for self-organizing large-scale swarm robots that can autonomously generating patterns for following and surrounding moving targets.

"Surrogate-assisted evolutionary many-objective optimization" funded by Honda Research Institute Europe (PI)

This project aims to address the main challenges in evolutionary many-objective optimisation using model-based techniques and surrogate-assisted evolutionary optimisation.

"Optimisation of CFRP Stiffened Panels of Aircraft" funded by EPSRC KTA (PI)

This project takes a detailed look at the design and use of materials in the aerospace industry, and will deliver a fully designed structure for use in aircraft design, and joins up a number of key themes in weight reduction, namely a reduction of fuel consumption and the knock-on environmental effects of this. It has been estimated that reduction in 1 Kg mass of the panel can lead to a saving of 1.5 to 2.million Euros based on today’s fuel prices. The project also pin-points the safety implications which must be taken into account when superseding already advanced aerospace composite materials.

"Evolutionary methods for generating hierarchical and multi-label classifiers" funded by Santander (PI)

Santander Doctoral Student Award

"Copyright protection and forensics bootleg museum images" funded by EPSRC CASE (PI)

Machine learning or pattern matching problem consists of two parts. Firstly, a set of features or statistics must be extracted from the object. The aim is to select features which include as much information relevant to the problem as possible, by avoiding unnecessary features. The second part is the classifier, like a support vector machine or artificial neural network. We will invest most of the time on feature extraction, because the features must be tailored to our particular problem of recognition. If the features are well-chosen, any classifier should be able to demonstrate some positive effect. Further work on the classifier design may improve results if the features are well-chosen, but may have no effect if they are properly not.

AI-assisted Automatic Dental Disease Detection with Radiography funded by EPSRC Impact Acceleration Account (IAA) Projects Fund (PI:Yunpeng Li, Co-I: Yaochu Jin)

The purpose aims to build a mobile phone app that empowers smartphones with Artificial Intelligence (AI) capability in firstly, correcting dental radiographic images to reduce errors for the viewer or prescriber, and secondly recognising normal anatomical structures and differentiate from subtle abnormalities. This project will provide a proof-of-concept study to incorporate AI into mobile devices to serve as a complementary method to help identify and classify dental diseases from digital radiographic images by improving the accuracy and diagnostic outcome

"Efficient Evolutionary Neural Architecture Search for Human Face and Shape Recognition" funded by industry (PI)

This project aims to develop computationally efficient, scalable, and powerful neural architecture search methods that are able to automatically generate deep neural network models best suited for a given problem at hand, in particular for human face and shape recognition.

"Bayesian evolutionary optimization for electric drive" funded by Bosch (PI)

This project aims to investigate the application of Bayesian optimization techniques to electric drive optimization with many objectives having various computational complexities.

Research collaborations

Academic collaborators:

  • Dr Spencer Thomas, NPL, UK
  • Prof Tianyou Chai, Northeastern University, China
  • Prof Kaisa Miettinen, University of Jyvaskyla, Finland
  • Dr Mana Mahapatra, The Pirbright Institute
  • Prof. Colin A. Smith and Dr Emma Laing, Department of Biological Sciences
  • Prof. Matthew Leach, CES
  • Prof. Soon-Thiam Khu, CES
  • John Doherty, MES.

Industrial collaborators:

  • Huawei Research Institute, Finland
  • Bosch, Germany
  • Honda R&D Europe, Germany
  • The National Physical Laboratory, UK
  • The Pirbright Institute, UK
  • Honda Research Institute Europe, Germany
  • Valtra, Finland
  • Fingrid, Finland
  • HR Wallingford, UK
  • Bosch Thermotechnology Ltd, UK
  • Airbus
  • QinetiQ
  • Intellas UK Ltd
  • Aero Optimal
  • Santander.

Indicators of esteem

Main conference activities

Main professional services

Keynotes and invited talks

Invited plenary / keynote talks and invited tutorials

  • Invited Keynote, “Scalable Model based Evolutionary Multi-objective Optimization”, 7th Joint International Conference on Computational Intelligence, Lisbon, Portugal, 12-14 November, 2015
  • Invited Keynote, “Evolutionary optimization of complex systems in uncertain environments”, The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT) , June 30 - July 3 2015, Gijón, Asturias, Spain
  • Invited Keynote, "Towards large-scale bio-inspired robot swarms", The 5th Joint International Conference on Swarm, Evolutionary and Memetic Computing", December 18-20, 2014, Bhubaneswar, Odisha, India
  • Invited Keynote, "Social and cellular swarm intelligence for scalable optimisation and swarm robot pattern formation", The 5th International Conference on Swarm Intelligence, October 17-19, 2014, Hefei, China
  • Invited Keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", 20th International Conference on Soft Computing (MENDEL'14), June 25-27, Brno, Czech Republic
  • 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 selected invited talks

  • Invited Seminar, "Evolution of gene regulated cellular growth models for morphological development", Department of Computer Science, University of Oxford, January 31, 2014
  • 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 Optimization" 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.

Prof Yaochu Jin | University of Surrey (2025)
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