Joe David

About

Joe David’s research lies at the intersection of human-robot collaboration, mixed reality, and semantic interoperability, with a focus on enabling truly adaptive and intelligent manufacturing systems. His major contributions center on developing agent-oriented architectures and ontology-based frameworks that allow humans and robots to communicate intent, share roles, and respond dynamically to customized product requirements—moving beyond rigid, pre-planned routines. His most-cited work, “Deploying OWL ontologies for semantic mediation of mixed-reality interactions for human–robot collaborative assembly” (2023, 20 citations), pioneers a standards-based approach to explicit bidirectional communication in collaborative assembly. David also introduced a web-based mixed reality interface for agent-oriented interactions and a system architecture for the Digital Thread in product-aware collaboration. His recent work explores TinyML-powered weld detection for robotic welding, demonstrating a commitment to practical, real-time AI solutions. With a growing portfolio that bridges semantic technologies, augmented reality, and industrial robotics, David is shaping the future of flexible, human-aware automation.

Research Focus

Key Achievements

Top Papers

1. 1
   Deploying OWL ontologies for semantic mediation of mixed-reality interactions for human–robot collaborative assembly

   20 citations · 2023
2. 2
   Enabling the Digital Thread for Product Aware Human and Robot Collaboration - An Agent-oriented System Architecture

   3 citations · 2021
3. 3
   A Web-based Mixed Reality Interface Facilitating Explicit Agent-oriented Interactions for Human-Robot Collaboration

   3 citations · 2022
4. 4
   TinyML-Powered Tack Weld Detection for Robotic Welding

   2 citations · 2025
5. 5
   Projecting Product-Aware Cues as Assembly Intentions for Human-Robot Collaboration

   2 citations · 2022

Key Collaborators

Contact & Links