Head, School of Computer Science
School of Computer Science
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD - email supervisor to discuss availability.
“Love [for academia] is like a friendship caught on fire. In the beginning a flame, very pretty, often hot and fierce, but still only light and flickering. As love grows older, our hearts mature and our love become as coals, deep-burning and unquenchable.”
by Bruce Lee [me]
This is not my primary website. For more information on my current research and teaching activies - including scientific articles, source code, results, and much more - please visit my main website: http://cs.adelaide.edu.au/~markus/
- My Research
- Grants and Funding
- Professional Activities
Follow me on Twitter:
Older News (I'm using Twitter for news newer than November 2019)
- [15 November 2019] Hasso Plattner Institute, FSOC Lab project approved: Designing practical algorithms through overfitting
- [17 October 2019] Times Higher Education World University Rankings: 120 (up from 135), computer science 96
- [16 October 2019] PGMO Days 2019: talk "An Improved Generic Bet-and-Run Strategy with Performance Prediction for Stochastic Local Search" accepted, slides used
- [8 October 2019] COST Action Training School, this year 25th-29th November 2019 in Coimbra, Portugal: I'm a lecturer
- [3 October 2019] IEEE Task Force on Automated Algorithm Design, Configuration and Selection (AADCS): I've become accepted the invitation to become a member
- [2 October 2019] Blavatnik Interdisciplinary Cyber Research Center: proposal passed stage 1
- [25 September 2019] CRC Transitions in Mining Economies: successfully moved to Stage 2 of the application process
- [16 September 2019] OptLog is now a "network member" of the "ICT-48 RIA proposal on the Foundations of Trustworthy AI - Integrating Learning, Reasoning and Optimization", with me as the point-of-contact.
- [15 September 2019] ICONIP 2019 paper accepted (CORE A): Adaptive Neuro-Surrogate-Based Optimization Method for Wave Energy Converters Placement Optimization
- [12 September 2019] Times Higher Education World University Rankings: now at 120 (was 135)
- [9-19 September 2019] Harbin Institute of Technology: I've taught "Evolutionary Computation" as an intensive course over two weeks
- [27 August 2019] $12.5m ARC Training Centre announced, news
- [26 August 2019] ECMS Connect: Riding the Renewable Energy Wave
- [20 August 2019] Listed at Tethys (U.S. Department of Energy): Optimizing the Wave Energy Converters by Metaheuristic Methods
- [20 August 2019] Configuration and Selection of Algorithms Workshop 2019: paper and poster online
- [17 July 2019] GECCO 2019 Best Paper Award for "A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters" (Neshat, Alexander, Sergiienko, Wagner) (project page with code and documents) best of 87 submissions in the RWA track
- [15 July 2019] elected to be SIGEVO's first ever Sustainability Officer
- [10 July 2019] New technical report: Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation
- [8 July 2019] BRACIS 2019 paper accepted: On updating probabilistic graphical models in a Bayesian Optimisation Algorithm
- [3 July 2019] Panel discussion member on Benchmarking at BB-DOB 2019
- [6 June 2019] FOGA 2019 paper accepted (CORE A*): Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators, code
- [4 June 2019] GECCO 2019, two Best Paper Nominations!! Tracks: GA and RWA, list
- [30 May 2019] GECCO 2019, invited speaker at Evolutionary Computation in Practice (ECiP) - [17 May 2019] CRC: Achieving Sustainable Mine Closure (www) bid by the University of Adelaide submitted to lead the project, with me as a Program Lead
- [18 April 2019] GECCO 2019 Workshops: 4 papers accepted!!!! 3x Genetic Improvement of Software (GI), 1x Black Box Discrete Optimization Benchmarking (BB-DOB)
- [13 April 2019] Hasso Plattner Institute, FSOC Lab project approved: Overfitting on purpose to design new algorithms
- [10 April 2019] Australia-China Joint Research Centre of Offshore Wind and Wave Energy Harnessing funded, with Shanghai Jiao Tonag University and others
- [21 March 2019] GECCO 2019 (CORE A, 35% acceptance rate): 4 full papers accepted!!!! Tracks: 1x ECOM, 1x GA, 1x GP, 1x RWA
- [8 March 2019] CEC 2019 paper accepted (CORE B): Mind the gap - a distributed framework for enabling energy optimisation on modern smart-phones in the presence of noise, drift, and statistical insignificance
- [2 March 2019] MSR 2019 paper accepted (CORE A, 25% acceptance rate): Predicting Good Configurations for GitHub and Stack Overflow Topic Models
- [18 February 2019] CEC 2019 Tutorial accepted: Genetic Improvement of Software
- [7 February 2019] Currently under review: 1x EMSE, 1x TEVC, 1x MSR, 2x CEC, 5x GECCO
- ACM SIGEVO Executive Committee Member (2019-2025, election outcome)
- Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence 2019
- GECCO 2020 Competitions Chair
- GECCO 2019 Competitions Chair
- Genetic Improvement of Software Workshop at GECCO 2019
- Special Session on Benchmarking of Evolutionary Algorithms For Discrete Optimisation at CEC 2019
- Special Session on Evolutionary Algorithms for Complex Optimization in the Energy Domain at CEC 2019
- Evolutionary Computation in Uncertain Environments: A Smart Grid Application at CEC 2019 (Competition)
- Bi-Objective Travelling Thief Problem Competition: EMO 2019, GECCO 2019 (successfully used in teaching at the Hasso-Plattner-Institute)
- Special Issue on Benchmarking of Computational Intelligence Algorithms in the Applied Soft Computing Journal
Open-Source Software Projects
- GIN - Genetic Improvement in No Time -- version 2.0 released on 13 June 2019!
- ICONIC - predictive modelling using genetic programming
- NEODYNAMICA - a symbolic regression application building on Jenetics
- TOYlib - a library on data sets for collectibles, tech report
- Search-Based Software Engineering GitHub version
- edX MOOC Computational Thinking and Big Data: course website, MicroMasters, Testimonial
- Reddit on free Computational Intelligence Courses: https://www.reddit.com/r/CompIntellCourses/
Selected older news from 2018-2016
- [6 December 2018] New technical report: Better Software Analytics via "DUO": Data Mining Algorithms Using/Used-by Optimizers
- [1 November 2018] AAAI 2019 (CORE A*, 16% acceptance rate): 1 full paper accepted!
- [11 September 2018] MOBIQUITOUS 2018 (CORE A, 39% acceptance rate): 1 full paper accepted!
- [30 August 2018] EU COST Action, Industry Day, Panel Discussion Lead
- [18 July 2018] School of Computer Science ranked 43 in the Shanghai Ranking
- [26 June 2018] New technical report: An Improved Generic Bet-and-Run Strategy for Speeding Up Stochastic Local Search
- [15 May 2018] PPSN 2018 (CORE A, 39% acceptance rate): 3 full papers accepted!!!
- [16 April 2018] New technical report: Per-Corpus Configuration of Topic Modelling for GitHub and Stack Overflow Collections
- [24 March 2018] GECCO 2018 (CORE A, 38% acceptance rate): 6 full papers accepted!!!!!! Tracks: 2x ECOM, 1x EMO, 2x GA, 1x RWA
- [2 March 2018] Data-Driven Search-Based Software Engineering vision paper on arXiv, accepted at Mining Software Repositories (CORE A, 33% acc rate), repository
- [15 February 2018] New technical reports
- [1 February 2018] Data-Driven Search-Based Software Engineering (vision paper on arXiv)
- [8 December 2017] Information Sciences paper accepted
- [26 October 2017] Hefei University, China: seminar, slides on Android energy consumption, slides on wave energy, News Post at Hefei University (with photo)
- [25 October 2017] Anhui University, China: Symposium on Evolutionary Computation, slides on Approximation-Guided Evolution and on the Travelling Thief Problem, News Post at Hefei University (with photos)
- [7 October 2017] Special Issue Benchmarking of Computational Intelligence Algorithms at Computational Intelligence Journal (Wiley) accepted
- [20 September 2017] Tunnelling and Underground Space Technology paper accepted
- [18 September 2017] PRIF RCP granted ($14.6million total budget), Unlocking Complex Resources through Lean Processing
- [1 September 2017] CSIRO ON Tribe Forum 2017 approved, flights and accommodation paid
- [23 August 2017] YSEP participation in Oct/Nov 2017 approved, Australia-China Young Scientists Exchange Program (two weeks fully funded networking program in Beijing, Hefei, and Shanghai, News Post at Hefei University, post by CSTEC, post by CISTC
- [16 July 2017] SEAL 2017 paper accepted, Exact Approaches for the Travelling Thief Problem
- [5 July 2017] Journal Genetic Programming and Evolvable Machines paper accepted, A Hyperheuristic Approach based on Low-Level Heuristics for the Travelling Thief Problem
- [15 June 2017] Many-Objective Optimisation Competition results: our AGE/AGEII achieved 3rd place (7 competitors)
- [14 April 2017] GI@GECCO 2017 paper accepted, Deep Parameter Optimisation on Android Smartphones for Energy Minimisation - A Tale of Woe and a Proof-of-Concept
- [20 March 2017] GECCO 2017 paper accepted, Theoretical results on bet-and-run as an initialisation strategy
- [20 March 2017] GECCO 2017 paper accepted, HSEDA: A Heuristic Selection Approach Based on Estimation of Distribution Algorithm for the Travelling Thief Problem
- [20 March 2017] GECCO 2017 poster accepted, A Case Study of Multi-objectiveness in Multi-component Problems
- [7 March 2017] CEC 2017 paper accepted, Improving local search in a minimum vertex cover solver for classes of networks
- [7 March 2017] CEC 2017 paper accepted, A Modified Indicator-based Evolutionary Algorithm (mIBEA)
- [6 March 2017] Journal of Heuristics paper accepted, A case study of algorithm selection for the traveling thief problem
- [17 February 2017] IWWWFB 2017 paper accepted, Study of fully submerged point absorber wave energy converter - modelling, simulation and scaled experiment
- [12 February 2017] LION 2017 paper accepted, Learning a Reactive Restart Strategy to Improve Stochastic Search (2x strong accept)
- [4 December 2016] Competition proposal accepted, "Optimisation of Problems with Multiple Interdependent Components" at GECCO 2017
- [4 December 2016] Workshop proposal accepted, "Evolutionary Methods for Smart Grid Applications" at GECCO 2017
- [5 September 2016] Promotion to Senior Lecturer, effective 1 January 2017
- [2 September 2016] Faculty ECMS Interdisciplinary Research Grant for “Nonlinear modelling of fully submerged wave energy converters for high fidelity yet computationally efficient numerival analysis and prototype design” with Dr. Boyin Ding, Dr. Javad Farrokhi Derakhshandeh, Dr. Markus Wagner, Dr. Luke Bennetts, Prof. Benjamin Cazzolato, A/Prof. Maziar Arjomandi, Prof. Frank Neumann, and Prof. Gus Nathan ($18,025)
- [24 August 2016] Successful NII Shonan Meeting proposal, topic "Data-Driven Search-Based Software Engineering 2017", organisers: Markus Wagner, Leandro Minku, Ahmed E. Hassan, John Clark
- [19 August 2016] ECMS Professional Development Grant for supporting a research stay at the University College London and attending an invitation-only Dagstuhl Seminar ($4,700)
- [13 August 2016] Invited Lecturer at the 5th International Optimisation Summer School in Kioloa, Australia in January 2017 PPTX, PDF
- [25 July 2016] Priority Partner Grant for enhancing the relationship with the University of Nottingham ($5,000)
- [20 July 2016] Best Presentation Award for "Optimising Energy Consumption Heuristically on Android Mobile Phones" at Genetic Improvement @ GECCO 2016
- [07 July 2016] MaxSAT 2016 Competition Results: my solver SC2016 achieved 1x First Place, 3x Second Place, 4x Third Place (17 competitors)
Recent service to the community
- Black-Box Discrete Optimization Benchmarking (BB-DOB) Workshops GECCO 2018, PPSN 2018
- Genetic Improvement of Software Workshop GI@GECCO
- PPSN 2018 Workshop Investigating Optimization Problems from Machine Learning and Data Analysis
- Adelaide Autumn School on Software Engineering 17/18 May 2018
- General Chair Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2018)
- Co-Chair International Workshop on Benchmarking of Computational Intelligence Algorithms (BOCIA)
- Competitions Chair GECCO 2018
- Program Chair Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2017)
- Workshop Chair GECCO 2017
- Chair IEEE CIS University Curricula 2017
- Associate Editor of Frontiers in Applied Mathematics and Statistics
- since 01/202: Associate Professor at the School of Computer Science, University of Adelaide, Australia
- 01/2017-12/2020: Senior Lecturer at the School of Computer Science, University of Adelaide, Australia
- 01/2016 - 12/2018: ARC DECRA Fellow "Dynamic adaptive software configuration", DE160100850, publications linked to this project: GoogleScholar search
- since 08/2015: Scientific Advisor at Complexica
- 03/2013 - 12/2016: Lecturer at the School of Computer Science, University of Adelaide, Australia
- 2013: PhD in Computer Science from the University of Adelaide, Australia (awarded the 1st University Doctoral Research Medal for Computer Science)
- 02/2011 - 05/2013: PhD student at the School of Computer Science, University of Adelaide, Australia
- 04/2010 - 01/2011: PhD student at the Max Planck Institute for Informatics, Department 1: Algorithms and Complexity, Saarbrücken
- 2009: Diplom in Computer Science (focus: Theoretical Computer Science and Artificial Intelligence) from the University of Koblenz-Landau, Germany
- 08/2006 - 05/2007: exchange student at the Institute for Artificial Intelligence, University of Georgia, USA
- PDF version: 13 March 2019
- openHPI lists the windfarm project as a showcase project (10/2019)
- CIS University Curricula Subcommittee intends to build up a collection of links to good quality courses on "everything CI" (10/2017)
- Unlocking Complex Resources through Lean Processing (09/2017)
- Adelaide Team Wins CSIRO On-Prime Performance Bonus (06/2017)
- Interdisciplinary Wave Energy Research with Coursework Students (05/2017)
- Dagstuhl Seminar 16412 Automated Algorithm Selection and Configuration, October 2016 (report)
- NII Shonan Computational Intelligence for Software Engineering, October 2014
- 2013-2014 International Postgraduate Research Prospectus
- Dagstuhl Seminar 13272 Computer Science in High Performance Sport - Applications and Implications for Professional Coaching, June 2013 (report)
- 1 Jahr Future SOC Lab (video about cooperation with the Hasso-Plattner-Institut) click (from 1:50min on...)-->watch from 1:50min on... (online at HPI)
Engagement, Service, and Leadership: I am strongly committed to supporting my local community at the University of Adelaide, my regional community in Australia and New Zealand, and my international community.
Outreach. My biggest contributions have been the co-organisation of the University’s Ingenuity 2015 and the development of a Wave Farm Optimisation Game that we have used at the University’s OpenDay 2017 and OpenDay 2018.
Summer schools. Besides these local events, I have also been very actively engaged in training those who have already committed to a degree in computer science, i.e., as a lecturer to three summer schools and as the organiser of two.
Conference organisation. I have regularly taken responsibilities at my flagship conferences. For example, for the Genetic and Evolutionary Computation Conference (GECCO), I have been its Workshop Chair 2016/17 and its Competition Chair 2018-2020. For GECCO 2022, I have coordinated the bids to organise it in Australia, and I will serve as its General Chair.
Society leadership. Since 2019, I have been on the Executive Committee of ACM SIGEVO, and I have since then also served as its first ever Sustainability Officer. Before that, in 2015-2017, I have led education-related subcommittees within the IEEE Computational Intelligence Society.
Editorial activities. I have been serving as Associate Editor on two boards and I have organised three journal special issues.
Administrative impact. Since 2020, I am my School’s Postgraduate Coordinator. As immediate reactions to the COVID19 outbreak, (1) I have worked with the HoS and School administrators to allow our students to sign out equipment for use at home, (2) I have appointed an HDR representative in March, and (3) I have setup an informal channel via a linoit.com corkboard, where students can post completely anonymously support each other.
Date Position Institution name 2020 - ongoing Associate Professor University of Adelaide 2017 - ongoing Senior Lecturer University of Adelaide 2013 - 2016 Lecturer University of Adelaide
Year Citation 2022 Wong, T., Wagner, M., & Treude, C. (2022). Self-adaptive systems: A systematic literature review across categories and domains. Information and Software Technology, 148, 106934.
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 Scopus4 WoS2
2022 He, X., Tu, Z., Wagner, M., Xu, X., & Wang, Z. (2022). Online Deployment Algorithms for Microservice Systems with Complex Dependencies. IEEE Transactions on Cloud Computing, 1.
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.
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 Scopus22 WoS16
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 Scopus27 WoS24
2021 Schlueter, M., Neshat, M., Wahib, M., Munetomo, M., & Wagner, M. (2021). GTOPX space mission benchmarks. SoftwareX, 14, 1-10.
DOI Scopus3 WoS1
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.
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.
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.
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 Scopus3 WoS1
2021 Chagas, J. B. C., & Wagner, M. (2021). Efficiently solving the thief orienteering problem with a max–min ant colony optimization approach. Optimization Letters, 19 pages.
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.
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 Scopus11 WoS10
2020 Sachdeva, R., Neumann, F., & Wagner, M. (2020). The Dynamic Travelling Thief Problem: Benchmarks and Performance of Evolutionary Algorithms.. CoRR, abs/2004.12045. 2020 Chagas, J. B. C., & Wagner, M. (2020). Ants can orienteer a thief in their robbery. Operations Research Letters, 48(6), 708-714.
DOI Scopus2 WoS1
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.
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 Scopus7 WoS3
2020 Neshat, M., Alexander, B., & Wagner, M. (2020). A hybrid cooperative co-evolution algorithm framework for optimising power take off and placements of wave energy converters.. Inf. Sci., 534, 218-244.
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 Scopus15 WoS12
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 Scopus6 WoS6
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., 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. 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 Scopus25 WoS27
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.
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 Scopus35 WoS22
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 Scopus46 WoS39
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 Scopus3 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 Scopus11 WoS10
2016 Wagner, M. (2016). Nested multi- and many-objective optimisation of team track pursuit cycling. Frontiers in Applied Mathematics and Statistics, 2, 1-10.
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.
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.
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.
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 Scopus22 WoS19
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 Scopus28 WoS22
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.
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.
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 Scopus75 WoS68
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 Scopus70 WoS52
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 Scopus60 WoS39
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. Reid, B., Barbosa, K., Amorim, M. D., Wagner, M., & Treude, C. (n.d.). NCQ: code reuse support for Node.js developers. Chinthanet, B., Reid, B., Treude, C., Wagner, M., Kula, R. G., Ishio, T., & Matsumoto, K. (n.d.). What makes a good Node.js package? Investigating Users, Contributors,
Yafrani, M. E., Martins, M. S. R., Delgado, M. R. B. S., Sung, I., Lüders, R., & Wagner, M. (n.d.). On resampling vs. adjusting probabilistic graphical models in estimation
of distribution algorithms.
Wagner, M., Lin, H., Li, S., & Saupe, D. (n.d.). Algorithm Selection for Image Quality Assessment. Aleti, A., Wallace, M., & Wagner, M. (n.d.). Is perturbation an effective restart strategy?. Weise, T., Wu, Z., & Wagner, M. (n.d.). An Improved Generic Bet-and-Run Strategy for Speeding Up Stochastic
Doerr, C., & Wagner, M. (n.d.). On the Effectiveness of Simple Success-Based Parameter Selection
Mechanisms for Two Classical Discrete Black-Box Optimization Benchmark
Friedrich, T., Kötzing, T., & Wagner, M. (n.d.). A Generic Bet-and-run Strategy for Speeding Up Traveling Salesperson and
Minimum Vertex Cover.
Assimi, H., Koch, B., Garcia, C., Wagner, M., & Neumann, F. (n.d.). Run-of-Mine Stockyard Recovery Scheduling and Optimisation for Multiple
Reid, B., Wagner, M., d'Amorim, M., & Treude, C. (n.d.). Software Engineering User Study Recruitment on Prolific: An Experience
Caddy, J., Wagner, M., Treude, C., Barr, E. T., & Allamanis, M. (n.d.). Is Surprisal in Issue Trackers Actionable?.
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.
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.
Year Citation 2022 Assimi, H., Neumann, F., Wagner, M., & Li, X. (2022). Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems. In L. P. Caceres, & S. Verel (Eds.), Evolutionary Computation in Combinatorial Optimization (Vol. 13222 LNCS, pp. 111-126). SPRINGER INTERNATIONAL PUBLISHING AG.
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.
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.
Year Citation 2018 Neumann, A., Gao, W., Wagner, M., & Neumann, F. (2018). Evolutionary Diversity Optimization Using Multi-Objective Indicators.. 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.
Year Citation 2018 Neumann, A., Gao, W., Doerr, C., Neumann, F., & Wagner, M. (2018). Discrepancy-based Evolutionary Diversity Optimization..
In my research, I focus on Evolutionary Algorithms. These form a sub-class of bio-inspired optimisation algorithms, which mimic fundamental aspects of the neo-Darwinian evolutionary process. My specialties are problem-specific hill-climbers (where solutions are improved iteratively) and multi-objective approaches (for problems with multiple conflicting objectives).
Research output and funding. My work spans theoretical investigations that show the impact of design choices and theory-motivated algorithm engineering (e.g., ARC DE160100850 and DP200102364) and also real-world applications of evolutionary algorithms (e.g., ARC IC190100017, Google Faculty Award 2019, Blavatnik Interdisciplinary Cyber Research Center Research Project 2020). In summary, I am a CI on projects with a total income of over AUD 9.2 million (AUD over 4.5 million from the ARC). Of these, I am lead CI of projects funded with AUD 360,200. My works have attracted three Best Paper Nominations, a Best Paper Award and a Best Presentation Award (all at GECCO, which is my field’s top conference), and I have published 79 articles since 2015, which have attracted 1471 citations (GoogleScholar).
Discipline impact and esteem; Research Culture and Leadership. I have built up a team at the University of Adelaide for the optimisation of code on smartphones. Internationally, to support code-level optimisation, I have developed the open-source software project GIN for the “genetic improvement of software in no time”. In recognition of my international standing and contributions, I have been opening keynote speaker at the Symposium on Evolutionary Computation, Hefei, China (2017), I have attended five invitation-only workshops, and I have delivered three conference tutorials. A particular highlight is my co-founding of the field called “Data-Driven Search-Based Software Engineering” (DSE), which was the result of my organisation of a NII Shonan Meeting in 2017. In addition, I have established my second IEEE Task Force in 2019, which organises two workshops, one special session, and one journal special issue in 2020.
Translation, commercialisation and industry engagement. While I greatly enjoy fundamental research, I also translate insights to practical approaches: I work with the Perth-based Carnegie Clean Energy Pty Ltd on the next generation of their wave energy converter technology, and with EKA in Adelaide on improving their iron ore stockpile management. In addition, Google funds my work on making software development more broadly accessible and the Blavatnik Interdisciplinary Cyber Research Center funds my work on minimising security threats.
List of Grants
- Defence Innovation Partnership: AI for Decision Making Initiative 2020 (Round One, Phase Two), sponsor: Office of National Intelligence
Contextually Situated Anomaly Detection
AUD 100,000 (A/Prof Markus Wagner, Dr Chetan Arora, Menasha Thilakaratne, Dr Christoph Treude, Dr Wei Zhang)
- Linkage Project LP200200881 (Australian Research Council) 2021-2024
Collaborative Sensing and Learning for Maritime Situational Awareness
AUD 643,565 (ARC) + AUD 301,171 (SEDA, cash) (A/Prof Markus, Prof Tat-Jun Chin, Prof Ian Reid, Dr Surabhi Gupta, Dr Christophe Guettier)
- Google Research Scholar Award 2021
Automatic Post-Quantum Cryptographic Code Generation and Optimization
USD 60,000 (Dr Chitchanok Chuengsatiansup, A/Prof Markus Wagner)
- Discovery Project DP210102670 (Australian Research Council) 2021-2023
Intelligent Technologies for Smart Cryptography
AUD 480,000 (Dr Yuval Yarom; Dr Markus Wagner; Dr Minhui Xue; Dr Chitchanok Chuengsatiansup, Prof Dr Lejla Batina)
- Defence Innovation Partnership: AI for Decision Making Initiative 2020 (Round One, Phase One)
Deceitful/Persuasive Writing Detection
AUD 20,000 (Dr Markus Wagner)
- Faculty ECMS Seed Funding 2020
Intelligence Technologies for Smart Cryptography
AUD 10,000 (Dr Yuval Yarom, Dr Chitchanok Chuengsatiansup, Dr Markus Wagner, Dr Jason Xue)
- Blavatnik Interdisciplinary Cyber Research Center, Research Project, 2020
Leakage-free Cryptography: Eliminating Side Channel Leakage Using Compiler Optimization
ILS 1,200,000 (AUD 512,000) (Dr Chitchanok Chuengsatiansup, Dr Markus Wagner, Dr Minhui Xue, Dr Yuval Yarom)
- Google Faculty Award 2020
Rewriting software documentation for non-native speakers
USD 39,722 (AUD 60,032) (Dr Christoph Treude, Dr Sebastian Baltes, Dr Markus Wagner)
- Discovery Project DP200102364 (Australian Research Council) 2020-2022
Multiobjective Memetic Algorithms for Multi-task Symbolic Regression
AUD 518,000 (Prof. Pablo Moscato; Dr Markus Wagner; Prof.Stanislav Djorgovski; Prof.Carlos Cotta; A/Prof. Massimo Cafaro)
- Hasso Plattner Institute: Future SOC Lab (Service-Oriented Computing) 2019/2020
“Designing practical algorithms through overfitting”
access to 1000-core cluster, October 2019 – September 2020
- Training Centre “Integrated Operations for Complex Resources” 2019-2023 (Australian Research Council)
AUD 3,703,664 (lead CI Prof. Peter Dowd, in total 20 Cis and 17 PIs), AUD 12,500,000 total
- Hasso Plattner Institute: Future SOC Lab (Service-Oriented Computing) 2019
“Overfitting on purpose to design new algorithms”
access to 1000-core cluster for 6 months, April-September 2019
- Special Studies Program (The University of Adelaide) 2019
AUD 4,800 (Dr. Markus Wagner)
- Analysis of Evolutionary Algorithms: Beyond Expected Optimization Times 2018 (Gaspard Monge Program for Optimization, operations research, and their interactions with data science (PGMO))
EUR 21,500 (lead: Dr. Carola Doerr, in total 10 partners)
- Pawsey Supercomputing Centre (Australia) 2018
“Intelligent Wave Power: Advance control of Carnegie's multi-moored wave energy converter”
1.3 million core hours (lead: Prof. Ben Cazzolato, in total 5 Cis)
- EPIC Expert Visit, Dr. Earl Barr from University College London (funded by European Union's Horizon 2020 research and innovation
programme (ICT) under grant agreement No 687794) 2018
EUR 2,000 (Dr. Markus Wagner, Dr. Christoph Treude, Dr. Marcel Böhme)
- Overseas Conference Leave Scheme Travel Award 2018 (The University of Adelaide)
AUD 2,000 (Dr. Markus Wagner)
- Premier's Research and Industry Fund: Research Consortia Program 2018-2021 (Department of State Development)
“Unlocking Complex Resources through Lean Processing”
AUD 4,000,000 (lead CI Prof. Stephen Grano, in total 22 CIs), total project AUD 14.6 million
- Australia-China Young Scientists Exchange Program 2017 (Australian Academy of Technology and Engineering and China Science and Technology Exchange Center), Two-week networking programm in China (all expenses paid)
- ARC Linkage Project Proposal Support (The University of Adelaide)
AUD 4,100 (Prof. Ben Cazzolato, A/Prof. Maziar Arjomandi, Dr. Markus Wagner, Dr. Luke Bennetts, Dr. Boyin Ding)
- CSIRO ON Prime Pre-Accelerator Program (CSIRO) 2017
“Portable Hardware Energy Optimisation”
AUD 3,200 (Dr. Brad Alexander, Francois Duvenage, Dr. Markus Wagner (lead applicant))
- Overseas Conference Leave Scheme Travel Award 2017 (The University of Adelaide)
AUD 3,065 (Dr. Markus Wagner)
- Faculty ECMS Interdisciplinary Research Grant 2016 (The University of Adelaide)
“Nonlinear modelling of fully submerged wave energy converters for high fidelity yet computationally efficient numerical analysis and prototype design”
AUD 18,025 (Dr. Boyin Ding, Dr. Javad Farrokhi Derakhshandeh, Dr. Markus Wagner, Dr. Luke Bennetts, Prof. Benjamin Cazzolato, A/Prof. Maziar Arjomandi, Prof. Frank Neumann, Prof. Gus Nathan)
- Faculty ECMS Professional Development Grant 2016 (The University of Adelaide)
AUD 4,700 (Dr. Markus Wagner)
- Priority Partner Grant 2016 Nottingham (The University of Adelaide)
AUD 5,000 (Dr. Markus Wagner (lead applicant), Prof. Frank Neumann)
- Discovery Early Career Researcher Award 2016 DE160100850 (Australian Research Council)
“Dynamic Adaptive Software Configurations”
AUD 330,000 (Dr. Markus Wagner)
The project was also granted AUD 20,000 from the University’s DVC-Research.
- Priority Partner Grant 2015 Strasbourg/Freiburg (The University of Adelaide)
AUD 5,000 (Dr. Markus Wagner (lead applicant), A/Prof. Frank Neumann)
- Interdisciplinary Research Fund 2015 (The University of Adelaide)
“Modelling and optimisation of submerged buoys for improved ocean wave energy production”
AUD 27,000 (Dr. Markus Wagner (lead applicant), Dr. Bojin Ding, A/Prof. Frank Neumann, Prof. Benjamin Cazzolato,
Dr. Maziar Arjomandi)
- Overseas Conference Leave Scheme Travel Award 2015 (The University of Adelaide)
AUD 2,000 (Dr. Markus Wagner)
- Faculty Research Internal Grant 2014 (The University of Adelaide)
AUD 8,500 for software licenses and specialised coprocessor cards (Dr. Bradley Alexander, Prof. Frank Neumann,
Dr. Markus Wagner)
- Overseas Conference Leave Scheme Travel Award 2014 (The University of Adelaide)
AUD 2,000 (Dr. Markus Wagner)
- School of Computer Science Research Internal Grant 2013 (The University of Adelaide)
AUD 30,000 for a computing cluster and software licenses (Dr. Bradley Alexander, Dr. Cruz Izu, Prof. Frank Neumann,
Dr. Markus Wagner)
- Google PhD Travel Prize 2012 (Google Australia Pty Ltd.)
- Bupa Postgraduate Travel Grant 2012 (Bupa Australia Pty Ltd.)
- Google PhD Top Up Grant 2011 for “meritorious academic record and high standard of research capability” (Google Australia Pty Ltd.)
- School of Computer Science Postgraduate Scholarship 2011/2012 (The University of Adelaide)
AUD 54,000 p.a. (approx)
- Max Planck Research School Postgraduate Scholarship 2010 (Max Planck Institute for Informatics)
EUR 16,000 p.a. (approx)
- Internationale Studien- und Ausbildungspartnerschaften ISAP (German Academic Exchange Service, DAAD), full scholarship for my MSc studies at the University of Athens, USA, 2006/2007
EUR 15,000 (approx)
- Travel awards to attend the following events (granted by the respective organising committees): Genetic and Evolutionary Computation Conference (GECCO) 2013, International Joint Conference on Artificial Intelligence (IJCAI) 2011, Interdisciplinary College (IC) 2010, Künstliche Intelligenz (KI) 2009, Congress on Evolutionary Computation (CEC) 2009, Genetic and Evolutionary Methods (GEM) 2008, EvoWorkshops 2008
- Jugend forscht (regional youth research competition)
3rd place in the field of Mathematics/Computer Science 2002
3rd place in the field of Technology 2000
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 2022 Principal Supervisor Fuzz Driver Generation Master of Philosophy Master Full Time Mr Supun Jeevaka Dissanayake 2022 Principal Supervisor Visualising Micro-Service Architectures Master of Philosophy Master Full Time Mr Oscar Manglaras 2021 Principal Supervisor Automatic Detection and Analysis of Outdated Architecture Documentation in GitHub Wikis Master of Philosophy Master Full Time Mr Wen Siang Tan 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 2020 Principal Supervisor Improving Developer Efficiency through Code Reuse Doctor of Philosophy Doctorate Full Time Ms Brittany Anne Reid 2020 Principal Supervisor Enhance State-of-the-Art Techniques which Generate Low Level Code for Cryptographic Arithmetic Doctor of Philosophy Doctorate Full Time Mr Joel Kuepper 2018 Co-Supervisor Optimisation of Supply Chains and Trusses Under Uncertainty Doctor of Philosophy Doctorate Part Time Mr Hirad Assimi 2018 Principal Supervisor Side-Channel Attack Mitigation Using Search Based Software Engineering Doctor of Philosophy Doctorate Full Time Mr Madura Anushanga Shelton
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2021 - 2022 Principal Supervisor Dissecting Malicious Behaviours of Mobile Applications Master of Philosophy Master Full Time Mr Zach Wang 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
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
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
Date Institution Department Organisation Type Country 2018 - ongoing Daitum . Business and professional Australia 2015 - ongoing Complexica . Business and professional Australia
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
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
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