Dr Michelle Blom

  • Room: Level: 06 Room: 14
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • AI Algorithms
  • Algorithms for Electoral Analysis
  • Optimisation for Supply Chains

Personal webpage

http://people.eng.unimelb.edu.au/michelleb/

Biography

Dr Michelle Blom is a Research Fellow in the Department of Computing and Information Systems at The University of Melbourne. Michelle completed her PhD in the Department of Computer Science and Software Engineering at the University of Melbourne in 2011. Her thesis explored the use of argumentation-based approaches for automated decision-making and planning. Michelle is a currently a research fellow at the University of Melbourne, working on an ARC Linkage Project with Rio Tinto Iron Ore. Her research involves developing new algorithms and heuristics for scheduling operations in large open-pit mining supply chains.

Recent publications

  1. Blom, M.; Stuckey, PJ.; Teague, VJ. Ballot-Polling Risk Limiting Audits for IRV Elections. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 11143 LNCS, pp. 17-34. DOI: 10.1007/978-3-030-00419-4_2
  2. Blom, M.; Stuckey, PJ.; Teague, VJ. Computing the Margin of Victory in Preferential Parliamentary Elections. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 11143 LNCS, pp. 1-16. DOI: 10.1007/978-3-030-00419-4_1
  3. Blom, M.; Shekh, S.; Gossink, D.; Miller, T.; Pearce, AR. Inventory routing for defense: Moving supplies in adversarial and partially observable environments. Journal of Defense Modeling and Simulation. 2018. DOI: 10.1177/1548512918798056
  4. Blom, M.; Pearce, AR.; Stuckey, PJ. Multi-objective short-term production scheduling for open-pit mines: a hierarchical decomposition-based algorithm. Engineering Optimization. TAYLOR & FRANCIS LTD. 2018, Vol. 50, Issue 12, pp. 2143-2160. DOI: 10.1080/0305215X.2018.1429601
  5. Blom, M.; Pearce, AR.; Stuckey, PJ. Short-term planning for open pit mines: a review. International Journal of Mining, Reclamation and Environment. 2018, pp. 1-22. DOI: 10.1080/17480930.2018.1448248
  6. Conway, A.; Blom, M.; Naish, L.; Teague, V. An analysis of New South Wales electronic vote counting. ACM International Conference Proceeding Series. 2017. DOI: 10.1145/3014812.3014837
  7. Blom, M.; Pearce, AR.; Stuckey, PJ. Short-term scheduling of an open-pit mine with multiple objectives. Engineering Optimization. TAYLOR & FRANCIS LTD. 2017, Vol. 49, Issue 5, pp. 777-795. DOI: 10.1080/0305215X.2016.1218002
  8. Blom, ML.; Pearce, AR.; Stuckey, PJ. A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods. Management Science. INFORMS. 2016, Vol. 62, Issue 10, pp. 3059-3084. DOI: 10.1287/mnsc.2015.2284
  9. Blom, M.; Teague, V.; Stuckey, PJ.; Tidhar, R. Efficient Computation of Exact IRV Margins. Frontiers in Artificial Intelligence and Applications. IOS PRESS. 2016, Vol. 285, pp. 480-488. DOI: 10.3233/978-1-61499-672-9-480
  10. Blom, M.; Burt, C.; Lipovetzky, N.; Pearce, A.; Stuckey, P. Scheduling Tools for Open-Pit Mining Operations. . 2015.
  11. Blom, ML.; Burt, CN.; Pearce, A.; Stuckey, PJ. A Decomposition-Based Heuristic for Collaborative Scheduling in a Network of Open-Pit Mines. INFORMS Journal on Computing. INFORMS. 2014, Vol. 26, Issue 4, pp. 658-689. DOI: 10.1287/ijoc.2013.0590
  12. Blom, M. Arguments and Actions: Decoupling Preference and Planning through Argumentation. . 2011.
  13. Blom, ML.; Pearce, AR. Relaxing regression for a heuristic GOLOG. Frontiers in Artificial Intelligence and Applications. IOS Press. 2010, Vol. 222, pp. 37-49. DOI: 10.3233/978-1-60750-676-8-37
  14. Blom, ML.; Pearce, A. An Argumentation-Based Interpreter for Golog Programs. IJCAI International Joint Conference on Artificial Intelligence. IJCAI Incorporated. 2009, pp. 690-695.
  15. Blom, M. An Argumentative Knowledge-Based Model Construction Approach for Bayesian Networks. . 6th European Workshop on Multi-Agent Systems (EUMAS-2008). 2008.
  16. Blom, M. Optimising the Interpretation of Golog Programs with Argumentation. . 6TH EUROPEAN WORKSHOP IN MULTI-AGENT SYSTEMS (EUMAS 2008). 2008.

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile