Jun He B.A. (Maths) Ph.D. (Computer Science) Wuhan University, China

Senior Lecturer

Contact Details

Room Number..........:  E33
Building....................:  Llandinam
Phone.......................:   +44 (0)1970 621787
E-Mail........................:   jqh
External Publication Websites:
Google Scholar

Research Groups

Teaching Areas

Modules Taught

  • CSM2120: The Object Oriented Programming Paradigm
  • CSM6320: Representation and Reasoning for Intelligent Systems


A new framework for analysis of coevolutionary systems - directed graph representation and random walksChong, S. Y., Tiňo, P., He, J. & Yao, X. 2017 In : Evolutionary Computation.
Improved gene expression programming to solve the inverse problem for ordinary differential equationsLi, K., Chen, Y., Li, W., He, J. & Xue, Y. 2017 In : Swarm and Evolutionary Computation.38, p. 231-2399 p.
On Easiest Functions for Mutation Operators in Bio-Inspired OptimisationCorus, D., He, J., Jansen, T., Oliveto, P. S., Sudholt, D. & Zarges, C. 2017 In : Algorithmica.78, 2, p. 714–740
Average Drift Analysis and Population ScalabilityHe, J. & Yao, X. 2017 In : IEEE Transactions on Evolutionary Computation.99, 13 p.
The Research of Solving Inverse Problems of Complex Differential EquationsLi, K., Chen, Y. & He, J. 2017 Bio-inspired Computing - Theories and Applications: 11th International Conference, BIC-TA 2016, Xi'an, China, October 28-30, 2016. Gong, M., Pen, L., Song, T. & Zhang, G. (eds.). Part 11 ed.Springer Nature, p. 518-5236 p. (Communications in Computer and Information Science; vol. 682)
A New Multi-objective Model for Constrained OptimisationXu, T., He, J., Shang, C. & Ying, W. 2016 Advances in Computational Intelligence Systems: Contributions presented at the 16th UK Workshop on Computational Intelligence, September 7-9, 2016, Lancaster UK. Angelov, P., Gegov, A., Jayne, C. & Shen, Q. (eds.). Springer Nature, p. 71-85 Chapter 6. (Advances in Computational Intelligence Systems; vol. 513)
An analytic expression of relative approximation error for a class of evolutionary algorithmsHe, J. 2016 p. 4366-4373
Average Convergence Rate of Evolutionary AlgorithmsHe, J. & Lin, G. 2015 In : IEEE Transactions on Evolutionary Computation.20, 2, p. 316-3216 p.
Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack ProblemHe, J., Wang, Y. & Zhou, Y. 2015 Evolutionary Computation in Combinatorial Optimization. Ochoa, G. (ed.). Springer Nature, Vol. 9026, p. 74-85 (Lecture notes in Computer Science; vol. 9026)
Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIIIHe, J. (ed.), Jansen, T. (ed.), Ochoa, G. (ed.) & Zarges, C. (ed.) 2015 Association for Computing Machinery.
On easiest functions for somatic contiguous hypermutations and standard bit mutationsCorus, D., He, J., Jansen, T., Oliveto, P., Sudholt, D. & Zarges, C. 2015 Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015). New York: Association for Computing Machinery, p. 1399-1406
A theoretical assessment of solution quality in evolutionary algorithms for the knapsack problemHe, J., Mitavskiy, B. & Zhou, Y. 2014 p. 141-148
On the Easiest and Hardest Fitness FunctionsHe, J., Chen, T. & Yao, X. 2014 In : IEEE Transactions on Evolutionary Computation.19, 2, p. 295-305
Geiringer theorems: from population genetics to computational intelligence, memory evolutive systems and Hebbian learningMitavskiy, B. S., Tuci, E., Cannings, C., Rowe, J. & He, J. 2013 In : Natural Computing.12, 4, p. 473-484
Performance Analysis of Evolutionary Algorithms for the Minimum Label Spanning Tree ProblemLai, X., Zhou, Y., He, J. & Zhang, J. 2013 In : IEEE Transactions on Evolutionary Computation.18, 6, p. 860-872
Combining drift analysis and generalized schema theory to design efficient hybrid and/or mixed strategy EAsMitavskiy, B. & He, J. 2013 2013 IEEE Congress on Evolutionary Computation.IEEE Press, p. 2028-2036
Mixed strategy may outperform pure strategy: An initial studyHe, J., Hou, W., Dong, H. & He, F. 2013 2013 IEEE Congress on Evolutionary Computation (CEC).IEEE Press, p. 562-569
A further generalization of the finite-population geiringer-like theorem for pomdps to allow recombination overarbitrary set coversMitavskiy, B. S. & He, J. 2013 p. 133-146
A polynomial time approximation scheme for a single machine scheduling problem using a hybrid evolutionary algorithmMitavskiy, B. & He, J. 2012 2012 IEEE Congress on Evolutionary Computation (CEC).IEEE Press, p. 1-8
Pure Strategy or Mixed Strategy?He, J., He, F. & Dong, H. 2012 Evolutionary Computation in Combinatorial Optimization: 12th European Conference, EvoCOP 2012, Málaga, Spain, April 11-13, 2012. Proceedings. Hao, J-K. & Middendorf, M. (eds.). Springer Nature, Vol. 7245, p. 218-229 Chapter 19. (Evolutionary Computation in Combinatorial Optimization; vol. 7245)
Drift conditions for estimating the first hitting times of evolutionary algorithmsChen, Y., Zou, X. & He, J. 2011 In : International Journal of Computer Mathematics.88, 1, p. 37-5013 p.
A Note on the First Hitting Time of (1+N) Evolutionary Algorithm for Linear Functions with Boolean InputsHe, J. 2010 Proceedings of 2010 IEEE Congress on Evolutionary Computation.IEEE Press, p. 1-66 p.
A Mixed Strategy for Evolutionary Programming Based on Local Fitness LandscapeLiang, S. & He, J. 2010 p. 3501 p.
Choosing selection pressure for wide-gap problemsChen, T., He, J., Chen, G. & Yao, X. 2010 In : Theoretical Computer Science.411, 6, p. 926-934
Approximating Covering Problems by Randomized Search Heuristics Using Multi-Objective ModelsFriedrich, T., He, J., Hebbinghaus, N., Neumann, F. & Witt, C. 2010 In : Evolutionary Computation.18, 4, p. 617-633
Analyses of Simple Hybrid Algorithms for the Vertex Cover ProblemFriedrich, T., He, J., Hebbinghaus, N., Neumann, F. & Witt, C. 2009 In : Evolutionary Computation.17, 1, p. 3-1917 p.
A New Approach for Analyzing Average Time Complexity of Population-Based Evolutionary Algorithms on Unimodal ProblemsChen, T., He, J., Chen, G. & Yao, X. 2009 In : IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).39, 5, p. 1092-1106
Analysis of the (1+1)-EA for Finding Approximate Solutions to Vertex Cover ProblemsOliveto, P. S., He, J. & Yao, X. 2009 In : IEEE Transactions on Evolutionary Computation.13, 5, p. 1006-102924 p.
A Mixed Strategy of Combining Evolutionary Algorithms with Multigrid MethodsHe, J. & Kang, L. 2009 In : International Journal of Computer Mathematics.86, 5, p. 837-84913 p.
A Comparative Runtime Analysis of Heuristic Algorithms for Satisfiability ProblemsZhou, Y., He, J. & Nie, Q. 2009 In : Artificial Intelligence.173, 2, p. 240-25718 p.
A Hybrid Artificial Immune System and Self Organising Map for Network Intrusion DetectionPowers, S. & He, J. 2008 In : Information Sciences.178, 15, p. 3024-304219 p.
A Note on Problem Difficulty Measures in Black-Box Optimization: Classification, Realizations and PredictabilityHe, J., Reeves, C., Witt, C. & Yao, X. 2007 In : Evolutionary Computation.15, 4, p. 435-443
A runtime analysis of evolutionary algorithms for constrained optimization problemsZhou, Y. & He, J. 2007 In : IEEE Transactions on Evolutionary Computation.11, 5, p. 608-61912 p.
Towards an Analytic Framework for Analysing the Computation Time of Evolutionary AlgorithmsHe, J. & Yao, X. 2003 In : Artificial Intelligence.145, 1-2, p. 59-9739 p.
From an Individual to a Population: An Analysis of the First Hitting Time of Population-based Evolutionary AlgorithmsHe, J. & Yao, X. 2002 In : IEEE Transactions on Evolutionary Computation.6, 5, p. 495-51117 p.
Conditions for the convergence of evolutionary algorithmsHe, J. & Yu, X. 2001 In : Journal of Systems Architecture.47, 7, p. 601-612
Drift analysis and average time complexity of evolutionary algorithmsHe, J. & Yao, X. 2001 In : Artificial Intelligence.127, 1, p. 57-8529 p.