Neuromorphic Computing for Development and Learning Workshop (NCDL)
International Conference on Development and Learning (ICDL)
Full-Day Workshop, 16 September 2025
Organizers
Dr. Giulia D'Angelo
Czech Technical University in Prague
Dr. Alexander Hadjiivanov
Netherlands eScience Center, Netherlands
Matthias Kampa
Zurich University of Applied Sciences
Dr. James Knight
University of Sussex
Prof. Yulia Sandamirskaya
Zurich University of Applied Sciences
Assistants
Olha Vedmedenko
Bachelor student, CTU
Lukáš Bartůněk
Master student, CTU
About the Workshop
The Neuromorphic Computing for Development and Learning Workshop is a full-day event uniting experts from academia and industry to explore advances in neuromorphic computing and developmental learning. The workshop focuses on brain-inspired sensing and computing, particularly spiking neural networks (SNNs), which enable efficient, adaptive, real-time processing. Topics include event-driven sensing, visual navigation, spike-based and contrastive learning, and neuromorphic architectures, highlighting their role in sensorimotor and cognitive development. Keynotes, poster sessions, and industry demos will showcase applications in robotics and sensory technologies, emphasizing perception, attention, and decision-making. Hands-on tutorials will offer practical experience in selective attention, perception, and embodied learning. The day concludes with a synthesis of insights and future research directions.
Keynote Speakers
Dr. Arren Glover
Arren Glover is a Technologist in the Event Driven Perception for Robotics research line (www.edpr.iit.it) at the Italian Institute of Technology. He obtained a Bachelors in Mechatronic Engineering (Honours) from the University of Queensland, Australia, and a Ph.D. in developmental robotics and on-line learning from the Queensland University of Technology, Australia. His interest is in real-time and online robotics with neuromorphic vision, exploiting neuromorphic technologies in robotics, space, and healthcare. He has worked on 6-DoF object pose tracking, human pose estimation, eye-tracking, optical flow, depth estimation, and reinforcement learning.
Dr. Arren Glover
Technologist at IIT, Italy. Expert in Event-Driven Perception.
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Prof. Thomas Nowotny
Thomas Nowotny has a background in theoretical and mathematical physics, with a Diplom (MSc) in theoretical Physics at Georg-August Universität Göttingen and a PhD in theoretical Physics at Universität Leipzig. After his PhD, he worked at the Institute for Nonlinear Science at the University of California, San Diego where he conducted research in Computational Neuroscience and bio-inspired AI. In 2007, he moved to the University of Sussex as an RCUK Academic Fellow and rapidly climbed the ranks to Professor of Informatics in the School of Engineering and Informatics. He is the head of the AI research group and one of two directors of the “Sussex AI” Centre of Excellence. His research spans insect olfaction, artificial olfaction, insect navigation, insect-inspired machine learning models, hybrid brain-computer systems and neuromorphic computing. He is the creator of the research software STDPC for hybrid brain-computer experimentation and GeNN/mlGeNN for simulating spiking neural networks and performing event-based machine learning. His recent work is focused on developing event-based neural networks that run on neuromorphic accelerators to save orders of magnitude of energy in machine learning.
Prof. Thomas Nowotny
Professor of Informatics at University of Sussex, UK.
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Dr. Chiara De Luca
Chiara De Luca is a physicist who earned her MSc in Physics and PhD in Behavioural Neuroscience from La Sapienza University of Rome. Now, she is a postdoctoral researcher at the Digital Society Initiative and the Institute of Neuroinformatics, University of Zurich and ETH Zurich, leading a project on applying neuromorphic learning systems to agriculture.
Dr. Chiara De Luca
Senior Researcher at Digital Society Initiative, Zurich, Switzerland.
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Dr. Arthur Aubret
Arthur Aubret is a postdoctoral researcher at the Frankfurt Institute for Advanced Studies. His research focuses on understanding the learning mechanisms that shape high-level visual representations in humans and machines, with a particular emphasis on developmental, bio-inspired, and self-supervised learning models. He holds a Ph.D. in computer science from Université Claude Bernard Lyon 1, where he studied intrinsic motivation and hierarchical reinforcement learning. His recent work explores how principles from early human development, such as temporal continuity and active object exploration, can support the emergence of robust and semantic object representations.
Dr. Arthur Aubret
Senior Researcher at Frankfurt Institute for Advanced Studies, Germany.
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Dr. Luca Peres
Luca obtained his PhD in computer science in 2022 at the University of Manchester exploring real-time simulations of large scale biologically-representative spiking neural networks on neuromorphic hardware. He then continued for a postdoctoral position in the same institution, working on event-driven sensing and processing for computer vision in the scope of edge applications. Luca’s main interests are in low-power sensing and processing, with focus on event-based sensor fusion applications and in-sensor and near-sensor computing. In addition, Luca is interested in exploring novel biologically-inspired architectures with the intent of producing more reliable and low-power systems aiming to overcome the von Neumann bottleneck.
Dr. Luca Peres
Lecturer at University of Manchester, UK.
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Dr. Srikanth Ramaswamy
Dr. Srikanth Ramaswamy, is a Marie Curie Fellow, a Lister Prize Fellow and an Assistant Professor in computational neuroscience at Newcastle University. He is also a Fulbright Scholar at MIT and a Theoretical Sciences Scholar at OIST. He directs the Neural Circuits Laboratory at Newcastle University. His research focuses on the role of neuromodulators in shaping cognition in biological neural networks and building biologically-informed neural network models. He is a founding scientist of the Blue Brain Project at Ecole Polytechnique Federale De Lausanne (EPFL). He earned his PhD at the EPFL in computational neuroscience, where he developed data-driven modelling frameworks for biologically detailed digital models of neural networks. As a scientist of colour, Dr Ramaswamy is passionately committed to promoting diversity, equity, and inclusion and is a founding member of the ALBA network, where he leads efforts to advance DEI in neuroscience, including launching the ALBA diversity podcast series in late 2020, highlighting the stories of emerging neuroscientists from underrepresented backgrounds.
Dr. Srikanth Ramaswamy
Academic Track Fellow, Newcastle University, UK.
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Dr. Katarzyna (Kasia) Kożdoń - Innatera
Dr. Katarzyna (Kasia) Kożdoń is a Strategic Business Development and Solutions Manager at Innatera, where she connects user needs with engineering to bring neuromorphic processors into real-world edge AI applications. She holds a PhD in AI from University College London, specialising in spiking neural networks and evolutionary algorithms. Kasia is also an Honorary Lecturer at UCL and serves on the Programme Committee of the International Society for Artificial Life.
Dr. Katarzyna (Kasia) Kożdoń - Innatera
Strategic Business Development & Solutions Manager, Netherlands.
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Dr. Thomas Ortner
Thomas Ortner is a Research Scientist at IBM Research Europe (Switzerland) in the Emerging Computing and Circuits group. He holds a PhD in Computer Science and multiple MSc degrees from Graz University of Technology, Austria. His research centers on developing efficient, stateful models for sequence processing that go beyond transformer architectures, leveraging concepts from neuro-inspired AI. He also works on novel learning algorithms and their application to NLP, time series, and speech.
Dr. Thomas Ortner - IBM Research
Research Scientist at IBM Research Europe
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Content
Traditional AI struggles with real-time adaptability, continual learning, and energy efficiency. Neuromorphic computing addresses these challenges through event-driven architectures and spiking neural networks (SNNs), enabling low-power, real-time processing ideal for robotics and smart sensors. By mimicking biological systems, neuromorphic models process only relevant environmental changes, reducing data load and supporting adaptive, context-aware behavior. SNNs add mechanisms like synaptic plasticity and temporal coding for experience-driven learning. Aligned with the goals of the International Conference on Development and Learning (ICDL), this workshop explores how neuromorphic principles support lifelong, embodied learning in autonomous agents. Topics include contrastive learning, continual adaptation, and the role of embodiment in cognitive systems. The program features both theoretical discussions and hands-on sessions on neuromorphic perception, navigation, and sensorimotor integration, fostering collaboration across neuroscience, robotics, psychology, and AI.
NCDL Topics
The workshop explores a wide range of topics, including BUT NOT LIMITED TO:
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Neural inspiration for learning systems: Synaptic plasticity vs. gradient descent and other optimization algorithms
Bio-plausible backpropagation
Local learning rules
Contrastive learning
Surprise-driven learning (Wulfram Gerstner)
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Continual learning
Low-data learning
Fast learning, one-shot/few-shot learning
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Neuromorphic computing: Bringing cognition back to robotics
Neural cognitive architectures
Autonomy and learning in a closed sensorimotor loop; Embodiment
Workshop Schedule
Time
Session
08:50-09:00
Dr. Giulia D'Angelo - Welcome and intro to the workshop
09:00-09:30
Keynote: Dr. Arren Glover (confirmed - in person) - Robot Perception with Bio-inspired Event Cameras + Q/A
09:30-10:00
Keynote: Prof. Thomas Nowotny (confirmed - in person) - How to efficiently train Spiking Neural Networks on machine learning tasks + Q/A
10:00-10:30
Keynote: Dr. Chiara De Luca (confirmed - in person) - Learning on the edge: local and online neuromorphic intelligence + Q/A
10:30-11:00
Coffee Break + Intro Poster Session
11:00-11:30
Keynote: Dr. Arthur Aubret (confirmed - in person) - Bio-inspired Self-Supervised Learning of Visual Object Representations + Q/A
11:30-12:00
Keynote: Dr. Luca Peres (confirmed - in person) - Events are all you need + Q/A
12:00-12:30
Keynote: Prof. Srikanth Ramaswamy (confirmed - in person) - What can artificial neural networks learn from biological neuromodulatory systems? + Q/A
12:30-14:00
Lunch
14:00-14:30
Panel Discussion or Debate: Interdisciplinary Approaches to Neuromorphic Systems
14:30-15:00
Keynote: Katarzyna (Kasia) Kożdoń (confirmed - in person) - Innatera - The Reality Gap: From Brain-Inspired Learning to Deployable Neuromorphic Systems + Q/A
15:00-15:30
Keynote: Thomas Ortner (confirmed - in person) - IBM Zurich - Neuro-inspired computing: Merging neuroscience and AI
15:30-16:30
Coffee Break + Poster Session
16:30-17:00
Tutorial 1: Selective Attention in Neuromorphic Systems - Giulia D'Angelo (confirmed - in person)
17:00-17:30
Tutorial 2: Pyrception: A Neuromorphic Approach to Perception - Alexander Hadjiivanov (confirmed - in person)
17:30-18:00
Dr. Giulia D'Angelo - Wrap-up and Closing Remarks
Accepted Abstracts - Poster Session
Browse the accepted contributions for the poster session
