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DTSTART;TZID=America/Los_Angeles:20230404T080000
DTEND;TZID=America/Los_Angeles:20230404T090000
DTSTAMP:20260418T021644
CREATED:20230331T122014Z
LAST-MODIFIED:20230331T122032Z
UID:10000175-1680595200-1680598800@www.neuropac.info
SUMMARY:INRC Forum: Arto Nurmikko
DESCRIPTION:Efficient Decoding of Multipoint Spiking Events Recorded by A Network of Wireless Biosensors\n\n\nAbstract: Our lab is developing tools for brain-machine interfaces using a concept of spatially distributed wireless microsensors\, “neurograins” implanted in a functional cortical area of interest (motor\, auditory\, visual). When a given sensor detects a spiking event\, the signal is immediately sent to an external radio-frequency receiver as a binary “1”. Thus\, for a network of thousand neurograins\, one goal of an ongoing research project\, the received data at the external detector is a stream of spikes in which the cortical computations of interest are embedded. Based on our work on smaller ensembles (hundred neurograins)\, we have discovered a major computational bottleneck in detecting and decoding signals for large ensembles of neurograins for a real-time (wearable/portable brain-interface systems. In this work\, we explore and apply the Loihi platform to integrate the demodulation (time-series correlation) and neural population decoding (spike-timing based model) steps into one parallel process. \nBio: Prof. Arto Nurmikko is a L. Herbert Ballou University Professor of Engineering and Physics at Brown. He recived his degrees from University of California\, Berkeley\, and did postdoctoral work at the Hebrew University (Jerusalem) and MIT. Prof. Nurmikko’s research spans the areas of neuroengineering\, photonics\, microelectronics\, nanosciences\, and the translation of device research to new technologies in physical and life science applications. Currently\, his research interests are focused on implantable neural interfaces. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-arto-nurmikko/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230404T180000
DTEND;TZID=UTC:20230404T193000
DTSTAMP:20260418T021644
CREATED:20230127T223552Z
LAST-MODIFIED:20230127T223552Z
UID:10000008-1680631200-1680636600@www.neuropac.info
SUMMARY:Hands-on session with Sinabs and Speck
DESCRIPTION:Speaker bio: Gregor Lenz graduated with a Ph.D. in neuromorphic engineering from Sorbonne University. He thinks that technology can learn a thing or two from how biological systems process information. \nHis main interests are event cameras that are inspired by the human retina and spiking neural networks that mimic human brain in an effort to teach machines to compute a bit more like humans do. At the very least there are some power efficiency gains to be made\, but hopefully more! Also he loves to build open source software for spike-based machine learning. You can find more information on his personal website. \nHe is the maintainer of two open source projects in the field of neuromorphic computing\, Tonic and expelliarmus.
URL:https://www.neuropac.info/event/hands-on-session-with-sinabs-and-speck/
LOCATION:Online
CATEGORIES:Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230406T163000
DTEND;TZID=UTC:20230406T173000
DTSTAMP:20260418T021644
CREATED:20230127T222256Z
LAST-MODIFIED:20230828T170621Z
UID:10000040-1680798600-1680802200@www.neuropac.info
SUMMARY:Theory of Neuromorphic Computing
DESCRIPTION:Recurring discussion meeting by researchers interested in the theory of neuromorphic computing. \nHosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings\, please contact Arne Diehl: arne.diehl@donders.ru.nl.
URL:https://www.neuropac.info/event/theory-of-neuromorphic-computing/2023-04-06/
LOCATION:Online
CATEGORIES:Discussion
ORGANIZER;CN="Arne Diehl":MAILTO:arne.diehl@donders.ru.nl
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230411
DTEND;VALUE=DATE:20230415
DTSTAMP:20260418T021644
CREATED:20230114T164825Z
LAST-MODIFIED:20230114T164825Z
UID:10000001-1681171200-1681516799@www.neuropac.info
SUMMARY:NICE
DESCRIPTION:The 2023 Neuro-Inspired Computing Elements (NICE) Conference is the 10th annual meeting of researchers in the neural computing field. Like previous editions\, NICE 2023 will focus on the interplay between neural theory\, neural algorithms\, neuromorphic architectures and hardware\, and applications for neural computing technology. \nNICE aims to involve diverse participation from all over the world and bring together research communities with universities\, government\, and industry.
URL:https://www.neuropac.info/event/nice/
LOCATION:University of Texas at San Antonio\, San Antonio\, TX\, United States
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230411T080000
DTEND;TZID=America/Los_Angeles:20230411T090000
DTSTAMP:20260418T021644
CREATED:20230416T091845Z
LAST-MODIFIED:20230416T091845Z
UID:10000176-1681200000-1681203600@www.neuropac.info
SUMMARY:INRC Forum: Guido de Croon
DESCRIPTION:Neuromorphic sensing and processing for small\, autonomous drones\n\n\n\nAbstract: Small drones are promising for many applications\, such as search-and-rescue\, greenhouse monitoring\, or keeping track of stock in warehouses. Since they are small\, they can fly in narrow areas. Moreover\, their light weight makes them very safe for flight around humans. However\, making such small drones fly completely by themselves is an enormous challenge due to the extreme resource restrictions in terms of sensing and processing. In my talk\, I will discuss the promises of novel neuromorphic sensing and processing technologies for autonomous flight of small drones\, illustrating this with recent experiments from our lab. Specifically\, I will delve into our multi-year effort to create a fully neuromorphic vision-to-control pipeline\, going from raw events to low-level control commands. Recently\, we have achieved this feat for optical-flow-based ego-motion estimation and control\, implementing the spiking neural network on the Loihi Kapoho bay onboard of a free-flying drone. \n\n\n\nBio: Guido de Croon received his M.Sc. and Ph.D. in the field of Artificial Intelligence (AI) at Maastricht University\, the Netherlands. His research interest lies with computationally efficient\, bio-inspired algorithms for robot autonomy\, with an emphasis on computer vision. Since 2008 he has worked on algorithms for achieving autonomous flight with small and light-weight flying robots\, such as the DelFly flapping wing MAV. In 2011-2012\, he was a research fellow in the Advanced Concepts Team of the European Space Agency\, where he studied topics such as optical flow based control algorithms for extraterrestrial landing scenarios. After his return at TU Delft\, his work has included fully autonomous flight of a 20-gram DelFly\, a new theory on active distance perception with optical flow\, and a swarm of tiny drones able to explore unknown environments. Currently\, he is Full Professor at TU Delft and scientific lead of the Micro Air Vehicle lab (MAVLab) of Delft University of Technology. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen-2-2/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230418T080000
DTEND;TZID=America/Los_Angeles:20230418T090000
DTSTAMP:20260418T021644
CREATED:20230416T091939Z
LAST-MODIFIED:20230416T091939Z
UID:10000177-1681804800-1681808400@www.neuropac.info
SUMMARY:INRC Forum: Akshit Saradagi
DESCRIPTION:Neuromorphic sensing in sub-terranean environments and neuromorphic solvers for model predictive control\nAbstract: In this talk\, I will be presenting some recent results in Neuromorphic Engineering from the Robotics and AI group at Luleå University of Technology\, Sweden.\nIn the first half of my talk\, I will be presenting a novel LiDAR and event camera fusion framework for fast and precise object and human detection in subterranean (SubT) environments. The fusion framework caters to the wide variety of adverse lighting conditions found in SubT environments\, such as low or no light\, high-contrast zones and in the presence of blinding light sources. The proposed fusion uses intensity filtering and K-means clustering on the LiDAR point cloud and frequency filtering and connectivity clustering on the events induced in an event camera by the returning LiDAR beams. The fusion framework was experimentally validated in a real SubT environment (a mine) with a Pioneer 3AT mobile robot. The experimental results show real-time performance for human detection and the NMPC-based controller allows for reactive tracking of a human or object of interest\, even in complete darkness.\nIn the second half of the talk\, I will be presenting our preliminary results on using neuromorphic solvers for solving quadratic programs arising in Model Predictive Control (MPC). More specifically\, we employed the floating-point LAVA QP solver\, which emulates the Proportional-Integral Projected Gradient (PIPG) Method for solving QP problems\, to solve terminally constrained MPC problems. The objective function in linear MPC problems being strongly convex\, the LAVA QP solver ensures that the distance to optimum and the constraint violation converge to zero at the rate of O(1/k^2) and O(1/k^3) respectively\, with ‘k’ being the number of solver iterates. Given this peculiar convergence property of the solver\, I will present a sketch of our proof for asymptotic stability of the closed loop system\, along with the simulation-based validation. \nBio: Akshit Saradagi is a Postdoctoral researcher in the Robotics and AI group at Luleå University of Technology\, Sweden. He received his M.S and Ph.D dual degree from the Indian Institute of Technology Madras (IITM)\, Chennai\, India. His current research focusses on distributed control of multi-agent systems\, control barrier functions-based safety guarantees in Robotics\, applications of Neuromorphic Computing in Robotics and control under resource constraints. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen-2-3/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20230418T210000
DTEND;TZID=Europe/Amsterdam:20230418T223000
DTSTAMP:20260418T021644
CREATED:20230320T142706Z
LAST-MODIFIED:20230320T142706Z
UID:10000033-1681851600-1681857000@www.neuropac.info
SUMMARY:NeuroPAC Seminar: Forum on Neuromorphic Navigation
DESCRIPTION:Panelists: \n\nAndrew Davidson\, Imperial College\, London\nKostas Daniilidis\, University of Pennsylvania\nMichael Milford\, Queensland University of Technology\n\nJoin the seminar: https://umd.zoom.us/j/93344217202 \nMore information: https://www.neuropac.info/seminars/
URL:https://www.neuropac.info/event/neuropac-seminar-forum-on-neuromorphic-navigation/
LOCATION:Online
CATEGORIES:Symposium,Talk
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230420T163000
DTEND;TZID=UTC:20230420T173000
DTSTAMP:20260418T021644
CREATED:20230127T222256Z
LAST-MODIFIED:20230828T170621Z
UID:10000041-1682008200-1682011800@www.neuropac.info
SUMMARY:Theory of Neuromorphic Computing
DESCRIPTION:Recurring discussion meeting by researchers interested in the theory of neuromorphic computing. \nHosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings\, please contact Arne Diehl: arne.diehl@donders.ru.nl.
URL:https://www.neuropac.info/event/theory-of-neuromorphic-computing/2023-04-20/
LOCATION:Online
CATEGORIES:Discussion
ORGANIZER;CN="Arne Diehl":MAILTO:arne.diehl@donders.ru.nl
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230425T080000
DTEND;TZID=America/Los_Angeles:20230425T090000
DTSTAMP:20260418T021644
CREATED:20230425T072512Z
LAST-MODIFIED:20230425T072512Z
UID:10000178-1682409600-1682413200@www.neuropac.info
SUMMARY:INRC Forum: James Knight
DESCRIPTION:Efficient training of sparse SNN classifiers using GeNN\nAbstract:Intuitive and easy to use application programming interfaces such as Keras have played a large part in the rapid acceleration of ANN-based machine learning. We want to unlock the potential of spike-based machine learning in the same way\, so here we present mlGeNN\, an easy way to define\, train and test spiking neural networks using GeNN — our efficient GPU-accelerated SNN simulator. Using GeNN\, we demonstrate that we can use e-prop to train recurrent SNN classifiers on datasets including the Spiking Heidelberg Digits (SHD) and DVS gesture. We show that these classifiers can not only offer comparable performance to LSTMs but are up to 7× faster when performing inference on the same GPU hardware. As GeNN is designed to exploit sparse connectivity\, by replacing the dense recurrent connectivity in classifier models with random sparse connectivity\, we can reduce the time taken to train such models by almost 10× — although this results in some reduction in classification accuracy. However\, in biological brains\, alongside the changes to the strength of existing synapses driven by synaptic plasticity\, structural plasticity prunes unused synapses and forms new ones. The Deep-R learning rule provides a framework for combining gradient-based learning with structural plasticity and by combining Deep-R with e-prop\, we demonstrate that the aforementioned reduction in classification accuracy can be eliminated\, even in very sparsely connected models. \nBio: Jamie Knight received his BEng degree in Electronic Engineering from the University of Warwick in 2006. After working as a games developer for several years\, he received an MPhil in Advanced Computer Science from the University of Cambridge in 2013 and a PhD in Computer Science from the University of Manchester in 2016. His doctoral work focussed on using the SpiNNaker neuromorphic supercomputer to simulate large-scale computational neuroscience models with synaptic plasticity. Since 2017 Jamie has worked at the University of Sussex\, first as a Research Fellow focussing on using GPU hardware to accelerate spiking neural network based robot controllers and\, since 2022\, as a EPSRC Research Software Engineering Fellow focussing on spike-based machine learning and the software to enable it. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen-2-4/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230426T180000
DTEND;TZID=UTC:20230426T193000
DTSTAMP:20260418T021644
CREATED:20230127T223705Z
LAST-MODIFIED:20230127T223705Z
UID:10000009-1682532000-1682537400@www.neuropac.info
SUMMARY:Hands-on session with Xylo and Rockpool
DESCRIPTION:Speaker bio: Dylan Muir is the Vice President for Global Research Operations; Director for Algorithms and Applications; and Director for Global Business Development at SynSense. Dr. Muir is a specialist in architectures for neural computation. He has published extensively in computational and experimental neuroscience. At SynSense he is responsible for the company research vision\, and directing development of neural architectures for signal processing. Dr. Muir holds a Doctor of Science (PhD) from ETH Zurich\, and undergraduate degrees (Masters) in Electronic Engineering and in Computer Science from QUT\, Australia.
URL:https://www.neuropac.info/event/hands-on-session-with-xylo-and-rockpool/
LOCATION:Online
CATEGORIES:Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230430
DTEND;VALUE=DATE:20230515
DTSTAMP:20260418T021644
CREATED:20230127T225007Z
LAST-MODIFIED:20230127T225007Z
UID:10000011-1682812800-1684108799@www.neuropac.info
SUMMARY:CapoCaccia Workshop 2023
DESCRIPTION:Workshop theme for 2023: “Lessons from machine learning and neuroscience for building efficient intelligent systems” \nIt is an exciting era of significant progress in the quest for implementing intelligence in artificial systems. This stems from major breakthroughs in our understanding of natural intelligence\, thanks to new tools for better data collection and analysis from the brain; in the development of machine learning algorithms for solving real-world problems; and in the availability of scalable computing substrates that are smaller\, denser\, faster and feature parallel processing capabilities. \nIn this workshop\, we combine all the above towards a more efficient and powerful implementation of intelligent systems. Specifically\, our objective is to pinpoint what current ideas from machine learning and neuroscience can lead to practical designs for implementing low-power and miniaturized neuromorphic intelligent systems. To do so\, in a setting that fosters brainstorming and cross-fertilization\, we stimulate exchange of ideas on topics in which biology\, modeling\, and engineering are dealt with simultaneously. These topics will range from fundamental principles such as learning\, memory and the neurobiology of time; to high-level functions such as navigation\, embodiment and active sensing. \nThe mission of the CapoCaccia Workshops for Neuromorphic Intelligence is to understand the principles of biological intelligence and apply this knowledge in technologies\, for the good of all mankind. \nThe workshop features open and highly interactive discussion sessions in the morning; hands-on projects\, tutorials\, and hardware and software jamming sessions during the day; and free-form discussions in the evenings. \nThe workshop is open to everyone\, but since resources are limited\, we can accept only a limited number of registrations. Due to the limited number of hotel rooms\, Ph.D. students are expected to pair up and share rooms. All participants are encouraged to stay for the full two week period\, but can stay for less if necessary
URL:https://www.neuropac.info/event/capocaccia-workshop-2023/
LOCATION:Alghero\, Sardinia\, Italy\, Alghero\, Sardinia\, Italy
CATEGORIES:Workshop
END:VEVENT
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