School of Computer Science
Faculty of Engineering, Computer and Mathematical Sciences
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/
- [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)
- [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
- [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!
- [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)
- Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence 2019
- 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
- Special Issue on Benchmarking of Computational Intelligence Algorithms in the Applied Soft Computing Journal
Open-Source Software Projects
- GIN - Genetic Improvement in No Time
- ICONIC - predictive modelling using genetic programming
- 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 2017/2016
- [8 December] Information Sciences paper accepted
- [26 October] Hefei University, China: seminar, slides on Android energy consumption, slides on wave energy, News Post at Hefei University (with photo)
- [25 October] 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] Special Issue Benchmarking of Computational Intelligence Algorithms at Computational Intelligence Journal (Wiley) accepted
- [20 September] Tunnelling and Underground Space Technology paper accepted
- [18 September] PRIF RCP granted ($14.6million total budget), Unlocking Complex Resources through Lean Processing
- [1 September] CSIRO ON Tribe Forum 2017 approved, flights and accommodation paid
- [23 August] 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] SEAL 2017 paper accepted, Exact Approaches for the Travelling Thief Problem
- [5 July] Journal Genetic Programming and Evolvable Machines paper accepted, A Hyperheuristic Approach based on Low-Level Heuristics for the Travelling Thief Problem
- [15 June] Many-Objective Optimisation Competition results: our AGE/AGEII achieved 3rd place (7 competitors)
- [14 April] 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] GECCO 2017 paper accepted, Theoretical results on bet-and-run as an initialisation strategy
- [20 March] GECCO 2017 paper accepted, HSEDA: A Heuristic Selection Approach Based on Estimation of Distribution Algorithm for the Travelling Thief Problem
- [20 March] GECCO 2017 poster accepted, A Case Study of Multi-objectiveness in Multi-component Problems
- [7 March] CEC 2017 paper accepted, Improving local search in a minimum vertex cover solver for classes of networks
- [7 March] CEC 2017 paper accepted, A Modified Indicator-based Evolutionary Algorithm (mIBEA)
- [6 March] Journal of Heuristics paper accepted, A case study of algorithm selection for the traveling thief problem
- [17 February] IWWWFB 2017 paper accepted, Study of fully submerged point absorber wave energy converter - modelling, simulation and scaled experiment
- [12 February] LION 2017 paper accepted, Learning a Reactive Restart Strategy to Improve Stochastic Search (2x strong accept)
- [4 December] Competition proposal accepted, "Optimisation of Problems with Multiple Interdependent Components" at GECCO 2017
- [4 December] Workshop proposal accepted, "Evolutionary Methods for Smart Grid Applications" at GECCO 2017
- [5 September] Promotion to Senior Lecturer, effective 1 January 2017
- [2 September] 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] 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] 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] Invited Lecturer at the 5th International Optimisation Summer School in Kioloa, Australia in January 2017 PPTX, PDF
- [25 July] Priority Partner Grant for enhancing the relationship with the University of Nottingham ($5,000)
- [20 July] Best Presentation Award for "Optimising Energy Consumption Heuristically on Android Mobile Phones" at Genetic Improvement @ GECCO 2016
- [07 July] 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
- 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) 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 100 articles with over 100 different colleagues.
- My h-index is 21 with over 1300 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, 1x 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 2019 Alghamdi, M., Treude, C., & Wagner, M. (2019). Toward human-like summaries generated from heterogeneous software artefacts. GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 1701-1702.
2018 Neumann, A., Gao, W., Doerr, C., Neumann, F., & Wagner, M. (2018). Discrepancy-based Evolutionary Diversity Optimization.. CoRR, abs/1802.05448. 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 Scopus5 WoS4
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.
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 Scopus5 WoS6
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 Scopus7 WoS6
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 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. A., Kawamura, Y., Sharifzadeh, M., Chanda, E. K., 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 Scopus16 WoS12
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 Scopus3 WoS2
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 Scopus15 WoS12
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 Scopus51 WoS47
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 Scopus35 WoS27
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 Scopus39 WoS22
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. 2007 Härder, T., Haustein, M., Mathis, C., & Wagner, M. (2007). Node labeling schemes for dynamic XML documents reconsidered. Data and Knowledge Engineering, 60(1), 126-149.
2001 Wald, I., Slusallek, P., Benthin, C., & Wagner, M. (2001). Interactive rendering with coherent ray tracing. Computer Graphics Forum, 20(3).
— Treude, C., & Wagner, M. (n.d.). Predicting Good Configurations for GitHub and Stack Overflow Topic
— Neshat, M., Alexander, B., Sergiienko, N., & Wagner, M. (n.d.). A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off
and Placements of Wave Energy Converters. GECCO 2019: 1293-1301.
— Neshat, M., Alexander, B., Sergiienko, N., & Wagner, M. (n.d.). A new insight into the Position Optimization of Wave Energy Converters
by a Hybrid Local Search.
— Neshat, M., Abbasnejad, E., Shi, Q., Alexander, B., & Wagner, M. (n.d.). Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy
Converters Placement Optimisation.
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 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 — Neumann, A., Gao, W., Wagner, M., & Neumann, F. (n.d.). Evolutionary Diversity Optimization Using Multi-Objective Indicators.
- 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)
“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)
- ARC Discovery Early Career Researcher Award (Australian Research Council)
AUD 330,000 + AUD 20,000 by the University of Adelaide (Dr. Markus Wagner)
- 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. Mazia Arjomandi)
- Faculty Research Internal Grant 2014 (The University of Adelaide)
AUD 8,500 for software licenses and specialised coprocessor cards (three investigators)
- Overseas Conference Leave Scheme Travel Award (The University of Adelaide)
- School of Computer Science Research Internal Grant 2013 (The University of Adelaide)
AUD 30,000 for a computing cluster and software licenses (four investigators)
- 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.)
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 100% in 2014, and 4x 100% in 2015.
- 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 three computer science students working on topics related to my ARC grant, and four 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 over 20 courses (six 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.
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.”
The number of courses for which I achieved a 100% broad agreement on whether “Markus Wagner is an effective university teacher” has been increasing steadily from two times in 2013 to four times in 2015.
My fourth-level courses are among the top-rated ones in my School, with the scores being significantly above not only my School’s and Faculty’s averages, but also above the University’s average. My courses are also (anecdotally) among the most popular ones, and they are well attended until the end of the course. Comments like the following show that I am raising the bar: “I am incredibly impressed with the way Evolutionary Computation has been run, and feel that this is the standard that all courses should be held to.”
In my courses I introduce my students to research culture. For example in my fourth-year courses, through challenging but achievable 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. The voluntary work done together with the students after the conclusion of the courses has resulted in three A-ranked conference articles with them, and two of the students are even pursuing their PhD studies at our School now.
I regard clear and timely communication to be a crucial attribute, not only for our graduates, but also for us academics. In my work with students and colleagues, I clearly define the requirements, phrase questions, and provide timely feedback. My colleagues and students appreciate this: “Markus was a great lecturer and course coordinator for this; he would respond to emails in an incredibly timely manner regardless of where he was around the world, and was always helpful and friendly with his responses. He was also always considerate of individual circumstances and was always respectful to students.”
Research Student Supervision
So far, I have supervised or I am supervising four Masters by Coursework students and three PhD students. In addition, I have been supervising two visiting PhD students. In the early stages of their studies, I focus most of my attention on collaboratively designing the projects. Together, we then outline potential approaches and I show them how to narrow down the approach. 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.
I engage not only PhD students but also other students in research at an early stage. With undergraduate and non-Doctoral postgraduate students, I have published a total of six articles so far; five of these are A-ranked. Three of the six were the result of voluntary coursework project extensions. The other three came out of the research conducted with my Masters by Coursework students.
Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2019 Principal Supervisor Innovation of Predictive and Actionable Analytics for Big Data Using Machine Learning Methodologies Doctor of Philosophy Doctorate Full Time Mr Supun Jeevaka Dissanayake 2018 Co-Supervisor Optimisation of Supply Chains 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 2016 Co-Supervisor The Application of Nature-inspired Metaheuristic Methods for Optimizing Wave Energy Converters Doctor of Philosophy Doctorate Full Time Mr Mehdi Neshat
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 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 Mrs Mojgan Pourhassan
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