Biography
Please note: This is a former member of the ORI.
Daniel was a postdoctoral researcher at the Oxford Robotics Institute (ORI), where I research explainability in robotic systems. He was developing responsible AI metrics for autonomous agents. He completed his PhD research at the University of Oxford's Computer Science Department within the Human-Centred Computing group and the Cognitive Robotics group. During his PhD, Daniel leveraged explainable AI and behavioural science theories to develop interpretable techniques for generating intelligible explanations for automated driving decisions. These explanation techniques have been deployed within large projects like the SAX and the RAILS projects. A prototype was exhibited at the 2022 Goodwood Festival of Speed. Before hisPhD in Oxford, he completed a masters degree in Information Technology from Carnegie Mellon University, and completed a couple of internships and work experiences, e.g., with IBM Research where he worked on anomalous pattern detection in neural network activations. He was a musician in his other life, playing the piano and a bunch of other musical instruments.
