Markus Wagner

• Appointments

  Date	Position	Institution name
  2023 - ongoing	Associate Professor	Monash University
  2023 - ongoing	Adjunct Associate Professor	University of Adelaide
  2020 - 2022	Associate Professor	University of Adelaide
  2017 - ongoing	Senior Lecturer	University of Adelaide
  2013 - 2016	Lecturer	University of Adelaide

• Journals

  Year	Citation
  2025	Caddy, J., Treude, C., Wagner, M., & Barr, E. T. (2025). The role of surprisal in issue trackers. Empirical Software Engineering, 30(1). DOI
  2024	Zanartu, F., Cook, J., Wagner, M., & García, J. (2024). A technocognitive approach to detecting fallacies in climate misinformation. Scientific Reports, 14(1). DOI
  2024	Stützle, T., & Wagner, M. (2024). Preface. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14632 LNCS, vi-vii.
  2024	Fieldsend, J., & Wagner, M. (2024). Introduction to the "Best of GECCO 2022" Special Issue: Part II. ACM Transactions on Evolutionary Learning and Optimization, 4(2), 1-2. DOI
  2024	Chung, B., Headland, D., & Withayachumnankul, W. (2024). Terahertz Imaging With 3D-Printed Risley-Prism and Telecentric Objective. IEEE Transactions on Terahertz Science and Technology, 14(4), 446-454. DOI
  2024	Callisto, A., Perkins, G. B., Troelnikov, A., Mhatre, S., Hissaria, P., & Smith, W. (2024). Prevention of exercise-induced anaphylaxis by ibrutinib. Journal of Allergy and Clinical Immunology: In Practice, 12(9), 2503-2505.e2. DOI
  2024	Oster, C., Powell, A., Hutchinson, C., Anderson, D., Gransbury, B., Walton, M., . . . Bogomolova, S. (2024). The process of co-designing a model of social prescribing: An Australian case study. Health Expectations, 27(3), 15 pages. DOI Europe PMC1
  2024	West, D. A., Killick, C., Jones, D., Tan, L., Knott, C., Brewster, D., . . . Farley, K. J. (2024). Use of point-of-care ultrasound during cardiac arrest in the intensive care unit: A cross-sectional survey. Australian Critical Care, 101058. DOI
  2024	Doan, A. -D., Nguyen, B. L., Gupta, S., Reid, I., Wagner, M., & Chin, T. -J. (2024). Assessing domain gap for continual domain adaptation in object detection. Computer Vision and Image Understanding, 238, 103885-1-103885-10. DOI
  2024	Tan, W. S., Wagner, M., & Treude, C. (2024). Detecting outdated code element references in software repository documentation. Empirical Software Engineering, 29(1). DOI
  2024	Nguyen, B. L., Nguyen, D. D., Nguyen, H. X., Ngo, D. T., & Wagner, M. (2024). Multi-Agent Task Assignment in Vehicular Edge Computing: A Regret-Matching Learning-Based Approach. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(2), 1527-1539. DOI Scopus3
  2024	Nguyen, B. L., Doan, A. -D., Chin, T. -J., Guettier, C., Gupta, S., Parra, E., . . . Wagner, M. (2024). Sensor Allocation and Online-Learning-Based Path Planning for Maritime Situational Awareness Enhancement: A Multi-Agent Approach. IEEE Transactions on Intelligent Transportation Systems, 25(9), 11635-11647. DOI Scopus1
  2023	Reid, B., Treude, C., & Wagner, M. (2023). Using the TypeScript compiler to fix erroneous Node.js snippets.
  2023	Kuepper, J., Erbsen, A., Gross, J., Conoly, O., Sun, C., Tian, S., . . . Yarom, Y. (2023). CryptOpt: Verified Compilation with Randomized Program Search for Cryptographic Primitives. Proceedings of the ACM on Programming Languages, 7(PLDI), 158-1-158-25. DOI Scopus1
  2023	Zanartu, F., Treude, C., & Wagner, M. (2023). Socialz: Multi-Feature Social Fuzz Testing.
  2023	Torres, A., Baltes, S., Treude, C., & Wagner, M. (2023). Applying information theory to software evolution. Proceedings - 2023 IEEE/ACM 2nd International Workshop on Natural Language-Based Software Engineering, NLBSE 2023, 48-55. DOI
  2023	El Yafrani, M., Scoczynski, M., Wagner, M., & Nielsen, P. (2023). A regression analysis of the impact of routing and packing dependencies on the expected runtime. Soft Computing, 27(17), 12099-12115. DOI
  2023	Fieldsend, J., & Wagner, M. (2023). Editorial to the "Best of GECCO 2022" Special Issue: Part I. ACM Transactions on Evolutionary Learning and Optimization, 3(2), 1-2. DOI
  2023	Tan, W. S., Wagner, M., & Treude, C. (2023). Wait, wasn't that code here before? Detecting Outdated Software Documentation.
  2023	Petke, J., Alexander, B., Barr, E. T., Brownlee, A. E. I., Wagner, M., & White, D. R. (2023). Program transformation landscapes for automated program modification using Gin. Empirical Software Engineering, 28(4), 104. DOI Scopus2
  2023	Reid, B., Amorim, M. D., Wagner, M., & Treude, C. (2023). NCQ: Code Reuse Support for Node.js Developers. IEEE Transactions on Software Engineering, 49(5), 1-21. DOI Scopus6 WoS1
  2023	He, X., Tu, Z., Wagner, M., Xu, X., & Wang, Z. (2023). Online Deployment Algorithms for Microservice Systems with Complex Dependencies. IEEE Transactions on Cloud Computing, 11(2), 1. DOI Scopus22 WoS1
  2022	Chagas, J. B. C., & Wagner, M. (2022). A weighted-sum method for solving the bi-objective traveling thief problem. Computers and Operations Research, 138, 105560. DOI Scopus22
  2022	Wong, T., Wagner, M., & Treude, C. (2022). Self-adaptive systems: A systematic literature review across categories and domains. Information and Software Technology, 148, 25 pages. DOI Scopus16 WoS4
  2022	Tan, W. S., Wagner, M., & Treude, C. (2022). Detecting Outdated Code Element References in Software Repository Documentation.
  2022	He, F., Wagner, M., Zhang, L., Shao, C., Xu, W., Chen, W., . . . Li, Y. (2022). A novel integrated approach for offshore wind power optimization. Ocean Engineering, 266, 15 pages. DOI Scopus8
  2022	Reid, B., Wagner, M., d'Amorim, M., & Treude, C. (2022). Software Engineering User Study Recruitment on Prolific: An Experience Report.
  2022	Zanartu, F., Treude, C., Cartaxo, B., Borges, H. S., Moura, P., Wagner, M., & Pinto, G. (2022). Automatically Categorising GitHub Repositories by Application Domain.
  2022	Caddy, J., Wagner, M., Treude, C., Barr, E. T., & Allamanis, M. (2022). Is Surprisal in Issue Trackers Actionable?.
  2022	Swan, J., Adriaensen, S., Brownlee, A. E. I., Hammond, K., Johnson, C. G., Kheiri, A., . . . White, D. R. (2022). Metaheuristics "In the Large". European Journal of Operational Research, 297(2), 393-406. DOI Scopus59 WoS17
  2022	Chagas, J. B. C., & Wagner, M. (2022). Efficiently solving the thief orienteering problem with a max–min ant colony optimization approach. Optimization Letters, 16(8), 2313-2331. DOI Scopus9 WoS2
  2021	Schlueter, M., Neshat, M., Wahib, M., Munetomo, M., & Wagner, M. (2021). GTOPX space mission benchmarks.. SoftwareX, 14, 100666.
  2021	Assimi, H., Koch, B., Garcia, C., Wagner, M., & Neumann, F. (2021). Run-of-Mine Stockyard Recovery Scheduling and Optimisation for Multiple Reclaimers.. CoRR, abs/2112.12294.
  2021	Assimi, H., Neumann, F., Wagner, M., & Li, X. (2021). Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems.. CoRR, abs/2112.07875.
  2021	Chagas, J. B. C., Blank, J., Wagner, M., Souza, M. J. F., & Deb, K. (2021). A non-dominated sorting based customized random-key genetic algorithm for the bi-objective traveling thief problem. Journal of Heuristics, 27(3), 297-301. DOI Scopus16 WoS4
  2021	Chinthanet, B., Reid, B., Treude, C., Wagner, M., Kula, R. G., Ishio, T., & Matsumoto, K. (2021). What makes a good Node.js package? Investigating Users, Contributors, and Runnability.
  2021	Schlueter, M., Neshat, M., Wahib, M., Munetomo, M., & Wagner, M. (2021). GTOPX space mission benchmarks. SoftwareX, 14, 1-10. DOI Scopus6 WoS2
  2021	Quinzan, F., Göbel, A., Wagner, M., & Friedrich, T. (2021). Evolutionary algorithms and submodular functions: benefits of heavy-tailed mutations. Natural Computing, 20(3), 561-575. DOI Scopus15 WoS9
  2021	Scoczynski, M., Delgado, M., Lüders, R., Oliva, D., Wagner, M., Sung, I., & El Yafrani, M. (2021). Saving computational budget in Bayesian network-based evolutionary algorithms. Natural Computing, 20(4), 775-790. DOI Scopus3
  2021	Jakobovic, D., Picek, S., Martins, M. S. R., & Wagner, M. (2021). Toward more efficient heuristic construction of Boolean functions. Applied Soft Computing, 107, 1-15. DOI Scopus17 WoS9
  2021	Neshat, M., Nezhad, M. M., Abbasnejad, E., Mirjalili, S., Groppi, D., Heydari, A., . . . Wagner, M. (2021). Wind turbine power output prediction using a new hybrid neuro-evolutionary method. Energy, 229, 120617-1-120617-24. DOI Scopus81 WoS51
  2021	Neshat, M., Nezhad, M. M., Abbasnejad, E., Mirjalili, S., Tjernberg, L. B., Astiaso Garcia, D., . . . Wagner, M. (2021). A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm. Energy Conversion and Management, 236, 1-25. DOI Scopus154 WoS83
  2020	Langdon, W. B., Weimer, W., Petke, J., Fredericks, E., Lee, S., Winter, E., . . . Gerten, M. (2020). Genetic Improvement @ ICSE 2020. ACM SIGSOFT Software Engineering Notes, 45(4), 24-30. DOI
  2020	Neshat, M., Sergiienko, N. Y., Amini, E., Nezhad, M. M., Garcia, D. A., Alexander, B., & Wagner, M. (2020). A new bi-level optimisation framework for optimising a multi-modewave energy converter design: A case study for the marettimo island, mediterranean sea. Energies, 13(20), 5498. DOI Scopus22 WoS16
  2020	Chagas, J. B. C., & Wagner, M. (2020). Ants can orienteer a thief in their robbery. Operations Research Letters, 48(6), 708-714. DOI Scopus10 WoS3
  2020	Sachdeva, R., Neumann, F., & Wagner, M. (2020). The Dynamic Travelling Thief Problem: Benchmarks and Performance of Evolutionary Algorithms.. CoRR, abs/2004.12045.
  2020	Weise, T., Wagner, M., Li, B., Zhang, X., & Lässig, J. (2020). Special Issue on Benchmarking of Computational Intelligence Algorithms in the Applied Soft Computing Journal. Applied Soft Computing Journal, 93, 3 pages. DOI
  2020	Bartz-Beielstein, T., Doerr, C., Bossek, J., Chandrasekaran, S., Eftimov, T., Fischbach, A., . . . Weise, T. (2020). Benchmarking in Optimization: Best Practice and Open Issues.. CoRR, abs/2007.03488.
  2020	Agrawal, A., Menzies, T., Minku, L. L., Wagner, M., & Yu, Z. (2020). Better software analytics via “DUO”: data mining algorithms using/used-by optimizers. Empirical Software Engineering, 25(3), 2099-2136. DOI Scopus17 WoS7
  2020	Neshat, M., Nezhad, M. M., Abbasnejad, E., Tjernberg, L. B., Garcia, D. A., Alexander, B., & Wagner, M. (2020). An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study of the Lillgrund Offshore Wind Farm.. CoRR, abs/2002.09106.
  2020	Neshat, M., Alexander, B., & Wagner, M. (2020). A hybrid cooperative co-evolution algorithm framework for optimising power take offand placements of wave energy converters. Information Sciences, 534, 218-244. DOI Scopus47 WoS32
  2020	Neshat, M., Alexander, B., Sergiienko, N. Y., & Wagner, M. (2020). New insights into position optimization of wave energy converters using hybrid local search. Swarm and Evolutionary Computation, 59, 100744-1-100744-18. DOI Scopus23 WoS14
  2020	Neshat, M., Nezhad, M. M., Abbasnejad, E., Groppi, D., Heydari, A., Tjernberg, L. B., . . . Wagner, M. (2020). Hybrid Neuro-Evolutionary Method for Predicting Wind Turbine Power Output.. CoRR, abs/2004.12794.
  2019	Neshat, M., Abbasnejad, E., Shi, Q., Alexander, B., & Wagner, M. (2019). Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation.. CoRR, abs/1907.03076.
  2019	Yafrani, M. E., Martins, M. S. R., Delgado, M. R. B. S., Sung, I., Lüders, R., & Wagner, M. (2019). On resampling vs. adjusting probabilistic graphical models in estimation of distribution algorithms.
  2019	Wagner, M., Lin, H., Li, S., & Saupe, D. (2019). Algorithm Selection for Image Quality Assessment.
  2019	Aleti, A., Wallace, M., & Wagner, M. (2019). Is perturbation an effective restart strategy?.
  2019	Neshat, M., Alexander, B., Sergiienko, N. Y., & Wagner, M. (2019). A new insight into the Position Optimization of Wave Energy Converters by a Hybrid Local Search.. CoRR, abs/1904.09599.
  2018	Doerr, C., & Wagner, M. (2018). On the Effectiveness of Simple Success-Based Parameter Selection Mechanisms for Two Classical Discrete Black-Box Optimization Benchmark Problems.
  2018	Neumann, A., Gao, W., Wagner, M., & Neumann, F. (2018). Evolutionary Diversity Optimization Using Multi-Objective Indicators.. CoRR, abs/1811.06804.
  2018	Weise, T., Wu, Z., & Wagner, M. (2018). An Improved Generic Bet-and-Run Strategy for Speeding Up Stochastic Local Search.
  2018	Neumann, A., Gao, W., Doerr, C., Neumann, F., & Wagner, M. (2018). Discrepancy-based Evolutionary Diversity Optimization.. CoRR, abs/1802.05448.
  2018	Wagner, M., Lindauer, M., Mısır, M., Nallaperuma, S., & Hutter, F. (2018). A case study of algorithm selection for the traveling thief problem. Journal of Heuristics, 24(3), 295-320. DOI Scopus42 WoS36
  2018	El Yafrani, M., Martins, M., Wagner, M., Ahiod, B., Delgado, M., & Lüders, R. (2018). A hyperheuristic approach based on low-level heuristics for the travelling thief problem. Genetic Programming and Evolvable Machines, 19(1-2), 121-150. DOI Scopus23
  2018	Moridi, M., Kawamura, Y., Sharifzadeh, M., Chanda, E., Wagner, M., & Okawa, H. (2018). Performance analysis of ZigBee network topologies for underground space monitoring and communication systems. Tunnelling and Underground Space Technology, 71, 201-209. DOI Scopus63 WoS30
  2018	Chand, S., Huynh, Q., Singh, H., Ray, T., & Wagner, M. (2018). On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems. Information Sciences, 432, 146-163. DOI Scopus84 WoS64
  2016	Bonyadi, M. R., Michalewicz, Z., Neumann, F., & Wagner, M. (2016). Evolutionary computation for multicomponent problems: opportunities and future directions.. CoRR, abs/1606.06818.
  2016	Kaufmann, P., Kramer, O., Neumann, F., & Wagner, M. (2016). Optimization methods in renewable energy systems design. Renewable Energy, 87, 835-836. DOI Scopus4 WoS3
  2016	Mahbub, M., Wagner, M., & Crema, L. (2016). Incorporating domain knowledge into the optimization of energy systems. Applied Soft Computing, 47, 483-493. DOI Scopus25 WoS17
  2016	Wagner, M. (2016). Nested multi- and many-objective optimisation of team track pursuit cycling. Frontiers in Applied Mathematics and Statistics, 2, 1-10. DOI
  2016	Friedrich, T., Kötzing, T., & Wagner, M. (2016). A Generic Bet-and-run Strategy for Speeding Up Traveling Salesperson and Minimum Vertex Cover.
  2015	Kawamura, Y., Wagner, M., Jang, H., Nobuhara, H., Shibuya, T., Kitahara, I., . . . Veenendaal, B. (2015). A multimedia data visualization based on Ad Hoc communication networks and its application to disaster management. ISPRS International Journal of Geo-Information, 4(4), 2004-2018. DOI Scopus2
  2015	Chand, S., & Wagner, M. (2015). Evolutionary many-objective optimization: A quick-start guide. Surveys in Operations Research and Management Science, 20(2), 35-42. DOI Scopus127
  2015	Moridi, M., Kawamura, Y., Sharifzadeh, M., Chanda, E., Wagner, M., Jang, H., & Okawa, H. (2015). Development of underground mine monitoring and communication system integrated ZigBee and GIS. International Journal of Mining Science and Technology, 25(5), 811-818. DOI Scopus86
  2015	Wagner, M., Bringmann, K., Friedrich, T., & Neumann, F. (2015). Efficient optimization of many objectives by approximation-guided evolution. European Journal of Operational Research, 243(2), 465-479. DOI Scopus27 WoS21
  2015	Wagner, M., Neumann, F., & Urli, T. (2015). On the performance of different genetic programming approaches for the SORTING problem. Evolutionary Computation, 23(4), 583-609. DOI Scopus6 WoS5
  2015	Friedrich, T., & Wagner, M. (2015). Seeding the initial population of multi-objective evolutionary algorithms: A computational study. Applied Soft Computing, 33, 223-230. DOI Scopus35 WoS29
  2015	Nallaperuma, S., Wagner, M., & Neumann, F. (2015). Analyzing the effects of instance features and algorithm parameters for max-min ant system and the traveling salesperson problem. Frontiers in Robotics and AI, 2(JUL), 18-1-18-16. DOI Scopus24 WoS19
  2015	Kawamura, Y., Jang, H., Wagner, M., Nobuhara, H., Dewan, A., Veenendaal, B., & Kitahara, I. (2015). Analysis of radio wave propagation in an urban environment and its application to initial disaster response support. Journal of Disaster Research, 10(4), 655-666. DOI Scopus2
  2013	Wagner, M., Day, J., & Neumann, F. (2013). A fast and effective local search algorithm for optimizing the placement of wind turbines. Renewable Energy, 51, 64-70. DOI Scopus88 WoS78
  2013	Vladislavleva, E., Friedrich, T., Neumann, F., & Wagner, M. (2013). Predicting the energy output of wind farms based on weather data: important variables and their correlation. Renewable Energy, 50, 236-243. DOI Scopus86 WoS60
  2013	Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem. Annals of Mathematics and Artificial Intelligence, 69(2), 151-182. DOI Scopus69 WoS44
  2012	Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., & Neumann, F. (2012). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. CoRR, abs/1208.2318.
  2009	Wagner, M., Roh, V., Strehlen, M., Laemmle, A., Stroka, D., Egger, B., . . . Vorburger, S. A. (2009). Effective treatment of advanced colorectal cancer by rapamycin and 5-FU/oxaliplatin monitored by TIMP-1. Journal of Gastrointestinal Surgery, 13(10), 1781-1790. DOI Scopus22 Europe PMC15

• Books

  Year	Citation
  2017	Wagner, M., Li, X., & Hendtlass, T. (Eds.) (2017). Artificial Life and Computational Intelligence: Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 – February 2, 2017, Proceedings (Vol. 10142). Springer International Publishing. DOI
  2017	Wagner, M., Li, X., & Hendtlass, T. (Eds.) (2017). Artificial Life and Computational Intelligence: Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 – February 2, 2017, Proceedings (Vol. 10142). Springer International Publishing. DOI

• Book Chapters

  Year	Citation
  2018	Bonyadi, M., Michalewicz, Z., Wagner, M., & Neumann, F. (2018). Evolutionary computation for multicomponent problems: opportunities and future directions. In S. Datta, & J. P. Davim (Eds.), Optimization in industry: present practices and future scopes (pp. 13-30). Cham, Switzerland: Springer. DOI
  2017	Wagner, M., Li, X., & Hendtlass, T. (2017). Preface. In M. Wagner, X. Li, & T. Hendtlass (Eds.), Artificial Life and Computational Intelligence - Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 – February 2, 2017, Proceedings (Vol. 10142 LNAI, pp. VI).
  2011	Neumann, F., O'Reilly, U., & Wagner, M. (2011). Computational Complexity Analysis of Genetic Programming - Initial Results and Future Directions. In R. Riolo, E. Vladislavleva, & J. Moore (Eds.), Genetic Programming Theory and Practice IX (1 ed., pp. 113-128). United States: Springer. DOI WoS6

• Conference Papers

  Year	Citation
  2024	Ma, C., Lees, H., Wagner, M., & Withayachumnankul, W. (2024). Design of Terahertz All-Dielectric Antenna via Optimisation.. In ISCIT (pp. 389-390). Online: IEEE. DOI
  2024	Blyth, S., Treude, C., & Wagner, M. (2024). Creative and Correct: Requesting Diverse Code Solutions from AI Foundation Models. In Proceedings - 2024 IEEE/ACM 1st International Conference on AI Foundation Models and Software Engineering, FORGE 2024 (pp. 119-123). PORTUGAL, Lisbon: ASSOC COMPUTING MACHINERY. DOI
  2024	Zanartu, F., Treude, C., & Wagner, M. (2024). Socialz: Multi-Feature Social Fuzz Testing. In GECCO 2024 - Proceedings of the 2024 Genetic and Evolutionary Computation Conference (pp. 1445-1453). ACM. DOI
  2024	Manglaras, O., Farkas, A., Fule, P., Treude, C., & Wagner, M. (2024). MicroKarta: Visualising Microservice Architectures. In M. D'Amorim (Ed.), FSE Companion - Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering (pp. 607-611). BRAZIL, Porto de Galinhas: ASSOC COMPUTING MACHINERY. DOI
  2024	Ahmad, H., Treude, C., Wagner, M., & Szabo, C. (2024). Smart HPA: A Resource-Efficient Horizontal Pod Auto-Scaler for Microservice Architectures. In Proceedings - IEEE 21st International Conference on Software Architecture, ICSA 2024 (pp. 46-57). Online: IEEE. DOI Scopus1
  2024	Brownlee, A. E. I., Haraldsson, S. O., Woodward, J. R., & Wagner, M. (2024). Genetic Improvement: Taking real-world source code and improving it using computational search methods. In GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion (pp. 1197-1230). ACM. DOI
  2024	Rudolph, G., & Wagner, M. (2024). Towards Adaptation in Multiobjective Evolutionary Algorithms for Integer Problems. In 2024 IEEE Congress on Evolutionary Computation, CEC 2024 - Proceedings (pp. 1-8). IEEE. DOI
  2023	Wang, Y., Wang, H., Wagner, M., & Liebman, A. (2023). Community Battery Energy Storage Systems for Enhancing Distribution System Operation: A Multi-objective Optimization Approach. In 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 (pp. 1-6). IEEE. DOI Scopus1
  2023	Manglaras, O., Farkas, A., Fule, P., Treude, C., & Wagner, M. (2023). Problems in Microservice Development: Supporting Visualisation. In Proceedings - 2023 IEEE Working Conference on Software Visualization, VISSOFT 2023 (pp. 62-72). COLOMBIA, Bogota: IEEE COMPUTER SOC. DOI Scopus2
  2023	Reid, B., Treude, C., & Wagner, M. (2023). Using the TypeScript compiler to fix erroneous Node.js snippets. In Proceedings - 2023 IEEE 23rd International Working Conference on Source Code Analysis and Manipulation, SCAM 2023 (pp. 220-230). IEEE. DOI
  2023	Tan, W. S., Wagner, M., & Treude, C. (2023). Wait, wasn't that code here before? Detecting Outdated Software Documentation. In Proceedings - 2023 IEEE International Conference on Software Maintenance and Evolution, ICSME 2023 (pp. 553-557). IEEE. DOI
  2023	Kuepper, J., Wu, D., Erbsen, A., Gross, J., Conoly, O., Sun, C., . . . Yarom, Y. (2023). CryptOpt: Automatic Optimization of Straightline Code. In Proceedings of the 45th IEEE/ACM 45TH International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Vol. abs/2305.19586 (pp. 141-145). Online: IEEE. DOI
  2023	Wagner, M., Kohlros, E., Quantmeyer, G., & Kötzing, T. (2023). ELEA – Build your own Evolutionary Algorithm in your Browser. In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 519-522). PORTUGAL, Lisbon: ASSOC COMPUTING MACHINERY. DOI
  2022	Assimi, H., Koch, B., Garcia, C., Wagner, M., & Neumann, F. (2022). Run-of-mine stockyard recovery scheduling and optimisation for multiple reclaimers. In Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing (SAC ’22) (pp. 1074-1083). New York, N.Y.: Association for Computing Machinery. DOI Scopus1
  2022	Assimi, H., Neumann, F., Wagner, M., & Li, X. (2022). Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems. In Lecture Notes in Computer Science Vol. 13222 LNCS (pp. 111-126). Madrid, Spain: Springer International Publishing. DOI
  2022	Wagner, M., & Fieldsend, J. (2022). Welcome. In GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. iii).
  2022	Kumar, Y. P. S., Ali Pourmousavi, S., Wagner, M., & Liisberg, J. A. R. (2022). Optimal offering strategy for an aggregator across multiple products of European day-ahead market. In IEEE PES Innovative Smart Grid Technologies Conference Europe Vol. 2022-October (pp. 1-6). Nova Sad, Serbia: IEEE. DOI
  2022	Chuengsatiansup, C., Wagner, M., & Yarom, Y. (2022). Opportunities for genetic improvement of cryptographic code. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1928-1929). Online: ACM. DOI
  2022	Yafrani, M. E., Scoczynski, M., Delgado, M. R. B. S., Lüders, R., Nielsen, P., & Wagner, M. (2022). On the fitness landscapes of interdependency models in the travelling thief problem. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 188-191). ACM. DOI Scopus3
  2022	Aleti, A., Wallace, M., & Wagner, M. (2022). Neighbours similar fitness and the effectiveness of restarting local search. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 172-175). ACM. DOI
  2022	Zameshina, M., Teytaud, O., Teytaud, F., Hosu, V., Carraz, N., Najman, L., & Wagner, M. (2022). Fairness in Generative Modeling: do it Unsupervised!. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 320-323). ACM. DOI Scopus2
  2022	Licorish, S. A., & Wagner, M. (2022). Dissecting Copy/Delete/Replace/Swap mutations: Insights from a GIN Case Study. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1940-1945). ACM. DOI Scopus2
  2022	Licorish, S. A., & Wagner, M. (2022). Combining GIN and PMD for code improvements. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 790-793). ACM. DOI Scopus4
  2022	Wagner, M., & Fieldsend, J. (2022). Welcome. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. iii).
  2021	Shelton, M. A., Chmielewski, Ł., Samwel, N., Wagner, M., Batina, L., & Yarom, Y. (2021). Rosita++: Automatic Higher-Order Leakage Elimination from Cryptographic Code. In CCS '21: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (pp. 685-699). New York, NY, United States: Association for Computing Machinery. DOI Scopus11 WoS4
  2021	El Yafrani, M., Scoczynski, M., Sung, I., Wagner, M., Doerr, C., & Nielsen, P. (2021). MATE: A Model-Based Algorithm Tuning Engine: A proof of concept towards transparent feature-dependent parameter tuning using symbolic regression. In Proceedings of the 21st European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP 2021), as published in Lecture Notes in Computer Science Vol. 12692 (pp. 51-67). Cham, Switzerland: Springer. DOI Scopus3
  2021	Assimi, H., Neumann, F., Wagner, M., & Li, X. (2021). Novelty particle swarm optimisation for truss optimisation problems. In GECCO Companion (pp. 67-68). New York, NY, USA: ACM. DOI Scopus1
  2021	Bossek, J., & Wagner, M. (2021). Generating instances with performance differences for more than just two algorithms.. In K. Krawiec (Ed.), GECCO Companion (pp. 1423-1432). ACM.
  2021	Aleti, A., Wallace, M., & Wagner, M. (2021). On the effectiveness of restarting local search. In GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion (pp. 333-334). New York, NY, USA: ACM. DOI Scopus1
  2021	Haraldsson, S., Brownlee, A., Woodward, J. R., Wagner, M., & Alexander, B. (2021). Genetic improvement: Taking real-world source code and improving it using genetic programming. In GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion (pp. 786-817). New York, NY, United States: Association for Computing Machinery. DOI
  2021	Shelton, M. A., Samwel, N., Batina, L., Regazzoni, F., Wagner, M., & Yarom, Y. (2021). ROSITA: Towards Automatic Elimination of Power-Analysis Leakage in Ciphers. In Proceedings of the 2021 Network and Distributed System Security Symposium (pp. 23137-1-23137-17). virtual online: Internet Society. DOI Scopus26 WoS13
  2021	Bossek, J., & Wagner, M. (2021). Generating Instances with Performance Differences for More Than Just Two Algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO 2021) Vol. abs/2104.14275 (pp. 1423-1432). New, NY, USA: ACM. DOI Scopus5
  2021	Assimi, H., Koch, B., Garcia, C., Wagner, M., & Neumann, F. (2021). Modelling and optimization of run-of-mine stockpile recovery. In Proceedings of the 36th ACM Symposium on Applied Computing (SAC '21) (pp. 450-458). New York, N.Y.: Association for Computing Machinery. DOI Scopus1 WoS1
  2020	Sergiienko, N. Y., Neshat, M., Silva, L. S. P. D., Alexander, B., & Wagner, M. (2020). Design optimisation of a multi-mode wave energy converter. In Proceedings of the 39th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2020) Vol. 9 (pp. 1-11). Online: American Society of Mechanical Engineers (ASME). DOI Scopus16
  2020	Alghamdi, M., Treude, C., & Wagner, M. (2020). Human-like summaries from heterogeneous and time-windowed software development artefacts. In T. Bäck, M. Preuss, A. Deutz, H. Wang, C. Doerr, M. Emmerich, & H. Trautmann (Eds.), Parallel Problem Solving from Nature - PPSN XVI: 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020. Proceedings, Part II Vol. 12270 LNCS (pp. 329-342). Cham, Switzerland: Springer. DOI Scopus1
  2020	Bokhari, M. A., Wagner, M., & Alexander, B. (2020). Genetic improvement of software efficiency: the curse of fitness estimation. In C. A. C. Coello (Ed.), GECCO'20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference (pp. 1926-1927). online: ACM. DOI Scopus1
  2020	Bokhari, M. A., Alexander, B., & Wagner, M. (2020). Towards rigorous validation of energy optimisation experiments.. In C. A. C. Coello (Ed.), GECCO (pp. 1232-1240). ACM.
  2020	Neshat, M., Alexander, B., Sergiienko, N. Y., & Wagner, M. (2020). Optimisation of large wave farms using a multi-strategy evolutionary framework.. In C. A. C. Coello (Ed.), GECCO (pp. 1150-1158). ACM.
  2020	Haraldsson, S., Woodward, J. R., & Wagner, M. (2020). Genetic improvement: Taking real-world source code and improving it using genetic programming. In GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (pp. 801-831). .: ACM. DOI
  2020	Durasevic, M., Jakobovic, D., Scoczynski Ribeiro Martins, M., Picek, S., & Wagner, M. (2020). Fitness landscape analysis of dimensionally-aware genetic programming featuring feynman equations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12270 LNCS (pp. 111-124). Switzerland: Springer Nature. DOI Scopus6
  2020	Sachdeva, R., Neumann, F., & Wagner, M. (2020). The Dynamic Travelling Thief Problem: Benchmarks and Performance of Evolutionary Algorithms.. In H. Yang, K. Pasupa, A. C. -S. Leung, J. T. Kwok, J. H. Chan, & I. King (Eds.), Proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020 Vol. 1333 (pp. 220-228). Switzerland: Springer Nature. DOI Scopus4
  2020	Neshat, M., Alexander, B., Sergiienko, N. Y., & Wagner, M. (2020). Optimisation of large wave farms using a multi-strategy evolutionary framework. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20) Vol. abs/2003.09594 (pp. 1150-1158). New York: Association for Computing Machinery. DOI Scopus15 WoS10
  2020	Bokhari, M. A., Alexander, B., & Wagner, M. (2020). Towards rigorous validation of energy optimisation experiments. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20) Vol. abs/2004.04500 (pp. 1232-1240). New York: Association for Computing Machinery. DOI Scopus8 WoS1
  2020	Baltes, S., & Wagner, M. (2020). An annotated dataset of stack overflow post edits. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20). GECCO 2020 Companion (pp. 1923-1925). online: Association for Computing Machinery. DOI Scopus4
  2020	Reid, B., Treude, C., & Wagner, M. (2020). Optimising the fit of stack overflow code snippets into existing code. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20) (pp. 1945-1953). New York, NY: Association for Computing Machinery. DOI Scopus9
  2020	Schmoeller, M., Stadter, C., Wagner, M., & Zaeh, M. F. (2020). Investigation of the influences of the process parameters on the weld depth in laser beam welding of AA6082 using machine learning methods. In M. Schmidt, F. Vollertsen, & E. Govekar (Eds.), Procedia CIRP Vol. 94 (pp. 702-707). Amsterdam, Netherlands: Elsevier BV. DOI Scopus5
  2019	Neshat, M., Alexander, B., Sergiienko, N. Y., & Wagner, M. (2019). A hybrid evolutionary algorithm framework for optimising power take off and placements of wave energy converters.. In M. López-Ibáñez (Ed.), GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference (pp. 1293-1301). New York, NY, USA: Association for Computing Machinery. DOI
  2019	El Yafrani, M., Scoczynski, M., Delgado, M., Luders, R., Sung, I., Wagner, M., & Oliva, D. (2019). On Updating Probabilistic Graphical Models in Bayesian Optimisation Algorithm. In Proceedings - 2019 Brazilian Conference on Intelligent Systems, BRACIS 2019 (pp. 311-316). online: IEEE. DOI Scopus2
  2019	Alghamdi, M., Treude, C., & Wagner, M. (2019). Toward human-like summaries generated from heterogeneous software artefacts. In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO 2019 Companion) (pp. 1701-1702). New York: Association for Computing Machinery. DOI Scopus2 WoS1
  2019	Neshat, M., Abbasnejad, E., Shi, Q., Alexander, B., & Wagner, M. (2019). Adaptive neuro-surrogate-based optimisation method for wave energy converters placement optimisation. In T. Gedeon, K. W. Wong, & M. Lee (Eds.), Proceedings of the 26th International Conference on Neural Information Processing (ICONIP 2019), as published in Lecture Notes in Computer Science (Neural Information Processing Proceedings, Part II) Vol. 11954 (pp. 353-366). Switzerland: Springer Nature. DOI Scopus25 WoS16
  2019	Neshat, M., Alexander, B., Sergiienko, N., & Wagner, M. (2019). A hybrid evolutionary algorithm framework for optimising power take off and placements of wave energy converters. In GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference Vol. abs/1904.07043 (pp. 1293-1301). New York: ACM. DOI Scopus19 WoS14
  2019	Petke, J., Alexander, B., Barr, E. T., Brownlee, A. E. I., Wagner, M., & White, D. R. (2019). A survey of genetic improvement search spaces. In GECCO '19 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 1715-1721). online: Association for Computing Machinery. DOI Scopus25 WoS15
  2019	Wagner, M. (2019). Kinder surprise's debut in discrete optimisation - A real-world toy problem that can be subadditive. In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 1813-1820). online: ACM. DOI
  2019	Bokhari, M. A., Wagner, M., & Alexander, B. (2019). The quest for non-functional property optimisation in heterogeneous and fragmented ecosystems: A distributed approach. In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 1705-1706). online: ACM. DOI Scopus1 WoS2
  2019	Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., & Trautmann, H. (2019). Evolving diverse TSP instances by means of novel and creative mutation operators. In FOGA '19: Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (pp. 58-71). online: Association for Computing Machinery. DOI Scopus41 WoS21
  2019	Bokhari, M. A., Weng, L., Wagner, M., & Alexander, B. (2019). Mind the gap - A distributed framework for enabling energy optimisation on modern smart-phones in the presence of noise, drift, and statistical insignificance. In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 1330-1337). online: IEEE. DOI Scopus10 WoS5
  2019	Brownlee, A. E. I., Petke, J., Alexander, B., Barr, E. T., Wagner, M., & White, D. R. (2019). Gin: Genetic improvement research made easy. In GECCO 2019: Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 985-993). New York: ACM. DOI Scopus35 WoS23
  2019	Jakobovic, D., Picek, S., Martins, M. S. R., & Wagner, M. (2019). A characterisation of S-box fitness landscapes in cryptography. In Proceedings of the 2019 Genetic and Evolutionary Computation Conference, as published in GECCO 2019 (pp. 285-293). online: ACM. DOI Scopus10 WoS4
  2019	Wagner, M., Einzinger, J., Velde, O., & Lampert, R. (2019). Automatic numerical analyses and optimization of operating maps applied to a radial compressor. In Proceedings of the ASME Turbo Expo Vol. 2D-2019. online: ASME. DOI Scopus1
  2019	Treude, C., & Wagner, M. (2019). Predicting good configurations for github and stack overflow topic models. In IEEE International Working Conference on Mining Software Repositories Vol. 2019-May (pp. 84-95). online: IEEE. DOI Scopus31
  2019	Weise, T., Wu, Z., & Wagner, M. (2019). An improved generic bet-and-run strategy with performance prediction for stochastic local search. In 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 Vol. 33 (pp. 2395-2402). USA: AAAI. DOI Scopus6
  2018	Bokhari, M. A., Alexander, B., & Wagner, M. (2018). In-vivo and offline optimisation of energy use in the presence of small energy signals: case study on a popular Android library. In MobiQuitous '18 Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (pp. 207-215). New York City, NY: Association for Computing Machinery. DOI Scopus17 WoS10
  2018	Neumann, A., Gao, W., Doerr, C., Neumann, F., & Wagner, M. (2018). Discrepancy-based evolutionary diversity optimization. In Proceedings of the 2018 Genetic and Evolutionary Computation Conference (GECCO'18) (pp. 991-998). New York, NY: Association for Computing Machinery. DOI Scopus47 WoS32
  2018	Wu, J., Polyakovskiy, S., Wagner, M., & Neumann, F. (2018). Evolutionary computation plus dynamic programming for the bi-objective travelling thief problem.. In H. E. Aguirre, & K. Takadama (Eds.), GECCO (pp. 777-784). ACM.
  2018	Neshat, M., Alexander, B., Wagner, M., & Xia, Y. (2018). A detailed comparison of meta-heuristic methods for optimising wave energy converter placements. In H. E. Aguirre, & K. Takadama (Eds.), Proceedings of the 2018 Genetic and Evolutionary Computation Conference as published in GECCO 2018 (pp. 1318-1325). online: ACM. DOI Scopus35 WoS26
  2018	Friedrich, T., Quinzan, F., & Wagner, M. (2018). Escaping large deceptive basins of attraction with heavy-tailed mutation operators. In Proceedings of the 2018 Genetic and Evolutionary Computation Conference, as published in ACM Digital Library (pp. 293-300). online: ACM. DOI Scopus50 WoS32
  2018	Yafrani, M. E., Wagner, M., Martins, M. S. R., Delgado, M. R. B. S., Lders, R., El Krari, M., & Ahiod, B. (2018). A fitness landscape analysis of the travelling thief problem. In Proceedings of the 2018 Genetic and Evolutionary Computation Conference, as published in ACM Digital Library (pp. 277-284). online: ACM. DOI Scopus27 WoS19
  2018	Doerr, C., & Wagner, M. (2018). Simple on-the-fly parameter selection mechanisms for two classical discrete black-box optimization benchmark problems. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 943-950). online: ACM. DOI Scopus30
  2018	Nair, V., Agrawal, A., Chen, J., Fu, W., Mathew, G., Menzies, T., . . . Yu, Z. (2018). Data-driven search-based software engineering. In Proceedings - International Conference on Software Engineering (pp. 341-352). online: ACM. DOI Scopus18 WoS7
  2018	Friedrich, T., Göbel, A., Quinzan, F., & Wagner, M. (2018). Heavy-tailed mutation operators in single-objective combinatorial optimization. In A. Auger, C. Fonseca, N. Lourenco, P. Machado, L. Paquete, & D. Whitley (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11101 LNCS (pp. 134-145). Univ Coimbra, Coimbra, PORTUGAL: SPRINGER INTERNATIONAL PUBLISHING AG. DOI Scopus37 WoS29
  2018	Arbonès, D., Sergiienko, N., Ding, B., Krause, O., Igel, C., & Wagner, M. (2018). Sparse incomplete LU-decomposition for wave farm designs under realistic conditions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11101 (pp. 512-524). Coimbra, Portugal: SPRINGER INTERNATIONAL PUBLISHING AG. DOI Scopus5 WoS4
  2018	Doerr, C., & Wagner, M. (2018). Sensitivity of parameter control mechanisms with respect to their initialization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11102 (pp. 360-372). Switzerland: Springer. DOI Scopus7
  2018	Neumann, A., Gao, W., Wagner, M., & Neumann, F. (2018). Evolutionary diversity optimization using multi-objective indicators. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '19) Vol. - (pp. 837-845). New York, NY: Association for Computing Machinery. DOI Scopus41 WoS26
  2018	Wu, J., Wagner, M., Polyakovskiy, S., & Neumann, F. (2018). Evolutionary computation plus dynamic programming for the Bi-objective travelling thief problem. In Proceedings of the 2018 Genetic and Evolutionary Computation Conference as published in the ACM Digital Library Vol. abs/1802.02434 (pp. 777-784). online: ACM. DOI Scopus20 WoS7
  2017	Yafrani, M. E., Chand, S., Neumann, A., Ahiod, B., & Wagner, M. (2017). Multi-objectiveness in the single-objective traveling thief problem. In Proceedings of the Genetic and Evolutionary Computation Conference Companion Vol. 2017-January (pp. 107-108). Berlin: ACM. DOI Scopus10 WoS5
  2017	Martins, M., Yafrani, M., Delgado, M., Wagner, M., Ahiod, B., & Lüders, R. (2017). HSEDA: A heuristic selection approach based on estimation of distribution algorithm for the travelling thief problem. In GECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference Vol. 2017-January (pp. 361-368). online: ACM. DOI Scopus23
  2017	Friedrich, T., Kötzing, T., & Wagner, M. (2017). A generic bet-and-run strategy for speeding up stochastic local search. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17) (pp. 801-807). San Francisco: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. Scopus8 WoS6
  2017	Wu, J., Wagner, M., Polyakovskiy, S., & Neumann, F. (2017). Exact approaches for the travelling thief problem. In Proceedings of the 11th International Conference on Simulated Evolution and Learning (SEAL 2017), as published in Lecture Notes in Computer Science Vol. 10593 (pp. 110-121). Cham, Switzerland: Springer. DOI Scopus28
  2017	Kadioglu, S., Sellmann, M., & Wagner, M. (2017). Learning a reactive restart strategy to improve stochastic search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10556 LNCS (pp. 109-123). Switzerland: Springer International Publishing. DOI Scopus6 WoS5
  2017	Bokhari, M. A., Bruce, B. R., Alexander, B., & Wagner, M. (2017). Deep parameter optimisation on android smartphones for energy minimisation-a tale of woe and a proof-of-concept. In P. A. N. Bosman (Ed.), GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1501-1508). online: ACM. DOI Scopus28
  2017	Lissovoi, A., Wagner, M., Sudholt, D., & Zarges, C. (2017). Theoretical results on bet-and-run as an initialisation strategy. In GECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference (pp. 857-864). New York, NY, USA: Association for Computing Machinery (ACM). DOI Scopus5 WoS3
  2017	Wagner, M., Friedrich, T., & Lindauer, M. (2017). Improving local search in a minimum vertex cover solver for classes of networks. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2017) (pp. 1704-1711). San Sebastián, SPAIN: IEEE. DOI Scopus11 WoS8
  2017	Ding, B., da Silva, L., Sergiienko, N., Meng, F., Piper, J., Bennetts, L., . . . Arjomandi, M. (2017). Study of fully submerged point absorber wave energy converter - modelling, simulation and scaled experiment. In Proceedings of the 32nd International Workshop on Water Waves and Floating Bodies (IWWWFB) (pp. 1-4). Dalian, China: IWWWFB.
  2017	Li, W., Özcan, E., John, R. I., Drake, J. H., Neumann, A., & Wagner, M. (2017). A modified indicator-based evolutionary algorithm (mIBEA). In Proceedings of the 2IEEE Congress on Evolutionary Computation (CEC 2017) (pp. 1047-1054). SPAIN: IEEE. DOI Scopus14 WoS11
  2017	Saghari, A., Rahmani, S., Kosari, A., & Wagner, M. (2017). Optimal orbit of a typical earth observation satellite with the purpose of propellant and payload mass minimization. In Proceedings of the International Astronautical Congress, IAC Vol. 3 (pp. 1378-1384). Online: Pergamon Press.
  2017	Rahmani, S., Saghari, A., Ebrahimi, M., & Wagner, M. (2017). Reliability-based orbital design optimization for an earth observation satellite. In Proceedings of the International Astronautical Congress, IAC Vol. 3 (pp. 1365-1372). Online: International Astronautical Federation.
  2017	Mahbub, M., Wagner, M., & Crema, L. (2017). Multi-objective optimisation with multiple preferred regions. In M. Wagner, X. Li, & T. Hendtlass (Eds.), Proceedings of the 3rd Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2017) Vol. 10142 (pp. 241-253). Cham, Switzerland: Springer. DOI Scopus3 WoS2
  2016	Wu, J., Shekh, S., Sergiienko, N., Cazzolato, B., Ding, B., Neumann, F., & Wagner, M. (2016). Fast and effective optimisation of arrays of submerged wave energy converters. In Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 1045-1052). Denver, CO: Association for Computing Machinery. DOI Scopus35 WoS20
  2016	Chand, S., & Wagner, M. (2016). Fast heuristics for the multiple traveling thieves problem. In Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 293-300). Denver, CO: ACM Press. DOI Scopus16 WoS13
  2016	Wagner, M. (2016). Speeding up the proof strategy in formal software verification. In - Proceedings of the 2016 Genetic and Evolutionary Computation Conference Companion (pp. 1137-1138). Denver, CO: ACM press. DOI Scopus1 WoS1
  2016	Bokhari, M., & Wagner, M. (2016). Optimising energy consumption heuristically on android mobile phones. In Proceedings of the 2016 Genetic and Evolutionary Computation Conference (Companion) (pp. 1139-1140). Denver, CO: ACM Press. DOI Scopus10 WoS9
  2016	Arbonès, D., Ding, B., Sergiienko, N., & Wagner, M. (2016). Fast and effective multi-objective optimisation of submerged wave energy converters. In Proceedings of the 14th International Conference on Parallel Problem Solving from Nature Vol. 9921 (pp. 675-685). Edinburgh, United Kingdom: Springer. DOI Scopus10 WoS6
  2016	Wagner, M. (2016). Stealing items more efficiently with ants: a swarm intelligence approach to the travelling thief problem. In Proceedings of the 10th International Conference on Swarm Intelligence Vol. 9882 LNCS (pp. 273-281). Brussels, Belgium: Springer. DOI Scopus37
  2016	Luckehe, D., Wagner, M., & Kramer, O. (2016). Constrained evolutionary wind turbine placement with penalty functions. In Proceedings of the 2016 IEEE Congress on Evolutionary Computation (pp. 4903-4910). Vancouver, Canada: IEEE. DOI Scopus6 WoS4
  2015	Bokhari, M., Bormer, T., & Wagner, M. (2015). An improved beam-search for the test case generation for formal verification systems. In M. Barros, & Y. Labiche (Eds.), Proceedings of the 7th International Symposium, Search-Based Software Engineering Vol. 9275 (pp. 77-92). Bergamo, Italy: Springer. DOI Scopus3
  2015	Faulkner, H., Polyakovskiy, S., Schultz, T., & Wagner, M. (2015). Approximate approaches to the traveling thief problem. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (pp. 385-392). Madrid, Spain: ACM. DOI Scopus54 WoS36
  2015	Bokhari, M., & Wagner, M. (2015). Improving test coverage of formal verification systems via beam search. In Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference (pp. 1357-1358). Madrid, Spain: ACM Press. DOI Scopus1
  2015	Lückehe, D., Wagner, M., & Kramer, O. (2015). On evolutionary approaches to wind turbine placement with geo-constraints. In Proceedings of the 2015 on Genetic and Evolutionary Computation Conference (pp. 1223-1230). Madrid, Spain: ACM press. DOI Scopus12 WoS5
  2014	Polyakovskiy, S., Bonyadi, M., Wagner, M., Michalewicz, Z., & Neumann, F. (2014). A comprehensive benchmark set and heuristics for the traveling thief problem. In GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference (pp. 477-484). Vancouver, Canada: Association for Computing Machinery. DOI Scopus99 WoS65
  2014	Wagner, M. (2014). Maximising axiomatization coverage and minimizing regression testing time. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation (pp. 2885-2892). Beijing, China: IEEE. DOI Scopus4
  2014	Wagner, M., & Neumann, F. (2014). Single- and multi-objective genetic programming: new runtime results for sorting. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014 (pp. 125-132). Beijing: IEEE. DOI Scopus6 WoS5
  2014	Nallaperuma, S., Wagner, M., & Neumann, F. (2014). Parameter prediction based on features of evolved instances for ant colony optimization and the traveling salesperson problem. In T. Bartz-Beielstein, J. Branke, B. Filipič, & J. Smith (Eds.), Proceedings of the 13th International Conference on Parallel Problem Solving from Nature Vol. 8672 (pp. 100-109). Ljubljana, Slovenia: Springer Verlag. DOI Scopus10 WoS9
  2014	Bonyadi, M., Michalewicz, Z., & Wagner, M. (2014). Beyond the edge of feasibility: analysis of bottlenecks. In Proceedings of the 10th International Conference on Simulated Evolution and Learning Vol. 8886 (pp. 431-442). New Zealand: Springer Verlag. DOI Scopus5 WoS3
  2014	Nguyen, A., Wagner, M., & Neumann, F. (2014). User preferences for approximation-guided multi-objective evolution. In G. Dick, & et al. (Eds.), Proceedings of the 10th International Conference on Simulated Evolution and Learning Vol. 8886 (pp. 251-262). Online: Springer. DOI Scopus3 WoS2
  2013	Wagner, M., Day, J., Jordan, C., Kroeger, T., & Neumann, F. (2013). Evolving pacing strategies for team pursuit track cycling. In Proceedings of Advances in Metaheuristics Vol. abs/1104.0775 (pp. 61-76). New York: Springer. DOI
  2013	Nguyen, A., Urli, T., & Wagner, M. (2013). Single- and multi-objective genetic programming: new bounds for weighted order and majority. In Proceedings of the 12th Workshop on Foundations of Genetic Algorithms, FOGA XII (pp. 161-172). online: ACM. DOI Scopus12
  2013	Nallaperuma, S., Wagner, M., Neumann, F., Bischi, B., Mersmann, O., & Trautmann, H. (2013). A feature-based comparison of local search and the Christofides algorithm for the travelling salesperson problem. In Proceedings of the 12th Workshop on Foundations of Genetic Algorithms, FOGA XII (pp. 147-159). online: ACM. DOI Scopus28
  2013	Tran, R., Wu, J., Denison, C., Ackling, T., Wagner, M., & Neumann, F. (2013). Fast and effective multi-objective optimisation of wind turbine placement. In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, GECCO'13 (pp. 1381-1388). online: ACM. DOI Scopus31 WoS30
  2013	Wagner, M., & Neumann, F. (2013). A fast approximation-guided evolutionary multi-objective algorithm. In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation (pp. 687-694). online: ACM. DOI Scopus70 WoS58
  2013	Beckert, B., Bormer, M., & Wagner, M. (2013). Heuristically creating test cases for program verification systems. In Proceedings of the 10th Metaheuristics International Conference, MIC2013 (pp. 37-46). online: Singapore Management University.
  2013	Nallaperuma, S., Wagner, M., & Neumann, F. (2013). Ant colony optimisation and the travelling salesperson problem - hardness, features and parameter settings. In Proceedings of the 15th Annual Conference Companion on Genetic and Evolutionary Computation, GECCO'13 (pp. 13-14). Amsterdam, Netherlands: ACM. DOI Scopus6
  2013	Wagner, M., & Friedrich, T. (2013). Efficient parent selection for Approximation-Guided Evolutionary multi-objective optimization. In Proceedings sof the 2013 IEEE Congress on Evolutionary Computation, CEC (pp. 1846-1853). United States: IEEE. DOI Scopus9 WoS6
  2013	Beckert, B., Bormer, M., & Wagner, M. (2013). A metric for testing program verification systems. In Proceedings of the 7th International Conference on Tests and Proofs, TAP 2013 Vol. 7942 LNCS (pp. 56-75). Germany: Springer. DOI Scopus4
  2012	Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local search and the traveling salesman problem: A feature-based characterization of problem hardness. In Proceedings of the 6th International Conference on Learning and Intelligent Optimization, LION 6 Vol. 7219 LNCS (pp. 115-129). Germany: Springer-Verlag. DOI Scopus35
  2012	Urli, T., Wagner, M., & Neumann, F. (2012). Experimental supplements to the computational complexity analysis of genetic programming for problems modelling isolated program semantics. In Proceedings of the12th International Conference on Parallel Problem Solving from Nature, PPSN 2012 Vol. 7491 LNCS (pp. 102-112). Germany: Springer-Verlag. DOI Scopus8
  2012	Wagner, M., & Neumann, F. (2012). Parsimony pressure versus multi-objective optimization for variable length representations. In Proceedings of the12th International Conference on Parallel Problem Solving from Nature, PPSN 2012 Vol. 7491 LNCS (pp. 133-142). Germany: Springer-Verlag. DOI Scopus14
  2012	Veeramachaneni, K., Wagner, M., O'Reilly, U., & Neumann, F. (2012). Optimizing energy output and layout costs for large wind farms using particle swarm optimization. In Proceedings of 2012 IEEE Congress on Evolutionary Computation, CEC 2012 (pp. 1-7). USA: IEEE. DOI Scopus37 WoS3
  2012	Yuen, J., Gao, S., Wagner, M., & Neumann, F. (2012). An adaptive data structure for evolutionary multi-objective algorithms with unbounded archives. In Proceedings of 2012 IEEE Congress on Evolutionary Computation, CEC 2012 (pp. 1-8). USA: IEEE. DOI Scopus3
  2011	Kötzing, T., Neumann, F., Sudholt, D., & Wagner, M. (2011). Simple max-min ant systems and the optimization of linear pseudo-boolean functions. In Proceeding: FOGA '11: Proceedings of the 11th Workshop Proceedings on Foundations of Genetic Algorithms Vol. abs/1007.4707 (pp. 209-218). New York: ACM Press. DOI Scopus26 WoS18
  2011	Wagner, M., Neumann, F., Veeramachaneni, K., & O'Reilly, U. (2011). Optimizing the Layout of 1000 Wind Turbines. In European Wind Energy Association 2011 Scientific Proceedings (pp. 205-209). Brussels, Belgium: UWEA. Scopus40
  2011	Bringmann, K., Friedrich, T., Neumann, F., & Wagner, M. (2011). Approximation-guided evolutionary multi-objective optimization. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (pp. 1198-1203). online: IJCAI. DOI Scopus78
  2011	Doerr, B., Johannsen, D., Kötzing, T., Lehre, P., Wagner, M., & Winzen, C. (2011). Faster black-box algorithms through higher arity operators. In Proceedings of the 11th Workshop Proceedings on Foundations of Genetic Algorithms (pp. 163-172). Schwarzenberg, Austria: ACM Press. DOI Scopus62 WoS39
  2011	Wagner, M., Day, J., Jordan, D., Kroeger, T., & Neumann, F. (2011). Evolving Pacing Strategies for Team Pursuit Track Cycling. In Proceedings (pp. 491-500). Udine, Italy: Universita degli Studi di Udine.
  2011	Kötzing, T., Neumann, F., Sudholt, D., & Wagner, M. (2011). Simple max-min ant systems and the optimization of linear pseudo-boolean functions.. In H. -G. Beyer, & W. B. Langdon (Eds.), FOGA (pp. 209-218). ACM.
  2010	Bormer, T., & Wagner, M. (2010). Towards Testing a Verifying Compiler. In International Conference on Formal Verification of Object-Oriented Software, FoVeOOS 2010, Paris, France, June 28-30, 2010. Pre-Proceedings (Technical Report Department of Informatics, KIT, 2010-13) (pp. 98-112). Karlsruhe Institute of Technology.
  2009	Wagner, M. (2009). Probabilistic User Models for the Verification of Human-Computer Interaction. In F. R. I. E. V. Gesellschaft (Ed.), Informatiktage 2009. Fachwissenschaftlicher Informatik-Kongress, 27. und 28. März 2009, B-IT Bonn-Aachen International Center for Information Technology in Bonn Vol. S-8 (pp. 139-142). K�llen Druck + Verlag GmbH.
  2009	Obermaier, C., & Wagner, M. (2009). Towards an evolved lower bound for the most circular partition of a square. In Evolutionary Computation, 2009. CEC '09. IEEE Congress on (pp. 1463-1469). Norway: IEEE. DOI
  2009	Wagner, M., & Beckert, B. (2009). Probabilistic models for the verification of human-computer interaction. In KI 2009: Advances in Artificial Intelligence: 32nd Annual German Conference on AI, Paderborn, Germany, September 15-18, 2009, Proceedings (KI2009) Vol. 5803 LNAI (pp. 687-694). Germany: Springer-Verlag. DOI Scopus2
  2009	Vorburger, S. A., Wagner, M., Laemmle, A. L., Trochsler, M., & Candinas, D. (2009). Effective Combination of mTOR-Inhibitor Rapamycin with 5-FU/Oxaliplatin in Advanced Colorectal Cancer Monitored By TIMP-1 (Tissue Inhibitor of Metalloproteinases 1). In GASTROENTEROLOGY Vol. 136 (pp. A921). IL, Chicago: W B SAUNDERS CO-ELSEVIER INC.
  2008	Oliwa, T., & Wagner, M. (2008). Composing music with neural networks and probabilistic finite-state machines. In Mario Giacobini (Ed.), Applications of evolutionary computing [electronic resource] : EvoWorkshops 2008, EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008 : proceedings Vol. 4974 LNCS (pp. 503-508). New York: Springer. DOI Scopus14
  2008	Boisclair, C., & Wagner, M. (2008). Better Huffman coding via genetic algorithm. In H. Arabnia, & M. Youngsong (Eds.), Proceedings of the 2008 International Conference on Genetic and Evolutionary Methods, GEM 2008, July 14-17, 2008, Las Vegas, Nevada, USA (pp. 30-34). USA: CSREA Press. Scopus1
  2006	Beuster, G., Henrich, N., & Wagner, M. (2006). Real world verification experiences from the verisoft email client. In CEUR Workshop Proceedings Vol. 192 (pp. 112-125). Scopus5
  2006	Wagner, M., Gloor, B., Ambuehl, M., Worni, M., Lutz, J. -A., Trochsler, M., . . . Candinas, D. (2006). Routine drainage of the pancreatic stump into a Roux-en-Y loop of jejunum decreases the incidence of postoperative pancreatic fistulas: A single centre study of 42 consecutive patients treated between January 2002 and September 2005. In GASTROENTEROLOGY Vol. 130 (pp. A884). CA, Los Angeles: W B SAUNDERS CO-ELSEVIER INC.

• Working Paper

  Year	Citation
  2017	Bokhari, M., Xia, Y., Zhou, B., Alexander, B., & Wagner, M. (2017). Validation of Internal Meters of Mobile Android Devices..
  2011	Wagner, M., & Neumann, F. (2011). Computational Complexity Results for Genetic Programming and the Sorting Problem.

• Preprint

  Year	Citation
  2022	Kuepper, J., Erbsen, A., Gross, J., Conoly, O., Sun, C., Tian, S., . . . Yarom, Y. (2022). CryptOpt: Verified Compilation with Random Program Search for Cryptographic Primitives..

I am reguarly involved in undergraduate and postgraduate teaching. For details, please see my teaching page: http://cs.adelaide.edu.au/~markus/teaching.html

I am passionate about teaching and I do my best to equip the students with the methods so that they can later make informed decisions. For example, in my fourth-year courses, through challenging but solvable assignments, I equip them with the tools for systematic and thorough research, improve their ability to work in groups, and train their communication and documentation skills.

Curriculum design. In 2017, I have developed my own course COMP SCI 4409/4809/7409 Search-Based Software Engineering. This course has been one of the top-rated courses in the University, e.g., in 2018: “well-organised” 7.0, “feedback” 6.7 “assessment” 6.7, “overall satisfied” 6.4. It was also in 2017/18 that I have developed half of the edX open-access course “Computational Thinking and Big Data”.

Curriculum delivery. Since 2015, I have been involved in the delivery over 18 courses (12 times as course coordinator). Eight times I achieved a 100% broad agreement on the SELT question "Markus is an effective university teacher". I have also taught at the Harbin Institute of Technology in China.

Discipline knowledge, pedagogical knowledge and innovation. In class, I am very interested in interacting with the students; otherwise, in my opinion, they could just watch a podcast at home. My favourite approach is Eric Mazur’s “think-pair-share” activity., I am a confident teacher who can alter the course of lectures on the spot if necessary.

Research supervision, research training and mentoring. I have grown my team to a good size: I am Principal Supervisor to 7 PhD students, and Co-Supervisor to 5 more. I have seen two to timely completion and two submitted in 2020. I have also supervised 16 two-semester projects of Honours and Master-by-coursework students.

Education, culture and leadership. I regard Honours, Master, and PhD students as crucial contributors to our research, and they should be taught at the highest level. With undergraduate and Master-by-coursework students, I have published five articles since 2015. My reputation in regard to PhD supervision led to two external thesis examinations in 2018 and one in 2021.

• Current Higher Degree by Research Supervision (University of Adelaide)

  Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
  2024	Co-Supervisor	Design of Terahertz Components via Optimisation	Doctor of Philosophy	Doctorate	Full Time	Mr Chenchu Ma
  2023	Principal Supervisor	Automating the reconstruction and visualisation of microservice architectures	Doctor of Philosophy	Doctorate	Full Time	Mr Oscar John Ammirato Manglaras
  2022	Co-Supervisor	Developing Self-Adaptive Architecture for Scalable Microservice-based Systems	Doctor of Philosophy	Doctorate	Full Time	Hussain Ahmad
  2021	Co-Supervisor	Industry PhD Flexible Aggregator Simulation Platform (FRESNO): Optimal Bidding in the Wholesale and Local Markets (FRESNO A)	Doctor of Philosophy	Doctorate	Full Time	Mr Yogesh Pipada Sunil Kumar
  2021	Principal Supervisor	Surprising artefacts in codebases: Finding them using natural language processing, determining their risk, and warning developers.	Doctor of Philosophy	Doctorate	Full Time	Mr James Michael Caddy

• Past Higher Degree by Research Supervision (University of Adelaide)

  Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
  2022 - 2022	Principal Supervisor	Fuzz Driver Generation	Master of Philosophy	Master	Full Time	Mr Supun Jeevaka Dissanayake
  2022 - 2024	Principal Supervisor	Applying Information Theory to Software Evolution: What can we Learn From Surprising Changes?	Master of Philosophy	Master	Full Time	Mr Adriano Rodrigues Figueiredo Torres
  2021 - 2023	Principal Supervisor	Automatic Detection and Analysis of Outdated Documentation in GitHub Repositories	Master of Philosophy	Master	Full Time	Mr Wen Siang Tan
  2021 - 2022	Principal Supervisor	Dissecting Malicious Behaviours of Mobile Applications	Master of Philosophy	Master	Full Time	Mr Zach Wang
  2020 - 2023	Principal Supervisor	Improving Developer Efficiency through Code Reuse	Doctor of Philosophy	Doctorate	Full Time	Ms Brittany Anne Reid
  2020 - 2024	Co-Supervisor	Enhancing State-of-the-Art Techniques Generating Low-Level Code for Cryptographic Arithmetic	Doctor of Philosophy	Doctorate	Full Time	Mr Joel Kuepper
  2018 - 2023	Co-Supervisor	Application of Bio-inspired Algorithms to Selected Real-World Problems	Doctor of Philosophy	Doctorate	Part Time	Dr Hirad Assimi
  2018 - 2022	Principal Supervisor	Towards Automatic Power Analysis Leakage Elimination	Doctor of Philosophy	Doctorate	Full Time	Mr Madura Anushanga Shelton
  2017 - 2022	Principal Supervisor	Multi-Document Summarisation from Heterogeneous Software Development Artefacts	Doctor of Philosophy	Doctorate	Full Time	Mr Mahfouth Ahmad Alghamdi
  2016 - 2021	Principal Supervisor	Genetic Improvement of Software for Energy Efficiency in Noisy and Fragmented Eco-Systems	Doctor of Philosophy	Doctorate	Full Time	Mr Mahmoud Abdulwahab K Bokhari
  2016 - 2020	Co-Supervisor	The Application of Nature-inspired Metaheuristic Methods for Optimizing Renewable Energy Problems and the Design of Water Distribution Networks	Doctor of Philosophy	Doctorate	Full Time	Mr Mehdi Neshat
  2013 - 2016	Co-Supervisor	Diversity Optimization and Parameterized Analysis of Heuristic Search Methods for Combinatorial Optimization Problems	Doctor of Philosophy	Doctorate	Full Time	Dr Wanru Gao
  2013 - 2017	Co-Supervisor	Parameterised Complexity Analysis of Evolutionary Algorithms for Combinatorial Optimization Problems	Doctor of Philosophy	Doctorate	Full Time	Dr Mojgan Pourhassan

• Board Memberships

  Date	Role	Board name	Institution name	Country
  2019 - 2025	Member	Business Committee	ACM SIG Evolutionary Computation	United States
  2019 - ongoing	Chair	Sustainability Officer	ACM SIG Evolutionary Computation	United States

• Committee Memberships

  Date	Role	Committee	Institution	Country
  2016 - 2017	Co-Chair	Task Force on Computational Intelligence in the Energy Domain	EEE Computational Intelligence Society	United States
  2016 - 2017	Chair	University Curricula	IEEE Computational Intelligence Society	United States
  2015 - 2015	Chair	Educational Material	IEEE Computational Intelligence Society	United States
  2014 - 2015	Founder	Task Force on Computational Intelligence in the Energy Domain	IEEE Computational Intelligence Society	United States
  2014 - 2014	Chair	Educational Repository	IEEE Computational Intelligence Society	United States

• Consulting/Advisories

  Date	Institution	Department	Organisation Type	Country
  2018 - ongoing	Daitum	.	Business and professional	Australia
  2015 - ongoing	Complexica	.	Business and professional	Australia

• Editorial Boards

  Date	Role	Editorial Board Name	Institution	Country
  2019 - ongoing	Associate Editor	IEEE Transactions on Emerging Topics in Computational Intelligence	IEEE	United States
  2018 - ongoing	Editor	Applied Soft Computing Journal	Elsevier	United States
  2015 - 2019	Associate Editor	Frontiers in Applied Mathematics and Statistics	Frontiers	United States
  2015 - 2016	Editor	Renewable Energy	Elsevier	United States
  2014 - 2014	Editor	Neurocomputing	Elsevier	United States

• Offices Held

  Date	Office Name	Institution	Country
  2018 - 2020	Chair for Competitions – Genetic and Evolutionary Computation Conference	ACM SIGEVO	United States
  2018 - 2018	Chair for Tutorials – Australasian Joint Conference on Artificial Intelligence	.	New Zealand
  2018 - 2018	General Chair – Australasian Conference on Artificial Life and Computational Intelligence	.	Australia
  2017 - 2017	Program Chair – Australasian Conference on Artificial Life and Computational Intelligence	.	Australia
  2016 - 2017	Chair for Workshops – Genetic and Evolutionary Computation Conference	ACM SIGEVO	United States

• Email: markus.wagner@adelaide.edu.au