Francisco J. Perales

About

Francisco J. Perales is a leading researcher in artificial intelligence, human-computer interaction, and affective computing, with a particular focus on human activity recognition and social robotics. His work bridges the gap between machine perception and natural human behavior, developing systems that can interpret complex human actions and emotional states in real-world environments. One of his most influential contributions is the development of a novel deep learning model that uses skeleton-based features for the prediction of human activities, achieving robust performance even in challenging, high-speed scenarios (42 citations). Complementing this, his research on social robotics demonstrates how robots can be deployed "in the wild" to evaluate facial expressions and emotional cues, advancing the field of human-robot interaction (40 citations). Perales’s work is notable for its practical, real-world application—moving beyond controlled lab settings to create AI systems that genuinely understand and respond to human users. His contributions have significant implications for assistive technologies, autonomous systems, and empathetic robotics, making him a key figure in the development of socially intelligent machines.

Research Focus

Key Achievements

Top Papers

1. 1
   Prediction of Human Activities Based on a New Structure of Skeleton Features and Deep Learning Model

   42 citations · 2020
2. 2
   Using a Social Robot to Evaluate Facial Expressions in the Wild

   40 citations · 2020

Key Collaborators

Contact & Links