Etor Arza Gonzalez

Etor Arza Gonzalez is a Research Fellow at the Norwegian University of Science and Technology (NTNU) with dual appointments in the Department of Engineering Cybernetics and Department of Language and Literature. His primary research focuses on optimization, machine learning, and reinforcement learning, particularly in hyperheuristic frameworks and algorithm performance analysis.

His research spans:

• Transfer learning across optimization problem domains
• Embedding problem instances into metric spaces for transferability analysis
• Predicting algorithm runtimes across heterogeneous hardware
• Random variable comparison methodologies

Gonzalez develops open-source tools including TransfAnalysis (problem instance embedding), RVCompare (statistical comparison), and RTDHW (runtime prediction). His 2022 paper demonstrates neural network controllers transferring learned behavior between optimization problems, enabling cross-domain solution strategies without problem-specific tuning.

He actively contributes to the NTNU Autonomous Robotics Lab (@ntnu-arl) and Reinforcement Learning Tools community (@rl-tools), with recent GitHub activity showing ongoing development in C++, Python, and MATLAB. No scientific awards or student supervision details were documented in available sources.