Sebastian Sardina is a Professor in Artificial Intelligence. He obtained his Bachelor in Computer Science at the South National University, Argentina, and his PhD at the University of Toronto, Canada, before joining RMIT.
Sebastian's research is mainly concerned with representation and reasoning in Artificial Intelligence for dynamic systems with the objective of better programming intelligent controllers that are meant to operate in complex and dynamic environments. His work spans several sub-fields of Artificial Intelligence, including AI automated planning, knowledge representation, agent-oriented programming, and reactive synthesis.
He has has contributed to the enhancement of agent programming languages with learning and planning capabilities, and to the study and development of advanced forms of AI planning, including non-deterministic planning and automatic behaviour composition of devices and agents. In recent years, Sebastian has worked on the the goal/intention recognition problem. Sebastian scientific contributions regularly appear in several premier AI scientific venues, including IJCAI, AAMAS, ICAPS, KR, AIJ, JAIR, JAAMAS, and AAAI, among others. His work has received several best paper awards or nominations, and been invited to be presented nationally and internationally at various forums and institutions.
Beyond his University-level teaching as academic, where he mostly focuses on the foundational CS courses (like Theory of Computation, Discrete Mathematics, and Intro to AI), Sebastian has also been recently involved in bringing Computational Thinking to the community, particularly to children and youth. He has delivered/supported various workshops on algorithmic thinking for primary and secondary students and educators, participated in several MAV conferences as presenter, and has been a member of the VCAA study review panel for the Algorithmics (HESS) VCE program, which would come into effect in 2023 in Victoria.
- PhD in Computer Science, University of Toronto, Canada, 2005.
- Master of Science in Computer Science, University of Toronto, Canada, 2000.
- Bachelor in Computer Science, South National University, Argentina . 1997.
- Su, Z.,Polyvyanyy, A.,Lipovetzky, N.,Sardina, S.,van Beest, N. (2023). Fast and accurate data-driven goal recognition using process mining techniques In: Artificial Intelligence, 323, 1 - 38
- Del Real, A.,Del Real, O.,Sardina, S.,Oyonarte, R. (2022). Use of automated artificial intelligence to predict the need for orthodontic extractions In: Korean Journal of Orthodontics, 52, 102 - 111
- De Giacomo, G.,Felli, P.,Logan, B.,Patrizi, F.,Sardina, S. (2022). Situation calculus for controller synthesis in manufacturing systems with first-order state representation In: Artificial Intelligence, 302, 1 - 30
- Ng, C.,Bil, C.,Sardina, S.,O'Bree, T. (2022). Designing an Expert System to Support Aviation Occurrence Investigations In: Expert Systems with Applications, 207, 1 - 19
- Jaramillo Yanez, A.,Benalcázar, M.,Sardina, S.,Zambetta, F. (2022). Towards Discriminant Analysis Classifiers Using Online Active Learning via Myoelectric Interfaces In: Proceedings of the AAAI Conference on Artificial Intelligence, Vancouver, Canada, 22 February - 1 March 2022
- Masters, P.,Sardina, S. (2021). Expecting the unexpected: Goal recognition for rational and irrational agents In: Artificial Intelligence, 297, 1 - 24
- Rodriguez, I.,Bonet, B.,Sardina, S.,Geffner, H. (2021). Flexible FOND Planning with Explicit Fairness Assumptions In: Proceedings of the 31st International Conference on Automated Planning and Scheduling (ICAPS 2021), Guangzhou, China, 2–13 August 2021
- Yadav, N.,Murawski, C.,Sardina, S.,Bossaerts, P. (2020). Is hardness inherent in computational problems performance of human and electronic computers on random instances of the 0-1 knapsack problem In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostela, Spain, 29 August - 8 September 2020
- Ciolek, D.,D’Ippolito, N.,Pozanco, A.,Sardina, S. (2020). Multi-tier automated planning for adaptive behavior In: Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling (ICAPS 2020), Nancy, France (Online), 26-30 October 2020
- Polyvyanyy, A.,Su, Z.,Lipovetzky, N.,Sardina, S. (2020). Goal recognition using off-the-shelf process mining techniques In: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent (AAMAS 2020), Auckland, New Zealand, 9 - 13 May 2020
4 PhD Current Supervisions6 PhD Completions
- Carer Manager Plus Scheduler – Phase 2. Funded by: Innovation Connections grant - Cat 1 from (2023 to 2024)
- Programming autonomous systems with resource and requirement constraints. Funded by: SIEF STEM+ Business Fellowship Program from (2022 to 2024)
- Optimisation of embedded virtual complex systems by re-using a library of available components. Funded by: ARC Discovery 2012 from (2012 to 2014)
- Intention Selection in Intelligent Agent Systems. Funded by: ARC Discovery 2010 from (2010 to 2013)
- Approximation Techniques for Behavior Composition. Funded by: AAS (Australian Academy of Science) Scientific Visits to Europe from (2010 to 2010)