Mingyu Guo

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


News

I am 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 research specialisation is algorithmic game theory, which is a subfield of artificial intelligence that studies the interaction (i.e., cooperation and competition) of intelligent agents in multi-agent systems (i.e., I study the game-theoretical foundation of multi-agent team cooperation strategy and design strategic defence for cyber security applications). I am also interested in applying machine learning to solve theoretical economics models (i.e., game-theoretical mechanism design via neural networks) and optimisation (i.e., machine learning assisted combinatorial optimisation).


Prior to joining the school, I was a Lecturer 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 (Chu Kochen Honour College) from Zhejiang University, China.


I have 30+ publications in CORE A*/CCF 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 9 research projects (combined actual/projected income over 1.5 million). I have 5 PhD completions as of 2024 and currently supervise 7 active HDR students (with a few more starting in 2025).

PhD/MPhil Opportunities

Currently, I do not have funding available for international PhD/MPhil students. However, if you are interested, you are welcome to contact me regarding the following opportunities:

My research interests primarily focus on theoretical topics related to algorithmic game theory, algorithms, and optimisation. I am also interested in applications of game theory in areas such as multi-agent reinforcement learning, cybersecurity, electricity markets, blockchain, (decentralized) finance, computer games, AI ethics, large language model (LLM) human alignment, and more.

Project Opportunities for UoA Students

You are welcome to contact me if you are a current University of Adelaide student and are interested in exploring what academic research is like. Over the past several years, I have collaborated with five coursework students on academic papers, including publications in CORE A* conferences.

If we decide to work together, my primary goal will be to produce top-quality publishable research. I believe that aiming for publication is what truly provides a real academic research experience, distinct from coursework-style projects. This ensures that our collaboration remains meaningful and productive for both sides. If you are genuinely interested in trying out research with the goal of producing top-quality publishable work, I would be happy to hear from you.

Selected Publications

  1. (CORE A*) Mingyu Guo. Worst-Case VCG Redistribution Mechanism Design Based on the Lottery Ticket Hypothesis. Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, Canada, Pages 9740--9748, 2024.
  2. (CORE A*) Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung X. Nguyen. Limited Query Graph Connectivity Test. Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, Canada, Pages 20718--20725, 2024.
  3. (CORE A*) Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen. Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs. Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Washington, DC, USA, February 7-14, 2023, Pages 5649--5656, 2023.
  4. (CORE A*) Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen. Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs. Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, February 22 - March 1, 2022, Pages 9360--9367, 2022.
  5. (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.
  6. (CORE A*) Mingyu Guo, Vincent Conitzer. Better Redistribution With Inefficient Allocation in Multi-unit Auctions. Artif. Intell., Volume 216, Pages 287--308, 2014.
  7. (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.
  8. (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, Pages 1676--1679, 2010.
  9. (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.
  10. (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.

Full Publication List

  1. (CORE A*) Mingyu Guo. Worst-Case VCG Redistribution Mechanism Design Based on the Lottery Ticket Hypothesis. Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, Canada, Pages 9740--9748, 2024.
  2. (CORE A*) Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung X. Nguyen. Limited Query Graph Connectivity Test. Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, Canada, Pages 20718--20725, 2024.
  3. (CORE A*) Huy Quang Ngo, Mingyu Guo, Hung X. Nguyen. Catch Me If You Can: Effective Honeypot Placement in Dynamic AD Attack Graphs. IEEE INFOCOM 2024 - IEEE Conference on Computer Communications, Vancouver, BC, Canada, May 20-23, 2024, Pages 451--460, 2024.
  4. (CORE A) Mingyu Guo, Diksha Goel, Guanhua Wang, Runqi Guo, Yuko Sakurai, Muhammad Ali Babar. Mechanism Design for Public Projects via Three Machine Learning Based Approaches. Auton. Agents Multi Agent Syst., Volume 38, Number 1, Pages 16, 2024.
  5. (CORE A) Diksha Goel, Kristen Moore, Mingyu Guo, Derui Wang, Minjune Kim, Seyit Camtepe. Optimizing Cyber Defense in Dynamic Active Directories Through Reinforcement Learning. Computer Security - ESORICS 2024 - 29th European Symposium on Research in Computer Security, Bydgoszcz, Poland, September 16-20, 2024, Proceedings, Part I, Volume 14982, Pages 332--352, 2024.
  6. (CORE A) Huy Quang Ngo, Mingyu Guo, Hung X. Nguyen. Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024, 2024.
  7. (CORE A) Sangwon Hyun, Mingyu Guo, Muhammad Ali Babar. METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities. IEEE Conference on Software Testing, Verification and Validation, ICST 2024, Toronto, ON, Canada, May 27-31, 2024, Pages 117--128, 2024.
  8. (CORE A) Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann. Evolutionary Multi-objective Diversity Optimization. Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV, Volume 15151, Pages 117--134, 2024.
  9. (CORE B) Congbo Ma, Wei Emma Zhang, Hu Wang, Haojie Zhuang, Mingyu Guo. Disentangling Specificity for Abstractive Multi-document Summarization. International Joint Conference on Neural Networks, IJCNN 2024, Yokohama, Japan, June 30 - July 5, 2024, Pages 1--8, 2024.
  10. Goel, Diksha, Ward, Max, Neumann, Aneta, Neumann, Frank, Nguyen, Hung, Guo, Mingyu. Hardening Active Directory Graphs via Evolutionary Diversity Optimization Based Policies. ACM Trans. Evol. Learn. Optim., 2024.
  11. Diksha Goel, Hong Shen, Hui Tian, Mingyu Guo. Effective Graph-neural-network Based Models for Discovering Structural Hole Spanners in Large-scale and Diverse Networks. Expert Syst. Appl., Volume 249, Pages 123636, 2024.
  12. Nam Trong Dinh, Sahand Karimi-Arpanahi, Rui Yuan, S. Ali Pourmousavi, Mingyu Guo, Jon A. R. Liisberg, Juli\'an Lemos-Vinasco. Modeling Irrational Behavior of Residential End Users Using Non-Stationary Gaussian Processes. IEEE Trans. Smart Grid, Volume 15, Number 5, Pages 4636--4648, 2024.
  13. (CORE A*) Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen. Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs. Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Washington, DC, USA, February 7-14, 2023, Pages 5649--5656, 2023.
  14. (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.
  15. (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.
  16. (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.
  17. (CORE A*, extended abstract) Huy Quang 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.
  18. (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.
  19. (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.
  20. Dinh, Nam Trong, Karimi-Arpanahi, Sahand, Pourmousavi, S. Ali, Guo, Mingyu, Liisberg, Jon Anders Reichert. Cost-Effective Community Battery Sizing and Operation Within a Local Market Framework. IEEE Transactions on Energy Markets, Policy and Regulation, Volume 1, Number 4, Pages 536-548, 2023.
  21. (CORE A*) Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen. Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs. Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, February 22 - March 1, 2022, Pages 9360--9367, 2022.
  22. (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.
  23. (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, Boston, Massachusetts, USA, July 9 - 13, 2022, Pages 684--693, 2022.
  24. (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, Boston, Massachusetts, USA, July 9 - 13, 2022, Pages 1191--1199, 2022.
  25. (CORE B) Masato Ota, Yuko Sakurai, Mingyu Guo, Itsuki Noda. Mitigating Fairness and Efficiency Tradeoff in Vehicle-Dispatch Problems. Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection - 20th International Conference, PAAMS 2022, L'Aquila, Italy, July 13-15, 2022, Proceedings, Volume 13616, Pages 307--319, 2022.
  26. (CORE B) Congbo Ma, Wei Emma Zhang, Hu Wang, Shubham Gupta, Mingyu Guo. Incorporating Linguistic Knowledge for Abstractive Multi-document Summarization. Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation, PACLIC 2022, Manila, Philippines, October 20-22, 2022, Pages 147--156, 2022.
  27. (CORE B) Diksha Goel, Hong Shen, Hui Tian, Mingyu Guo. Discovering Structural Hole Spanners in Dynamic Networks via Graph Neural Networks. IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2022, Niagara Falls, ON, Canada, November 17-20, 2022, Pages 64--71, 2022.
  28. 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.
  29. 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. e-Energy '22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022 - 1 July 2022, Pages 34--46, 2022.
  30. (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.
  31. (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.
  32. (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.
  33. (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.
  34. (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.
  35. (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.
  36. (CORE B) Guanhua Wang, Wuli Zuo, Mingyu Guo. Redistribution in Public Project Problems via Neural Networks. WI-IAT '21: IEEE/WIC/ACM International Conference on Web Intelligence, Melbourne VIC Australia, December 14 - 17, 2021, Pages 406--413, 2021.
  37. (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.
  38. (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.
  39. 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.
  40. (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.
  41. (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.
  42. (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.
  43. (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.
  44. 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.
  45. 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.
  46. (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.
  47. (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.
  48. (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.
  49. (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.
  50. (CORE A*, 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.
  51. (CORE A*) Mingyu Guo, Vincent Conitzer. Better Redistribution With Inefficient Allocation in Multi-unit Auctions. Artif. Intell., Volume 216, Pages 287--308, 2014.
  52. (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.
  53. (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.
  54. (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.
  55. (CORE A) Mingyu Guo, Evangelos Markakis, Krzysztof R. Apt, Vincent Conitzer. Undominated Groves Mechanisms. J. Artif. Intell. Res., Volume 46, Pages 129--163, 2013.
  56. (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.
  57. (CCF-A) 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.
  58. (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, Pages 675--680, 2011.
  59. (CCF-A) 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.
  60. (Ph.D. dissertation) Mingyu Guo. Computationally Feasible Approaches to Automated Mechanism Design (runner-up for the Victor Lessor Distinguished Dissertation Award -- Annual Best Ph.D. Dissertation Award for the Field of Multiagent Systems Worldwide). Duke University, Durham, NC, USA, 2010.
  61. (CORE A*) Mingyu Guo, Vincent Conitzer. Optimal-in-expectation Redistribution Mechanisms. Artif. Intell., Volume 174, Number 5-6, Pages 363--381, 2010.
  62. (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, Pages 1676--1679, 2010.
  63. (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.
  64. (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.
  65. (CORE A*, 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.
  66. (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.
  67. (CORE A*) Mingyu Guo, David M. Pennock. Combinatorial Prediction Markets for Event Hierarchies. 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), Budapest, Hungary, May 10-15, 2009, Volume 1, Pages 201--208, 2009.
  68. (CCF-A) 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.
  69. (CCF-A) 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.
  70. (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.
  71. (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.
  72. (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.
  73. (CCF-A) 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.
  74. (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.

Higher Degree by Research Students

  1. Grant Cameron Douglas, Ph.D. (active), Principal supervisor (with Stephen Franklin@Saab), started in 2024. Drone swarm behaviours and counter strategies.
  2. Jialiang Li, M.Phil. (active), Principal supervisor (with A/Prof. Hung Nguyen), started in 2021. Combinatorial optimisation via neural networks.
  3. Liam Wigney, Ph.D. (active), Co-supervisor (with Prof. Frank Neumann), started in 2024. Search algorithms for space and energy.
  4. Quang Huy Ngo, Ph.D. (active), Co-supervisor (with A/Prof. Hung Nguyen), started in 2022. Game-theoretical cyber defence graph optimisation.
  5. Xiankun Yan, Ph.D. (active), Co-supervisor (with Prof. Frank Neumann and Dr. Aneta Neumann), started in 2022. Complexity with chance constraints.
  6. Gamage Kokila Kasuni Perera, Ph.D. (active), Co-supervisor (with Dr. Aneta Neumann and Prof. Frank Neumann), started in 2022. Evolutionary computation with chance constraints.
  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 research scientist in CSIRO.
  11. Viet Anh Do, Ph.D. (completed), Co-supervisor (with Prof. Frank Neumann and Dr. Aneta Neumann), started in 2020, finished in 2024. Diversity Evolutionary Optimisation.
  12. Congbo Ma, Ph.D. (completed), Co-supervisor (with Dr. Wei Emma Zhang), started in 2020, finished in 2024. Multi-Document Summarization.

Professional Services

Research Grants

Other Research Presentations

  1. Worst-Case VCG Redistribution Mechanism Design Based on the Lottery Ticket Hypothesis
    •Harvard EconCS Seminar 2024
    •Rutgers University Computer Science Colloquium 2024
    •Google DeepMind 2024
    •Oxford Algorithmic Game Theory Seminar 2024
    •Bath University Algorithm Seminar 2024
    •Carnegie Mellon University Foundation of Cooperative AI Lab Seminar 2024
  2. Defending Active Directory Network by Combining Fixed Parameter Analysis and Machine Learning
    •Global Engagement Webinar, Univeristy of Adelaide 2023
  3. Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs
    •Workshop on AI-based Optimisation (AI-OPT), Melbourne, Australia 2022
  4. 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
  5. 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
  6. Gini Index based Initial Coin Offering Mechanism
    •Guest Lecture on Blockchain, Peking University, Beijing, China, 2019
  7. Cost Sharing Security Information with Minimal Release Delay
    •University of New South Wales, Sydney, Australia, 2019
  8. Revenue Maximizing Markets for Zero-Day Exploits
    •University of Electro-Communications, Tokyo, Japan, 2017
  9. Competitive Repeated Allocation Without Payments: Carsharing Applications
    •Nara Institute of Technology, Nara, Japan, 2017
    •Sun Yat-Sen University, Guangzhou, China, 2016
  10. Revenue Maximization via Hiding Item Attributes
    •Adam Smith Business School, University of Glasgow, Glasgow, UK, 2013
  11. 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
  12. Better Redistribution with Inefficient Allocation in Multi-Unit Auctions
    •Centrum Wiskunde & Informatica (CWI), Amsterdam, Netherlands, 2011
  13. Computationally Feasible Automated Mechanism Design: General Approach and Case Studies
    •University of Southampton, UK, 2010
  14. Undominated Groves Mechanisms
    •Workshop on Prior-free Mechanism Design, Guanajuato, Mexico, 2010
  15. Optimal VCG Redistribution Mechanisms
    •GAMES 2008 Third World Congress of the Game Theory Society, Evanston, Illinois, USA, 2008
  16. 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
  17. 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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