Noorbakhsh Amiri Golilarz

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About

Noorbakhsh Amiri Golilarz is a researcher at the forefront of robotic perception and multimodal sensing, with a primary focus on surface material recognition and the integration of tactile and visual data. His most notable contribution, the Surformer v1, introduces a transformer-based architecture that fuses structured tactile features with vision inputs to achieve robust surface classification—a critical capability for robots interacting with physical environments. This work, published in 2025, has already garnered 2 citations, signaling early impact in the field. Golilarz’s research addresses fundamental challenges in robotic manipulation and haptic perception, aiming to bridge the gap between human-like touch sensing and machine learning. By leveraging attention mechanisms, his approach enhances the accuracy and adaptability of material recognition systems. His work is particularly relevant for applications in assistive robotics, industrial automation, and autonomous systems requiring nuanced physical interaction. Golilarz continues to push the boundaries of how robots perceive and understand their surroundings through touch and sight, making him a promising voice in the evolving landscape of embodied AI and sensor fusion.