Sebastian
Rojas-Ordoñez
PhD Researcher & Mechatronic Engineer
I research and build systems at the boundary between simulation and reality — designing FMI/FMU co-simulation architectures validated in high-fidelity environments, then deploying them as real-time ROS 2-based autonomous systems. At IKERLAN and UPV/EHU, my work directly addresses industrial reliability challenges in cyber-physical systems.
Alongside my research, I bring hands-on engineering depth: embedded AI inference on edge hardware, model-based design with MATLAB/Simulink and Modelica, and full robotic system integration from sensing to actuation. I hold dual master's degrees in Mechatronics (Erasmus Mundus EU4M) and Artificial Intelligence.
Research
Published contributions in model-based engineering, edge AI, and intelligent control systems.
Systematic review of 121 studies establishing a unified conceptual framework for Cognitive Digital Twins in autonomous robotic systems. Synthesizes approaches across robust localization, navigation, and manipulation, identifying open challenges toward self-aware robotic agents.
Fine-tuning-free edge framework deploying Large Language Models on NVIDIA Jetson-class hardware for autonomous robot navigation via zero-shot prompt engineering. Demonstrates real-time LLM inference fully offline on resource-constrained hardware, with no cloud dependency.
Proof-of-concept coupling an LLM to an industrial relay controller for a SISO thermal plant. Validated against a conventional hysteresis controller, demonstrating viability of LLM-based control in cyber-physical systems with natural-language setpoint specification and explainable decisions.
Presents an architecture for integrating physical simulation models with AI components using open interoperability standards (FMI/FMU). Demonstrates how model-based design tools (OpenModelica, MATLAB/Simulink) and AI inference pipelines can co-simulate within a unified, vendor-neutral framework for industrial cyber-physical systems validation.
Engineering
Systems designed, built, and delivered — from funded R&D platforms to academic mechatronic projects.
Background
Academic formation, professional trajectory, and distinctions.
Outstanding Graduate
Automation & Mechatronics
Robotics & Automotive
Deep Learning & Computer Vision
Factory & Process Automation
FMI · ROS 2 · Edge AI
Present
Jul 2024
Aug 2022
Feb 2018
Present
Sep 2024
Micro & Nano Technology, Robotics, Automotive Engineering
Control Systems, Factory and Process Automation
Automation, Mechatronics, Programming
Nov 2022
Dec 2019
Contact
Open to research collaborations, industry R&D partnerships, and opportunities at engineering-focused organizations.