Team

Hugo is a Machine Learning researcher and engineer, with a special interest in Reinforcement Learning. At DeepMind (Google) he was part of the initial AlphaFold team, where they tackled an important open problem in Computational Biology, now largely solved. At Inductiva, he collaborates with a diverse group of people looking into Math and Physics research problems from the ML perspective.

Luís has a technical career spanning more than two decades, divided between academia and industry. He has conducted research and development in Natural Language Processing, Search Engines, Recommender Systems and Intelligent Voice Assistants. At Inductiva, Luís is working on developing a team of talented Scientific Machine Learning researchers and engineers capable of achieving breakthroughs in fundamental sciences.

Clara is a strong believer in the value of Innovation and Technology. She has an award-winning track record in building and fostering knowledge networks at global scale, bringing together academic communities, enterprises and startups. At Inductiva she leads the efforts to expand our industrial and academic partnerships, investor relations and defining a long term business strategy. Clara is also an active member of the Women in Tech community, which aligns perfectly with Inductiva's values around diversity.

Augusto holds a MSc in Applied Mathematics from Instituto Superior Técnico, Lisbon. At Inductiva he is currently investigating Deep Learning and Reinforcement Learning techniques for combinatorial optimization problems.

David holds a PhD in Theoretical and Mathematical Physics from Heriot-Watt University and a MSc in Mathematics and Physics from the University of Warwick. He has largely been working in the theory of condensed matter, notably in light-matter interactions in quantum materials. At Inductiva he is working on Quantum Physics problems using Machine Learning techniques.

Maria holds a MSc in Physics Engineering from University of Coimbra and has worked as a software engineer in medical imaging projects. At Inductiva she applies Machine Learning techniques to fundamental problems in Physics.

Manuel holds a MSc in Biomedical Engineering from Instituto Superior Técnico, in Lisbon, which gave him a very solid and diverse background in Math, Physics, Chemistry, Biology and Machine Learning. At Inductiva he researches and applies Deep Learning techniques to solving physics-inspired Partial Differential Equations.

Fábio holds a PhD in Plasma Physics from Instituto Superior Técnico, in Lisbon. He has extensive experience developing computational methods for complex physical systems, often combining knowlege from different sub-fields, including Fluid Dynamics, Electromagnetism, General Relativity and Quantum Mechanics. At Inductiva he combines his previous expertise with Deep Learning techniques for solving physics-inspired Partial Differential Equations.

Eduardo holds a PhD in Algebraic Geometry from the University of Warwick, and undergraduate degrees in Mathematics from the University of Coimbra. He is currently identifying interesting Math problems and “translating” them into a computational formulation, to be tackled with Machine Learning techniques.

MEng in Mechanical Engineering, now pursuing a joint PhD with FEUP and MIT. At Inductiva he is researching how neural networks can help solve differential equations related to mechanical parts.

MEng in Mechanical Engineering, at the beginning of his PhD studies. At Inductiva Bruno is looking into neural methods to solve Partial Differential Equations relevant to his domain.

Ana is completing her MSc in Mathematics at the University of Coimbra. At Inductiva she is applying Machine Learning methods to an Algebra and Optimization problem.

David is completing his MSc in Physics at the University of Porto. At Inductiva he is applying Machine Learning methods to Statistical Physics problems.

José holds a BSc in Mathematics from the University of Coimbra, and he is passionate about Machine Learning and Research. He collaborates with Inductiva on Physics-inspired Partial Differential Equations and neural solver methods.

Mariana holds (two) MSc in Applied Mathematics and has conducted research in Machine Learning, Optimization and Numerical Methods. She collaborates with Inductiva on Deep Learning methods for Partial Differential Equations.

Kevin is a Medicine student, with a long track record of medals in Math Olympiads and Programming competitions. At Inductiva he contributs to implementing efficient Linear Algebra and Combinatorial Optimization algorithms.

Computer scientist by training and experienced ex-Google engineer, Ștefan is helping Inductiva establish a culture of engineering excellence and an agile infrastructure to conduct Machine Learning research.