Workshop

2025 ICONIP Workshop

We are pleased to advise that the following Workshops are confirmed for the 2025 program and we would like to thank the organizers for the time they took to put forward and manage these sessions.

No.	Wokrshop Title	Runtime	Workshop Organiser
1	Accelerating Large-Scale Computational Neuroscience Using Transformers and Large Language Models (LLMs)	3h	Dr. Riichiro Hira
2	The Third International Whole Brain Architecture Workshop	3h	Dr. Yoshimasa Tawatsuji
			Dr. Hiroshi Yamakawa
3	Frontiers and Hardware Applications of Neural Network Models	3h	Dr Yuichi Katori
			Dr. Hideaki Yamamoto
			Dr. Ayumi Hirano-Iwata
4	Ultra-Brain Neuromorphic by Material-Device-System Co-Research	3h	Dr. Mutsumi Kimura
5	Deep learning for Multi-modal Data	3h	Dr. Nistor Grozavu
6	The 18th International Workshop on Artificial Intelligence and Cybersecurity (AICS 2025)	6h	Dr. Tao Ban
			Dr. Bin Dong
			Dr. Ryo Karakida
7	Quantifying and simulating multi-neuromodulatory dynamics in the biological brain: Experimental advances, data-centric practices, and computational models	6h	Dr. Jie Mei
			Dr.  Srikanth Ramaswamy

1. Accelerating Large-Scale Computational Neuroscience Using Transformers and Large Language Models (LLMs)

Under the AMED Bain/Minds 2.0 domain 4 project, our research aims to transform computational neuroscience through four key objectives. First, we seek to develop a standard platform for analyzing large-scale brain measurement and simulation data. While a fully detailed digital brain capturing every molecular to behavioral nuance is theoretically possible, the enormous number of undetermined parameters makes it impractical. Instead, we propose building a functional digital brain model using Transformer architectures applied to both experimental and simulation datasets, linking molecular, cellular, circuit, and behavioral scales. Second, we aim to unravel the inner workings of large language models (LLMs) and multimodal models (LMMs). Although these Transformers excel in next-word prediction and implicitly generate linguistic structures, how high-level representations emerge remains unclear. We plan to create innovative, large-scale analytical methods that extend beyond current techniques like attention flow analysis. Third, we will apply these Transformer-based techniques to neural data to optimize models for predicting brain activity, capturing the essential dynamics and spatiotemporal interactions of neural populations, and refining our digital brain model. Lastly, we intend to develop a specialized LLM to automate script generation and evaluation , streamlining complex simulations and data analysis. Join us as we bridge advanced computational methods with neuroscience, paving the way for a new era in data-driven brain research!

Website: https://cath.sakura.ne.jp/ICONIP2025/index.html

2. The Third International Whole Brain Architecture Workshop

The International Whole Brain Architecture Workshop (WBA-WS) brings together researchers from neuroscience, AI, cognitive science, and engineering to advance the integration of brain-inspired knowledge into AI systems. Central to the workshop is the Brain Reference Architecture (BRA), a structured, high-level representation of functional brain organization designed to support interpretable, biologically grounded AI. BRA emphasizes the mapping between neural structures and cognitive functions in a modular, reusable format, making it accessible even to non-specialists. BRA data and associated papers are authored and published through the Brain Reference Architecture Editing System (BRAES), which ensures interoperability and scalability. The workshop features three presentation types: (1) BRA Data Presentations, (2) Work-in-Progress BRA Data, and (3) General Presentations on supporting knowledge or BRA dissemination. Accepted BRA data will be archived and made citable via BRAES. We invite submissions of BRA data, papers, and related contributions to foster a shared platform for cross-disciplinary collaboration and innovation in brain-inspired AI.

Website: https://wba-initiative.org/en/25942/

3. Frontiers and Hardware Applications of Neural Network Models

Neural networks have revolutionized various fields, including artificial intelligence, computational neuroscience, and hardware-based computing. This workshop aims to explore cutting-edge developments in neural network models, their biological foundations, and their implementation in hardware. The workshop will bring together experts from diverse disciplines to discuss advancements in neural dynamics, reservoir computing, robotics, and hardware-based implementations of neural computations.

Website:  https://www.mnbc.riec.tohoku.ac.jp/eng/iconip2025/

4. Ultra-Brain Neuromorphic by Material-Device-System Co-Research

It is extremely important to consider the close correlation between material, device, circuit, and systems at each level in analog-type neuromorphic systems, like living brains, comparing conventional digital-type computers. Many researchers continue to aim not only to imitate brains but also to realize beyond-the-brain) neuromorphic system with ultra-compact and low energy. By promoting research aware through the co-research, utilizing advantages of superior materials and manufacturing technologies, and wiping out the disadvantages of integration, systems, and applications, we dream of success of a final great turnaround in the electronics industry. Interesting invited talks on material intelligence, outstanding memdevices and synaptic devices, exotic materials and devices, and slow electronics, which are promising for dramatic breakthrough of neuromorphic systems, will be presented. Some referrals have come from organizations that strongly promote this theme. This workshop welcomes regular submissions.

*Cutting-edge research of material, device, circuit, and system for neuromorphic and vice-versa
*Co-research of them for neuromorphic and vice-versa
*Requests from the research of material, device, circuit, and system to neuromorphic and vice-versa

Website: https://url.au.m.mimecastprotect.com/s/sp9lCJyBrGfKR1BVLhVfWhyFqPb?domain=sites.google.com

5. Deep learning for Multi-modal Data

*To be updated

6. The 18th International Workshop on Artificial Intelligence and Cybersecurity (AICS 2025)

The International Workshop on Artificial Intelligence and Cybersecurity (AICS 2025), formerly known as the International Data Mining and Cybersecurity Workshop (DMC), builds upon a decade-long legacy of success. AICS 2025 is dedicated to advancing awareness of cybersecurity and promoting the integration of AI in securing industrial and societal systems. The workshop also serves as a valuable platform for early-career researchers to engage with pressing challenges and current research in AI and cybersecurity. This event offers a dynamic forum for researchers, security professionals, engineers, and students to present cutting-edge work, exchange innovative ideas, and explore future trends in data mining, AI, machine learning, and cybersecurity.

Website: https://url.au.m.mimecastprotect.com/s/fLzFCP7LAXf3AErmGszfzhxyDDs?domain=csmining.org

7. Quantifying and simulating multi-neuromodulatory dynamics in the biological brain: Experimental advances, data-centric practices, and computational models

Neuromodulatory processes in the brain have been viewed as homogeneous and spatially unified, with early evidence linking neuromodulators such as dopamine, acetylcholine, serotonin and noradrenaline with broad and basic brain functions. Nevertheless, with advances in experimental neuroscience tools, researchers have identified projection-specific functions of neuromodulators, as well as intricate interconnections across neuromodulatory systems. For example, depending on brain region and contextual information, a pair of neuromodulators such as dopamine and serotonin can exhibit opposing, convergent, or modulatory interactions.

These new findings challenge the conventional view of neuromodulatory systems, necessitating an updated, integrative perspective on their computational roles and learning mechanisms. The proposed workshop will highlight recent experimental discoveries in multi-neuromodulatory interactions, alongside modeling efforts that attempt to capture their complexity. These discussions will be followed by how open science practices – such as data sharing and standardization of simulation tools – can foster a synergy between experimental and computational research.