Javier Hernandez

概要

Javier Hernandez is a Principal Researcher in the Interactive Multimodal Futures (IMF) team at Microsoft Research and an Associate Editor of the IEEE Transactions on Affective Computing.

Javier’s research combines affective computing, conversational AI, and human-centered machine learning. He builds multimodal systems that sense, interpret, and respond to human emotional and social signals, with the goal of making AI interactions more natural, empathetic, and effective. His foundational contributions span the measurement and management of daily-life stress through physiological sensing in everyday settings. His recent work investigates how large language models break down in collaborative dialogue, using large-scale behavioral data and systematic taxonomy-building methods to inform the design of more reliable conversational agents.

Javier’s work has been recognized with an MIT Technology Review Innovators Under 35 (TR35) award and multiple best paper awards at top venues. His research has been featured in National Geographic, The Economist, and The Times. He serves on program committees for premier HCI and affective computing conferences, gives guest lectures at MIT and other universities, and speaks at a wide range of academic and industry venues.

Javier earned a B.S. in Computer Systems Engineering (2004) and an M.S. in Information Technology (2007) from Ramon Llull University in Barcelona, Spain. He also received an M.S. in Robotics and Artificial Intelligence (2010) from Carnegie Mellon University and a Ph.D. in Media Arts and Sciences (2015) from the Massachusetts Institute of Technology.