Alex Mihailidis

This paper develops an EMG foundation model for neural decoding that outperforms subject-optimized models in both in-distribution and out-of-distribution evaluations.

This paper develops a multimodal vision-language system for egocentric perception of walking environments, generating detailed image captions with user personalization.

The paper compares static and sequential image classification of walking environments using temporal neural networks, finding that 3D models outperform 2D ones but have higher computational demands.

This paper develops AI-powered smart glasses for real-time environment sensing and recognition in human-robot walking scenarios, achieving 93.6% accuracy with low latency.

This paper introduces a semi-supervised learning system for visual perception in human-robot walking environments, achieving high accuracy with fewer labeled images.