My industrial research applies automated negotiation, multiagent systems, and AI to real-world production systems. The two areas below — developed jointly with NEC Corporation and international consortia — translate the research on the research page into deployed technology.
Digital twins — high-fidelity virtual replicas of physical assets — are most valuable when they can act on the world they mirror: orchestrating, coordinating, and negotiating on behalf of their physical counterparts. My work in this area is carried out in collaboration with the Digital Twin Consortium, where I contribute to the NEGOTIATE testbed — a consortium initiative bringing automated negotiation technology into the digital-twin ecosystem so that twins of different assets (from different vendors) can reach agreements without a human broker in every loop.
I presented this work at the Digital Twin Consortium’s member meetings and related industrial venues since 2024 (e.g. DTC Q3 Member Meeting, Chicago, 2024). The underlying automated-negotiation research feeding the testbed is summarized in my Journal of Innovation paper, Generative AI for Automated Negotiation (Mohammad, Chen, Higa, Ando & Morinaga, 2025).
Data Spaces are federated, sovereign data ecosystems where organizations share data without surrendering control of it — a foundation for trustworthy cross-company AI. My work in this area sits at the intersection of two leading consortia: the Catena-X automotive data space (the world’s first scaled Catena-X deployment) and the Industrial Digital Twin Consortium, whose twin definitions underpin the asset descriptions exchanged in the data space.
The challenge I work on is making the agents that participate in a data space — trading, brokering, or reasoning over data — trustworthy by design rather than by audit. This is the subject of the IDSA position paper, Data Spaces and AI: Trustworthy Agentic Participation in Data Spaces (Achatz, … Mohammad, … et al., 2026), co-authored with the International Data Spaces Association (IDSA) (DOI / full text).