Dr Mingyu Guo

• Journals

  Year	Citation
  2024	Guo, M., Li, J., Neumann, A., Neumann, F., & Hung, N. (2024). Limited Query Graph Connectivity Test. THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 18, abs/2302.13036, 20718-20725.
  2024	Dinh, N. T., Karimi-Arpanahi, S., Pourmousavi, S. A., Yuan, R., Guo, M., Liisberg, J. A. R., & Lemos-Vinascco, J. (2024). Modelling Irrational Behaviour of Residential End Users using Non-Stationary Gaussian Processes. IEEE Transactions on Smart Grid, 15(5), 4636-4648. DOI
  2024	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2024). Evolutionary Multi-Objective Diversity Optimization.. CoRR, abs/2401.07454.
  2024	Goel, D., Shen, H., Tian, H., & Guo, M. (2024). Effective graph-neural-network based models for discovering Structural Hole Spanners in large-scale and diverse networks. Expert Systems with Applications, 249, 16 pages. DOI
  2024	Guo, M., Goel, D., Wang, G., Guo, R., Sakurai, Y., & Babar, M. A. (2024). Mechanism design for public projects via three machine learning based approaches. Autonomous Agents and Multi-Agent Systems, 38(1), 30 pages. DOI
  2023	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2023). Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint. IJCAI International Joint Conference on Artificial Intelligence, 2023-August, 5558-5566. Scopus1
  2023	Dinh, N. T., Karimi-Arpanahi, S., Pourmousavi, S. A., Guo, M., Lemos-Vinasco, J., & Liisberg, J. A. R. (2023). On the Financial Consequences of Simplified Battery Sizing Models without Considering Operational Details.. CoRR, abs/2310.02494.
  2023	Guo, M., Ward, M., Neumann, A., Neumann, F., & Nguyen, H. (2023). Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs. Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023, 37(5), 5649-5656. DOI Scopus6
  2023	Dinh, N. T., Karimi-Arpanahi, S., Pourmousavi, S. A., Guo, M., & Liisberg, J. A. R. (2023). Cost-Effective Community Battery Sizing and Operation Within a Local Market Framework. IEEE Transactions on Energy Markets, Policy, and Regulation, 1(4), 536-548. DOI
  2023	Guo, M., Ward, M., Neumann, A., Neumann, F., & Hung, N. (2023). Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs. THIRTY-SEVENTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 37 NO 5, abs/2212.04326, 5649-5656.
  2023	Ma, C., Zhang, W. E., Guo, M., Wang, H., & Sheng, Q. Z. (2023). Multi-document Summarization via Deep Learning Techniques: A Survey. ACM COMPUTING SURVEYS, 55(5), 37 pages. DOI Scopus45 WoS15
  2023	Goel, D., Shen, H., Tian, H., & Guo, M. (2023). Effective Graph-Neural-Network based Models for Discovering Structural Hole Spanners in Large-Scale and Diverse Networks. CoRR, abs/2302.12442. DOI
  2023	Goel, D., Shen, H., Tian, H., & Guo, M. (2023). Discovering Top-k Structural Hole Spanners in Dynamic Networks. CoRR, abs/2302.13292. DOI
  2023	Guo, M. (2023). Worst-Case VCG Redistribution Mechanism Design Based on the Lottery Ticket Hypothesis. CoRR, abs/2305.11011. DOI
  2023	Guo, M., Goel, D., Wang, G., Yang, Y., & Babar, M. A. (2023). Cost Sharing Public Project with Minimum Release Delay. CoRR, abs/2305.11657. DOI
  2022	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Analysis of Evolutionary Diversity Optimisation for Permutation Problems. ACM Transactions on Evolutionary Learning and Optimization, 2(3), 1-27. DOI Scopus9
  2022	Guo, M., Wang, Z., & Sakurai, Y. (2022). Gini index based initial coin offering mechanism. Autonomous Agents and Multi-Agent Systems, 36(1), 1-20. DOI Scopus2 WoS1
  2022	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Analysis of Evolutionary Diversity Optimization for Permutation Problems.. ACM Trans. Evol. Learn. Optim., 2, 11:1.
  2022	Wang, G., Zuo, W., & Guo, M. (2022). Redistribution in Public Project Problems via Neural Networks. CoRR, abs/2203.05778. DOI
  2022	Goel, D., Shen, H., Tian, H., & Guo, M. (2022). Discovering Structural Hole Spanners in Dynamic Networks via Graph Neural Networks. CoRR, abs/2212.08239. DOI
  2022	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem.. CoRR, abs/2201.10316.
  2021	Ma, C., Zhang, W. E., Wang, H., Gupta, S., & Guo, M. (2021). Dependency Structure for News Document Summarization. CoRR, abs/2109.11199.
  2021	Guo, M., Li, J., Neumann, A., Neumann, F., & Nguyen, H. (2021). Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs.. CoRR, abs/2112.13175.
  2021	Sun, R., Xue, M., Tyson, G., Dong, T., Li, S., Wang, S., . . . Nepal, S. (2021). Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors.
  2021	Guo, M., Wang, G., Hata, H., & Babar, M. A. (2021). Revenue maximizing markets for zero-day exploits. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 35(2), 15 pages. DOI Scopus7 WoS1
  2021	Guo, M. (2021). An asymptotically optimal VCG redistribution mechanism for the public project problem. Autonomous Agents and Multi-Agent Systems, 35(2), 1-27. DOI Scopus1
  2021	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2021). Analysis of Evolutionary Diversity Optimisation for Permutation Problems.. CoRR, abs/2102.11469.
  2020	Guo, M., Wang, Z., & Sakurai, Y. (2020). Gini Index based Initial Coin Offering Mechanism. CoRR, abs/2002.11387.
  2020	Ma, C., Zhang, W. E., Guo, M., Wang, H., & Sheng, Q. Z. (2020). Multi-document Summarization via Deep Learning Techniques: A Survey. CoRR, abs/2011.04843.
  2019	Iqbal, A., Gunn, L. J., Guo, M., Babar, M. A., & Abbott, D. (2019). Game theoretical modelling of network/cybersecurity. IEEE Access, 7, 154167-154179. DOI Scopus12 WoS9
  2014	Guo, M., & Conitzer, V. (2014). Better redistribution with inefficient allocation in multi-unit auctions. Artificial Intelligence, 216, 287-308. DOI Scopus12
  2013	Guo, M., Markakis, E., Apt, K., & Conitzer, V. (2013). Undominated Groves mechanisms. Journal of Artificial Intelligence Research, 46, 129-163. DOI Scopus20
  2013	Guo, M., & Deligkas, A. (2013). Revenue Maximization via Hiding Item Attributes. CoRR, abs/1302.5332.
  2012	Guo, M., Markakis, E., Apt, K. R., & Conitzer, V. (2012). Undominated Groves Mechanisms. CoRR, abs/1203.1809.
  2010	Guo, M., & Conitzer, V. (2010). Optimal-in-expectation redistribution mechanisms. Artificial Intelligence, 174(5-6), 363-381. DOI Scopus26
  2009	Guo, M., & Conitzer, V. (2009). Worst-case optimal redistribution of VCG payments in multi-unit auctions. Games and Economic Behavior, 67(1), 69-98. DOI Scopus76
  2008	Apt, K. R., Conitzer, V., Guo, M., & Markakis, E. (2008). Welfare Undominated Groves Mechanisms. CoRR, abs/0810.2865.
  -	Goel, D., Ward, M., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (n.d.). Hardening Active Directory Graphs via Evolutionary Diversity Optimization based Policies. ACM Transactions on Evolutionary Learning and Optimization. DOI

• Conference Papers

  Year	Citation
  2024	Ngo, H. Q., Guo, M., & Nguyen, H. (2024). Catch Me if You Can: Effective Honeypot Placement in Dynamic AD Attack Graphs. In Proceedings - IEEE INFOCOM (pp. 451-460). IEEE. DOI
  2024	Guo, M., Li, J., Neumann, A., Neumann, F., & Nguyen, H. (2024). Limited Query Graph Connectivity Test. In M. J. Wooldridge, J. G. Dy, & S. Natarajan (Eds.), Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 20718-20725). Online: Association for the Advancement of Artificial Intelligence (AAAI). DOI
  2024	Guo, M. (2024). Worst-Case VCG Redistribution Mechanism Design Based on the Lottery Ticket Hypothesis. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 9740-9748). Online: Association for the Advancement of Artificial Intelligence (AAAI). DOI
  2024	Ngo, H., Guo, M., & Nguyen, H. (2024). Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys. In Proceedings of the Genetic and Evolutionary Computation Conference. Online: ACM. DOI
  2023	Goel, D., Shen, H., Tian, H., & Guo, M. (2023). Discovering Structural Hole Spanners in Dynamic Networks via Graph Neural Networks. In Proceedings - 2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2022 (pp. 64-71). Online: IEEE. DOI Scopus1
  2023	Goel, D., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (2023). Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '23) (pp. 1348-1356). New York, NY: Association for Computing Machinery. DOI Scopus2
  2023	Neumann, A., Gounder, S., Yan, X., Sherman, G., Campbell, B., Guo, M., & Neumann, F. (2023). Diversity Optimization for the Detection and Concealment of Spatially Defined Communication Networks. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '23) (pp. 1436-1444). New York, NY: Association for Computing Machinery. DOI Scopus3
  2023	Zhang, Y., Ward, M., Guo, M., & Nguyen, H. (2023). A Scalable Double Oracle Algorithm for Hardening Large Active Directory Systems. In Proceedings of the 18th ACM Asia Conference on Computer and Communications Security (ACM ASIACCS, 2023) (pp. 993-1003). Melbourne Victoria, Australia: Association for Computing Machinery. DOI Scopus4
  2023	Ngo, H. Q., Guo, M., & Nguyen, H. (2023). Near Optimal Strategies for Honeypots Placement in Dynamic and Large Active Directory Networks. In N. Agmon, B. An, A. Ricci, & W. Yeoh (Eds.), Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023, London, United Kingdom, 29 May 2023 - 2 June 2023 Vol. 2023-May (pp. 2517-2519). ACM. DOI Scopus4
  2022	Goel, D., Ward-Graham, M. H., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (2022). Defending active directory by combining neural network based dynamic program and evolutionary diversity optimisation. In J. E. Fieldsend, & M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22) Vol. abs/2204.03397 (pp. 1191-1199). New York, NY: Association for Computing Machinery. DOI Scopus7 WoS2
  2022	Dinh, N. T., Pourmousavi, S. A., Karimi-Arpanahi, S., Kumar, Y. P. S., Guo, M., Abbott, D., & Liisberg, J. A. R. (2022). Optimal sizing and scheduling of community battery storage within a local market. In e-Energy 2022 - Proceedings of the 2022 13th ACM International Conference on Future Energy Systems (pp. 34-46). Online: ACM. DOI Scopus5 WoS2
  2022	Ota, M., Sakurai, Y., Guo, M., & Noda, I. (2022). Mitigating Fairness and Efficiency Tradeoff in Vehicle-Dispatch Problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13616 LNAI (pp. 307-319). Online: Springer International Publishing. DOI
  2022	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Niching-based evolutionary diversity optimization for the traveling salesperson problem. In J. E. Fieldsend, & M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22) (pp. 684-693). Online: Association for Computing Machinery. DOI Scopus1
  2022	Guo, M., Li, J., Neumann, A., Neumann, F., & Nguyen, H. (2022). Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-2022) Vol. 36 (pp. 9360-9367). virtual online: AAAI Press. DOI Scopus11 WoS2
  2022	Ma, C., Zhang, W. E., Wang, H., Gupta, S., & Guo, M. (2022). Incorporating Linguistic Knowledge for Abstractive Multi-document Summarization. In S. Dita, A. O. Trillanes, & R. I. Lucas (Eds.), Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation, PACLIC 2022 (pp. 147-156). Online: De La Salle University.
  2021	Wang, G., & Guo, M. (2021). Public Project with Minimum Expected Release Delay. In 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 Vol. 13031 LNAI (pp. 101-112). Switzerland: Springer International Publishing. DOI Scopus1
  2021	Wang, G., Zuo, W., & Guo, M. (2021). Redistribution in Public Project Problems via Neural Networks. In WI-IAT '21: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (pp. 406-413). New York, NY, United States: Association for Computing Machinery. DOI Scopus2
  2021	Wang, G., Guo, R., Sakurai, Y., Babar, M. A., & Guo, M. (2021). Mechanism design for public projects via neural networks. In Proceedings of the 20th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021) Vol. 3 (pp. 1380-1388). Richland, SC, United States: International Foundation for Autonomous Agents and Multiagent Systems. DOI Scopus4
  2021	Goel, D., Shen, H., Tian, H., & Guo, M. (2021). Maintenance of Structural Hole Spanners in Dynamic Networks. In 2021 IEEE 46th Conference on Local Computer Networks (LCN) Vol. 2021-October (pp. 339-342). online: IEEE. DOI Scopus2 WoS1
  2021	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2021). Analysis of Evolutionary Diversity Optimization for Permutation Problems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2021) (pp. 574-582). New York, NY, United States: Association for Computing Machinery. DOI Scopus16
  2019	Guo, M. (2019). An asymptotically optimal VCG redistribution mechanism for the public project problem. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2019-August (pp. 315-321). online: IJCAI Organization. DOI Scopus3
  2019	Sakurai, Y., Oyama, S., Guo, M., & Yokoo, M. (2019). Deep False-Name-Proof Auction Mechanisms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11873 LNAI (pp. 594-601). Switzerland: Springer. DOI Scopus2
  2018	Kitagawa, K., Guo, M., Kogiso, K., & Hata, H. (2018). Utility design for two-player normal-form games. In 2017 Asian Control Conference, ASCC 2017 Vol. 2018-January (pp. 2077-2082). online: IEEE. DOI
  2018	Guo, M., Yang, Y., & Babar, M. A. (2018). Cost sharing security information with minimal release delay. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11224 LNAI (pp. 177-193). Switzerland: Springer Nature. DOI Scopus3
  2017	Kanda, T., Guo, M., Hata, H., & Matsumoto, K. (2017). Towards understanding an open-source bounty: Analysis of Bountysource. In SANER 2017 - 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (pp. 577-578). Klagenfurt, Austria: Institute of Electrical and Electronics Engineers (IEEE). DOI Scopus8
  2017	Guo, M., & Shen, H. (2017). Speed up Automated Mechanism Design by Sampling Worst-Case Profiles: An Application to Competitive VCG Redistribution Mechanism for Public Project Problem. In Proceedings of the 20th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2017) as published in Lecture Notes in Computer Science Vol. 10621 (pp. 127-142). Switzerland: Springer. DOI Scopus4 WoS3
  2017	Guo, M., Hata, H., & Babar, A. (2017). Optimizing Affine Maximizer Auctions via Linear Programming: An Application to Revenue Maximizing Mechanism Design for Zero-Day Exploits Markets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10621 LNAI (pp. 280-292). Switzerland: Springer Nature. DOI Scopus3
  2017	Hata, H., Guo, M., & Babar, M. (2017). Understanding the Heterogeneity of Contributors in Bug Bounty Programs. In International Symposium on Empirical Software Engineering and Measurement Vol. 2017-November (pp. 223-228). Toronto, CANADA: IEEE. DOI Scopus25 WoS16
  2016	Guo, M. (2016). Competitive VCG redistribution mechanism for public project problem. In Proceedings of the 19th International Conference on Principles and Practice of Multi-Agent Systems: PRIMA 2016 Vol. 9862 LNCS (pp. 279-294). Phuket, Thailand: Springer International Publishing. DOI Scopus6
  2016	Guo, M., Sakurai, Y., Todo, T., & Yokoo, M. (2016). Individually rational strategy-proof social choice with exogenous indifference sets. In Proceeding of the 19th International Conference International Conference on Principles and Practice of Multi-Agent Systems: PRIMA 2016 Vol. 9862 LNCS (pp. 181-196). Phuket, Thailand: Springer International Publishing. DOI
  2016	Guo, M., Hata, H., & Babar, A. (2016). Revenue maximizing markets for zero-day exploits. In Proceedings of the 19th International Conference on Principles and Practice of Multi-Agent Systems: PRIMA 2016 Vol. 9862 LNCS (pp. 247-260). Phuket, Thailand: Springer International Publishing. DOI Scopus5
  2015	Guo, M., Shen, H., Todo, T., Sakurai, Y., & Yokoo, M. (2015). Social decision with minimal efficiency loss: An automated mechanism design approach. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems Vol. 1 (pp. 347-355). Istanbul, Turkey: ACM. Scopus3 WoS3
  2015	Iwasaki, A., Fujita, E., Todo, T., Iwane, H., Anai, H., Guo, M., & Yokoo, M. (2015). Parametric mechanism design via quantifier elimination. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems Vol. 3 (pp. 1885-1886). Istanbul, Turkey: IFAAMS.
  2014	Guo, M., Deligkas, A., & Savani, R. (2014). Increasing VCG revenue by decreasing the quality of items. In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence Vol. 1 (pp. 705-711). online: AAAI. Scopus2
  2014	Tsuruta, S., Oka, M., Todo, T., Kawasaki, Y., Guo, M., Sakurai, Y., & Yokoo, M. (2014). Optimal false-name-proof single-item redistribution mechanisms. In Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems Vol. 1 (pp. 221-228). Paris, France: International Foundation for Autonomous Agents and Multiagent Systems. Scopus4
  2013	Guo, M., & Deligkas, A. (2013). Revenue maximization via hiding item attributes. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 13) (pp. 157-163). California; USA: AAAI Press. Scopus20
  2012	Guo, M. (2012). Worst-case optimal redistribution of VCG payments in heterogeneous-item auctions with unit demand. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (pp. 745-752). UK: International Foundation for Autonomous Agents and Multiagent Systems.
  2012	Naroditskiy, V., Guo, M., Dufton, L., Polukarov, M., & Jennings, N. (2012). Redistribution of VCG payments in public project problems. In P. Goldberg (Ed.), Internet and Network Economics: Proceedings of 8th International Workshop, WINE 2012, Liverpool, UK, December 10-12, 2012. Vol. 7695 LNCS (pp. 323-336). UK: Springer. DOI Scopus11
  2012	Guo, M. (2012). Worst-case optimal redistribution of VCG payments in heterogeneous-item auctions with unit demand. In 11th International Conference on Autonomous Agents and Multiagent Systems 2012, AAMAS 2012: Innovative Applications Track Vol. 2 (pp. 1016-1023). Scopus9
  2011	Guo, M., Naroditskiy, V., Conitzer, V., Greenwald, A., & Jennings, N. (2011). Budget-balanced and nearly efficient randomized mechanisms: public goods and beyond. In N. Chen, E. Elkind, & E. Koutsoupias (Eds.), Internet and Network Economics: Proceedings of 7th International Workshop, WINE 2011, Singapore, December 11-14, 2011 Vol. 7090 LNCS (pp. 158-169). UK: Springer. DOI Scopus15
  2011	Guo, M. (2011). VCG redistribution with gross substitutes. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence Vol. 1 (pp. 675-680). Menlo Park, California: AAAI Press. Scopus10
  2010	Guo, M., & Conitzer, V. (2010). False-name proofness with Bid Withdrawal. In W. van der Hoek, G. Kaminka, Y. Lesperance, M. Luck, & S. Sen (Eds.), AAMAS2010 Toronto - The 9th International Conference on Autonomous Agents and Multiagent Systems May 10-14, 2010, Toronto Canada Conference Proceedings Volume1 (pp. 1475-1476). USA: IFAAMAS.
  2010	Iwasaki, A., Conitzer, V., Omori, Y., Sakurai, Y., Todo, T., Guo, M., & Yokoo, M. (2010). Worst-case efficiency ratio in false-name-proof combinatorial auction mechanisms. In W. van der Hoek, G. Kaminka, Y. Lesperance, M. Luck, & S. Sen (Eds.), AAMAS 2010 - The 9th International Conference on Autonomous Agents and Multiagent Systems May 10-14, 2010, Toronto Canada, Conference Proceedings, vol. 1 Vol. 2 (pp. 633-640). USA: International Foundation for Autonomous Agents and Multiagent Systems. Scopus29
  2010	Guo, M., & Conitzer, V. (2010). Strategy-proof allocation of multiple items between two agents without payments or priors. In W. van der Hoek, G. Kaminka, Y. Lesperance, M. Luck, & S. Sen (Eds.), AAMAS 2010 - The 9th International Conference on Autonomous Agents and Multiagent Systems May 10-14, 2010, Toronto Canada, Conference Proceedings, vol. 1 Vol. 2 (pp. 881-888). USA: International Foundation for Autonomous Agents and Multiagent Systems. Scopus41
  2010	Guo, M., & Conitzer, V. (2010). Computationally feasible automated mechanism design: general approach and case studies. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10) Vol. 3 (pp. 1676-1679). California; USA: AAAI. Scopus30
  2010	Guo, M., & Conitzer, V. (2010). False-name-proofness with bid withdrawal. In W. V. D. Hoek, G. A. Kaminka, Y. Lespérance, M. Luck, & S. Sen (Eds.), 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10-14, 2010, Volume 1-3 (pp. 1475-1476). IFAAMAS.
  2009	Guo, M., & Pennock, D. (2009). Combinatorial prediction markets for event hierarchies. In AAMAS '09 8th International Conference on Autonomous Agents and Multi Agent Systems Budapest, Hungary, May 10 - 15, 2009 (pp. 201-208). South Carolina, USA: International Foundation for Autonomous Agents and Multiagent Systems.
  2009	Shi, P., Conitzer, V., & Guo, M. (2009). Prediction mechanisms that do not incentivize undesirable actions. In Stefano Leonardi (Ed.), Internet and Network Economics: 5th International Workshop, WINE 2009, Rome, Italy, December 14-18, 2009, Proceedings Vol. 5929 LNCS (pp. 89-100). Berlin, Germany: Springer. DOI Scopus22
  2009	Guo, M., Conitzer, V., & Reeves, D. (2009). Competitive repeated allocation without payments. In Stefano Leonardi (Ed.), Internet and Network EconomicsL: 5th International Workshop, WINE 2009, Rome, Italy, December 14-18, 2009, Proceedings (pp. 244-255). Berlin, Germany: Springer. DOI
  2009	Guo, M., & Pennock, D. M. (2009). Markets for event hierarchies combinatorial prediction. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 1 (pp. 173-180).
  2009	Guo, M., Conitzer, V., & Reeves, D. M. (2009). Competitive repeated allocation without payments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5929 LNCS (pp. 244-255). Springer Berlin Heidelberg. DOI Scopus25
  2008	Guo, M., & Conitzer, V. (2008). Undominated VCG redistribution mechanisms. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 1021-1028). Scopus25
  2008	Guo, M., & Conitzer, V. (2008). Optimal-in-expectation redistribution mechanisms. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 1029-1036). Scopus19
  2008	Guo, M., & Conitzer, V. (2008). Optical-in-Expectation redistribution mechanisms. In L. Padgham, D. Parkes, J. Muller, & S. Parsons (Eds.), The Seventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS-08), Estoril, Portugal - Proceedings Volume 1 (pp. 1047-1054). Online: Autonomous Agents and Multiagent Systems.
  2008	Guo, M., & Conitzer, V. (2008). Undominated VCG redistribution mechanisms. In L. Padgham, D. Parkes, J. Muller, & S. Parsons (Eds.), The Seventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS-08), Estoril, Portugal - Proceedings Volume 1 (pp. 1039-1046). Online: Autonomous Agents and Multiagent Systems.
  2008	Guo, M., & Conitzer, V. (2008). Better redistribution with inefficient allocation in multi-unit auctions with unit demand. In EC '08 Proceedings of the 9th ACM Conference on Electronic Commerce (pp. 210-219). USA: Association for Computing Machinery. DOI Scopus27
  2008	Apt, K., Conitzer, V., Guo, M., & Markakis, E. (2008). Welfare undominated Groves mechanisms. In C. Papadimitriou, & S. Zhang (Eds.), Internet and Network Economics: 4th InternationalWorkshop, WINE 2008, Shanghai, China, December 17-20, 2008. Proceedings Vol. 5385 LNCS (pp. 426-437). Berlin, Germany: Springer. DOI Scopus21
  2007	Guo, M., & Conitzer, V. (2007). Worst-case optimal redistribution of VCG payments. In EC'07 - Proceedings of the Eighth Annual Conference on Electronic Commerce (pp. 30-39). ACM. DOI Scopus34

• Conference Items

  Year	Citation
  2022	Goel, D., Ward-Graham, M. H., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (2022). Defending active directory by combining neural network based dynamic program and evolutionary diversity optimisation.. Poster session presented at the meeting of GECCO. ACM.

• Theses

  Year	Citation
  2010	Guo, M. (2010). Computationally Feasible Approaches to Automated Mechanism Design. (PhD Thesis).

• Internet Publications

  Year	Citation
  2019	Iqbal, A., Guo, M., Gunn, L., Babar, M., & Abbott, D. (2019). Game theoretical modelling of network/cyber security [Review paper]. ArXiv.org.

• Preprint

  Year	Citation
  2024	Ngo, H. Q., Guo, M., & Nguyen, H. (2024). Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys.
  2024	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2024). Evolutionary Multi-Objective Diversity Optimization.
  2023	Guo, M., Li, J., Neumann, A., Neumann, F., & Nguyen, H. (2023). Limited Query Graph Connectivity Test.
  2023	Dinh, N. T., Karimi-Arpanahi, S., Pourmousavi, S. A., Yuan, R., Guo, M., Liisberg, J. A. R., & Lemos-Vinascco, J. (2023). Modelling Irrational Behaviour of Residential End Users using Non-Stationary Gaussian Processes..
  2023	Goel, D., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (2023). Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems..

2014 S1: Scientific Computing, Algorithm Design and Data Structures

2014 S2: Algorithm Design and Data Structures, Distributed Systems

2015 S1: Advanced Algorithm, Algorithm Design and Data Structures

2015 S2: Algorithm Design and Data Structures, Algorithm and Data Structure Analysis, Specialised Programming

2016 S1: Advanced Algorithm, Algorithm Design and Data Structures

2016 S2: Algorithm Design and Data Structures, Specialised Programming

2017 S1: Advanced Algorithm, Specialised Programming

2017 S2: Algorithm and Data Structure Analysis, Specialised Programming

• Current Higher Degree by Research Supervision (University of Adelaide)

  Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
  2024	Co-Supervisor	Heuristic search algorithms for complex optimisation problems in space and energy	Doctor of Philosophy	Doctorate	Full Time	Mr Liam Joshua Wigney
  2024	Co-Supervisor	AI-based Time Use Optimisation for Improving Health and Well-being Outcomes	Doctor of Philosophy	Doctorate	Full Time	Mr Khalil Ahammad
  2022	Co-Supervisor	Scalable Hypergame models and solutions for Autonomous Cyber Operations.	Doctor of Philosophy	Doctorate	Full Time	Mr Quang Huy Ngo
  2022	Co-Supervisor	Bio-inspired Computing for Problems with Chance Constraints	Doctor of Philosophy	Doctorate	Full Time	Mr Xiankun Yan
  2022	Co-Supervisor	Bio-inspired Computing for Problems with Chance Constraints	Doctor of Philosophy	Doctorate	Full Time	Mrs Kokila Perera
  2021	Co-Supervisor	Flexible Aggregator Simulation Platform (FRESNO): Local Energy and Ancillary Services Markets (FRESNO C)	Doctor of Philosophy	Doctorate	Full Time	Mr Trong Nam Dinh
  2021	Principal Supervisor	Algorithms and Equilibrium Computation for Defending Active Directory Style Attack Graphs	Master of Philosophy	Master	Full Time	Mr Jialiang Li

• Past Higher Degree by Research Supervision (University of Adelaide)

  Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
  2021 - 2023	Principal Supervisor	Enhancing Network Resilience through Machine Learning-powered Graph Combinatorial Optimization: Applications in Cyber Defense and Information Diffusion	Doctor of Philosophy	Doctorate	Full Time	Miss Diksha Goel
  2020 - 2024	Co-Supervisor	Deep Learning Based Multi-document Summarization	Doctor of Philosophy	Doctorate	Full Time	Ms Congbo Ma
  2020 - 2024	Co-Supervisor	Analysis of Search Heuristics for Diverse Solutions to Combinatorial Problems	Doctor of Philosophy	Doctorate	Full Time	Mr Viet Anh Do
  2019 - 2022	Principal Supervisor	Machine Learning Approaches to Automated Mechanism Design for Public Project Problem	Doctor of Philosophy	Doctorate	Full Time	Dr Guanhua Wang
  2016 - 2020	Co-Supervisor	Towards Quality-centric Design and Evaluation of Big Data Cyber Security Analytics Systems	Doctor of Philosophy	Doctorate	Full Time	Mr Faheem Ullah

• Position: Lecturer
• Phone: 83131893
• Email: mingyu.guo@adelaide.edu.au
• Fax: 83134366
• Campus: North Terrace
• Building: Ingkarni Wardli, floor 4
• Org Unit: Computer Science