STAFF PROFILE
Professor John Thangarajah
Professor John Thangarajah's passion is in innovation and leadership.
He is a Professor in Artificial Intelligence and the Associate Dean (Head) of Computer Science and Software Engineering at RMIT University.
His interests are in Agent Oriented Software Development (how do we build and construct Intelligent Systems), Agent Reasoning (how can programs behave in smart ways), Intelligent Conversation Systems (how can systems interact intelligently satisfying a user's information needs), Agent Testing (providing assurance that the systems work) and in Intelligent Games (how can intelligent game masters be introduced into role playing games).
He collaborates with industry partners and researchers both local and international and have secured research grants from both government and industry sectors. He also has many years experience in teaching IT related courses to undergraduate, postgraduate and industry personnel.
Professor John Thangarajah's goal is to continue to be involved in developing smart systems that are not only intellectually challenging but also have practical benefit and impact.
Associate Professor John Thangarajah has taught and continues to teach a variety of courses, both undergraduate and postgraduate ranging from general Programming courses to more specialised Artificial Intelligence courses.
- PhD. Computer Science, RMIT University, 2005
- Vukovic, M.,Sethu, V.,Parker, J.,Cavedon, L.,Lech, M.,Thangarajah, J. (2019). Estimating cognitive load from speech gathered in a complex real-life training exercise In: International Journal of Human-Computer Studies, 124, 116 - 133
- Dann, M.,Zambetta, F.,Thangarajah, J. (2018). Integrating skills and simulation to solve complex navigation tasks in infinite Mario In: IEEE Transactions on Computational Intelligence and AI in Games, 10, 101 - 106
- Booth, E.,Thangarajah, J.,Zambetta, F. (2017). Applying norms and preferences for designing flexible game rules In: International Journal of Agent-Oriented Software Engineering, 5, 69 - 103
- Abushark, Y.,Miller, T.,Thangarajah, J.,Winikoff, M.,Harland, J. (2017). Requirements specification via activity diagrams for agent-based systems In: Autonomous Agents and Multi-Agent Systems, 31, 423 - 468
- Dann, M.,Zambetta, F.,Thangarajah, J. (2017). Reusing skills for first-time solution of navigation tasks in platform videogames In: Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brasil, 8-12 May 2017
- Abushark, Y.,Thangarajah, J.,Harland, J.,Miller, T. (2017). A framework for automatically ensuring the conformance of agent designs In: Journal of Systems and Software, 131, 266 - 310
- Logan, B.,Thangarajah, J.,Yorke-Smith, N. (2017). Progressing Intention Progression: A Call for a Goal-Plan Tree Contest In: Proceedings of the 16th International Conference on Autonomous Agents and Multi-agent Systems, Sao Paulo, Brazil, 8-12 May 2017
- Yadav, N.,Thangarajah, J.,Sardina, S. (2017). Agent design consistency checking via planning In: Proceedings of the 26h International Joint Conferences on Artifical Intelligence (IJCAI 2017), Melbourne, Australia, 19-25 August 2017
- Dann, M.,Zambetta, F.,Thangarajah, J. (2017). Real-time navigation in classical platform games via skill reuse In: Proceedings of the 26h International Joint Conferences on Artifical Intelligence (IJCAI 2017), Melbourne, Australia, 19-25 August 2017
- Evertsz, R.,Thangarajah, J.,Papasimeon, M. (2017). The Conceptual Modelling of Dynamic Teams for Autonomous Systems In: Proceedings of the 36th International Conference on Conceptual Modeling (ER2017), Valencia, Spain, 6-9 November 2017
- Shared situation picture compilation exploiting next generation data links. Funded by: Defence Science and Technology Group - Competitive from (2018 to 2019)
- An Investigation into how best to present autonomous system decision making to human team members. Funded by: DST Competitive Evaluation Research Agreement (CERA) Program 2017 from (2017 to 2019)
- Introducing teaming to the intelligent Watch Dog (iWD). Funded by: Defence Science Institute Grant 2015 from (2016 to 2016)
- Specification, Discovery of Team Tactical Behaviour & Plasticity in Planning. Funded by: Defence Science Institute Grant 2015 from (2016 to 2017)
- Modelling Team Behaviour for intelligent agent systems.. Funded by: Defence Science Institute Grant 2015 from (2016 to 2020)
3 PhD Completions3 PhD Current Supervisions