Master's Thesis: AI Agent for Log Interpretation and Visual Engineering Explanation

We are offering a Master’s thesis opportunity in collaboration with academic and industrial partners linked to the MONA LISA research initiative. The thesis focuses on how an AI agent can help engineers interpret log data, identify relevant patterns, connect signals to system context, and generate clear technical explanations and visual summaries that support issue understanding.

The topic is closely aligned with one of the documented Alstom / MONA LISA use cases, which explicitly describes AI-supported visualisation of logs as an important step towards faster understanding of reported product issues. It is intended as a Master’s-thesis project for students interested in LLMs, agent development, industrial analytics, multimodal AI, and visual decision support.


Thesis objective

The objective of this thesis is to design, implement, and evaluate an AI-based log-interpretation agent for industrial engineering scenarios. The system should help turn low-level log evidence into higher-level technical understanding by identifying patterns, anomalies, or event sequences and relating them to issue descriptions or system context. Depending on scope, the thesis may focus on a single intelligent assistant or on a small agent-based design where one component analyses logs, another retrieves supporting context, and another generates an explanation or visual summary.