Amal Chebbi, Ph.D.

Dr. Amal Chebbi applies advanced machine-learning, control-systems, and large-language-model (LLM) techniques to create data-driven solutions for energy and industrial AI clients. She recently completed her Ph.D. in Mechanical Engineering at the University of Houston, where she developed real-time estimation and control algorithms for advanced MOCVD semiconductor manufacturing.

Before joining Fitila in January 2025, Amal built Gemini Pro and GPT-4o agents with Retrieval-Augmented Generation (RAG) that speed image analysis and report generation for ChampionX’s down-hole equipment diagnostics. As a consultant to Transocean, she designed a digital twin and hydraulic-power-bank concept that simulations show could cut ring-line energy use by 69 %. Amal’s toolkit spans Python, MATLAB/Simulink, Vertex AI, Azure OpenAI, and Neo4j, and she is an active member of ASME and SWE.