Introduction

The convergence of biological neural systems, artificial intelligence, advanced sensing, and edge computing is opening a new frontier in human-machine intelligence. Brain-Computer Interfaces (BCIs), high-density EEG, fNIRS, wearable neurotechnology, and multimodal sensing are moving beyond controlled laboratories toward clinical, consumer, robotic, and extreme environments.

This workshop focuses on the frontier of neural intelligence across this continuum. It begins with robust neural sensing and structured representations of noisy, non-stationary signals, advances toward adaptive representation that can generalize across users, sessions, and environments, and brings these capabilities to edge intelligence for resource-constrained, real-time inference. These foundations enable reliable human-machine systems and ultimately extend neural intelligence into extreme environments, including future space missions.

This progression connects machine learning, neuroscience, neuroengineering, robotics, embedded systems, and aerospace technology around fundamental advances in geometric and statistical neural representations, dynamic covariance modeling, self-supervised learning, continual adaptation, zero-calibration decoding, neuro-AI-hardware co-design, and efficient neural computing.

The workshop aims to advance neural intelligence from static laboratory decoding toward adaptive, resource-aware, and robust systems capable of operating across users, sensors, environments, and missions.

Topics

Adaptive Neural Learning

Riemannian geometry, Symmetric Positive Definite (SPD) learning, and covariance estimation
Dynamic neural-state and covariance-trajectory modeling
Self-supervised and contrastive neural representation learning
Continual learning and test-time adaptation
Zero-/few-calibration and cross-subject neural decoding
Domain generalization and robust neural representations

Neuro-AI and Edge Systems

TinyML and ultra-low-power neural decoding
Quantization, pruning, and knowledge distillation
Hardware-aware neural representation learning
Adaptive sensor selection and multimodal fusion
EEG-fNIRS, ear-EEG, wearable, and novel neural sensors
Real-time closed-loop neural control

Extreme and Space Environments

Astronaut cognitive-state and workload monitoring
Neural decoding under altered physiology and motion
Robust neural sensing under resource constraints
Human-machine teaming in extreme environments
Neural interfaces for autonomous systems and space habitats
Terrestrial analogues and validation methodologies for space deployment

Safety, Privacy, and Responsible Neurotechnology

Privacy-preserving and federated neural learning
Neural-data security and governance
Fairness and cross-population robustness
Uncertainty estimation and safe adaptive neural systems
Clinical and operational validation

ANI particularly encourages contributions combining new theory, algorithms, datasets, hardware, and reproducible experimental systems.

Important Dates

See Important Dates for all paper and abstract submission deadlines.

Author and Submission Guidelines

Please follow Author and Submission Guidelines to submit your work.

If you are interested in serving on the workshop program committee or paper reviewing, please apply online.