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About

James Akl is a robotics researcher whose work bridges perception, manipulation, and industrial automation. His primary research areas include visuotactile sensing for object pose estimation, vision-based control for robotic cutting, and autonomous systems for metal scrap recycling. Akl’s major contributions lie in developing zero-shot generalization methods for robotics—most notably, ViTa-Zero, a framework for visuotactile 6D object pose estimation that overcomes the data scarcity bottleneck by eliminating the need for task-specific training data. In the domain of industrial robotics, he has pioneered vision-based oxy-fuel torch control and feature-driven cutting path generation, directly addressing the labor-intensive and hazardous nature of metal scrap recycling. His work on human-robot collaboration in unstructured scrapyards, where workers mark cut lines and robots autonomously generate trajectories, exemplifies a practical, safety-focused approach to automation. With each of his top papers accumulating 3–5 citations in a short span, Akl’s research is gaining traction for its real-world applicability. His achievements include proposing novel workflows that reduce human exposure to dangerous cutting environments, positioning him as a rising voice in the integration of robotic perception and industrial sustainability.