HiPEAC 2024
2024-01-17 - 2024-01-19 | Munich, Munich, Germany
19th International Conference on High Performance, Edge And Cloud computing
The HiPEAC conference is the premier European forum for experts in computer architecture, programming models, compilers and operating systems for embedded and general-purpose systems.
The 19th HiPEAC conference will take place in Munich, Germany from Wednesday 17 to Friday 19 January, 2024. Associated workshops, tutorials, special sessions, several large poster sessions and an industrial exhibition will run in parallel with the conference. The three-day event attracts over 500+ delegates each year.
Topics of interest include, but are not limited to:
· Processor, memory, interconnect, and storage architectures
· Parallel, multi-core and heterogeneous systems
· Interconnection networks
· Architectural support for programming productivity
· Power, performance and implementation efficient designs
· Reliability and real-time support in processors, compilers and run-time systems
· Application-specific processors, accelerators and reconfigurable processors
· Architecture and programming environments for GPU-based computing
· Architectural simulation and methodology
· Architectural and run-time support for programming languages
· Programming models, frameworks and environments for exploiting parallelism
· Program characterization and analysis techniques
· Dynamic compilation, adaptive execution, and continuous profiling/optimization
· Binary translation/optimization
· Code size/memory footprint optimizations
· Architectures for emerging technologies such as neuromorphic, photonics, quantum, etc.
· Machine learning applied to the above
· Computing systems research from application studies

Cristian Axenie @ ONM - Hybrid Learning for Event-Based Visual Motion Detection and Tracking of Pedestrians
2024-01-15 18:00 - 19:30 (Europe/Zurich) | Online
The Vision Zero Program’s purpose is to reduce traffic-related fatalities and serious injuries while promoting equitable, safe, and healthy mobility for all. Ultimately, the challenge is to detect pedestrians during the day and especially at night in order to implement safety measures.
The current study introduces an award-winning low-power solution employing neuromorphic visual sensing and hybrid neuro-statistical processing developed by the Technische Hochschule Nürnberg team for the TinyML Vision Zero San Jose Competition. The solution proposes a novel neuromorphic edge fusion of spiking neural networks and event-based expectation maximization for the detection and tracking of pedestrians and bicyclists.
We provide a deployment-ready evaluation of the detection performance along with robustness, energy footprint, and weatherization while emphasizing the advantages of the neuro-statistical edge solution and its city-level scaling capabilities.

About the Speaker
Dr. Axenie is Professor of Artificial Intelligence and Research Group Leader in Cognitive Neurocomputing at the Technische Hochschule Nürnberg Georg Simon Ohm in Germany.
After earning a Dr. Eng. Sc. in Neuroscience and Robotics from the Technical University of Munich in 2016, Dr. Axenie joined the Huawei Research Center in Munich. Between 2017 and 2023 Dr. Axenie was Staff Research Engineer with Huawei Research Center. At the same time, Dr. Axenie was the Principal Investigator and Head of the Audi Konfuzius-Institut Ingolstadt Laboratory at the Technische Hochschule Ingolstadt.
Dr. Axenie is a seasoned researcher with more than 15 years of academic research and more than 10 years of industrial research experience. His research was disseminated in more than 50 peer-reviewed publications and more than 10 patents. Currently Dr. Axenie focuses on sustainable and efficient deployment of intelligent algorithms for sensor fusion and closed-loop control.

Brad Aimone @ ONM - Programming Scalable Neuromorphic Algorithms With Fugu
2023-12-19 18:00 - 19:30 (Europe/Berlin) | Online
From the Open Neuromorphic website
Explore neural-inspired computing with Brad Aimone, a leading neuroscientist at Sandia Labs. Join us for insights into next-gen technology and neuroscience.

Kade Heckel @ ONM - Neuromorphic Hackathon with Spyx
2023-12-13 06:00 - 08:00 (Europe/Berlin) | Online
From the open-neuromorphic.org website:
Join us on December 13th for an exciting Spyx hackathon and ONM talk! Learn how to use and contribute to Spyx , a high-performance spiking neural network library, and gain insights into the latest developments in neuromorphic frameworks. The session will cover Spyx’s utilization of memory and GPU to maximize training throughput, along with discussions on the evolving landscape of neuromorphic computing.
Don’t miss this opportunity to engage with experts, collaborate on cutting-edge projects, and explore the potential of Spyx in shaping the future of neuromorphic computing. Whether you’re a seasoned developer or just curious about the field, this event promises valuable insights and hands-on experience.
Agenda:

18:00 – 19:00: Spyx Introduction

Dive into Spyx, its features, and how to contribute
Hands-on session: Explore Spyx functionalities and tackle real-world challenges
Q&A and collaborative discussions

19:00 – 20:00: Hackathon

Collaborate on cutting-edge projects and explore the potential of Spyx
Q&A and collaborative discussions

Speakers:

Kade Heckel

Note: The event will be hosted virtually. Stay tuned for the video link and further updates. Let’s come together to push the boundaries of neuromorphic computing!

NeuroEng Workshop @ Western Sydney University
2023-12-11 - 2023-12-13 | St George Sailing Club, 2 Riverside Drive, Sans Souci, Sydney, NSW, Australia
The International Centre for Neuromorphic Systems welcomes NeuroEng Association members and guests to join in a 3-day workshop focusing on computational neuroscience and neuromorphic engineering as well providing a valuable platform for networking and collaboration.
Hosted at the newly refurbished St George Sailing Club, attendees will be treated to sensational waterfront views of the Georges River and the pristine beaches of the Sans Souci and Botany Bay region – a hidden gem known to locals. Furthermore, guests can enjoy a number of local accommodation options as well as an array of activities in the area.
Prepare for a workshop that combines cutting-edge knowledge sharing with the serenity of a beach setting. We look forward to welcoming you to the 2023 ICNS NeuroEng Workshop!
Call for abstracts until October 31st, 2023.

NeurIPS 2023
2023-12-10 - 2023-12-16 | New Orleans, New Orleans, LA, United States
Conference on Neural Information Processing Systems (NeurIPS) 2023
NeurIPS 2023 will be held again at the at the New Orleans Ernest N. Morial Convention Center.

The conference was founded in 1987 and is now a multi-track interdisciplinary annual meeting that includes invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers. Along with the conference is a professional exposition focusing on machine learning in practice, a series of tutorials, and topical workshops that provide a less formal setting for the exchange of ideas.

Michael Jurado @ INRC - Enhancing Performance and Efficiency of SNNs
2023-12-05 08:00 - 09:00 (America/Los_Angeles) | Online
Title:
Enhancing Performance and Efficiency of SNNs: From Spike-Based Loss Improvements to Synaptic Sparsification Techniques.
Abstract:
The introduction of offline training capabilities like Spike Layer Error Reassignment in Time (SLAYER) and advancements in the probabilistic interpretations of Spiking Neural Network (SNN) output reinforce SNNs as a viable alternative to Artificial Neural Networks (ANNs). However, special care must be taken during Surrogate Gradient (SG) training to achieve desired performance and efficiency. This talk will cover our recent work in improving spike-based loss functions for SNNs as well as sparsifying SNNs for low cost, high performant neuromorphic computing.
Spikemax was previously introduced as a family of differentiable loss methods which use windowed spike counts to form classification probabilities. We modify the Spikemaxs loss method to use rates and a scaling parameter instead of counts to form Scaled-Spikemax. Our mathematical analysis shows that an appropriate scaling term can yield less coarse probability outputs from the SNN and help smooth the gradient of the loss during training. Experimentally, we show that Scaled-Spikemax achieves faster training convergence than Spikemax and results in relative improvements of 4.2% and 9.9% in accuracy for NMNIST and N-TIDIGITS18, respectively. We then extend Scaled-Spikemax to construct a spike-based loss function for multi-label classification called Spikemoid. The viability of Spikemoid is shown via the first known multi-label classification results on N-TIDIGITS18 and 2NMNIST, a novel variation of NMNIST that superimposes event-driven sensory data.
However, SNNs trained through SG methods oftentimes use dense or convolutional connections which are not always suitable for Loihi2. In order to minimize core usage and power consumption on chip, we employ synaptic pruning techniques as part of our SNN training pipelines. We demonstrate the effectiveness of synaptic pruning techniques for ANN to SNN conversion of vgg16 on Loihi1 as well as for a lava-dl trained SNN for the Intel DNS Challenge. This later approach involved the use of Gradual Magnitude Pruning (GMP) applied during SLAYER training, which reduced the memory footprint of the baseline SDNN by 50-75%. We highlight infrastructure changes to netX which enable conversion of lava-dl trained SNNs into sparsity aware lava processes.
Meeting link to join is available to INRC members and affiliates on the INRC Forum Schedule (click here).
If you are not yet a member of the INRC, please see the “Joining the INRC link” below.
Bio: Michael Jurado is a research engineer at the Georgia Tech Research Institute. He studied computer science at Georgia Tech and received his master’s degree in Machine Learning in 2022. Lately, Michael has been studying and developing neuromorphic algorithms for edge computing and a regular contributor to the lava code base. In his free time, he likes to read and study languages.

For the recording and slides, see the full INRC Forum 2023 Schedule (accessible only to INRC Affiliates and Engaged Members).
If you are interested in becoming a member, here is the information about ”Joining the INRC.

IEEE ICRC 2023
2023-12-05 - 2023-12-06 | San Diego, San Diego, CA, United States
The IEEE International Conference on Rebooting Computing is the premier venue for novel computing approaches, including algorithms and languages, system software, system and network architectures, new devices and circuits, and applications of new materials and physics. This is an interdisciplinary conference that has participation from a broad technical community, with emphasis on all aspects of the computing stack.
IEEE ICRC 2023 is an in-person event with an option for virtual attendance. While all speakers will deliver their talks in-person, attendees will have the option of attending the conference virtually. Check that option when you REGISTER!
The International Roadmap on Devices and Systems (IRDS) will also be featured at ICRC 2023 with talks from academia, industry, and government research centers spanning materials, devices, circuits, and systems for computing.

Jannik Lubeoinski @ INRC - Brian2Lava: connecting the Brian 2 simulator to neuromorphic hardware
2023-11-28 08:00 - 09:00 (America/Los_Angeles) | Online
Abstract:
Neuromorphic hardware allows for fast and energy-efficient simulation of spiking neural networks. However, the usage of such devices is still a challenge, as it requires detailed knowledge about the neuromorphic hardware as well as the used software interface, e.g., the Lava framework for neuromorphic computing spearheaded by Intel. This stands in contrast to the relative ease of simulating spiking neural networks on conventional CPU or GPU architectures, for which user-friendly simulation environments exist. The Brian 2 simulator, for instance, allows to readily define a spiking neural network with a set of equations, handling all subsequent hardware interactions.
To link the best of both worlds, we are developing Brain2Lava. Brian2Lava combines the intuitive user interface of Brian 2 with the functionality of Lava. By means of a so-called device for Brian 2, Brian2Lava seamlessly generates and executes the desired simulations in Lava without the need for users to write additional code. At the current stage, Brian2Lava supports most Brian 2 features when executing Lava on CPU, and a selection of essential features for the execution on Intel’s Loihi 2 chip. We are constantly working to expand the number of features supported with the chip, aiming to enable to flexibly execute simulations on different hardware platforms.
In summary, by bridging the gap between user-friendly model definition and neuromorphic implementation, Brian2Lava empowers engineers and neuroscientists alike to leverage the potential of neuromorphic hardware with greater ease and efficiency.
Bio: Jannik Luboeinski is currently a postdoctoral researcher at University of Göttingen. He received his B.Sc. and M.Sc. degrees in Physics from Technical University of Darmstadt and Goethe University Frankfurt, respectively. From 2017 to 2021, he did his Ph.D. with Christian Tetzlaff at University of Göttingen, investigating the role of two-phase synaptic plasticity in recurrent spiking neural networks, which resulted in the publication of several journal papers. In 2021, Dr. Luboeinski continued to work in the group of Professor Tetzlaff (now Computational Synaptic Physiology Group) as a postdoctoral researcher. A major aim of his research is to identify properties that enable efficient memory processes in biological and artificial neural systems. His work currently focuses on neuromorphic computing and the development of simulation software for recurrent spiking neural networks.
Meeting link to join is available to INRC members and affiliates on the INRC Forum Schedule (click here).
If you are not yet a member of the INRC, please see the “Joining the INRC link” below.
For the recording and slides, see the full INRC Forum 2023 Schedule (accessible only to INRC Affiliates and Engaged Members).
If you are interested in becoming a member, here is the information about ”Joining the INRC.”

Timoleon Moraitis @ ONM - Making Neuromorphic Computing Mainstream
2023-11-16 18:00 - 19:00 (Europe/Berlin) | Online
From the Open Neuromorphic website
Join us for a workshop with Timoleon Moraitis, research group leader in neuromorphic computing, at the interface of computational neuroscience with artificial intelligence.

SNUFA Workshop 2023
2023-11-07 - 2023-11-08 | Online
SNUFA is an online workshop and community focused on research advances in the field of “Spiking Networks as Universal Function Approximators”. The annual SNUFA online workshop brings together researchers in spiking neural networks to present their work and discuss translating these findings into a better understanding of neural circuits and novel brain-inspired computing approaches. Topics of interest include artificial and biologically plausible learning algorithms and the dissection of trained spiking circuits toward understanding neural processing.
The workshops are organised by Dan Goodman and Friedemann Zenke.
Register or submit on the website: https://snufa.net/2023/

HBP Brain Innovation Days 2023
2023-10-26 - 2023-10-27 | Brussels, Brussels, Belgium
The Brain Innovation Days bring the brain ecosystem together to foster dialogue, exchange knowledge, accelerate investment in research & innovation and facilitate business development.
The 3rd edition of the Brain Innovation Days will take place on 26-27 October 2023 in Brussels (Belgium) under the overarching theme “The Brain in the 21st Century”, centred around building resilience and better brain health for future generations and increasing our brains’ readiness to adapt to an ever-changing environment. Get ready for two jam-packed days of high-level brain innovation!

International Conference on Neuromorphic, Natural and Physical Computing
2023-10-25 - 2023-10-27 | Hannover, Germany, Castle of Herrenhausen, Hannover, Germany
We are happy to announce the “Neuromorphic, Natural and Physical Computing: Interdisciplinary Foundations (NNPC 2023)”, organized with generous support by the Volkswagen Foundation. The conference will take place the 25th – 27th of October 2023 in Hanover, Germany, and the deadline for submitting a 2-page abstract is March 15th.
The general aim of NNPC 2023 is to boost interdisciplinary transfer of ideas and networking in the wider fields of non-digital computing. NNPC 2023 is a successor to the 2018 conference “Cognitive Computing: Merging Concepts with Hardware” (https://nnpc-conference.com/2018) whose very productive and motivating format will be kept, as well as the location and the generous funding conditions.
Each session is devoted to a specific theme. We encourage active engagement of attendants by requiring submission of a 2-page abstract on a subject relating to one of the session themes. These abstracts are peer-reviewed. From the accepted abstracts three are chosen for oral presentations and the remaining ones for posters. Importantly, novelty is not essential as our aim is to make knowledge to diffuse across boundaries of the scientific domains involved.

7th BigBrain Workshop - Challenges of Big Data Integration
2023-10-04 - 2023-10-06 | Gróska Innovation and business growth center, Bjargargata 1 102, Reykjavík, 101, Iceland
This workshop is an opportunity for the neuroscientific community to come together and present their cutting-edge research, discuss future prospects of the BigBrain associated data and tools, and explore how to better leverage high-performance computing and artificial intelligence to create multimodal, multiresolution tools for the high-resolution BigBrain and related datasets.

Neuromorphic Computing Netherlands 2023
2023-10-02 | University of Groningen, Grote Markt 21, Groningen, 9712 HC, Netherlands
The NCN2023 (Neuromorphic Computing in the Netherlands) meeting aims to gather in one place leading experts and junior researchers to discuss current trends and open challenges in the field, from algorithmic, architectural, and application domains. Complementing previous years’ topics, this edition will focus on Bio-inspired computing paradigms and emerging technologies.
For more information, see https://www.rug.nl/research/fse/cognitive-systems-and-materials/news/events/ncn2023/.

Giulia D’Angelo: What’s catching your eye? The visual attention mechanism
2023-09-26 18:00 - 19:30 (Europe/Berlin) | Online
Abstract
Every agent, whether animal or robotic, needs to process its visual sensory input in an efficient way, to allow understanding of, and interaction with, the environment. The process of filtering revelant information out of the continuous bombardment of complex sensory data is called selective attention. Visual attention is the result of the complex interplay between bottom-up and top-down mechanisms to perceptually organise and understand the scene. Giulia will describe how to approach visual attention using bio-inspired models emulating the human visual system to allow robots to interact with their surroundings.
Speaker’s bio
Giulia D’Angelo is a postdoctoral researcher in neuroengineering in the EDPR laboratory at the Italian Institute of Technology. She obtained a B.Sc. in biomedical engineering and an M.Sc. in neuroengineering, developing a neuromorphic visual system at the King’s College of London. She successfully defended her Ph.D. VIVA in 2022 at the university of Manchester, proposing a biologically plausible model for event-driven saliency-based visual attention. She is currently working on bio-inspired visual algorithms exploiting neuromorphic platforms.

Bernstein Conference 2023
2023-09-26 - 2023-09-29 | Humboldt Universität, Luisenstraße 56, Berlin, 10115, Germany
Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renown conferences worldwide in this field, attracting students, postdocs and PIs from around the world to meet and discuss new scientific discoveries.
Alongside the conference, there will also be multiple satellite workshops, such as: “Biologically plausible learning in artificial neural networks”, “How can machine learning be used to generate insights and theories in neuroscience?”, and “Brain inspiration in neuromorphic computing”. For more information, see https://bernstein-network.de/bernstein-conference/program/satellite-workshops/.
For more information, see the website: https://bernstein-network.de/en/bernstein-conference/.

HBP Concluding Event - Pioneering digital brain research
2023-09-12 - 2023-09-13 | Forschungszentrum Jülich, Wilhelm-Johnen-Straße, Jülich, 52428, Germany
From September 12 – 13, 2023, the Human Brain Project will celebrate its successful conclusion with a public scientific symposium at Forschungszentrum Jülich. In addition to the international project partners, representatives from politics and the media are cordially invited to attend.
In short presentations, researchers from the Human Brain Project will highlight the project’s achievements. The symposium will be accompanied by scientific exhibits, an impressive picture gallery and hands on trainings. In guided tours guests can explore the laboratories and facilities of Forschungszentrum Jülich and get insights into the practical work behind the Human Brain Project.

Frontiers of Neuromorphic Computing
2023-09-05 - 2023-09-07 | Max Planck Institute for the Science of Light, Staudtstr. 2, Erlangen, 91058, Germany
The recent explosion of deep learning applications imposes an urgent need for new energy-efficient alternative neuromorphic hardware concepts running at high speeds and relying on a high degree of parallelism. In this workshop, we will explore this rapidly developing area of (classical) neuromorphic computing over a range of scalable platforms, both on a theoretical and experimental level. These platforms include systems in the domains of optics, integrated photonics, spin systems, semi- and superconducting systems, soft matter, and others. In addition, new physical learning approaches will be discussed.
The in-person workshop will start on 5 September at 9 am and end on 7 September at approximately 5:30 pm. There will be invited talks, contributed talks, a poster session and a panel discussion. On Wednesday, we will organise a conference dinner which is included in the registration fee.

ICONS Conference - International Conference on Neuromorphic Systems
2023-08-01 - 2023-08-03 | Santa Fe, Santa Fe, NM, United States
ICONS 2023 will be held in a hybrid format: physical location will be Santa Fe. Virtual attendance details will also be provided to the participants. The meeting will take place August 1-3, 2023.
The goal of ICONS is to bring together leading researchers in neuromorphic computing to present new research, develop new collaborations, and provide a forum to publish work in this area. Our focus will be on architectures, models, algorithms and applications of neuromorphic systems.

Theory of Neuromorphic Computing
2023-07-13 16:30 - 17:30, 2023-06-29 16:30 - 17:30, 2023-06-15 16:30 - 17:30 UTC | Online
Recurring discussion meeting by researchers interested in the theory of neuromorphic computing.
Hosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings, please contact Arne Diehl: arne.diehl@donders.ru.nl.

INRC Forum: Robert Legenstein
2023-06-27 08:00 - 09:00 (America/Los_Angeles) | Online
Memory-enriched computation and learning through synaptic and non-synaptic plasticity
Abstract:Virtually any task faced by humans has a temporal component and therefore demands some form of memory. Consequently, a variety of memory systems and mechanisms have been shown to exist in the brain of humans and other animals. These memory systems operate on a multitude of time scales, from seconds to years. Yet, it is still not well understood how memory is implemented in the brain and how cortical neuronal networks utilize these systems for computation. In this talk, I will present some recent models that extend (spiking and non-spiking) neural network models with memory using Hebbian and non-Hebbian types of plasticity. I will discuss the similarities between these models and transformers, arguably the most powerful models for sequence processing in the area of machine learning. I will show that Hebbian plasticity can significantly increase the computational and learning capabilities of spiking neural networks. Further, I will show how neurons with non-synaptic plasticity can be utilized for memory and how networks of such neurons can be trained without the need to backpropagate errors through time.
Bio: Dr. Robert Legenstein received his PhD in computer science from the Graz University of Technology, Graz, Austria, in 2002. He is a full professor at the Department of Computer Science, TU Graz, head of the Institute for Theoretical Computer Science, and leading the Graz Center for Machine Learning. Dr. Legenstein has served as associate editor of IEEE Transactions on Neural Networks and Learning Systems (2012-2016). He is an action editor for Transactions on Machine Learning Research, and he was on the program committee for NeurIPS and ICLR several times. His primary research interests are learning in models for biological networks of neurons and neuromorphic hardware, probabilistic neural computation, novel brain-inspired architectures for computation and learning, and memristor-based computing concepts.
For the meeting link, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).

tinyML EMEA Innovation Forum 2023
2023-06-26 - 2023-06-28 | Marriott Hotel, Amsterdam, Netherlands
The tinyML EMEA Innovation Forum is accelerating the adoption of tiny machine learning across the region by connecting the efforts of the private sector with those of academia in pushing the boundaries of machine learning and artificial intelligence on ultra-low powered devices.

Telluride Neuromorphic Cognition Engineering Workshop
2023-06-25 - 2023-07-14 | TBA
The workshop is a 3-week project based meeting organized around specific topic areas to bring the organizing principles of neural cognition into machine intelligence, and to use lessons and technology from machine intelligence to understand how brains work.

INRC Forum: Wolfgang Maass, Christoph Stoeckl & Yukun Yang
2023-06-20 08:00 - 09:00 (America/Los_Angeles) | Online
Local prediction-learning in high-dimensional spaces enables neural networks to plan
Abstract: Being able to plan a sequence of actions in order to reach a goal, or more generally to solve a problem, is a cornerstone of higher brain function. But compelling models which explain how the brain can achieve that are missing. We show that local synaptic plasticity enables a neural network to create high-dimensional representations of actions and sensory inputs so that they encode salient information about their relationship. In fact, it can create a cognitive map that reduces planning to a simple geometric problem in a high-dimensional space that can easily be solved by a neural network. This method also explains how self-supervised learning enables a neural network to control a complex muscle system so that it can handle locomotion challenges that never occurred during learning. The underlying learning strategy bears some similarity to self-attention networks (Transformers). But it does not require non-local learning rules or very large datasets. Hence it is suitable for implementation in highly energy-efficient neuromorphic hardware, in particular for on-chip learning on Loihi 2.
One goal of our presentation will be to initiate discussions about the relation of this learning-based use of large vectors to other VSA approaches, its relation to Transformers, and possible applications in robotics.
Bio: Wolfgang Maass is a Professor of Computer Science at Technische Universität Graz. He received his PhD (1974) and Habilitation (1978) in Mathematics from Ludwig-Maximilians-Universität in Munich. He conducted research at MIT, the University of Chicago, and UC Berkeley, as a Heisenberg Fellow of the Deutsche Forschungsgemeinschaft. He has been the Editor of Machine Learning (1995-1997), Archive for Mathematical Logic (1987-2000), and Biological Cybernetics (2006-present). He was also a Sloan Fellow at the Computational Neurobiology Lab of the Salk Institute in La Jolla, California from 1997-1998. Since 2005, he has been an Adjunct Fellow of the Frankfurt Institute of Advanced Studies (FIAS).
Christoph Stoeckl is a Postdoc researcher at Technische Universität Graz working in the intersection between computational neuroscience and AI. His research interests include neuromorphic hardware as well as exploring connections between Transformers and neural networks. Before joining the research lab of Prof. Maass, he obtained a Master’s degree in Computer Science also at TU Graz.
Yukun Yang is a 1st-year Doctoral Student at Technische Universität Graz, supervised by Prof. Wolfgang Maass. His primary research interest is at the intersection of AI and neuroscience, with a focus on discovering the learning principles of the brain and its neuromorphic applications. Before joining TU Graz, he earned M.S. in the ECE Department at Duke University in 2020. Earlier, he received B.E. in Information Engineering from Xi’an Jiaotong University in 2018.
For the meeting link, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).

Workshop on Event-based Vision @ CVPR 2023
2023-06-19 | Vancouver, Canada, Vancouver, Canada
4th International Workshop on Event-Based Vision.
Held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition 2023, as part of the track: CV for non-traditional modalities

This workshop is dedicated to event-based cameras, smart cameras, and algorithms processing data from these sensors. Event-based cameras are bio-inspired sensors with the key advantages of microsecond temporal resolution, low latency, very high dynamic range, and low power consumption. Because of these advantages, event-based cameras open frontiers that are unthinkable with standard frame-based cameras (which have been the main sensing technology for the past 60 years). These revolutionary sensors enable the design of a new class of algorithms to track a baseball in the moonlight, build a flying robot with the agility of a bee, and perform structure from motion in challenging lighting conditions and at remarkable speeds. These sensors became commercially available in 2008 and are slowly being adopted in computer vision and robotics. In recent years they have received attention from large companies, e.g., the event-sensor company Prophesee collaborated with Intel and Bosch on a high spatial resolution sensor, Samsung announced mass production of a sensor to be used on hand-held devices, and they have been used in various applications on neuromorphic chips such as IBM’s TrueNorth and Intel’s Loihi. The workshop also considers novel vision sensors, such as pixel processor arrays (PPAs), which perform massively parallel processing near the image plane. Because early vision computations are carried out on-sensor, the resulting systems have high speed and low-power consumption, enabling new embedded vision applications in areas such as robotics, AR/VR, automotive, gaming, surveillance, etc. This workshop will cover the sensing hardware, as well as the processing and learning methods needed to take advantage of the above-mentioned novel cameras.

International Joint Conference on Neural Networks (IJCNN)
2023-06-18 - 2023-06-23 | Gold Coast Convention and Exhibition Centre, Queensland, Australia
The International Joint Conference on Neural Networks is organized jointly by the International Neural Network Society and the IEEE Computational Intelligence Society, and is the premiere international meeting for researchers and other professionals in neural networks and related areas.
Each year, the conference features invited plenary talks by world-renowned speakers in the areas of neural network theory and applications, computational neuroscience, robotics, and distributed intelligence. In addition to regular technical sessions with oral and poster presentations, the conference program will include special sessions, competitions, tutorials, and workshops on topics of current interest.

Computer Vision and Pattern Recognition Conference (CVPR) 2023
2023-06-18 - 2023-06-22 | Vancouver Convention Center, Vancouver, Canada
The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.
