Natalia Diaz Rodriguez on Pitt HexAI

Health and Explainable AI Podcast - A podcast by Pitt Health and Explainable AI (Pitt HexAI) Research Laboratory

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Natalia Díaz Rodríguez, an Assistant Professor focusing on trustworthy AI and responsible AI systems at the University of Granada, Spain and a researcher at DaSCI (Andalusian Data Science and Computational Intelligence Institute), speaks with Pitt HexAI's podcast host Jordan Gass-Poore' about her work and thoughts on explainable AI. Natalia graduated from University of Granada (Spain) in 2010 and got her double PhD from Abo Akademi (Finland) and University of Granada in 2015 on symbolic Artificial Intelligence. She was Asst. Prof. of Artificial Intelligence at the Autonomous Systems and Robotics Lab at ENSTA Paris, Institute Polytechnique de Paris, and INRIA Flowers team on developmental robotics. Her background is on knowledge representation, reasoning and machine learning. Her current interests include deep, reinforcement and unsupervised learning, open-ended learning, continual/lifelong learning, (state) representation learning, neural-symbolic computation, computer vision, autonomous systems, explainable AI, and AI for social good. She has worked on R&D at CERN (Switzerland), Philips Research (Netherlands), University of California Santa Cruz, and in industry in Silicon Valley.