Ignacio Parra Alonso

Ignacio Parra Alonso is a Professor at the Department of Automation in the University of Alcalá, Spain. He is affiliated with the INVETT research group (Intelligent vehicles and Traffic technologies), focusing on autonomous systems, sensor fusion, and intelligent transportation. His work emphasizes vehicle localization, trajectory prediction, and human-vehicle interaction in urban environments. He holds a PhD in Engineering from the University of Alcalá (2010), with a thesis on visual odometry for intelligent vehicles.

His research interests span autonomous vehicle technologies, including sensor-based localization (e.g., WiFi, LiDAR, and vision systems), trajectory prediction using deep learning (e.g., Transformers and CNNs), and safety-critical systems for automotive applications. He has contributed to projects like DRIVERTIVE (2016 GCDC) and published extensively on topics like pedestrian intention recognition, lane change prediction, and fail-safe navigation systems.

Recent publications (2021–2024) highlight advancements in transformer-based trajectory prediction, WiFi localization for autonomous driving, and bias evaluation in visual datasets. His work often bridges machine learning techniques with real-world automotive challenges, emphasizing fail-safe mechanisms and human-centric safety.

No scientific awards are explicitly mentioned in the provided texts. His advising record is not detailed here, though he was supervised by Dr. Miguel Angel Sotelo Vázquez during his doctoral studies. He collaborates on projects involving multi-modal sensor integration and has developed tools for dataset labeling and performance analysis in autonomous systems.

Led the INVETT group, which focuses on intelligent vehicles and traffic technologies, advancing interdisciplinary solutions for autonomous navigation challenges.