. . . Michail Maniadakis

Computer Scientist, PhD
Computational Vision and Robotics Laboratory, Institute of Computer Science,
Foundation fro Research and Technolohy, Hellas (FORTH)
GREECE


Short Bio


Michail Maniadakis is a computer scientist working at the Computational Vision and Robotics Laboratory (CVRL) of FORTH-ICS. He is specialized in machine learning and cognitive robotic systems pursuing research for almost 20 years. He has working experience in leading research institutes in Greece (FORTH), Germany (Fraunhofer-Gesellschaft) and Japan (RIKEN) with a recognized research track. He has participated in several National, EU and International projects as assistant, developer and recently, as key proposer and scientific coordinator. Michail Maniadakis has pioneered robotic time perception, having already more than eight years experience in this hot topic that is expected to provide new impetus in robotics. He is the leading scientific contributor in the CVRL research strand exploring robotic temporal cognition and he has been the key initiator of the two relevant EU funded projects, namely the FET-Proactive project TimeStorm and the more recent FET-Open project Entiment.


Research Interests


The last years my research has mainly focused on the time perception and time processing capacities of robotic systems. This largely unexplored dimmension of artificial cognition, plays a key role in the development of autonomous and intelligent systems.

Time is everywhere. It is involved in nearly all aspects of our daily life. In the way our experiences are stored, the way we learn new skills based on previous knowledge, the way we jointly recall past events with friends, the way we make long term plans and schedule our future acivities, and many more.

Besides time, I am also interested in high-level cognition. Overall, my research interests are listed below:


Publications

JOURNALS
  1. E. Argento, G. Papagiannakis, E. Baka, M. Maniadakis, P. Trahanias, I. Nestoros, Augmented Cognition via Brainwave Entrainment in Virtual Reality: an open, integrated brain augmentation in a neuroscience system approach, Augmented Human Research, (in press).
  2. M. Maniadakis, E. Hourdakis, P. Trahanias, Time-informed task planning in multi-agent collaboration, Cognitive Systems Research, 2017.
  3. S. Droit-Volet, P. Trahanias, M. Maniadakis, Passage of time judgements in everyday life are not related to duration judgements except for long durations of several minutes, Acta Psychologica, 173, 126-121, 2017.
  4. M. Maniadakis, P. Trahanias, When and how long: A unified approach for time perception, Frontiers in Psychology, 7(34), 2016.
  5. M. Maniadakis, P. Trahanias, Integrated intrinsic and dedicated representations of time: a computational study involving robotic agents, Timing & Time Perception, 3(3-4), 246-268,2015.
  6. M. Maniadakis, P. Trahanias, Time models and cognitive processes: a review, Frontiers in NeuroRobotics, Research Topic: Towards embodied artificial cognition: TIME is on my side, edited by M. Maniadakis, M. Wittmann. Y. Choe, S. Droit-Volet, 2014.
  7. J. Tani, M. Maniadakis, and R. Paine, Understanding Higher-Order Cognitive Brain Mechanisms by Conducting Evolutional Neuro-robotics Experiments, The Horizons of Evolutionary Robotics, edited by Patricia A. Vargas, Ezequiel A. Di Paolo, Inman Harvey, and Phil Husbands, 2014.
  8. M. Maniadakis, P. Trahanias, J. Tani, Self-organizing high-order cognitive functions in artficial agents: implications for possible prefrontal cortex mechanisms, Neural Networks, Vol 33, 2012.
  9. M. Maniadakis, P. Trahanias, Temporal cognition: a key ingredient of intelligent systems, Frontiers in Neurorobotics, vol 5, 2011.
  10. M. Maniadakis, P. Trahanias, J. Tani, Explorations on Artificial Time Perception, Neural Networks, vol 22(5-6), pp 509-517, 2009.
  11. M. Maniadakis, P. Trahanias, Agent-based Brain Modelling for Artificial Organisms by means of Hierarchical Cooperative CoEvolution, Artificial Life, vol 15(3), pp 293-336, 2009.
  12. M. Maniadakis, J. Tani, Acquiring Rules for Rules: Neuro-Dynamical Systems Account for Meta-Cognition, Adaptive Behavior, vol 17(1), pp.58-80, 2009.
  13. M. Maniadakis, P. E. Trahanias, Hierarchical Cooperative CoEvolution: Presentation and Assessment Study, International Journal of AI Tools, vol 18(1), pp 99-120, 2009.
  14. M. Maniadakis, P. Trahanias, Hierarchical CoEvolution of Cooperating Agents Acting in the Brain-Arena , Adaptive Behavior, vol 16, pp 221-245, 2008.
  15. P. Fattori, R. Breveglieri, N. Marzocchi, M. Maniadakis, C. Galletti, Brain area V6A: a cognitive model for an embodied artificial intelligence, Lecture Notes in Artificial Intelligence - 50 Years of Artificial Intelligence, vol. 4850, pp.206-220, 2007.
  16. M. Maniadakis, P. E. Trahanias, Modelling Robotic Cognitive Mechanisms by Hierarchical Cooperative CoEvolution, International Journal of AI Tools, vol. 16(6), pp. 935-966, 2007.
  17. M. Maniadakis, P. E. Trahanias, Modelling brain emergent behaviours through coevolution of neural agents, Neural Networks, 19(5), 705-720, 2006 .
  18. G.A. Rovithakis, M. Maniadakis, M. Zervakis, A Hybrid Neural Network/Genetic Algorithm Approach to Optimizing Feature Extraction for Signal Classification, IEEE Transactions on Systems, Man and Cybernetics, Part B, vol. 34(1), pages 695- 703, 2004.
  19. H. Surmann, M. Maniadakis, Learning feed-forward and recurrent fuzzy systems: a genetic approach, Journal of Systems Architecture, vol 47, no 7, pp. 649-662, 2001.
  20. G.A. Rovithakis, M. Maniadakis, M. Zervakis, G. Fillipidis, G. Zacharakis, A. Katsamouris, T. Papazoglou, \93Artificial Neural Networks for Discriminating Pathologic from Normal Peripheral Vascular Tissue\94, IEEE Trans. On Biomedical Engineering, vol 48, no 10, pp. 1088-1097, 2001.
CONFERENCES
  1. M. Maniadakis, S. Droit-Volet, P. Trahanias, Emotionally Modulated Time Perception for Prioritized Robot Assistance, in Proc. ACM/IEEE Int. Conference on Human-Robot Interaction (HRI), 2017.
  2. M. Sigalas, M. Maniadakis, P. Trahanias, Time-aware Long-term Episodic Memory for recurring HRI, in Proc. ACM/IEEE Int. Conference on Human-Robot Interaction (HRI), 2017.
  3. M. Maniadakis, E.E. Aksoy, T. Asfour, P. Trahanias, Collaboration of Heterogeneous Agents in Time Constrained Tasks, in Proc. IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2016.
  4. M. Maniadakis, P. Trahanias, Time-informed, Adaptive Multi-robot Synchronization, in Proc. Simulation of Adaptive Behavior (SAB), 2016.
  5. D. Bhowmik, K. Nikiforou, M. Shanahan, M. Maniadakis, P. Trahanias, A Reservoir Computing Model Of Episodic Memory, in Proc. International Joint Conference on Neural Networks (IJCNN), 2016.
  6. M. Maniadakis, P. Trahanias, Artificial Agents Perceiving and Processing Time, in Proc. International Joint Conference on Neural Networks (IJCNN), 2015.
  7. M. Maniadakis, P. Trahanias, Time in consciousness, memory and human-robot interaction, in Proc. Simulation of Adaptive Behavior (SAB), 2014.
  8. M. Maniadakis, E. Hourdakis, P. Trahanias, Robotic interval timing based on active oscillations , in Proc. International Conference on Timing and Time Perception (ICTTP), pp. 72-81, 2014.
  9. M. Maniadakis, P. Trahanias, Self-organized Neural Representation of Time , in Proc. 20th International Conference on Neural Information Processing (ICONIP), pp. 74-81, 2013.
  10. M. Maniadakis, P. Trahanias, Time in robot cognition: an emerging research branch, in Proc. First International Conference on Time Perspective (ICTP), Coimbra, Portugal, 2012.
  11. M. Maniadakis, P. Trahanias, Experiencing and Processing Time with Neural Networks, in Proc. 4th International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE), Nice, France, 2012.
  12. M. Maniadakis, J. Tani, P. Trahanias, Ego-centric and allo-centric abstraction in self-organized hierarchical neural networks, in Proc. combined IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EPIROB), 2011.
  13. M. Maniadakis, M. Wittmann, P. Trahanias, Time Experiencing by Robotic Agents, in Proc. European Symposium on Artificial Neural Networks (ESANN), 2011.
  14. M. Maniadakis, P. Trahanias, J. Tani, Self-Organized Executive Control Functions, in Proc. International Joint Conference On Neural Networks (IJCNN), pp. 3633-3640, 2010.
  15. M. Maniadakis, J. Tani, P. Trahanias, Time perception in shaping cognitive neurodynamics in artificial agents, in Proc. International Joint Conference On Neural Networks (IJCNN), pp. 1993-2000, 2009.
  16. M. Maniadakis, J. Tani, Dynamical Systems Account for Meta-Level Cognition, in Proc. of the 10th International Conference on the Simulation of Adaptive Behavior (SAB), pp. 311-320, 2008.
  17. M. Maniadakis, P. Trahanias, Assessing Hierarchical Cooperative CoEvolution, in Proc. 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp. 391-398, 2007.
  18. M. Maniadakis, E. Hourdakis, P. Trahanias, Modelling Overlapping Execution/Observation Pathways, in Proc. International Joint Conference On Neural Networks (IJCNN), pp.1255-1260, 2007.
  19. E. Hourdakis, M. Maniadakis, P. Trahanias, A biologically inspired approach for the control of the hand, in Proc. Congress on Evolutionary Computation (CEC), pp.1503-1510, 2007.
  20. M. Maniadakis, P. E. Trahanias, Hierarchical Cooperative CoEvolution Facilitates the Redesign of Agent-based Systems, in Proc. 9th International Conference on the Simulation of Adaptive Behavior (SAB), pp. 582-593, 2006.
  21. M. Maniadakis, P. E. Trahanias, Design and Integration of Partial Brain Models Using Hierarchical Cooperative CoEvolution, in Proc. International Conference on Cognitive Modelling (ICCM), pp. 196-201, 2006.
  22. M. Maniadakis, P. E. Trahanias, Modelling Robotic Cognitive Mechanisms by Hierarchical Cooperative CoEvolution, in Proc. 4th Hellenic Conference on Artificial Intelligence (SETN), pp. 224-234, 2006.
  23. M. Maniadakis, P. E. Trahanias, Distributed Brain Modelling by means of Hierarchical Collaborative CoEvolution, Proc. IEEE Congress on Evolutionary Computation, (CEC), pp. 2699-2706, 2005.
  24. M. Maniadakis, P. E. Trahanias, CoEvolutionary Incremental Modelling of Robotic Cognitive Mechanisms, Proc. VIIIth European Conference on Artificial Life (ECAL), pp.200-209, 2005.
  25. M. Maniadakis, P. E. Trahanias, A Hierarchical Coevolutionary Method to Support brain-Lesion Modelling, Proc. International Joint Conference on Neural Networks (IJCNN), pp. 434-439, 2005.
  26. M. Maniadakis, P. E. Trahanias, Evolution Tunes Coevolution: Modelling Robot Cognition Mechanisms, Proc. GECCO 2004, pp. 640-641, 2004.
  27. M. Maniadakis, P. E. Trahanias, A Computational Model of Neocortical-Hippocampal Cooperation and Its Application to Self-Localization, Proc. VIIth European Conference on Artificial Life (ECAL), pp. 183-190, 2003.
  28. G. Filippidis, G. Zacharakis, A. Katsamouris, G. A. Rovithakis, M. Maniadakis, M. Zervakis, T. G. Papazoglou, Artificial neural networks analysis of laser-induced fluorescence spectra for charcterization of peripheral vascular tissue, Proc. SPIE Vol. 4158, Biomonitoring and Endoscopy Technologies, Israel Gannot; Yuri V. Gulyaev; Theodore G. Papazoglou; Christiaan F. van Swol; Eds., pp. 199-208, 2001.
  29. G.A. Rovithakis, M. Maniadakis, and M. Zervakis, A genetically optimized artificial neural network structure for feature extraction and classification of vascular tissue luorescence spectrums, International Workshop on Computer Architectures for Machine Perception, CAMP 2000
  30. G. Filippidis, G. Zacharakis, A. Katsamouris, G.A. Rovithakis, M. Maniadakis, M. Zervakis, and T.G. Papazoglou, Artificial Neural Network analysis of laser-induced fluorescence spectra for characterization of peripheral vascular tissue, EOS/SPIE European Biomedical Optics (EBIOS), 2000.
  31. G. Rovithakis, M. Maniadakis, M. Zervakis, Artificial Neural Networks for Feature Extraction and Classification of Vascular Tissue Fluorescence Spectrums, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2000.
  32. G.A. Rovithakis, M. Maniadakis, M. Zervakis, G. Fillipidis, G. Zacharakis, T. Papazoglou Optimization of a ANN Diagnostic System using GAs, Second Panhellinic Conference on Biomedical Technology 1999.
  33. G.A. Rovithakis, M. Maniadakis, M. Zervakis, G. Fillipidis, G. Zacharakis, T. Papazoglou, Vascular Tissue Characterization using Laser Fluorescence Spectrums and ANNs, Second Panhellinic Conference on Biomedical Technology, 1999.
  34. M. Maniadakis, H. Surmann A Genetic Algorithm for Structural and Parametrical Tuning of Fuzzy Systems, European Symposium on Intelligent Techniques (ESIT), 1999.
WORKSHOPS
  1. M. Maniadakis, P. Trahanias, Time Perception: An Indispensable Trait of Robotic Cognition, to appear in the ICRA Workshop on General Intelligence and Humanoid Robotics, Hong-Kong, 2014.
  2. M. Maniadakis, P. Trahanias, Time in Symbiotic Human Robot Interaction, appeared in the workshop Timing in Human-Robot Interaction, 9th ACM/IEEE International conference on Human-Robot Interaction, 2014.
  3. M. Maniadakis, P. Trahanias, Is Time the Next Big Thing in Robot Cognition?, Cognitive Neuroscience Robotics Workshop, IEEE/RSJ International Conference on Intelligent Robots and System 2012 (IROS), Vilamoura, Portugal, 2012.

Invited Talks


  • M. Maniadakis, Do Robots Sense the Flow of Time? EUROCOGSCI 2011, Symposium Current advances on Time perception: Psychophysical, Neuronal, and Applied Perspectives, 21-24 May, 2011.
  • M. Maniadakis, Time Perception as a Key Ingredient of Robotic Intelligence, 1st International Workshop on the Multidisciplinary Aspects of Time Perception, 7-8 October, 2010.
  • M. Maniadakis, Panos Trahanias and Jun Tani, Self-organizing neural mechanisms for higher-order cognitive functions in human prefrontal cortex, Brain Lunch Seminar, RIKEN, 31 July 2009.

  • Other


  • M. Maniadakis, P. Trahanias, Executive Control in Artificial Agents, ERCIM News, 84, 32-33, 2011
  • M. Maniadakis, P. Trahanias, High Level Cognition for Artificial Agents in FORTH Retreat, Loutra Kyllinis, Greece, October 2009.
  • M. Maniadakis, J. Tani, Executive Control Dynamics, in RIKEN-BSI Retreat, 2008.
  • M. Maniadakis, J. Tani, Investigating Mental Shifting Mechanisms in Dynamical Systems, in RIKEN-BSI Retreat, 2007.
  • M. Maniadakis, Hierarchical Cooperative CoEvolution: A New Tool to Assist Brain Modeling Efforts, RIKEN BSI, December 14, 2006.
  • M. Maniadakis, P. Trahanias, Mechanisms for Cognition Development Inspired by the Mammalian Paradigm, ERCIM News, 55, 12-13, 2003.

  • Free Time


    In my free time, I enjoy cooking for friends and myself.
    I love greek traditional food with gourmet touches, but I am also fun of asian and particularly japanese food!
    I am now trying to train my 18-month-old daughter in liking gourmet dishes. This is a top secret, you know, but my wife doesn't. So please say nothing if you meet her around. ;-)

    In addition to cooking, I had co-founded the website foodadvisor.gr (unfortunately not running anymore) that was dedicated in reviewing restaurants around Greece.