Publications
2023:
Low-latency monocular depth estimation using event timing on neuromorphic hardware.
Chiavazza, S.; Meyer, S. M.; & Sandamirskaya, Y. Computer Vision and Pattern Recognition (CVPR) Workshop on Event Based Vision. 2023 [link]
2022:
Rethinking computing hardware for robots.
Sandamirskaya, Y.
Science Robotics, 7(67), 2022 [pdf]
Neuromorphic computing hardware and neural architectures for robotics.
Sandamirskaya, Y.; Kaboli, M.; Conradt, J.; & Celikel, T.
Science Robotics, 7(67), 2022 [pdf].
Sparse Vector Binding on Spiking Neuromorphic Hardware Using Synaptic Delays.
Renner, A.; Sandamirskaya, Y.; Sommer, F. T.; Frady, E. P.
In International Conference on Neuromorphic Systems (ICONS), 2022 [pdf]
Interactive continual learning for robots: a neuromorphic approach.
Hajizada, E.; Berggold, P.; M. Ioacono; Glover, A.; & Sandamirskaya, Y.
In International Conference on Neuromorphic Systems (ICONS), 2022 [pdf]
Fine-tuning Deep Reinforcement Learning Policies with r-STDP for Domain Adaptation.
Akl, M.; Sandamirskaya, Y.; Ergene, D.; Walter, F.; & Knoll, A.
In International Conference on Neuromorphic Systems (ICONS), 2022 [pdf]
Neuro-inspired electronic skin for robots.
Liu, F.; Deswal, S.; Christou, A.; Sandamirskaya, Y.; Kaboli, M.; & Dahiya, R.
Science Robotics, 7(67), 2022 [pdf]
What does it mean to represent? Mental representations as falsifiable memory patterns.
Parra-Barrero, E. & Sandamirskaya, Y.
Seeds of Science, 2022 [link] arXiv preprint arXiv:2203.02956.
2021:
Effective and natural human-robot interaction requires multidisciplinary research.
Kragic, D.; & Sandamirskaya, Y.
Science Robotics, 6(58), 2021 [pdf]
Advancing neuromorphic computing with Loihi: A survey of results and outlook.
Davies, M.; Wild, A.; Orchard, G.; Sandamirskaya, Y.; Fonseca Guerra, G.A.; Joshi, P.; Plank, P.; Risbud, S. R.
Proceedings of the IEEE, 109, no. 5,pp. 911-934, 2021 [link]
Event-driven Vision and Control for UAVs on a Neuromorphic Chip
Vitale, A.; Renner, A.; Nauer, C.; Scaramuzza, D.; & Sandamirskaya, Y.
IEEE International Conference on Robotics and Automation (ICRA), 2021 [pdf]
Porting Deep Spiking Q-Networks to Neuromorphic Chip Loihi
Akl, M.; Sandamirskaya, Y.; Walter, F.; & Knoll, A.
International Conference on Neuromorphic Systems (ICONS), 2021 [pdf]
2020:
An on-chip spiking neural network for estimation of the head pose of the iCub robot.
Kreiser, R.; Renner, A.; Leite, V. R.; Serhan, B.; Bartolozzi, C.; Glover, A., & Sandamirskaya, Y. Frontiers in Neuroscience, 14, 551, 2020 [link]
Toward neuromorphic control: A spiking neural network based PID controller for UAV.
Stagsted, R., Vitale, A., Binz, J., Bonde Larsen, L., & Sandamirskaya, Y.
Robotics Science and Systems (RSS), virtual, 2020 [pdf]
Event-based PID controller fully realized in neuromorphic hardware: A one DoF study.
Stagsted, R. K., Vitale, A., Renner, A., Larsen, L. B., Christensen, A. L., & Sandamirskaya, Y.
In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 10939-10944, 2020 [pdf]
Error estimation and correction in a spiking neural network for map formation in neuromorphic hardware.
Kreiser, R.; Waibel, G.; Armengol, N.; Renner, A. & Sandamirskaya, Y.
IEEE International Conference on Robotics and Automation (ICRA), 2020 [pdf]
Visual Pattern Recognition with on On-chip Learning: towards a Fully Neuromorphic Approach.
Baumgartner, S.; Renner, A.; Kreiser, R.; Liang, D.; Indiveri, G. & Sandamirskaya, Y. IEEE International Symposium on Circuits and Systems (ISCAS), 2020 [pdf]
Event-Based Attention and Tracking on Neuromorphic Hardware.
Renner, A.; Evanusa, M.; Orchard, G. & Sandamirskaya, Y.
2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Demo, 2020 [pdf]
A digital multiplier-less neuromorphic model for learning a context dependent task.
Asgari, H.; Mazloom-Nezhad Maybodi, B.; Kreiser, R. & Sandamirskaya, Y.
2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020 [pdf]
A Real-Time Retinomorphic Simulator Using a Conductance-Based Discrete Neuronal Network.
Baek, S.; Eshraghian, J. K.; Thio, W.; Sandamirskaya, Yulia abd Ho-Ching Iu, H. & Lu, W.
2nd IEEE International Conference on Aritficial Intelligence Circuits and Systems (AICAS), 2020 [pdf]
Digital multiplier-less implementation of high precision SDSP and synaptic strength-based STDP
Asgari, H.; Mazloom-Nezhad Maybodi, B.; Kreiser, R. & Sandamirskaya, Y.
International Journal of Circuit Theory and Applications, 2020, in press [pdf]
2019:
Neural State Machines for Robust Learning and Control of Neuromorphic Agents.
Liang, D.; Kreiser, R.; Nielsen, C.; Qiao, N.; Sandamirskaya, Y. & Indiveri, G. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2019 [url] [pdf]
Closing the Accuracy Gap in an Event-Based Visual Recognition Task.
Rückauer, B.; Känzig, N., Liu, Sh-Ch.; Delbruck, T.; & Sandamirskaya, Y.
https://arxiv.org/abs/1906.08859
Autonomous Sequence Generation for a Neural Dynamic Robot: Scene Perception, Serial Order, and Object-Oriented Movement.
Tekülve, J.; Fois, Adrien; Sandamirskaya, Y. & Schöner, G. Frontiers in Neurorobotics, 2019, 13, 95 [url] [pdf]
Parameter Optimization and Learning in a Spiking Neural Network for UAV Obstacle Avoidance Targeting Neuromorphic Processors.
Salt, L; Howard D.; Indiveri, G. & Sandamirskaya, Y. IEEE Transactions on Neural Networks and Learning Systems. p. 1-14, 2019, early access [url] [pdf]
The Importance of Space and Time for Signal Processing in Neuromorphic Agents: The Challenge of Developing Low-Power Autonomous Agents that Interact with the Environment.
Indiveri, G. & Sandamirskaya, Y. IEEE Signal Processing Magazine, Vol. 36, Issue 6, 2019 [url] [pdf]
Self-calibration and learning on chip: towards neuromorphic robots.
Kreiser, R.; Waibel, G.; Renner, A. & Sandamirskaya, Y.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Breaking news, 2019 [pdf]
Error-driven learning for self-calibration in a neuromorphic path integration system.
Kreiser, R.; Renner, A. & Sandamirskaya, Y. Robust AI for Neurorbotics, Edinburgh, UK, 2019 [url] [pdf]
Event-based attention and tracking on neuromorphic hardware.
Renner, A.; Evanusa, M. & Sandamirskaya, Y.
IEEE Computer Vision and Pattern Recognition (CVPR), ``Event-based vision'' workshop, 2019 [pdf]
Adaptive motor control and learning in a spiking neural network, fully realised on a mixed-signal analog/digital neuromorphic processor.
Glatz, S.; Kreiser, R.; Martel, J. N. P.; Qiao, N. & Sandamirskaya, Y. IEEE International Conference on Robotics and Automation, ICRA, 2019 [pdf]
Robust Learning and Recognition of Visual Patterns in Neuromorphic Electronic Agents.
Liang, D.; Kreiser, R.; Nielsen, C.; Qiao, N.; Sandamirskaya, Y. & Indiveri, G.
IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2019, 71-75 [pdf]
2018:
Organising Sequential Memory in a Neuromorphic Device Using Dynamic Neural Fields.
Kreiser, R.; Aathmani, D.; Qiao, N.; Indiveri, G. & Sandamirskaya, Y. Frontiers in Neuromorphic Engineering, 2018 [pdf]
Pose Estimation and Map Formation with Spiking Neural Networks: towards Neuromorphic SLAM.
Kreiser, R.; Pienroj, P.; Renner, A. & Sandamirskay, Y. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018 [pdf]
Real-Time Depth from Focus on a Programmable Focal Plane Processor.
Martel, J. N.; Müller, L. K.; Carey, S. J.; Müller, J.; Sandamirskaya, Y. & Dudek, P. IEEE Transaction on Circuits and Systems--I, 2018, 65, 925-934 [pdf]
An Active Approach to Solving the Stereo Matching Problem using Event-Based Sensors.
Martel, J. N.; Müller, J.; Conradt, J. & Sandamirskaya, Y. EEE International Symposium on Circuits and Systems (ISCAS), 2018 [pdf]
A Neuromorphic approach to path integration: a head direction spiking neural network with visually-driven reset.
Kreiser, R., Cartiglia, M., Martel, J. N. P., Conradt, J. & Sandamirskaya, Y. IEEE Symposium for Circuits and Systems, ISCAS, 2018 [pdf]
2017:
On-chip unsupervised learning in Winner-Take-All networks of spiking neurons.
Kreiser, R.; Moraitis, T.; Sandamirskaya, Y. & Indiveri, G. Biological Circuits and Systems (BioCAS), 2017 [pdf]
A neuromorphic controller for a robotic vehicle equipped with a dynamic vision sensor.
Blum, H.; Dietmüller, A.; Milde, M.; Conradt, J.; Indiveri, G. & Sandamirskaya, Y. Robotics Science and Systems Conference, RSS, 2017 [pdf]
Obstacle avoidance and target acquisition for robot navigation using a mixed signal analog/digital neuromorphic processing system.
Milde, M. B.; Blum, H.; Dietmüller, A.; Sumislawska, D.; Conradt, J.; Indiveri, G. & Sandamirskaya, Y. Frontiers in Neurorobotics, 2017. http://journal.frontiersin.org/article/10.3389/fnbot.2017.00028/full [pdf]
Obstacle avoidance and target acquisition in mobile robots equipped with neuromorphic sensory-processing systems.
Milde, M.; Dietmüller, A.; Blum, H.; Indiveri, G.; & Sandamirskaya, Y. IEEE International Symposium on Circuits and Systems (ISCAS), 2017 [pdf]
Obstacle avoidance with Locust Giant Looming Detector neuron: towards a neuromorphic UAV implementation.
Salt, L., Indiveri, G., & Sandamirskaya, Y. IEEE International Symposium on Circuits and Systems (ISCAS), 2017 [pdf]
Dynamic Neural Fields with Intrinsic Plasticity.
Strub, C.; Schöner, G.; Wörgötter, F. & Sandamirskaya, Y. Frontiers in Computational Neuroscience, 11, 74, 2017 [pdf]
Learning Temporal Intervals with Neural Dynamics.
Duran, B. & Sandamirskaya, Y. IEEE Transactions on Cognitive and Developmental Systems. Issue 99, 2017. http://dx.doi.org/10.1109/TCDS.2017.2676839 [pdf]
Affective–associative two-process theory: a neurocomputational account of partial reinforcement extinction effects.
Lowe, R.; Almèr, A.; Billing, E.; Sandamirskaya, Y. & Balkenius, C. Biological Cybernetics, 2017, 11, 365-388 [pdf]
2016:
A Neuromorphic Approach for tracking using Dynamic Neural Fields on a Programmable Vision-chip.
Martel, J. & Sandamirskaya, Y. International Conference on Distributed and Smart Cameras (ICDSC), 2016 [pdf]
2015:
Learning to look and looking to remember: a neural-dynamic embodied model for generation of saccadic gaze shifts and memory formation.
Sandamirskaya, Y. & Storck, T. In Artificial Neural Networks, Springer, 2015, 4 [pdf]
Learning to Reach after Learning to Look: a Study of Autonomy in Learning Sensorimotor Transformations.
Rudolf, C., Storck, T. & Sandamirskaya, Y. In IJCNN, 2015 [pdf]
Simultaneous Planning and Action: Neural-dynamic Sequencing of Elementary Behaviours in Robot Navigation.
Billing, E.; Lowe, R. & Sandamirskaya, Y. Adaptive Behavior, 9, 2015, 1-22 [pdf]
Parsing of action sequences: A neural dynamics approach.
Lobato, D.; Sandamirskaya, Y.; Richter, M. & Schöner, G. Paladyn Journal of Behavioural Robotics, Vol. 6, 2015 [pdf]
NARLE: Neurocognitive architecture for the autonomous task recognition, learning, and execution
Sandamirskaya, Y. & Burtsev, M. BICA, 2015, 13 [pdf]
2014:
Neural-Dynamic Architecture for Looking: from Visual to Motor Target Representation for Memory Saccades.
Sandamirskaya, Y. & Storck, T. 12th IEEE International Conference on Development and Learning (ICDL), 2014 [pdf]
Learning to Look: a Dynamic Neural Fields Architecture for Gaze Shift Generation.
Bell, C.; Storck, T. & Sandamirskaya, Y. International Conference for Artificial Neural Networks (ICANN), 2014 [pdf]
Using Haptics to Extract Object Shape from Rotational Manipulations.
Strub, C.; Wörgötter, F.; Ritter, H.; & Sandamirskaya, Y. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2014 [pdf]
Correcting Pose Estimates during Tactile Exploration of Object Shape: a Neuro-robotic Study.
Strub, C.; Wörgötter, F.; Ritter, H.; & Sandamirskaya, Y. 12th IEEE International Conference on Development and Learning (ICDL), 2014 [pdf]
Reinforcement and Shaping in Learning Action Sequences with Neural Dynamics.
Luciw, M.; Sandamirskaya, Y.; Kazerounian, S.; Schmidhuber, J, & Schöner, G. 12th IEEE International Conference on Development and Learning (ICDL), 2014 [pdf]
A Neural Dynamic Model of Associative Two-Process Theory: The Differential Outcomes Effect and Infant Development.
Lowe, R.; Sandamirskaya, Y.; & Billing, E. 12th IEEE International Conference on Development and Learning (ICDL), 2014, [pdf]
Reinforcement-Driven Shaping of Sequence Learning in Neural Dynamics.
Luciw, M.; Kazerounian, S.; Sandamirskaya, Y.; Schöner, G; & Schmidhuber, J. Simulation of Adaptive Behavior (SAB) , 2014 [pdf]
Learning the Condition of Satisfaction of an Elementary Behavior in Dynamic Field Theory.
Luciw, M.; Kazerounian, S.; Lakhmann, K.; Richter, M. & Sandamirskaya, Y. Robotics Paladyn: Journal of Behavioral Robotics, Vol. 6, 2015 [pdf]
Autonomous Neural Dynamics to Test Hypotheses in a Model of Spatial Language.
Richter, M.; Lins, J.; Schneegans, S.; Sandamirskaya, Y. & Schöner, G. The Annual Meeting of the Cognitive Science Society, CogSci, 2014 [pdf]
2013:
Dynamic Neural Fields as a Step Towards Cognitive Neuromorphic Architectures.
Sandamirskaya, Y. Frontiers in Neuroscience, Vol. 7, pp. 276, 2013 (http://www.frontiersin.org/journal/10.3389/fnins.2013.00276/abstract) [pdf]
Using Dynamic Field Theory to Extend the Embodiment Stance toward Higher Cognition.
Sandamirskaya, Y.; Zibner, S.; Schneegans, S.; & Schöner, G. New Ideas in Psychology, 2013 (http://dx.doi.org/10.1016/j.newideapsych.2013.01.002) [pdf]
Learning Sensorimotor Transformations with Dynamic Neural Fields.
Sandamirskaya, Y.; Conradt, J. International Conference on Artificial Neural Networks (ICANN), 2013 [pdf]
Increasing Autonomy of Learning Sensorimotor Transformations with Dynamic Neural Fields.
Sandamirskaya, Y.; Conradt, J. IEEE International Conference on Robotics and Automation (ICRA), Workshop on “Autonomous Learning -- from Machine Learning to Learning in Real-World Autonomous Systems”, 2013 [pdf]
Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics.
Kazerounian, S.; Luciw, M; Richter, M; & Sandamirskaya, Y. International Joint Conference on Neural Networks (IJCNN), 2013 [pdf]
Learning the Perceptual Conditions of Satisfaction of Elementary Behaviors.
Luciw, M.; Kazerounian, S.; Lakhmann, K.; Richter, M. & Sandamirskaya, Y. Robotics: Science and Systems (RSS), Workshop "Active Learning in Robotics: Exploration, Curiosity, and Interaction", 2013 [pdf]
2012:
A Dynamic Field architecture for generation of hierarchically organized sequences.
Duran, B.; Sandamirskaya, Y.; & Schöner, G. International Conference on Artificial Neural Networks (ICANN), 2012 [pdf]
Neural Dynamics of Hierarchically Organized Sequences: a Robotic Implementation.
Duran, B & Sandamirskaya, Y. Proceedings of 2012 IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2012 [pdf]
A robotic architecture for action selection and behavioral organization inspired by human cognition.
Richter, M.; Sandamirskaya, Y.; & Schöner, G. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012 [pdf]
A neural-dynamic architecture for flexible spatial language: intrinsic frames, the term “between”, and autonomy.
van Hengel, U.; Sandamirskaya, Y.; Schneegans, S. & Schöner, G. 21st IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2012, 2012 [pdf]
2011:
A neural-dynamic architecture for behavioral organization of an embodied agent.
Sandamirskaya, Y.; Richter, M. & Schöner, G. IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL EPIROB 2011), 2011 [pdf]
A Neurobehavioral Model of Flexible Spatial Language Behaviors.
Lipinski, J.; Schneegans, S.; Sandamirskaya, Y.; Spencer, J. & Schöner, G. Journal of Experimental Psychology: Learning, Memory, and Cognition (JEP:LMC), 2011 (http://psycnet.apa.org/psycinfo/2011-08228-001/) [pdf]
2010:
An embodied account of serial order: How instabilities drive sequence generation.
Sandamirskaya, Y. & Schöner, G. Neural Networks, Vol. 23, pp. 1164-1179 2010, (http://www.sciencedirect.com/science/article/pii/S0893608010001516) [pdf]
Serial order in an acting system: a multidimensional dynamic neural fields implementation.
Sandamirskaya, Y. & Schöner, G. Development and Learning, 2010. ICDL 2010. 9th IEEE International Conference on, 2010 [pdf]
Natural human-robot interaction through spatial language: a dynamic neural fields approach.
Sandamirskaya, Y.; Lipinski, J.; Iossifidis, I. & Schöner, G. 19th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN, 2010, 600-607 [pdf]
2009:
Swing it to the Left, Swing it to the Right: Enacting Flexible Spatial Language Using a Neurodynamic Framework.
Lipinski, J.; Sandamirskaya, Y. & Schöner, G. Cognitive Neurodynamics, special issue on Language Dynamics, 2009, 3 (http://link.springer.com/article/10.1007%2Fs11571-009-9096-y?LI=true) [pdf]
Behaviorally Flexible Spatial Communication: Robotic Demonstrations of a Neurodynamic Framework.
Lipinski, J.; Sandamirskaya, Y. & Schöner, G. KI 2009, Lecture Notes in Artificial Intelligence, Mertsching, B.; Hund, M. & Z., A. (Eds.), Berlin: Springer-Verlag, 2009, 5803, 257-264 [pdf]
Flexible Spatial Language Behaviors: Developing a Neural Dynamic Theoretical Framework.
Lipinski, J.; Sandamirskaya, Y. & Schöner, G. 9th International Conference on Cognitive Modeling, ICCM 2009. Manchester, UK, 2009 [pdf]
2008:
Dynamic Field Theory of Sequential Action: A Model and its Implementation on an Embodied Agent.
Sandamirskaya, Y. & Schöner, G. Development and Learning, 2008. ICDL 2008. 7th IEEE International Conference on, 2008 [pdf]
2006:
Dynamic Field Theory and Embodied Communication.
Sandamirskaya, Y. & Schöner, G. Modeling communication with robots and virtual humans, G. Wachsmuth, I. & Knoblich, G. (Eds.) Springer, 2006, 260-278 (http://link.springer.com/chapter/10.1007%2F978-3-540-79037-2_14?LI=true) [pdf]
Supervised MSc theses:
Müller, J.
Memory Stereo Depth Perception with Event Based Vision Sensors and Temporally Structured Light
D-ITET, ETH Zurich, May 2017
Renner, A.
Memory for serial order in spiking neural networks. MSc Thesis.
NSC Programm, INI, ETH Zurich and University of Zurich, Jan. 2017 [pdf]
English, G.
Spiking Neural Network Models for the Emergence of Patterned Activity in Grid Cell Populations. MSc Thesis.
NCS Programm, INI, ETH Zurich and University of Zurich, Oct. 2017
Parra Barrero, E.
Mismatch Detection Neural Circuit Applied to Navigation. MSc Thesis.
NSC Programm, INI, ETH Zurich and University of Zurich, Aug. 2017 [pdf]
Salt, L.
Optimising a Neuromorphic Locust Looming Detector for UAV Obstacle Avoidance. MSc Thesis.
School of Information Technology and Electrical Engineering, The University of Queensland, Nov. 2016