Mingyu Guo

Mingyu Guo mingyu.guo at adelaide dot edu dot au
4.19 Ingkarni Wardli Building
University of Adelaide, Australia
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News

I will be on special study leave in 2024. I will visit the Foundations of Cooperative AI Lab at Carnegie Mellon University led by Prof. Vincent Conitzer.

About Me

I am a Senior Lecturer and also the Associate Head International of the School of Computer and Mathematical Sciences, University of Adelaide. My main research focus is algorithmic game theory and its application to cyber security. I am also interested in combinatorial optimisation via neural networks and evolutionary computation. Prior to joining the school, I was a Lecturer in the Economics and Computation group at the University of Liverpool, UK. I received my Ph.D. degree in Computer Science from Duke University, USA. My Ph.D. Dissertation was recognised as the runner-up for the Victor Lessor Distinguished Dissertation Award (annual best Ph.D. Dissertation award for the field of multiagent systems worldwide). I hold a M.S. degree in Applied Mathematics from University of Florida, USA and a B.S. degree in Mathematics from Zhejiang University, China.


I have over 20 publications as lead author in CORE A* venues such as AAAI/IJCAI/AAMAS and have served on the senior program committees of all the above conferences. Since 2022, I have led/participated in 8 research projects funded by industry partners including Cybersecurity CRC and DSTG (combined actual/projected income over 1.5 million). I currently supervise 7 active HDR students. My recent Ph.D. graduate Dr. Guanhua Wang (2022) received Dean's Commendation for Doctoral Thesis Excellence.


Over the last 5 years, I teach 5 courses per year on average, mostly on algorithms, programming, and machine learning. My SELT average is 87.3% in the last three years based on Individual Academic Profile. In terms of individual rating, for the question "Is an effective university teacher", my average rating (over 32 SELTs since 2018) is 6.08, which is higher than the average of Computer Science 5.81 and higher than the average of SET 6.03. In terms of course rating, for the question "Overall, I am satisfied with the quality of this course", my average rating (over 22 courses since 2018) is 5.81, which is also higher than the average of Computer Science 5.34 and higher than the average of ECMS 5.60.


In 2022, I am the assessment coordinator, student activity coordinator, academic integrity officer and postgraduate course advisor of our school.

Conference Publications

  1. (CORE A*) Mingyu Guo. Worst-Case VCG Redistribution Mechanism Design Based on the Lottery Ticket Hypothesis. The 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024.
  2. (CORE A*) Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen. Limited Query Graph Connectivity Test. The 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024.
  3. (CORE A*) Huy Q. Ngo, Mingyu Guo, Hung Nguyen. Catch Me If You Can: Effective Honeypot Placement in Dynamic AD Attack Graphs. IEEE International Conference on Computer Communications (INFOCOM), Vancouver, Canada, 2024.
  4. (CORE A) Huy Q. Ngo, Mingyu Guo, Hung Nguyen. Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, Australia, 2024.
  5. (CORE A) Sangwon Hyun, Mingyu Guo, M. Ali Babar. METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities. 17th IEEE International Conference on Software Testing, Verification and Validation (ICST), Toronto, Canada, 2024.
  6. (CORE B) Congbo Ma, Wei Zhang, Hu Wang, Haojie Zhuang, Mingyu Guo. Disentangling Specificity for Abstractive Multi-Document Summarization. International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 2024.
  7. (CORE A*, selected for oral presentation) Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen. Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs. The 37th AAAI Conference on Artificial Intelligence (AAAI), Washington DC, USA, 2023, 2023.
  8. (CORE A*) Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann. Diverse Approximations for Monotone Submodular Maximization Problems With a Matroid Constraint. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023, 19th-25th August 2023, Macao, SAR, China, Pages 5558--5566, 2023.
  9. (CORE A) Diksha Goel, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo. Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023, Pages 1348--1356, 2023.
  10. (CORE A) Aneta Neumann, Sharlotte Gounder, Xiankun Yan, Gregory Sherman, Benjamin Campbell, Mingyu Guo, Frank Neumann. Diversity Optimization for the Detection and Concealment of Spatially Defined Communication Networks. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023, Pages 1436--1444, 2023.
  11. (CORE A) Yumeng Zhang, Max Ward, Mingyu Guo, Hung Nguyen. A Scalable Double Oracle Algorithm for Hardening Large Active Directory Systems. Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, ASIA CCS 2023, Melbourne, VIC, Australia, July 10-14, 2023, Pages 993--1003, 2023.
  12. (Extended Abstract) Huy Q. Ngo, Mingyu Guo, Hung Nguyen. Near Optimal Strategies for Honeypots Placement in Dynamic and Large Active Directory Networks. Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023, London, United Kingdom, 29 May 2023 - 2 June 2023, Pages 2517--2519, 2023.
  13. (CORE A*, selected for oral presentation) Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen. Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs. The 36th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2022, 2022.
  14. (CORE A) Diksha Goel, Max Hector Ward-Graham, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo. Defending Active Directory by Combining Neural Network Based Dynamic Program and Evolutionary Diversity Optimisation. GECCO '22: Genetic and Evolutionary Computation Conference, 2022, 2022.
  15. (CORE A) Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann. Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem. GECCO '22: Genetic and Evolutionary Computation Conference, 2022, 2022.
  16. (CORE B) Masato Ota, Yuko Sakurai, Mingyu Guo, Itsuki Noda. Mitigating Fairness and Efficiency Tradeoff in Vehicle-Dispatch Problems. 20th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2022), 2022.
  17. (CORE B) Congbo Ma, Wei Emma Zhang, Hu Wang, Shubham Gupta, Mingyu Guo. Incorporating Linguistic Knowledge for Abstractive Multi-document Summarization. The 36th annual Meeting of Pacific Asia Conference on Language, Information and Computation (PACLIC 36), 2022.
  18. Nam Trong Dinh, S. Ali Pourmousavi, Sahand Karimi-Arpanahi, Yogesh Pipada Sunil Kumar, Mingyu Guo, Derek Abbott, Jon A. R. Liisberg. Optimal Sizing and Scheduling of Community Battery Storage within a Local Market. The 13th ACM International Conference on Future Energy Systems (e-Energy 2022), 2022.
  19. (CORE B) Diksha Goel, Hong Shen, Hui Tian, Mingyu Guo. Discovering Structural Hole Spanners in Dynamic Networks via Graph Neural Networks. The 21st IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Niagara Falls, Canada, 2022.
  20. (CORE A*) Guanhua Wang, Runqi Guo, Yuko Sakurai, Muhammad Ali Babar, Mingyu Guo. Mechanism Design for Public Projects via Neural Networks. AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, Virtual Event, United Kingdom, May 3-7, 2021, Pages 1380--1388, 2021.
  21. (CORE A, Nominated for Best Paper!) Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann. Analysis of Evolutionary Diversity Optimisation for Permutation Problems. GECCO '21: Genetic and Evolutionary Computation Conference, Lille, France, July 10-14, 2021, Pages 574--582, 2021.
  22. (CORE B) Guanhua Wang, Wuli Zuo, Mingyu Guo. Redistribution in Public Project Problems via Neural Networks. The 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Melbourne, Australia, 2021, 2021.
  23. (CORE B) Diksha Goel, Hong Shen, Hui Tian, Mingyu Guo. Maintenance of Structural Hole Spanners in Dynamic Networks. 46th IEEE Conference on Local Computer Networks, LCN 2021, Edmonton, AB, Canada, October 4-7, 2021, Pages 339--342, 2021.
  24. (CORE B) Guanhua Wang, Mingyu Guo. Public Project With Minimum Expected Release Delay. PRICAI 2021: Trends in Artificial Intelligence - 18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021, Hanoi, Vietnam, November 8-12, 2021, Proceedings, Part I, Volume 13031, Pages 101--112, 2021.
  25. (CORE A*) Mingyu Guo. An Asymptotically Optimal VCG Redistribution Mechanism for the Public Project Problem. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, Pages 315--321, 2019.
  26. (CORE B) Yuko Sakurai, Satoshi Oyama, Mingyu Guo, Makoto Yokoo. Deep False-Name-Proof Auction Mechanisms. PRIMA 2019: Principles and Practice of Multi-Agent Systems - 22nd International Conference, Turin, Italy, October 28-31, 2019, Proceedings, Volume 11873, Pages 594--601, 2019.
  27. (CORE B) Mingyu Guo, Yong Yang, Muhammad Ali Babar. Cost Sharing Security Information With Minimal Release Delay. PRIMA 2018: Principles and Practice of Multi-Agent Systems - 21st International Conference, Tokyo, Japan, October 29 - November 2, 2018, Proceedings, Volume 11224, Pages 177--193, 2018.
  28. Koji Kitagawa, Mingyu Guo, Kiminao Kogiso, Hideaki Hata. Utility Design for Two-player Normal-form Games. 11th Asian Control Conference, ASCC 2017, Gold Coast, Australia, December 17-20, 2017, Pages 2077--2082, 2017.
  29. (CORE A) Hideaki Hata, Mingyu Guo, Muhammad Ali Babar. Understanding the Heterogeneity of Contributors in Bug Bounty Programs. 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2017, Toronto, ON, Canada, November 9-10, 2017, Pages 223--228, 2017.
  30. (CORE B) Mingyu Guo, Hong Shen. Speed up Automated Mechanism Design by Sampling Worst-Case Profiles: An Application to Competitive VCG Redistribution Mechanism for Public Project Problem. PRIMA 2017: Principles and Practice of Multi-Agent Systems - 20th International Conference, Nice, France, October 30 - November 3, 2017, Proceedings, Volume 10621, Pages 127--142, 2017.
  31. (CORE B) Mingyu Guo, Hideaki Hata, Muhammad Ali Babar. Optimizing Affine Maximizer Auctions via Linear Programming: An Application to Revenue Maximizing Mechanism Design for Zero-Day Exploits Markets. PRIMA 2017: Principles and Practice of Multi-Agent Systems - 20th International Conference, Nice, France, October 30 - November 3, 2017, Proceedings, Volume 10621, Pages 280--292, 2017.
  32. Tetsuya Kanda, Mingyu Guo, Hideaki Hata, Ken-ichi Matsumoto. Towards Understanding an Open-source Bounty: Analysis of Bountysource. IEEE 24th International Conference on Software Analysis, Evolution and Reengineering, SANER 2017, Klagenfurt, Austria, February 20-24, 2017, Pages 577--578, 2017.
  33. (CORE B) Mingyu Guo, Yuko Sakurai, Taiki Todo, Makoto Yokoo. Individually Rational Strategy-Proof Social Choice With Exogenous Indifference Sets. PRIMA 2016: Princiles and Practice of Multi-Agent Systems - 19th International Conference, Phuket, Thailand, August 22-26, 2016, Proceedings, Volume 9862, Pages 181--196, 2016.
  34. (CORE B) Mingyu Guo, Hideaki Hata, Muhammad Ali Babar. Revenue Maximizing Markets for Zero-Day Exploits. PRIMA 2016: Princiles and Practice of Multi-Agent Systems - 19th International Conference, Phuket, Thailand, August 22-26, 2016, Proceedings, Volume 9862, Pages 247--260, 2016.
  35. (CORE B) Mingyu Guo. Competitive VCG Redistribution Mechanism for Public Project Problem. PRIMA 2016: Princiles and Practice of Multi-Agent Systems - 19th International Conference, Phuket, Thailand, August 22-26, 2016, Proceedings, Volume 9862, Pages 279--294, 2016.
  36. (CORE A*) Mingyu Guo, Hong Shen, Taiki Todo, Yuko Sakurai, Makoto Yokoo. Social Decision With Minimal Efficiency Loss: An Automated Mechanism Design Approach. Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, May 4-8, 2015, Pages 347--355, 2015.
  37. (Extended Abstract) Atsushi Iwasaki, Etsushi Fujita, Taiki Todo, Hidenao Iwane, Hirokazu Anai, Mingyu Guo, Makoto Yokoo. Parametric Mechanism Design via Quantifier Elimination. Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, May 4-8, 2015, Pages 1885--1886, 2015.
  38. (CORE A*) Mingyu Guo, Argyrios Deligkas, Rahul Savani. Increasing VCG Revenue by Decreasing the Quality of Items. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Qu\'ebec City, Qu\'ebec, Canada, Pages 705--711, 2014.
  39. (CORE A*) Shunsuke Tsuruta, Masaaki Oka, Taiki Todo, Yujiro Kawasaki, Mingyu Guo, Yuko Sakurai, Makoto Yokoo. Optimal False-name-proof Single-item Redistribution Mechanisms. International conference on Autonomous Agents and Multi-Agent Systems, AAMAS '14, Paris, France, May 5-9, 2014, Pages 221--228, 2014.
  40. (CORE A*) Mingyu Guo, Argyrios Deligkas. Revenue Maximization via Hiding Item Attributes. IJCAI 2013, Proceedings of the 23rd International Joint Conference on Artificial Intelligence, Beijing, China, August 3-9, 2013, Pages 157--163, 2013.
  41. (CORE A*) Mingyu Guo. Worst-case Optimal Redistribution of VCG Payments in Heterogeneous-item Auctions With Unit Demand. International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, Valencia, Spain, June 4-8, 2012 (3 Volumes), Pages 745--752, 2012.
  42. Victor Naroditskiy, Mingyu Guo, Lachlan Dufton, Maria Polukarov, Nicholas R. Jennings. Redistribution of VCG Payments in Public Project Problems. Internet and Network Economics - 8th International Workshop, WINE 2012, Liverpool, UK, December 10-12, 2012. Proceedings, Volume 7695, Pages 323--336, 2012.
  43. (CORE A*) Mingyu Guo. VCG Redistribution With Gross Substitutes. Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2011, San Francisco, California, USA, August 7-11, 2011, 2011.
  44. Mingyu Guo, Victor Naroditskiy, Vincent Conitzer, Amy Greenwald, Nicholas R. Jennings. Budget-Balanced and Nearly Efficient Randomized Mechanisms: Public Goods and Beyond. Internet and Network Economics - 7th International Workshop, WINE 2011, Singapore, December 11-14, 2011. Proceedings, Volume 7090, Pages 158--169, 2011.
  45. (CORE A*) Mingyu Guo, Vincent Conitzer. Computationally Feasible Automated Mechanism Design: General Approach and Case Studies. Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2010, Atlanta, Georgia, USA, July 11-15, 2010, 2010.
  46. (CORE A*) Atsushi Iwasaki, Vincent Conitzer, Yoshifusa Omori, Yuko Sakurai, Taiki Todo, Mingyu Guo, Makoto Yokoo. Worst-case Efficiency Ratio in False-name-proof Combinatorial Auction Mechanisms. 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10-14, 2010, Volume 1-3, Pages 633--640, 2010.
  47. (CORE A*) Mingyu Guo, Vincent Conitzer. Strategy-proof Allocation of Multiple Items between Two Agents without Payments or Priors. 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10-14, 2010, Volume 1-3, Pages 881--888, 2010.
  48. (Extended Abstract) Mingyu Guo, Vincent Conitzer. False-name-proofness With Bid Withdrawal. 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10-14, 2010, Volume 1-3, Pages 1475--1476, 2010.
  49. (CORE A*) Mingyu Guo, David M. Pennock. Combinatorial Prediction Markets for Event Hierarchies. 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), Budapest, Hungary, May 10-15, 2009, Volume 1, Pages 201--208, 2009.
  50. Peng Shi, Vincent Conitzer, Mingyu Guo. Prediction Mechanisms That Do Not Incentivize Undesirable Actions. Internet and Network Economics, 5th International Workshop, WINE 2009, Rome, Italy, December 14-18, 2009. Proceedings, Volume 5929, Pages 89--100, 2009.
  51. Mingyu Guo, Vincent Conitzer, Daniel M. Reeves. Competitive Repeated Allocation without Payments. Internet and Network Economics, 5th International Workshop, WINE 2009, Rome, Italy, December 14-18, 2009. Proceedings, Volume 5929, Pages 244--255, 2009.
  52. (CORE A*) Mingyu Guo, Vincent Conitzer. Undominated VCG Redistribution Mechanisms. 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 2, Pages 1039--1046, 2008.
  53. (CORE A*) Mingyu Guo, Vincent Conitzer. Optimal-in-expectation Redistribution Mechanisms. 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 2, Pages 1047--1054, 2008.
  54. (CORE A*) Mingyu Guo, Vincent Conitzer. Better Redistribution With Inefficient Allocation in Multi-unit Auctions With Unit Demand. Proceedings 9th ACM Conference on Electronic Commerce (EC-2008), Chicago, IL, USA, June 8-12, 2008 (this conference is now called ACM Conference on Economics and Computation), Pages 210--219, 2008.
  55. Krzysztof R. Apt, Vincent Conitzer, Mingyu Guo, Evangelos Markakis. Welfare Undominated Groves Mechanisms. Internet and Network Economics, 4th International Workshop, WINE 2008, Shanghai, China, December 17-20, 2008. Proceedings, Volume 5385, Pages 426--437, 2008.
  56. (CORE A*) Mingyu Guo, Vincent Conitzer. Worst-case Optimal Redistribution of VCG Payments. Proceedings 8th ACM Conference on Electronic Commerce (EC-2007), San Diego, California, USA, June 11-15, 2007 (this conference is now called ACM Conference on Economics and Computation), Pages 30--39, 2007.

Journal Publications

  1. (CORE A) Mingyu Guo, Diksha Goel, Guanhua Wang, Runqi Guo, Yuko Sakurai, Muhammad Ali Babar. Mechanism Design for Public Projects via Three Machine Learning Approaches. Autonomous Agents and Multiagent Systems, to appear, 2024.
  2. Diksha Goel, Hong Shen, Hui Tian, Mingyu Guo. Effective Graph-Neural-Network-based Models for Discovering Structrual Hole Spanners in Large-Scale and Diverse Networks. Expert Systems with Applications, to appear, 2024.
  3. Nam Trong Dinh, Sahand Karimi-Arpanahi, S. Ali Pourmousavi, Rui Yuan, Mingyu Guo, Jon A. R. Liisberg, Julian Lemos-Vinascco. Modelling Irrational Behaviour of Residential End Users using Non-Stationary Gaussian Processes. IEEE Transactions on Smart Grid, to appear, 2024.
  4. Nam Trong Dinh, Sahand Karimi-Arpanahi, S. Ali Pourmousavi, Mingyu Guo, Jon A. R. Liisberg. Cost-Effective Community Battery Sizing and Operation Within a Local Market Framework. IEEE Transactions on Energy Markets, Policy and Regulation, Pages 1-13, 2023.
  5. (CORE A*) Congbo Ma, Wei Emma Zhang, Mingyu Guo, Hu Wang, Quan Z. Sheng. Multi-document Summarization via Deep Learning Techniques: A Survey. ACM Comput. Surv., Volume 55, Number 5, Pages 102:1--102:37, 2023.
  6. Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann. Analysis of Evolutionary Diversity Optimization for Permutation Problems. ACM Trans. Evol. Learn. Optim., Volume 2, Number 3, Pages 11:1--11:27, 2022.
  7. (CORE A) Mingyu Guo, Zhenghui Wang, Yuko Sakurai. Gini Index Based Initial Coin Offering Mechanism. Auton. Agents Multi Agent Syst., Volume 36, Number 1, Pages 7, 2022.
  8. (CORE A) Mingyu Guo, Guanhua Wang, Hideaki Hata, Muhammad Ali Babar. Revenue Maximizing Markets for Zero-day Exploits. Auton. Agents Multi Agent Syst., Volume 35, Number 2, Pages 36, 2021.
  9. (CORE A) Mingyu Guo. An Asymptotically Optimal VCG Redistribution Mechanism for the Public Project Problem. Auton. Agents Multi Agent Syst., Volume 35, Number 2, Pages 40, 2021.
  10. Azhar Iqbal, Lachlan J. Gunn, Mingyu Guo, Muhammad Ali Babar, Derek Abbott. Game Theoretical Modelling of Network/Cybersecurity. IEEE Access, Volume 7, Pages 154167--154179, 2019.
  11. (CORE A*) Mingyu Guo, Vincent Conitzer. Better Redistribution With Inefficient Allocation in Multi-unit Auctions. Artif. Intell., Volume 216, Pages 287--308, 2014.
  12. (CORE A) Mingyu Guo, Evangelos Markakis, Krzysztof R. Apt, Vincent Conitzer. Undominated Groves Mechanisms. J. Artif. Intell. Res., Volume 46, Pages 129--163, 2013.
  13. (CORE A*) Mingyu Guo, Vincent Conitzer. Optimal-in-expectation Redistribution Mechanisms. Artif. Intell., Volume 174, Number 5-6, Pages 363--381, 2010.
  14. (ERA-10 A*) Mingyu Guo, Vincent Conitzer. Worst-case Optimal Redistribution of VCG Payments in Multi-unit Auctions. Games Econ. Behav., Volume 67, Number 1, Pages 69--98, 2009.

Higher Degree by Research Students

  1. Jialiang Li, M.Phil. (active), Principal supervisor (with A/Prof. Hung Nguyen), started in 2021. Game-theoretical Cyber Attack Graphs.
  2. Quang Huy Ngo, Ph.D. (active), Co-supervisor (with A/Prof. Hung Nguyen), started in 2022. Abnormality Detection Based on Security Logs.
  3. Viet Anh Do, Ph.D. (active), Co-supervisor (with Prof. Frank Neumann and Dr. Aneta Neumann), started in 2020. Diversity Evolutionary Optimisation.
  4. Xiankun Yan, Ph.D. (active), Co-supervisor (with Prof. Frank Neumann and Dr. Aneta Neumann), started in 2022. Evolutionary Computation.
  5. Gamage Kokila Kasuni Perera, Ph.D. (active), Co-supervisor (with Dr. Aneta Neumann and Prof. Frank Neumann), started in 2022. Evolutionary Computation.
  6. Congbo Ma, Ph.D. (active), Co-supervisor (with Dr. Wei Emma Zhang), started in 2020. Multi-Document Summarization.
  7. Trong Nam Dinh, Ph.D. (active), Co-supervisor (with Dr. Ali Pourmousavi Kani), started in 2021. Stackelberg Game Based Electricity Market.
  8. Faheem Ullah, Ph.D. (completed), Co-supervisor (with Prof. Ali Babar), started in 2017, finished in 2020. Cyber Security Software Architecture. Now continuing Level B Lecturer at University of Adelaide.
  9. Guanhua Wang, Ph.D. (completed), Principal supervisor (with Dr. Wei Emma Zhang), started in 2019, finished in 2022. Neural Network Mechanism Design. Dean's Commendation for Doctoral Thesis Excellence!
  10. Diksha Goel, Ph.D. (completed), Principal supervisor (with Prof. Hong Shen and Dr. Hui Tian), started in 2021, finished in 2023. Graph Theory and Graph Neural Networks. Now postdoctoral researcher in CSIRO.

Professional Services

Research Grants

Other Research Presentations

  1. Defending Active Directory Network by Combining Fixed Parameter Analysis and Machine Learning
    •Global Engagement Webinar, Univeristy of Adelaide 2023
  2. Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs
    •Workshop on AI-based Optimisation (AI-OPT), Melbourne, Australia 2022
  3. Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs
    •International Joint Conference On Theoretical Computer Science – Frontier of Algorithmic Wisdom, City University of Hong Kong, 2022
    •OPTIMA AI-based Optimisation Seminar Series, Australia 2022
  4. Mechanism Design for Public Projects via Neural Networks
    •Cyber, Games and AI Seminar Series, Adelaide, Australia, 2021
    •Australasian Economic Theory Workshop, Adelaide, Australia, 2020
    •Peking University, Beijing, China, 2019
  5. Gini Index based Initial Coin Offering Mechanism
    •Guest Lecture on Blockchain, Peking University, Beijing, China, 2019
  6. Cost Sharing Security Information with Minimal Release Delay
    •University of New South Wales, Sydney, Australia, 2019
  7. Revenue Maximizing Markets for Zero-Day Exploits
    •University of Electro-Communications, Tokyo, Japan, 2017
  8. Competitive Repeated Allocation Without Payments: Carsharing Applications
    •Nara Institute of Technology, Nara, Japan, 2017
    •Sun Yat-Sen University, Guangzhou, China, 2016
  9. Revenue Maximization via Hiding Item Attributes
    •Adam Smith Business School, University of Glasgow, Glasgow, UK, 2013
  10. Computationally Feasible Automated Mechanism Design: General Approach and Case Study on VCG Redistribution Mechanisms
    •Microsoft Research Asia, Beijing, China, 2012
    •Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China, 2012
  11. Better Redistribution with Inefficient Allocation in Multi-Unit Auctions
    •Centrum Wiskunde & Informatica (CWI), Amsterdam, Netherlands, 2011
  12. Computationally Feasible Automated Mechanism Design: General Approach and Case Studies
    •University of Southampton, UK, 2010
  13. Undominated Groves Mechanisms
    •Workshop on Prior-free Mechanism Design, Guanajuato, Mexico, 2010
  14. Optimal VCG Redistribution Mechanisms
    •GAMES 2008 Third World Congress of the Game Theory Society, Evanston, Illinois, USA, 2008
  15. Worst-Case Optimal Redistribution of VCG Payments in Multi-Unit Auctions
    •DIMACS Workshop on the Boundary between Economic Theory and Computer Science, New Jersey, USA, 2007
  16. Improved VCG Redistribution Mechanisms
    •Mini-Workshop on Selected Topics in E-Commerce, North Carolina State University, Raleigh, North Carolina, USA, 2007
    •The 18th International Conference on Game Theory, Stony Brook, NY, USA, 2007

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