Data-Driven Collaborative Decision Making in Complex Industrial Systems

Chirag Vaghela

Research Associate

Chirag Vaghela is a machine learning and data engineering professional with experience in applied AI, time-series analysis, and industrial data-driven solutions. He is associated with SMS group and has an academic background from Jacobs University Bremen. His work combines practical industrial problem-solving with strong interests in machine learning, data integration, and advanced digital technologies for complex systems.

Since 1 February 2026, he has also been serving as a PhD Researcher at the Data-Driven Industrial Systems group. His current research focuses on multimodal semantic data integration using Agentic AI, Large Language Models (LLMs), and Vision Language Models (VLMs). In this work, he explores how intelligent agents and semantic technologies can integrate heterogeneous industrial data sources across text, images, and structured data, enabling more context-aware, interoperable, and scalable decision support for complex industrial environments.