Max Robotics — Global Service Robot Directory + US Certification

About

Daniel Palacios-Alonso is a leading voice at the intersection of artificial intelligence and human-centered computing. His research primarily focuses on advancing data science, explainable AI (XAI), and the application of computational intelligence to real-world challenges. Palacios-Alonso’s major contributions include synthesizing the transformative role of AI in society, as evidenced by his highly cited work on the interplay between natural and artificial computation (312 citations), which explores how machine and deep learning are reshaping social welfare. He has also been pivotal in demystifying deep learning through his influential survey on computational approaches to XAI (191 citations), providing a critical framework for transparency in complex neural systems. Beyond theoretical advances, his work demonstrates practical impact, including innovative methods for stress classification from voice samples using Independent Component Analysis. Palacios-Alonso also contributes to educational technology, developing open online platforms for robot programming competitions. With a career marked by both high-impact reviews and applied research, he stands out as a researcher dedicated to making AI more accessible, understandable, and beneficial for society.