David Gómez-Ullate Oteiza

David Gómez-Ullate Oteiza started his career as a theoretical physicist, but branched out into applied mathematics, data science and machine learning. After several years spent studying the fundamental questions of quantum mechanics, he discovered the pleasure of tackling and solving more practical questions. His latest personal project involves optimizing maritime shipping routes with performance and weather data, with a view to decarbonizing maritime transport.

For David, this is the appeal of applied mathematics—it solves real-world problems. “There are many problems across all sciences and fields of human activity that can be framed in mathematical terms,” he notes. He takes great pleasure in being able to contribute his mathematical and computational knowledge to some of these, a task which often involves learning enough domain knowledge to communicate with the experts in a particular field.

One of David’s main goals is to participate in the development of machine learning (ML) and data science, which he sees as not only transforming the world from an industrial perspective, but also as challenging the foundation of many scientific disciplines. Understanding why ML models work so well, and what their limits are, is a challenge which he feels poses many mathematical questions.

The importance of keeping up with the pace at which research in machine learning is progressing was another factor in David’s decision to pursue a teaching career. “I feel the responsibility to transmit knowledge to younger generations,” he explains. He was drawn to IE University because of its reputation for providing a first-class student experience. He would like to transmit the sense of curiosity and excitement that triggers scientific discovery to his students at IE School of Science & Technology, where he’s currently the area director for Applied Mathematics, as well as head of faculty. David is enthusiastic about promoting the recently reimagined IE School of Science & Technology, emphasizing that the school has an exciting road ahead of them on the way to reach the levels of excellence already achieved by other schools at IE University. He’s particularly proud of the Bachelor in Applied Mathematics, which he describes as the program he wishes he could have studied. “Mathematics is a powerful tool, but it becomes much more powerful when combined with other disciplines: this is the spirit of the Bachelor in Applied Mathematics program.” He recalls spending many hours following lectures in which he had little interest, or learning theory with no immediate practical application, so he appreciated the fact that IE University granted him and his team the freedom to design a modern program balancing math fundamentals, data science, computation and cross-disciplinary skills.

Currently, David teaches Machine Learning and Analytics to third-year Dual Degree in Business Administration and Data & Business Analytics students. For most of his students, this is one of the most technical courses they will study, so he’s put extra effort into making it as easy to digest as possible, in order to give future business leaders the necessary level of technical understanding. The course provides a broad vision of the current trends in machine learning, primarily deep learning and its applications to language models and computer vision. As well as covering the fundamentals, the course delves into practical aspects such as code implementation, deploying models and reflecting on the business and social implications of this technology. 

David’s career so far has been varied and impressive—so what does he feel are the keys to success? While acknowledging that success is a subjective concept, he lists the factors which have helped him throughout his career: self-confidence, having role models to look up to while being humble about your own achievements, gathering smart, but good-hearted people around you; and finally, learning how to get up and maintain motivation when things get tough. His main piece of advice is, “Just try to love what you do and focus on looking ahead rather than behind.”