About
- I am a PhD student at the Centre for Doctoral Training in Robotics and Autonomous Systems, part of the Edinburgh Centre for Robotics. I am also a member of the HRI Lab and the Interaction Lab at Heriot-Watt University. Previously, I was awarded an Electronics Engineering degree by the National University of Rosario (Argentina), and an Erasmus Mundus Masters in Vision and Robotics (VIBOT) jointly awarded by the University of Burgundy (France), the University of Girona (Spain) and Heriot-Watt University (UK). I carried out my Masters thesis in the Institute of Perception, Action and Behaviour (IPAB) at the University of Edinburgh. I also hold a Masters in Robotics and Autonomous Systems awarded as part of my doctoral training.
- My current research interests include lifelong machine learning, situated interactive learning, hierarchical task learning, language grounding, learning through dialogue and visual demonstrations, and cognitive systems, but more importantly how to apply all these things to robots operating alongside people and in human-centred environments.
News
- May 2020 - I have started a part-time position as a research associate within the SPRING project at Heriot-Watt University.
- Mar 2019 - I started running a reading group on planning and learning with Frank Broz at Heriot-Watt University.
- Feb 2019 - Our review paper on continual lifelong learning with neural networks has been published on Neural Networks. You can get a copy from here.
- Dec 2018 - I have started a part-time position as a research associate within the SoCoRo project at Heriot-Watt University.
- Feb 2018 - New review paper on continual lifelong learning with neural networks. Preprint already available on arXiv.
Publications
Journals
- G. I. Parisi, R. Kemker, J. L. Part, C. Kanan and S. Wermter, Continual Lifelong Learning with Neural Networks: A Review, in Neural Networks, 2019. [doi] [bib]
Conferences
- P. E. McKenna, I. Keller, J. L. Part, M. Y. Lim, R. Aylett, F. Broz and G. Rajendran, "Sorry to Disturb You": Autism and Robot Interruptions (LBR Extended Abstract), in Companion Proceedings of the 15th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Cambridge, UK, March 2020. [doi] [bib] [video]
- J. L. Part and O. Lemon, Towards a Robot Architecture for Situated Lifelong Object Learning, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 2019. [doi] [pdf] [bib] [video]
- A. Vanzo, J. L. Part, Y. Yu, D. Nardi and O. Lemon, Incrementally Learning Semantic Attributes through Dialogue Interaction, in Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Stockholm, Sweden, July 2018. [pdf] [bib]
- J. L. Part and O. Lemon, Incremental Online Learning of Objects for Robots Operating in Real Environments, in Proceedings of the 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EPIROB), Lisbon, Portugal, September 2017. [doi] [pdf] [bib]
- J. L. Part and O. Lemon, Teaching Robots through Situated Interactive Dialogue and Visual Demonstrations (DC Extended Abstract), in Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 2017. [pdf] [bib]
Workshops
- P. McKenna, F. Broz, I. Keller, J. L. Part, G. Rajendran and R. Aylett, Towards Robot-Assisted Social Skills Training for Adults with ASC, in Workshop on the Challenges of Working on Social Robots that Collaborate with People at the ACM Conference on Human Factors in Computing Systems (CHI), Glasgow, UK, May 2019. [pdf] [bib]
- I. Papaioannou, A. Cercas Curry, J. L. Part, I. Shalyminov, X. Xu, Y. Yu, O. Dušek, V. Rieser and O. Lemon, An Ensemble Model with Ranking for Social Dialogue, in Workshop on Conversational AI at the Conference on Neural Information Processing Systems (NeurIPS), Long Beach, CA, USA, December 2017. [pdf] [bib]
- J. L. Part and O. Lemon, Incremental On-Line Learning of Object Classes using a Combination of Self-Organizing Incremental Neural Networks and Deep Convolutional Neural Networks, in Workshop on Bio-inspired Social Robot Learning in Home Scenarios at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, October 2016. [pdf] [bib]