Francesco Strada

Francesco Strada is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. He serves as a Course Lecturer for Virtual Reality and Technical Art for Cinema and Video Games, and as a Course Collaborator for multiple courses across Computer Engineering, Film and Media Engineering, and Architecture programs. He is an active member of the College of Computer, Film and Mechatronics Engineering and the College of Architecture and Design teaching committees.

Dr. Strada's research focuses on Computer Graphics, Virtual Reality, Augmented Reality, and Human-Computer Interaction with particular emphasis on Embodied Conversational Agents, emotion recognition, and serious games applications. His work bridges technical computer science with psychological and human factors considerations to create more believable and effective virtual experiences. His research spans applications in education, healthcare, automotive interfaces, cultural heritage, and emergency response training.

His recent publications demonstrate a strong trend toward emotionally intelligent virtual agents, VR/AR applications in specialized domains, and technical innovations in latency management and digital human representation. His work often combines psychological principles with technical implementations to enhance user experience and system effectiveness.

Dr. Strada actively supervises PhD students including Alessandro Emmanuel Pecora, Stefano Calzolari, and Leonardo Vezzani, whose research focuses on Emotionally Aware Embodied Conversational Agents (E2CA) and Car AR-HUD design. He leads significant research projects including Holo-BLSD (2024-2025), a Mixed Reality tool for first aid emergency response training, and '50 shadows of AI' (2025), focusing on personalized education in corporate settings.

He is a member of the CGVG - Computer Graphics and Vision Group at DAUIN, where his team develops cutting-edge applications in AR/VR, Human-Computer Interaction, User Experience, Computer Vision, Machine Learning, and Artificial Intelligence. His research has practical applications in education, training, healthcare, automotive interfaces, and cultural heritage preservation.