Iván Rodríguez
Iván has a PhD in theoretical physics from Florence University. After spending a few years doing research in different topics in quantum physics, he became interested in AI at the Max Planck Institute of Quantum Optics, where he applied Deep Neural Network techniques to study different properties of complex quantum materials. After his journey in academia he decided to move to the private sector in order to apply his experience in AI, physics and mathematics to challenging real life problems. Before joining appliedAI in 2021, he worked at a startup applying AI and GPGPU computing to optimize CNC-manufacturing processes.

Iván's work

Seminar

Concept Activation Vectors

In the last seminar of our XAI series, Iván Rodríguez from appliedAI talks about Concept Activation Vectors (CAVs). CAVs go beyond feature …

Iván Rodríguez
Explainable AI
Training

Safe and efficient deep reinforcement learning

This 2-day dive into deep RL for decision and control is suitable for engineers who want to solve real-world control problems with efficient …

Seminar

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

In this presentation, we revisit landmark research that interprets the dropout training process in deep neural networks as approximations of …

Iván Rodríguez
Uncertainty Quantification
Training

An introduction to Bayesian methods in ML

A two-day workshop introducing Bayesian modelling, using practical examples and probabilistic programming.