Dr John Woodward

Senior Lecturer
Email: j.woodward@qmul.ac.ukTelephone: +44 20 7882 5813Room Number: Engineering, Eng 212
Teaching
Introductory Java Programming (BUPT joint programme)
Research
Publications
- Winter ER, Nowack V, Bowes D et al. (2022), Let's Talk With Developers, Not About Developers: A Review of Automatic Program Repair Research $nameOfConference
- Wang X, Brownlee AEI, Weiszer M et al. (2021), A chance-constrained programming model for airport ground movement optimisation with taxi time uncertainties $nameOfConference
- Hong L, Woodward JR, Özcan E et al. (2021), Hyper-heuristic approach: automatically designing adaptive mutation operators for evolutionary programming $nameOfConference
- Haraldsson S, Brownlee A, Woodward JR et al. (2021), Genetic improvement: Taking real-world source code and improving it using genetic programming $nameOfConference
- Tauritz DR, Woodward J (2021), Hyper-heuristics tutorial $nameOfConference
- Krari ME, Guibadj RN, Woodward J et al. (2021), Introducing a hash function for the travelling salesman problem for differentiating solutions $nameOfConference
- Kirbas S, Windels E, Mcbello O et al. (2021), On the Introduction of Automatic Program Repair in Bloomberg $nameOfConference
- Wang X, Gu Y, Wu G et al. (2021), Robust scheduling for multiple agile Earth observation satellites under cloud coverage uncertainty $nameOfConference
- Rezaei MJ, Woodward JR, Ramírez J et al. (2021), A novel two-stage heart arrhythmia ensemble classifier $nameOfConference
- De Lemos F, Woodward J (2021), Calculating block time and consumed fuel for an aircraft model $nameOfConferenceDOI: 10.1017/aer.2020.137
- Craven MJ, Woodward JR (2021), Evolution of group-theoretic cryptology attacks using hyper-heuristics $nameOfConference
- Nowack V, Bowes D, Counsell S et al. (2021), Expanding Fix Patterns to Enable Automatic Program Repair $nameOfConference
- Gan Y, Chen X, Huang Q et al. (2021), Towards robustness of text-to-SQL models against synonym substitution $nameOfConference
- Wang X, Brownlee AEI, Woodward JR et al. (2020), Aircraft taxi time prediction: Feature importance and their implications $nameOfConference
- Rezaei MJ, Woodward JR, Ramirez J et al. (2020), Data Augmentation for Heart Arrhythmia Classification $nameOfConference
- Volkovas R, Fairbank M, Woodward JR et al. (2020), Practical Game Design Tool: State Explorer $nameOfConference
- Nowack V, Bowes D, Counsell S et al. (2020), Exploiting Fault Localisation for Efficient Program Repair GECCO ’20 Companion
- Haraldsson S, Woodward JR, Wagner M (2020), Genetic improvement: Taking real-world source code and improving it using genetic programming $nameOfConference
- Tauritz DR, Woodward J (2020), Hyper-heuristics tutorial $nameOfConference
- Winter E, Bowes D, Counsell S et al. (2020), Human Factors in the Study of Automatic Software Repair: Future Directions for Research with Industry $nameOfConference
- Martin SP, Craven MJ, Woodward JR (2020), A structured approach to modifying successful heuristics $nameOfConference
- Wang S, Drake JH, Fairbrother J et al. (2019), A Constructive Heuristic Approach for Single Airport Slot Allocation Problems $nameOfConference
- Volkovas R, Fairbank M, Woodward JR et al. (2019), Extracting learning curves from puzzle games $nameOfConference
- Volkovas R, Fairbank M, Woodward JR et al. (2019), Mek: Mechanics prototyping tool for 2d tile-based turn-based deterministic games $nameOfConference
- Warriar VR, Woodward JR, Tokarchuk L (2019), Modelling player preferences in AR mobile games IEEE Conference on Computatonal Intelligence and Game
- Warriar VR, Ugarte C, Woodward JR et al. (2019), PlayMapper: Illuminating design spaces of platform games IEEE Conference on Computatonal Intelligence and Game
- Tauritz DR, Woodward J (2019), Hyper-heuristics Tutorial $nameOfConference
- Lucas S, Liu J, Bravi I et al. (2019), Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best Game Simulations Workshop (AAAI)
- Burke EK, Hyde MR, Kendall G et al. (2019), A classification of hyper-heuristic approaches: Revisited $nameOfConference
- Pappa GL, Emmerich MTM, Bazzan A et al. (2018), Tutorials at PPSN 2018 $nameOfConference
- Tauritz DR, Woodward J (2018), Hyper-heuristics tutorial $nameOfConference
- Christie LA, Brownlee AEI, Woodward JR (2018), Investigating benchmark correlations when comparing algorithms with parameter tuning $nameOfConference
- Brownlee AEI, Woodward JR, Veerapen N (2018), Relating training instances to automatic design of algorithms for bin packing via features $nameOfConference
- Brownlee AEI, Weiszer M, Woodward JR et al. (2018), A rolling window with genetic algorithm approach to sorting aircraft for automated taxi routing $nameOfConference
- Petke J, Haraldsson SO, Harman M et al. (2018), Genetic Improvement of Software: A Comprehensive Survey $nameOfConference
- Brownlee AEI, WEISZER M, CHEN J et al. (2018), A Fuzzy Approach to Addressing Uncertainty in Airport Ground Movement Optimisation $nameOfConference
- DRAKE J, woodward JR (2017), A Hyper-heuristic Approach to Automated Generation of Mutation Operators for Evolutionary Programming $nameOfConference
- WOODWARD JR (2017), The use of predictive models in dynamic treatment planning $nameOfConference
- Haraldsson SO, Woodward JR, Brownlee AEI et al. (2017), Fixing bugs in your sleep: How genetic improvement became an overnight success $nameOfConference
- Haraldsson SO, Woodward JR, Brownlee AEI et al. (2017), Genetic Improvement of Runtime and its Fitness Landscape in a Bioinformatics Application $nameOfConference
- Tauritz DR, Woodward J (2017), Hyper-heuristics tutorial $nameOfConference
- Haraldsson SO, Woodward JR, Brownlee AIE (2017), The use of automatic test data generation for genetic improvement in a live system $nameOfConferenceDOI: 10.1109/SBST.2017.10
- Bai R, Woodward JR, Subramanian N et al. (2017), Optimisation of transportation service network using κ -node large neighbourhood search $nameOfConference
- Bai R, Woodward JR, Subramanian N (2017), A new fast large neighbourhood search for service network design with asset balance constraints $nameOfConference
- Haraldsson SO, Woodward JR, Brownlee AEI et al. (2017), Exploring fitness and edit distance of mutated python programs $nameOfConference
- Benlic U, Burke EK, Woodward JR (2017), Breakout local search for the multi-objective gate allocation problem $nameOfConference
- Hong L, Drake JH, Woodward JR et al. (2016), Automatically designing more general mutation operators of Evolutionary Programming for groups of function classes using a hyper-heuristic $nameOfConference
- Woodward JR, Johnson CG, Brownlee AEI (2016), Connecting automatic parameter tuning, genetic programming as a hyper-heuristic, and genetic improvement programming $nameOfConference
- López-Ibáez M, Tauritz D, Woodward J (2016), ECADA 2016 chairs' welcome $nameOfConference
- Woodward JR, Brownlee AEI, Johnson CG (2016), Evals is not enough: Why we should report wall-clock time $nameOfConference
- Woodward JR, Johnson CG, Brownlee AEI (2016), GP vs GI: If you can't beat them, join them $nameOfConference
- Johnson CG, Woodward JR (2015), Fitness as task-relevant information accumulation $nameOfConference
- Haraldsson SO, Woodward JR (2015), Genetic improvement of energy usage is only as reliable as the measurements are accurate $nameOfConference
- Woodward J, Tauritz DR (2015), Hyper-heuristics tutorial $nameOfConference
- Brownlee AEI, Woodward JR, Swan J (2015), Metaheuristic design pattern: Surrogate fitness functions $nameOfConference
- Pappa GL, Ochoa G, Hyde MR et al. (2014), Contrasting meta-learning and hyper-heuristic research: The role of evolutionary algorithms $nameOfConference
- Swan J, Woodward J, Özcan E et al. (2014), Searching the Hyper-heuristic Design Space $nameOfConference
- Brownlee AEI, Atkin JAD, Woodward JR et al. (2014), Airport ground movement: Real world data sets and approaches to handling uncertainty $nameOfConference
- Haraldsson SO, Woodward JR (2014), Automated design of algorithms and genetic improvement: Contrast and commonalities $nameOfConference
- Woodward J, Martin S, Swan J (2014), Benchmarks that matter for genetic programming $nameOfConference
- Chuang Y, Chen L, Chen G et al. (2014), Isophote based center-surround contrast computation for image saliency detection $nameOfConference
- Woodward J, Swan J (2014), Template method hyper-heuristics $nameOfConference
- Woodward J, Swan J, Martin S (2014), The 'composite' design pattern in metaheuristics $nameOfConference
- Majid A, Chen L, Chen G et al. (2013), A context-aware personalized travel recommendation system based on geotagged social media data mining $nameOfConference
- Swan J, Drake J, Özcan E et al. (2013), A comparison of acceptance criteria for the daily car-pooling problem $nameOfConference
- Woodward J, Swan J (2013), A syntactic approach to prediction $nameOfConference
- Cui T, Li J, Woodward JR et al. (2013), An ensemble based Genetic Programming system to predict English football premier league games $nameOfConference
- Hong L, Woodward J, Li J et al. (2013), Automated design of probability distributions as mutation operators for evolutionary programming using genetic programming $nameOfConference
- Burke EK, Hyde MR, Kendall G et al. (2012), Automating the packing heuristic design process with genetic programming $nameOfConferenceDOI: 10.1162/EVCO_a_00044
- Woodward J, Swan J (2012), The automatic generation of mutation operators for Genetic Algorithms $nameOfConference
- Chen L, Lv M, Ye Q et al. (2011), A personal route prediction system based on trajectory data mining $nameOfConference
- Woodward JR, Swan J (2011), Automatically designing selection heuristics $nameOfConference
- Woodward JR (2010), The Necessity of meta bias in search algorithms $nameOfConference
- Woodward JR, Swan J (2010), Why classifying search algorithms is essential $nameOfConference
- Woodward JR, Gindy N (2010), A hyper-heuristic multi-criteria decision support system for eco-efficient product life cycle $nameOfConferenceDOI: 10.1049/cp.2010.0436
- Burke EK, Hyde M, Kendall G et al. (2010), A genetic programming hyper-heuristic approach for evolving 2-D strip packing heuristics $nameOfConference
- Woodward JR, Farjudian A (2010), Artificial life, the second law of thermodynamics, and Kolmogorov complexity $nameOfConference
- Woodward JR (2009), Computable and incomputable functions and search algorithms $nameOfConference
- Woodward JR, Bai R (2009), Canonical representation genetic programming $nameOfConference
- Burke EK, Hyde MR, Kendall G et al. (2009), Exploring hyper-heuristic methodologies with genetic programming $nameOfConference
- Woodward JR, Bai R (2009), Why evolution is not a good paradigm for program induction; A critique of genetic programming $nameOfConference
- Poli R, Woodward J, Burke EK (2007), A histogram-matching approach to the evolution of bin-packing strategies $nameOfConference
- Burke EK, Hyde MR, Kendall G et al. (2007), The scalability of evolved on line bin packing heuristics $nameOfConference
- Burke EK, Hyde MR, Kendall G et al. (2007), Automatic heuristic generation with genetic programming: Evolving a jack-of-all-trades or a master of one $nameOfConference
- Woodward JR (2006), Complexity and Cartesian genetic programming $nameOfConferenceDOI: 10.1007/11729976_23
- Woodward JR (2006), Invariance of function complexity under primitive recursive functions $nameOfConferenceDOI: 10.1007/11729976_28
- Woodward J (2005), Complexity and cartesian genetic programming $nameOfConference
- Woodward J (2005), Invariaiice of function complexity under primitive reeursive functions $nameOfConference
- Woodward JR (2003), Evolving turing complete representations $nameOfConference
- Woodward JR (2003), GA or GP? That is not the question $nameOfConference
- Woodward JR (2003), Modularity in Genetic Programming $nameOfConference
- Woodward JR, Neil JR (2003), No free lunch, program induction and combinatorial problems $nameOfConference