Dr Francisco Cruz Naranjo
Senior Lecturer

Dr Francisco Cruz Naranjo

Engineering
Computer Science and Engineering

*** I am currently recruiting PhD students to work on topics such as social and cognitive robotics, reinforcement learning, interactive machine learning, explainability, and multi-agent systems. If you are interested or would like to discuss further details, please get in touch or check my personal webpage (https://www.franciscocruz.org). ***

I received a bachelor’s degree in engineering and a master’s degree in computer engineering from the University of Santiago, Chile, in 2004 and 2006, respectively, and a Ph.D. degree from the University of Hamburg, Germany, in 2017, working in developmental robotics focused on interactive reinforcement learning.

In 2015, I was a Visiting Researcher within the Emergent Robotics Laboratory, Osaka University and in 2018, a Visiting Researcher within the Polytechnic School, University of Pernambuco, Brazil. I joined UNSW in 2022 as a Lecturer in Cognitive Robotics. My current research interests include reinforcement learning, explainable artificial intelligence, human-robot interaction, artificial neural networks, and psychologically and bio-inspired models.
 

Phone
+61 2 9348 0597
Location
Ainsworth Building (J17) Room 510J
  • Book Chapters | 2019
    Cruz F; Dazeley R; Vamplew P, 2019, 'Memory-Based Explainable Reinforcement Learning', in , pp. 66 - 77, http://dx.doi.org/10.1007/978-3-030-35288-2_6
  • Journal articles | 2022
    Ayala A; Fernandes BJT; Cruz F; Macedo D; Zanchettin C, 2022, 'Convolution Optimization in Fire Classification', IEEE Access, vol. 10, pp. 23642 - 23658, http://dx.doi.org/10.1109/ACCESS.2022.3151660
    Journal articles | 2022
    Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2022, 'Human engagement providing evaluative and informative advice for interactive reinforcement learning', Neural Computing and Applications, http://dx.doi.org/10.1007/s00521-021-06850-6
    Journal articles | 2022
    Millán-Arias C; Fernandes B; Cruz F, 2022, 'Proxemic behavior in navigation tasks using reinforcement learning', Neural Computing and Applications, http://dx.doi.org/10.1007/s00521-022-07628-0
    Journal articles | 2022
    Portugal E; Cruz F; Ayala A; Fernandes B, 2022, 'Analysis of Explainable Goal-Driven Reinforcement Learning in a Continuous Simulated Environment', Algorithms, vol. 15, pp. 91 - 91, http://dx.doi.org/10.3390/a15030091
    Journal articles | 2021
    Ayala A; Ortiz Figueroa T; Fernandes B; Cruz F, 2021, 'Diabetic retinopathy improved detection using deep learning', Applied Sciences (Switzerland), vol. 11, pp. 11970 - 11970, http://dx.doi.org/10.3390/app112411970
    Journal articles | 2021
    Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2021, 'An evaluation methodology for interactive reinforcement learning with simulated users', Biomimetics, vol. 6, pp. 1 - 15, http://dx.doi.org/10.3390/biomimetics6010013
    Journal articles | 2021
    Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2021, 'Persistent rule-based interactive reinforcement learning', Neural Computing and Applications, http://dx.doi.org/10.1007/s00521-021-06466-w
    Journal articles | 2021
    Bignold A; Cruz F; Taylor ME; Brys T; Dazeley R; Vamplew P; Foale C, 2021, 'A conceptual framework for externally-influenced agents: an assisted reinforcement learning review', Journal of Ambient Intelligence and Humanized Computing, http://dx.doi.org/10.1007/s12652-021-03489-y
    Journal articles | 2021
    Cruz F; Dazeley R; Vamplew P; Moreira I, 2021, 'Explainable robotic systems: understanding goal-driven actions in a reinforcement learning scenario', Neural Computing and Applications, http://dx.doi.org/10.1007/s00521-021-06425-5
    Journal articles | 2021
    Dazeley R; Vamplew P; Foale C; Young C; Aryal S; Cruz F, 2021, 'Levels of explainable artificial intelligence for human-aligned conversational explanations', Artificial Intelligence, vol. 299, http://dx.doi.org/10.1016/j.artint.2021.103525
    Journal articles | 2021
    Millan-Arias CC; Fernandes BJT; Cruz F; Dazeley R; Fernandes S, 2021, 'A Robust Approach for Continuous Interactive Actor-Critic Algorithms', IEEE Access, vol. 9, pp. 104242 - 104260, http://dx.doi.org/10.1109/ACCESS.2021.3099071
    Journal articles | 2020
    Contreras R; Ayala A; Cruz F, 2020, 'Unmanned aerial vehicle control through domain-based automatic speech recognition', Computers, vol. 9, pp. 1 - 15, http://dx.doi.org/10.3390/computers9030075
    Journal articles | 2020
    Moreira I; Rivas J; Cruz F; Dazeley R; Ayala A; Fernandes B, 2020, 'Deep reinforcement learning with interactive feedback in a human-robot environment', Applied Sciences (Switzerland), vol. 10, http://dx.doi.org/10.3390/app10165574
    Journal articles | 2018
    Cruz F; Magg S; Nagai Y; Wermter S, 2018, 'Improving interactive reinforcement learning: What makes a good teacher?', Connection Science, vol. 30, pp. 306 - 325, http://dx.doi.org/10.1080/09540091.2018.1443318
    Journal articles | 2016
    Cruz F; Baraglia J; Nagai Y; Wermter S, 2016, 'Special issue on bio-inspired social robot learning in home scenarios', IEEE Transactions on Cognitive and Developmental Systems, vol. 8, pp. 1 - 2, http://dx.doi.org/10.1109/TCDS.2016.2603000
    Journal articles | 2016
    Cruz F; Magg S; Weber C; Wermter S, 2016, 'Training Agents With Interactive Reinforcement Learning and Contextual Affordances', IEEE Transactions on Cognitive and Developmental Systems, vol. 8, pp. 271 - 284, http://dx.doi.org/10.1109/TCDS.2016.2543839
  • Preprints | 2022
    Cruz F; Young C; Dazeley R; Vamplew P, 2022, Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios, http://arxiv.org/abs/2207.03214v1
    Preprints | 2021
    Ayala A; Cruz F; Fernandes B; Dazeley R, 2021, Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task, http://arxiv.org/abs/2108.08911v1
    Preprints | 2021
    Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2021, Persistent Rule-based Interactive Reinforcement Learning, http://arxiv.org/abs/2102.02441v2
    Preprints | 2021
    Dazeley R; Vamplew P; Cruz F, 2021, Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey, http://arxiv.org/abs/2108.09003v1
    Preprints | 2021
    Dazeley R; Vamplew P; Foale C; Young C; Aryal S; Cruz F, 2021, Levels of explainable artificial intelligence for human-aligned conversational explanations, http://dx.doi.org/10.1016/j.artint.2021.103525
    Preprints | 2021
    Millán-Arias C; Fernandes B; Cruz F, 2021, Learning Proxemic Behavior Using Reinforcement Learning with Cognitive Agents, http://arxiv.org/abs/2108.03730v1
    Preprints | 2021
    Nguyen HS; Cruz F; Dazeley R, 2021, A Broad-persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments, http://arxiv.org/abs/2110.08003v2
    Conference Papers | 2020
    Ayala A; Cruz F; Campos D; Rubio R; Fernandes B; Dazeley R, 2020, 'A Comparison of Humanoid Robot Simulators: A Quantitative Approach', in ICDL-EpiRob 2020 - 10th IEEE International Conference on Development and Learning and Epigenetic Robotics, http://dx.doi.org/10.1109/ICDL-EpiRob48136.2020.9278116
    Preprints | 2020
    Ayala A; Cruz F; Campos D; Rubio R; Fernandes B; Dazeley R, 2020, A Comparison of Humanoid Robot Simulators: A Quantitative Approach, http://arxiv.org/abs/2008.04627v1
    Conference Papers | 2020
    Ayala A; Fernandes B; Cruz F; MacEdo D; Oliveira ALI; Zanchettin C, 2020, 'KutralNet: A Portable Deep Learning Model for Fire Recognition', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN48605.2020.9207202
    Preprints | 2020
    Ayala A; Fernandes B; Cruz F; Macêdo D; Oliveira ALI; Zanchettin C, 2020, KutralNet: A Portable Deep Learning Model for Fire Recognition, http://dx.doi.org/10.1109/IJCNN48605.2020.9207202
    Conference Papers | 2020
    Barros P; Tanevska A; Cruz F; Sciutti A, 2020, 'Moody Learners-Explaining Competitive Behaviour of Reinforcement Learning Agents', in ICDL-EpiRob 2020 - 10th IEEE International Conference on Development and Learning and Epigenetic Robotics, http://dx.doi.org/10.1109/ICDL-EpiRob48136.2020.9278125
    Preprints | 2020
    Barros P; Tanevska A; Cruz F; Sciutti A, 2020, Moody Learners -- Explaining Competitive Behaviour of Reinforcement Learning Agents, http://arxiv.org/abs/2007.16045v1
    Preprints | 2020
    Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2020, Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning, http://dx.doi.org/10.1007/s00521-021-06850-6
    Preprints | 2020
    Bignold A; Cruz F; Taylor ME; Brys T; Dazeley R; Vamplew P; Foale C, 2020, A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review, http://dx.doi.org/10.1007/s12652-021-03489-y
    Preprints | 2020
    Contreras R; Ayala A; Cruz F, 2020, Unmanned Aerial Vehicle Control Through Domain-based Automatic Speech Recognition, http://dx.doi.org/10.3390/computers9030075
    Preprints | 2020
    Cruz F; Dazeley R; Vamplew P; Moreira I, 2020, Explainable robotic systems: Understanding goal-driven actions in a reinforcement learning scenario, http://dx.doi.org/10.1007/s00521-021-06425-5
    Preprints | 2020
    Cuevas J; Henriquez C; Cruz F, 2020, Towards Assistive Diagnoses in m-Health: A Gray-box Neural Model for Cerebral Autoregulation Index, http://arxiv.org/abs/2011.12115v1
    Conference Papers | 2020
    Millán-Arias C; Fernandes B; Cruz F; Dazeley R; Fernandes S, 2020, 'A Robust Approach for Continuous Interactive Reinforcement Learning', in HAI 2020 - Proceedings of the 8th International Conference on Human-Agent Interaction, pp. 278 - 280, http://dx.doi.org/10.1145/3406499.3418769
    Preprints | 2020
    Moreira I; Rivas J; Cruz F; Dazeley R; Ayala A; Fernandes B, 2020, Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment, http://dx.doi.org/10.3390/app10165574
    Conference Papers | 2019
    Ayala A; Henríquez C; Cruz F, 2019, 'Reinforcement learning using continuous states and interactive feedback', in ACM International Conference Proceeding Series, http://dx.doi.org/10.1145/3309772.3309801
    Conference Papers | 2019
    Ayala A; Lima E; Fernandes B; Bezerra BLD; Cruz F, 2019, 'Lightweight and efficient octave convolutional neural network for fire recognition', in 2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019, http://dx.doi.org/10.1109/LA-CCI47412.2019.9037059
    Preprints | 2019
    Cruz F; Magg S; Nagai Y; Wermter S, 2019, Improving interactive reinforcement learning: What makes a good teacher?, http://dx.doi.org/10.1080/09540091.2018.1443318
    Conference Papers | 2019
    Cruz F; Wuppen P; Fazrie A; Weber C; Wermter S, 2019, 'Action Selection Methods in a Robotic Reinforcement Learning Scenario', in 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018, http://dx.doi.org/10.1109/LA-CCI.2018.8625243
    Conference Papers | 2019
    Millán C; Fernandes B; Cruz F, 2019, 'Human feedback in continuous actor-critic reinforcement learning', in ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 661 - 666
    Conference Papers | 2018
    Cruz F; Parisi GI; Wermter S, 2018, 'Multi-modal Feedback for Affordance-driven Interactive Reinforcement Learning', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN.2018.8489237
    Conference Papers | 2018
    Cruz F; Wuppen P; Magg S; Fazrie A; Wermter S, 2018, 'Agent-advising approaches in an interactive reinforcement learning scenario', in 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017, pp. 209 - 214, http://dx.doi.org/10.1109/DEVLRN.2017.8329809
    Conference Papers | 2016
    Cruz F; Parisi GI; Twiefel J; Wermter S, 2016, 'Multi-modal integration of dynamic audiovisual patterns for an interactive reinforcement learning scenario', in IEEE International Conference on Intelligent Robots and Systems, pp. 759 - 766, http://dx.doi.org/10.1109/IROS.2016.7759137
    Conference Papers | 2016
    Cruz F; Parisi GI; Wermter S, 2016, 'Learning contextual affordances with an associative neural architecture', in ESANN 2016 - 24th European Symposium on Artificial Neural Networks, pp. 665 - 670
    Conference Papers | 2015
    Cruz F; Twiefel J; Magg S; Weber C; Wermter S, 2015, 'Interactive reinforcement learning through speech guidance in a domestic scenario', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN.2015.7280477
    Conference Papers | 2014
    Cruz F; Magg S; Weber C; Wermter S, 2014, 'Improving reinforcement learning with interactive feedback and affordances', in IEEE ICDL-EPIROB 2014 - 4th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, pp. 165 - 170, http://dx.doi.org/10.1109/DEVLRN.2014.6982975
    Conference Papers | 2010
    Naranjo FC; Leiva GA, 2010, 'Indirect training with error backpropagation in gray-box neural model: Application to a chemical process', in Proceedings - International Conference of the Chilean Computer Science Society, SCCC, pp. 265 - 269, http://dx.doi.org/10.1109/SCCC.2010.41
    Conference Papers | 2007
    Cruz F; Acuña G; Cubillos F; Moreno V; Bassi D, 2007, 'Indirect training of grey-box models: application to a bioprocess', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 391 - 397, http://dx.doi.org/10.1007/978-3-540-72393-6_47
    Conference Papers | 2006
    Acuña G; Cruz F; Moreno V, 2006, 'Identifiability of time varying parameters in a Grey-Box Neural Model: Application to a biotechnological process', in 4th International Conference on Simulation and Modelling in the Food and Bio-Industry 2006, FOODSIM 2006, pp. 26 - 31