Dani Servén Marín

I am a data scientist interested in creating tools to study and address current issues in human rights and renewable energies.

My passions include teaching and learning from other people because very often the solutions to our problems already exist, they just have to be applied in a new ways.

I also love traveling and meeting new people, open source software, improvising music, machine learning, trying new things, and learning to not be scared of failure.

Worked most recently creating electrical power forecasting models and predictive control loops to reduce carbon footprint in smart buildings. Studied telecommunications engineering, focusing on machine learning and signal processing.

I am from Spain and USA, and I have a twin brother.

My ML research interests include unsupervised learning, adversarial algorithms, reinforcement learning, bayesian inference, and interpretable models.

I am a core contributor to the pyGAM open source library.


pyGAM: balancing interpretability and predictive power using Generalized Additive Models in Python

Sunday 11:45–12:30 in Hörsaal 3

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