Artificial Neural Networks are programs that write themselves when given an objective, some training data, and abundant computing power. Recently, these programs have brought about a wide array of impressive innovations, such as self-driving cars, face recognition, and human-like speech generators. This course offers you an introduction to Deep Artificial Neural Networks (i.e. “Deep Learning”). With focus on both theory and practice, we cover models for various applications, how they are trained and tested, and how they can be deployed in real-world applications
PhD in Electrical Engineering from the University of Valencia 2020. Research focused on the incorporation of physical knowledge in machine learning models. Data science consultant to various startups 2020 such as eeSea and Pensure. MSc in Mathematical modelling and computation from the Technical University of Denmark 2016. Teaching assistant in various courses 2015-2016. With DIS since 2021.
PhD in Computer Science from Cornell University 2012. Assistant professor at ITU Copenhagen since 2015. ERCIM Postdoctoral Fellow at the Swedish Institute of Computer Science (2012-2013) and Project Leader in the Media Technology and Interaction Design Department at the Royal Institute of Technology (2014). With DIS since 2019.