School of Computer Science
Faculty of Engineering, Computer and Mathematical Sciences
Eligible to supervise Masters and PhD, but is currently at capacity - 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
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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 01/2017: 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)
- I attracted funding with a total value of AUD 420,500 (AUD 382,000 as the lead investigator).
- I have co-authored over 150 articles with over 150 different colleagues.
- My h-index is 23 with over 1700 citations (Google Scholar), with the number of citations per year steadily increasing.
- I was invited four times to prestigious invitation-only seminars on hot topics in computer science [3x Dagstuhl, 2x NII Shonan], and I have organised one NII Shonan Seminar as the lead.
In my research, I focus on the so-called Evolutionary Algorithms. These form a sub-class of bio-inspired algorithms, who mimic some fundamental aspects of the neo-Darwinian evolutionary process. They simultaneously search with a population of candidate solutions and associate an objective score as a fitness value for each one. The algorithms then select among the population to favour those solutions that are more fit. The next generation (i.e. a new population) consists of replicates of the fitter solutions that have been genetically mutated and crossed over in a biological metaphor: the decision variables were perturbed such that they inherit characters of their parents, as well as change in random ways.
For the past decades, the algorithms’ success has led to strongly practical-oriented interests. Although the theory of them is far behind the knowledge gained from experiments, there are theoretical investigations about some of their properties. My work spans theoretical investigations that show the impact of design choices, theory-motivated algorithm engineering, and also the real-world applications of evolutionary algorithms.
When is comes to algorithms, my specialties are problem-specific hill-climbers (where solutions are improved iteratively) and multi-objective approaches (for problems with multiple conflicting objectives). Most of my over 60 articles belong to either of these two categories. My work on energy consumption minimisation and energy production maximisation has resulted in two grants so far (total value AUD 377,000), and in a very active collaboration with the Wave Energy Converter group at the School of Mechanical Engineering. The latter involves the company Carnegie Wave Energy Pty Ltd in Perth, and together we are working on unlocking the full potential of Australia’s energy resources. In the research group Optimisation and Logistics (lead by Prof Frank Neumann), I have been the coordinator of energy-related research since 2013.
I am not only an established and independent researcher, but also an important part of research groups. So far, I have co-authored over 60 articles with a total of over 60 different colleagues. I the last five years, I have visited leading colleagues at their institutes to conduct research with them. For example, I have visited A/Prof Frank Hutter at the Albert Ludwigs University, Freiburg, Prof Tobias Friedrich at the Hasso Plattner Institute, Potsdam and at the Friedrich-Schiller-University, Jena, Prof Yuri Kochetov at the Sobolev Institute of Mathematics, Novosibirsk, and Prof Andrea Schaerf at the Università degli Studi di Udine, Udine.
In order to bring my research outcomes into the industrial sector, I have also collaborated with the Adelaidean companies SolveIT Software Pty Ltd., Optimatics Solutions Pty Ltd, and Complexica Pty Ltd., and with Schneider Electric’s local office. Currently, I am Scientific Advisor for Complexica.
Over the last years, I have established at my School the field of search-based software engineering. This is an innovative approach to software engineering in which search-based optimisation algorithms are used to address problems. It has a high potential because it offers a suite of adaptive automated and semi-automated solutions in situations typified by large and complex problem spaces with multiple competing and conflicting objectives. This approach has been applied to a number of software engineering activities, right across the life-cycle from requirements engineering, project planning and cost estimation through testing, to automated maintenance, service-oriented software engineering, compiler optimisation and quality assessment. Together with my team, I work at the intersection of optimisation and software engineering, which are long-term foci of my School.
As recognition of my expertise, I have been invited to prestigious seminars three times (Dagstuhl Seminar twice, NII Shonan Seminar once). These seminars bring together personally invited scientists from academia and industry from all over the world to discuss their newest ideas and problems in informatics. The number of participants is limited to enable discussion. For 2017, I am leading a team of experts who proposed to organise a NII Shonan Seminar on search-based software engineering. This team includes Dr. Leandro Minku from the University of Leicester, UK, Dr. Gordon Fraser from the University of Sheffield, UK, and Prof Ahmed Hassan from Queen's University, USA.
Despite this high output, my productivity has not yet peaked. On 21st April 2016, I have submitted my 12th article in 2016. Nine of these have already been accepted, and I am expecting many more to come this year.
Year Citation 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 Scopus1 WoS1
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.
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. 2020 Chagas, J. B. C., Blank, J., Wagner, M., Souza, M. J. F., & Deb, K. (2020). A non-dominated sorting based customized random-key genetic algorithm for the bi-objective traveling thief problem. Journal of Heuristics, OnlinePubl, 1-35.
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), 23 pages.
DOI Scopus1 WoS1
2020 Chagas, J., & Wagner, M. (2020). Ants can orienteer a thief in their robbery. Operations Research Letters, 48(6), 708-714.
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, 106502.
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.
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. 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 Scopus17 WoS15
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 Scopus19 WoS11
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.
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 Scopus9 WoS9
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 Scopus21 WoS18
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 Scopus18 WoS16
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 Scopus63 WoS58
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 Scopus52 WoS37
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 Scopus50 WoS30
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. — Shelton, M. A., Samwel, N., Batina, L., Regazzoni, F., Wagner, M., & Yarom, Y. (n.d.). Rosita: Towards Automatic Elimination of Power-Analysis Leakage in
— Wong, T., Wagner, M., & Treude, C. (n.d.). Self-Adaptive Systems: A Systematic Literature Review Across Categories
— Reid, B., Barbosa, K., Amorim, M. D., Wagner, M., & Treude, C. (n.d.). NCQ: code reuse support for Node.js developers.
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.
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..
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). I conduct research on my interactive whiteboard, on the University’s HPC Phoenix (e.g., 2.4M CPU hours in 2016-18), and on my team’s Android phone farm. In total, I am a CI on projects with a total income of over AUD 9.2 million (excluding the large Training Centre and Research Consortium: income of over AUD 1.5 million). Of these, I am lead CI of projects funded with AUD 360,200.
- 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 2019
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
- Outstanding perception by students: in "Markus Wagner is an effective university teacher" I scored 2x 100% broad agreement in 2013, 3x in 2014, 4x in 2015, 1x in 2016, 1x in 2017, and 2x in 2018.
- Above University-average SELT scores and fantastic comments, and course improvements as manifested in improved course SELT scores and reduced failure rates for “Introduction to Programming”.
- Projects with coursework students resulted in the publication of six refereed articles (five A-ranked).
- Team leadership: I have had over a dozen computer science students working on topics related to my ARC grants, and about a dozen computer science students on topics related to my collaboration with the School of Mechanical Engineering.
I am passionate about teaching and my experience in computer science teaching ranges from foundational courses to complex software engineering projects. So far, I have been involved in the teaching of a plethora of courses (sixteen times as course coordinator) at the University of Adelaide. The courses covered all levels, and the enrolment numbers ranged from 10 to over 300 students. In my teaching, I apply active learning methods for small groups, and in-class feedback systems, which aligns perfectly with the Beacon Initiative on Small Group Discovery Experience, and more recently with the Future Making iniitiative.
In order to improve my teaching skills, I regularly attend teaching workshops and seminars. Among them was a very beneficial two-day teaching workshop in 2013. Since then, I have integrated into my teaching ideas from this workshop, from Rick Rice’s “Tomorrow’s Professor” newsletter, and from other sources of best-practice information. The implementation of new approaches has not always been easy, however, I have learned from the challenges. Nowadays, I am a confident teacher who can alter the course of lectures on the spot if necessary, and who can successfully run interactive sessions spontaneously. Regularly, I act like a guide and moderator in class, who lets the students discover the knowledge.
In my classes I use active learning methods, in particular Eric Mazur’s “think-pair-share”. In the first phase of this activity, students think about a given task individually for 30 seconds to two minutes. Then, I give them a minute or two to discuss their thoughts with a partner. I measure the success of this phase in the loudness of the room: the louder, the better, as this means that the students are engaged. In the final sharing phase, pairs can volunteer to present their thoughts. Also, as I typically walk around during the second phase, I will have one or more groups that I can call upon as backups. Such an exercise hardly ever takes longer than five minutes. I think this is very well invested time, as the students reflect immediately upon covered content, they practice their communication skills, and I get to briefly check whether the class is ready to move on. Comments like the following prove to me that the students not only enjoy such activities, but that they also see the benefits of this increased level of student engagement: “I love the small interactive things in the lectures. Breaks up the listening, lets us stretch out a little to be able to refocus better.”
Besides using innovative teaching techniques, I use in-class response systems (through the learning management system) to get feedback, and I run and modify code live in class to demonstrate aspects and behaviour, instead of just talking about them. Thus, the lectures become more interactive and hands-on compared to a traditional top-down approach. It also gives me the flexibility to react to misconceptions and questions. The students enjoy my approach as evidenced by the following comment: “In lectures Markus explains complex concepts very well. He incorporates use of diagrams through the projector well, and engages the class in discussion of possible solutions for problems.”
I bring in guest speakers when possible, especially for the higher-level courses. So far, I have successfully invited over ten external speakers from local consulting agencies, University spin-offs, the Australia Computer Science Society, and the Department of Infrastructure and Regional Development. I am encouraged in this practice by feedback such as “It was also good to have a person from industry come and talk to us and show us their software (Darren from Optimatics), and I feel this should be present in more courses.”
Since 2015, I have been involved in the delivery of over 18 courses (12 times as course coordinator). The enrolment numbers in these 2nd to 4th year courses ranged from 10 to over 150 students.
My SELT scores reflect my capacity to develop and deliver seminars and lectures, and to contribute to other teaching activities. My fourth-level courses are among the top-rated ones in my School, with scores being significantly above not only my School’s and Faculty’s averages, but also above the University’s average. Moreover, their feedback is very encouraging; for example, when asked what the best aspects of my teaching are the students replied: “Very straight to the point.”, “Gives good explanations of what students are being taught.”, and “Encouraging participation in lectures, providing engaging and enjoyable lectures”. In general, my teaching approach gets scored pretty well. Eight times I achieved a 100% broad agreement on the SELT question "Markus is an effective university teacher": 2015-S1 four times (MECH ENG 1102BR, COMP SCI 7403, Semester 2: COMP SCI 4095, COMP SCI 7093), 2016-S1: once (COMP SCI 1102); 2017-S2 once (COMP SCI 7409); 2018-S2 twice (COMP SCI 4409, COMP SCI 7409). In 2019, I have not had an official SELT result: due to a scheduling clash, my courses have been very small and not enough students submitted their SELT feedback.
I have delivered courses not only in Adelaide by also overseas. In September 2019, following a referral by one of my colleagues, I have taught a two-week, 16-hour compact version of my course Evolutionary Computation at the Harbin Institute of Technology (HIT) in Harbin, China. 139 students took the course, and they were assessed based on 49 online questions, a short essay on recent conference papers, and on a group homework. Among the challenges that I have had to overcome was the initial hesitation of the local students to ask questions and to interact with me in class. My initial idea to use Mentimeter.com (a provider of interactive presentations) hit an unexpected roadblock due to the platform’s reliance on Google-hosted services that are not available in China – while I have been in direction contact with the Mentimeter support team who made adjustments to their platform on the spot, we could not get their services to work reliably. Luckily, I have had the already mentioned LinoIt.com and OnlineClicker.org as backups, as well as HIT’s YuKeTang that is based on WeChat. In late 2020, I will deliver this course again, but this time as on online course.
Research supervision, research training and mentoring
I have grown my team to a good size: I am Principal Super-visor to 7 PhD students, and Co-Supervisor to 5 more. I have co-supervised two to timely completion, one submitted in June 2020, one will in October 2020 (with me as Principal), and one will join in 2021 on an approved Divisional Scholarship. Since 2015, I have supervised 16 two-semester projects of Honours and Master-by-coursework students.
In the early stages of their PhD studies, I focus most of my attention on collaboratively designing the projects. Together, we then outline potential approaches and I show them how to refine them. Right from the beginning of their studies, I include them in research projects with more advanced PhD students. This way, while going through the initial reading phase, they experience research methods and collaborative research immediately. The students also have an important contribution to experimental design, data analysis, interpretation, and writing of the paper. Initially, my major contribution to their work is in the overall design of the projects, and the rigorous testing of the code, which is sometimes accompanied with code contributions from my side. Especially at the beginning of their studies, it is important that we critically verify together their first data analyses – this greatly helps to sharpen their skills to assess the validity of computational experiments: in a field where small design decisions can have substantial effects, we need to be able to detect inconsistencies between the conceptual designs and the experimental outcomes produced by the implementations. Later, when it is time to write the first article, I take over most of the writing. With increasing progress of the students, and with their adoption of systematic approaches, I step more and more into the background. At every point in time, I am open to their suggestions, which can include deviations from previously agreed-upon plans. It depends then on the situation at hand and at the resources available on whether detours can be taken, or excursions into other fields.
I measure the students’ success in the number of publications. A good target is three to five articles at leading international conferences or in top journals. To reach this, I align work packages with short-term and long-term submission deadlines. This goal setting helps everybody in the research teams to see the next goals and the overall goals. Also, this approach automatically provides a “plan B”.
It is my greatest joy if, towards the end of their training, I can consider my PhD students as colleagues, who have more specialised knowledge about their research area than me.
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. Some of them continue our work after graduation, whereas others will at the very least benefit from having experienced systematic approaches to solving challenging problems. With undergraduate and non-Doctoral postgraduate students, I have published five articles since 2015, three of these are full papers at A-ranked conferences. Two of the five were the result of voluntary coursework project extensions. The other three came out of their research conducted during their Master projects.
In my supervision, I aim at guiding them in such a way that they can reach the highest international level. This involves their inclusion in my own research collaborations. For example, together with my former Master student Mahmoud Bokhari, we worked with colleagues from the Karlsruhe Institute of Technology, Germany during his Master project. This international collaboration led to two articles at flagship events. To one of them, Mahmoud flew in September 2015 with financial support from the School of Computer Science, and he presented our results. Later, he became my PhD student funded by his overseas institution. Similarly, my Master students Slava Shekh, Yuanzhong Xia, and Lujun Weng have been contributors to interdisciplinary research with the School of Mechanical Engineering. For them, this has resulted in conference articles, and one journal version is currently being prepared.
Two of my current PhD students, Brittany Reid and Terence Wong, have also been former students of mine. Brittany, now in receipt of a RTPS, has done her Honours project with me and my colleague Dr Christoph Treude in 2019. Just in April 2020, we have published our first article with her. Terence, on the other hand, is a DST-funded, part-time PhD student who approached me last year after taking my SBSE course. He has also started in 2020 and is currently conducting a systematic literature review on self-adaptive software systems, a topic that is very close to my heart.
In addition to mentoring my local students, I also collaborate a lot with PhD students from all over the world. These connections come from discussions at conferences and also because I take the time to respond to emails from students when they have questions. For example, I have published two papers with Jonatas Chagas (Universidade Federal de Ouro Preto, Brazil), two with Daniel Lückehe (Uni Oldenburg, Germany), two with Mohammad Ali Moridi (Curtin University, Australia), one with Julian Blank (Michigan State University, USA), and one with Wenwen Li (University of Nottingham, UK). Often, these result in long-lasting professional friendships; among these are Shahriar Mahbub (two papers, formerly Fondazione Bruno Kessler, Italy), Shelvin Chand (four papers, formerly at UNSW, Australia), and Mohamed El Yafrani (seven papers, formerly Mohammad V University, Morocco). Out of one of these discussions, Mehdi Neshat (who contacted me in early 2016) has joined my team in December 2016 on an ASI, and he will submit his thesis timely after 3.5 years in July 2020. Among Mehdi’s outstanding achievements are two Q1 journal articles, as well as three CORE A-ranked conference papers, a Best Paper Award, and an additional Best Paper Nomination – he is an excellent example of how our university has been a magnet for talent.
My reputation in regard to PhD supervision led to two external thesis examinations in 2018: first, as examiner for a PhD thesis from RMIT University; then, as a panel member at a PhD defence at Mohammed V University, Morocco.
Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2021 Principal Supervisor Automatic Detection and Analysis of Outdated Architecture Documentation in GitHub Wikis Master of Philosophy Master Full Time Mr Wen Siang Tan 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 2020 Principal Supervisor Improving Developer Efficiency through Code Reuse Doctor of Philosophy Doctorate Full Time Ms Brittany Anne Reid 2019 Principal Supervisor Fuzz Target Generation Doctor of Philosophy Doctorate Full Time Mr Supun Jeevaka Dissanayake 2018 Co-Supervisor Optimisation of Supply Chains and Trusses Under Uncertainty Doctor of Philosophy Doctorate Full 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 2017 Principal Supervisor Summarising Algorithms for Software Engineering Data Doctor of Philosophy Doctorate Full Time Mr Mahfouth Ahmad Alghamdi 2016 Principal Supervisor Dynamic Adaptive Software Configuration Doctor of Philosophy Doctorate Full Time Mr Mahmoud Abdulwahab K Bokhari
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 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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