Esther Villar Rodríguez (PhD) holds a PhD (Cum Laude) in Information and Communication Technologies (2015) from the University of Alcalá (Spain), a BSc in Computer Science (2010) by the University of Deusto, and a M.Sc. (2012) in Computer Languages and Systems by UNED (National University of Distance Education, Spain). She was a senior researcher in Artificial Intelligence at TECNALIA (Spain), specialized in Shallow Learning and Deep Machine Learning models, distributed privacy-aware learning strategies (including Federated Learning), Reinforcement Learning and outlier detection, among others. She authored several contributions at conferences and articles in journals related to these research areas, with a focus on their applicability to practical problems (prediction and optimization of management and industrial processes, resource planning, scheduling, energy efficiency, and other assorted applications alike). She was the head of the Artificial Intelligence group in Optima (Optimization, Modelling and Analytics) from the ICT department in Tecnalia R&I, mainly in charge of the definition of the technological strategy and funding plan. From 2022 on, she is the leader of the Quantum Technologies group in Tecnalia R&I, department created as a result of the new company technological strategy spanning from 2022 up to 2025. She is also directing a doctoral thesis focused on collaboration mechanisms and optimal exploration in Reinforcement Learning applied to problems with sparse rewards and collaborates technically and actively in new lines such as Quantum Computing or Coevolutive/Multitasking Optimization.