Biosketch (中文简历）
Professor Yaochu Jin holds a Chair in Computational Intelligence and heads the Nature Inspired Computing and Engineering (NICE) Group , Department of Computing, University of Surrey, Guildford, Surrey, UK. He is also a Visiting Professor of Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, and Donghua University, Shanghai, China.He received the BSc, MSc and PhD degrees, all in automatic control from Zhejiang University, China and the Dr.-Ing. degree from Ruhr-University Bochum, Germany. He was Principal Scientist and Group Leader at the Honda Research Institute Europe, Germany before he was appointed Chair in Computational Intelligence at University of Surrey in June 2010. He was Associate Lecturer, Lecturer and Associate Professor with the Electrical Engineering Department, Zhejiang University from 1991 to 1996. His main research interests include computational modeling of evolution, learning and development in biology, and bio-inspired approaches to optimization, learning and self-organisation. He has published over 150 journal and conference papers and was granted 7 US/EU/Japan patents. His papers have reported approximately 5,000 citations (according to Google Scholar). Since he joined Surrey in June 2010, he has successfully attracted fundings from EU FP7, UK EPSRC, and industries, including Santander, Bosch UK, HR Wallingford, Intellas UK Ltd, Aero Optimal and Honda.
Professor Jin is a Distinguished Lecturer (2013-2015), an AdCom member (2012-2014), a member of the Award Committee (2012) and Chair (2011-2012) of the Intelligent Systems Application Technical Committee of the IEEE Computational Intelligence Society. He currently serves as an Associate Editor of BioSystems, the IEEE Transactions on Cybernetics (previously IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics), the IEEE Transactions on Neural Networks and Learning Systems, the IEEE Transactions on Nanobioscience, IEEE Computational Intelligence Magazine, the Soft Computing Journal and the International Journal of Fuzzy Systems. He was the founding General Co-Chair of the 2007, 2009, 2011 and 2013 IEEE Symposium on Computational Intelligence in Multi-Criterion Decision-Making, and the founding General Co-Chair of 2011 and 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments. He is the General Chair of the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. He has delivered over 14 Keynote speeches at international conferences on morphogenetic robotics and morphogenetic self-organizing systems, developmental neural computation, modeling and analysis of gene regulatory networks, evolutionary optimization in dynamic and uncertain environments and multi-objective machine learning.
Professor Jin is a member of Peer Review College of EPSRC, UK, a member of Computer Science Review Panel, Academy of Finland, an Evaluator of EU FP7 FET, a Peer Reviewer of Italian Evaluation of Research Quality exercise (VQR 2004-2010), and a Grant reviewer for many funding agencies, including the Royal Academy of Engineering (UK), the Levehulme Trust (UK), the Marsden Fund (New Zealand), Killam Fellowship Program (Canada), the Netherlands Organization for Scientific Research, and the European Science Foundation.
He is a Fellow of British Computer Society, Senior Member of IEEE and Member of INNS.
Recently Funded Projects (since 06/2010)
- "SWARM-ORGAN: A theoretical framework for swarms of GRN-controlled agents which display adaptive tissue-like organisation", EU FP7 (PI at Surrey, in collboration with CRG, Spain, University of Amsterdam, the Netherlands, and University of East Anglia, UK, 03.2013-08.2016)
- "Sparse multi-way digital signal processing approach for detection of deep medial temporal discharges from scalp EEG", funded by EPSRC (Co-I, 01.2013-06.2015. PI: Dr Saeid Sanei)
- "Model-based evolutionary many-objective optimisation" funded by Honda Research Institute Europe (PI, 01.2013-12.2015)
- "Evolutionary optimisation of CFRP stiffened panels of aircraft", funded by EPSRC KTA and Aero Optimal (PI, 09.2011-09.2012)
- "Fast and robust feature extraction for detection of bootlegged museum images", funded by EPSRC CASE and Intellas UK Ltd (PI, 01.2011-06.2014)
- "Evolutionary methods for generating hierarchical and multi-label classifiers", Santander Doctoral Student Award, (PI, 03.2012-08.2012)
- "Reconstruction of global regulatory networks governing the production of antibiotics in Streptomyces bacteria", funded by EPSRC DTC, in collaboration with Microbial and Cellular Sciences Department, University of Surrey (PI, 07.2011-03.2014)
- "Heterogeneous ensenbles for convergence prediction in surrogate-asssited evolutionary optimisation", funded by EPSRC DTC, incollaboration with Division of Mechanical, Medical and Aerospace Engineering, University of Surrey (PI, 07.2011-03.2014)
- "Modeling neural plasticity for spatiotemporal pattern recognition", funded by EPSRC DTG (PI, 07.2011-12.2014)
- "Intelligent heat solutions: Concepts and strategies for product development", funded by EPSRC EngD and Bosch Thermotechnology (PI, 09.2011-08.2014)
- "Knowledge extraction and development of decision support systems for conceptual design of sustainable liquified nitrogen gas terminals", funded by EPSRC EngD and HR Wallingford (Co-I, 05.2011-04.2014)
- "Predicting suitable vaccines for foot-and-mouth disease virus based on genetic sequence", jointly funded by Microbial and Cellular Sciences Department and Computing Department, University of Surrey, in collaboration with Institute for Animal Health, Surrey (PI, 10.2011-09.2014)
- "Semi-supervised ensemble learning for BCI-based game control", funded by Department of Computing, University of Surrey (PI, 10.2011-09.2014)
- "Computational modeling of neural plasticity", start-up grant, funded by Department of Computing, University of Surrey (PI, 11.2010-10.2012)
Research Interests
Professor Jin's primary research interests include the computational approach to a systems-level understanding of evolution, learning and development in biology, and nature-inspired approaches to solving complex engineering problems. Relevant research fields cover artificial life, bio-inspired robotics, computational intelligence, computational systems biology and computational neuroscience. Currently, he is interested in the following research topics:- Computational Intelligence (CI)
- Evolutionary optimization in the presence of uncertainties, in particular surrogate-assisted (metamodel) evolutionary optimization of expensive problems, search for robust solutions, dynamic optimization and dynamicalization
- Efficient and scalable evolutionary multi-objective optimization
- Multi-objective machine learning; Pareto-analysis of evolutionary and learning systems; interactions of evolution and learning in changing environments
- Hybrid systems (neural-fuzzy-genetic systems), interpretability of data-driven fuzzy systems, knowledge extraction from trained neural networks,knowledge incorporation into neural networks, and knowledge incorporation into evolutionary algorithms
- 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, machine learning approach to analysis of biological data
- Computational and Cognitive Neuroscience (CCN)
- Evolutionary developmental neurocomputing: Understanding neural organization in evolution through brain-body co-evolution, modeling of activity-independent and activity-dependent neural development; modeling of synaptic, neuronal and homeostatic plasticity, structural and synaptic plasticity in spiking neural networks and liquid state machines
- Computational cognitive neuroscience: Memory organization, top-down and bottom-up pathways in neural information processing
- Real-world Applications of CI, CSBB and CCN
- Morphogenetic robotics, morphogenetic self-organization of engineered collective systems (UAVs, small satellites, and mobile sensor networks), cellular design of materials
- Complex engineering optimization, auch as aerodynamic design optimization, micro heat exchanger optimization, vehicle design and optimization, decision-making and decision support
- Human behavior recognition, image forensics, medical image analysis, spatiotemporal pattern recognition
- Electric and process control, robotic control, industrial automation, and data mining
Research Team
Current Vacancies
- A postdoc and a PhD position on morphogenetic swarm robots for self-organised pattern formation are expected to open soon
- A PhD position on evolutionary optimisation funded by industry is now open. Earliest entry date: January 2013.
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PhD scholarship is available for Brasilian students to study at Surrey. Interested students should first apply for PhD admission at Surrey and then apply for the scholarship. An undergraduate upper second class honours degree or above (quivalent to Bacharel, Licenciado or professional title with 7.0 out of 10 or ‘bom’ / 'muito bom' in Brasil) and IELTS (a minimum 6.5 on average and 6.0 for all single items) are required.
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