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Dr Francisco Cruz Naranjo

Dr Francisco Cruz Naranjo

Senior Lecturer
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
E-mail
f.cruz@unsw.edu.au
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 | 2024
    Ly A; Dazeley R; Vamplew P; Cruz F; Aryal S, 2024, 'Elastic step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks', Neurocomputing, 576, http://dx.doi.org/10.1016/j.neucom.2023.127170
    Journal articles | 2023
    Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2023, 'Human engagement providing evaluative and informative advice for interactive reinforcement learning', Neural Computing and Applications, 35, pp. 18215 - 18230, http://dx.doi.org/10.1007/s00521-021-06850-6
    Journal articles | 2023
    Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2023, 'Persistent rule-based interactive reinforcement learning', Neural Computing and Applications, 35, pp. 23411 - 23428, http://dx.doi.org/10.1007/s00521-021-06466-w
    Journal articles | 2023
    Bignold A; Cruz F; Taylor ME; Brys T; Dazeley R; Vamplew P; Foale C, 2023, 'A conceptual framework for externally-influenced agents: an assisted reinforcement learning review', Journal of Ambient Intelligence and Humanized Computing, 14, pp. 3621 - 3644, http://dx.doi.org/10.1007/s12652-021-03489-y
    Journal articles | 2023
    Cruz F; Dazeley R; Vamplew P; Moreira I, 2023, 'Explainable robotic systems: understanding goal-driven actions in a reinforcement learning scenario', Neural Computing and Applications, 35, pp. 18113 - 18130, http://dx.doi.org/10.1007/s00521-021-06425-5
    Journal articles | 2023
    Cruz F; Karimpanal TG; Solis MA; Barros P; Dazeley R, 2023, 'Human-aligned reinforcement learning for autonomous agents and robots', Neural Computing and Applications, 35, pp. 16689 - 16691, http://dx.doi.org/10.1007/s00521-023-08748-x
    Journal articles | 2023
    Cruz F; Solis MA; Navarro-Guerrero N, 2023, 'Editorial: Cognitive inspired aspects of robot learning', Frontiers in Neurorobotics, 17, http://dx.doi.org/10.3389/fnbot.2023.1256788
    Journal articles | 2023
    Dazeley R; Vamplew P; Cruz F, 2023, 'Explainable reinforcement learning for broad-XAI: a conceptual framework and survey', Neural Computing and Applications, 35, pp. 16893 - 16916, http://dx.doi.org/10.1007/s00521-023-08423-1
    Journal articles | 2023
    Harland H; Dazeley R; Nakisa B; Cruz F; Vamplew P, 2023, 'AI apology: interactive multi-objective reinforcement learning for human-aligned AI', Neural Computing and Applications, 35, pp. 16917 - 16930, http://dx.doi.org/10.1007/s00521-023-08586-x
    Journal articles | 2023
    Millán-Arias C; Fernandes B; Cruz F, 2023, 'Proxemic behavior in navigation tasks using reinforcement learning', Neural Computing and Applications, 35, pp. 16723 - 16738, http://dx.doi.org/10.1007/s00521-022-07628-0
    Journal articles | 2023
    Nguyen HS; Cruz F; Dazeley R, 2023, 'Towards a Broad-Persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments', Sensors, 23, http://dx.doi.org/10.3390/s23052681
    Journal articles | 2023
    de Andrade JVR; Fernandes BJT; Izídio ARLC; da Silva Filho NM; Cruz F, 2023, 'Vessel Velocity Estimation and Docking Analysis: A Computer Vision Approach', Algorithms, 16, http://dx.doi.org/10.3390/a16070326
    Journal articles | 2022
    Ayala A; Fernandes BJT; Cruz F; Macedo D; Zanchettin C, 2022, 'Convolution Optimization in Fire Classification', IEEE Access, 10, pp. 23642 - 23658, http://dx.doi.org/10.1109/ACCESS.2022.3151660
    Journal articles | 2022
    Azevedo GODA; Fernandes BJT; Silva LHDS; Freire A; de Araújo RP; Cruz F, 2022, 'Event-Based Angular Speed Measurement and Movement Monitoring', Sensors, 22, http://dx.doi.org/10.3390/s22207963
    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, 15, 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), 11, 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, 6, pp. 1 - 15, http://dx.doi.org/10.3390/biomimetics6010013
    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, 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, 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, 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), 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, 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, 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, 8, pp. 271 - 284, http://dx.doi.org/10.1109/TCDS.2016.2543839
  • Preprints | 2024
    Lin Z; Cruz F; Sandoval EB, 2024, Self context-aware emotion perception on human-robot interaction, , http://arxiv.org/abs/2401.10946v1
    Conference Papers | 2023
    Babcinschi M; Cruz F; Duarte N; Santos S; Alves S; Neto P, 2023, 'Intuitive Robot Programming by Capturing Human Manufacturing Skills: A Framework for the Process of Glass Adhesive Application', in Lecture Notes in Mechanical Engineering, pp. 677 - 684, http://dx.doi.org/10.1007/978-3-031-17629-6_71
    Preprints | 2023
    Bernotat J; Jirak D; Sandoval EB; Cruz F; Sciutti A, 2023, Asch Meets HRI: Human Conformity to Robot Groups, , http://arxiv.org/abs/2308.13307v1
    Conference Papers | 2023
    Cruz F; Safeea M; Babcinschi M; Neto P, 2023, 'Design and 3D Printing Fabrication of a Low-Cost Lightweight Robot Manipulator', in Lecture Notes in Mechanical Engineering, pp. 387 - 394, http://dx.doi.org/10.1007/978-3-031-17629-6_40
    Conference Papers | 2023
    Lin Z; Cruz F; Sandoval EB, 2023, 'Self context-aware emotion perception on human-robot interaction', in Australasian Conference on Robotics and Automation, ACRA
    Conference Papers | 2023
    Ly A; Dazeley R; Vamplew P; Cruz F; Aryal S, 2023, 'Elastic step DDPG: Multi-step reinforcement learning for improved sample efficiency', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN54540.2023.10191774
    Conference Papers | 2023
    Portugal E; Ayala A; Cruz F; Fernandes B; Murilo S, 2023, 'Time estimation for deep learning model’s inference in distributed processing units', in 2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023, http://dx.doi.org/10.1109/LA-CCI58595.2023.10409398
    Conference Papers | 2023
    Tong Z; Ayala A; Sandoval EB; Cruz F, 2023, 'Urban Autonomous Driving of Emergency Vehicles with Reinforcement Learning', in 2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023, http://dx.doi.org/10.1109/LA-CCI58595.2023.10409469
    Preprints | 2022
    Cruz F; Bignold A; Nguyen HS; Dazeley R; Vamplew P, 2022, Broad-persistent Advice for Interactive Reinforcement Learning Scenarios, , http://arxiv.org/abs/2210.05187v1
    Conference Papers | 2022
    Cruz F; Young C; Dazeley R; Vamplew P, 2022, 'Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios', in IEEE International Conference on Intelligent Robots and Systems, pp. 894 - 901, http://dx.doi.org/10.1109/IROS47612.2022.9981334
    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 | 2022
    Ly A; Dazeley R; Vamplew P; Cruz F; Aryal S, 2022, Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks, , http://arxiv.org/abs/2210.03325v1
    Conference Papers | 2022
    Millán-Arias C; Contreras R; Cruz F; Fernandes B, 2022, 'Reinforcement Learning for UAV control with Policy and Reward Shaping', in Proceedings - International Conference of the Chilean Computer Science Society, SCCC, http://dx.doi.org/10.1109/SCCC57464.2022.10000286
    Preprints | 2022
    Millán-Arias C; Contreras R; Cruz F; Fernandes B, 2022, Reinforcement Learning for UAV control with Policy and Reward Shaping, , http://arxiv.org/abs/2212.03828v1
    Conference Papers | 2022
    Muñoz H; Portugal E; Ayala A; Fernandes B; Cruz F, 2022, 'Explaining Agent's Decision-making in a Hierarchical Reinforcement Learning Scenario', in Proceedings - International Conference of the Chilean Computer Science Society, SCCC, http://dx.doi.org/10.1109/SCCC57464.2022.10000321
    Preprints | 2022
    Muñoz H; Portugal E; Ayala A; Fernandes B; Cruz F, 2022, Explaining Agent's Decision-making in a Hierarchical Reinforcement Learning Scenario, , http://arxiv.org/abs/2212.06967v1
    Conference Papers | 2022
    Schroeter N; Cruz F; Wermter S, 2022, 'Introspection-based Explainable Reinforcement Learning in Episodic and Non-episodic Scenarios', in Australasian Conference on Robotics and Automation, ACRA, Queensland University of Technology (QUT), presented at Australasian Conference on Robotics and Automation, ACRA, Queensland University of Technology (QUT), 06 December 2022 - 08 December 2022, https://ssl.linklings.net/conferences/acra/acra2022_proceedings/views/includes/files/pap114s2.pdf
    Preprints | 2022
    Schroeter N; Cruz F; Wermter S, 2022, Introspection-based Explainable Reinforcement Learning in Episodic and Non-episodic Scenarios, , http://arxiv.org/abs/2211.12930v1
    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), IEEE, ECUADOR, Guayaquil, pp. 87 - 92, presented at IEEE Latin American Conference on Computational Intelligence (LA-CCI), ECUADOR, Guayaquil, 11 November 2019 - 15 November 2019, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000926088100015&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    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 | 2017
    Cruz F; Wuppen P; Magg S; Fazrie A; Wermter S, 2017, '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