Samuele Russo

About

Samuele Russo is a leading researcher at the intersection of computer vision, affective computing, and human-robot interaction. His work focuses on enabling robots and smart environments to perceive and respond to human emotional and cognitive states. A key contribution is his development of holistic scene understanding frameworks that integrate visual perception with context-aware reasoning, allowing robots to interpret not just objects but also human intent and social cues during interaction. His 2022 paper on this topic has garnered 14 citations, establishing a foundation for more intuitive human-robot collaboration. Russo has also advanced the field of Ambient Assisted Living (AAL), where his 2025 work on facial emotion recognition systems translates a user’s emotional state into adaptive environmental cues, such as colored lighting, to enhance comfort and engagement. This application of affective computing to assistive technology demonstrates a clear path from theory to real-world impact. Additionally, he has tackled the critical challenge of data scarcity in attention assessment, creating a custom dataset of ~120,000 photographs and employing GAN-based data augmentation to train robust machine learning models for determining user focus. Through these contributions, Russo is shaping a future where technology is not only intelligent but also emotionally and socially aware.

Research Focus

Key Achievements

Top Papers

1. 1
   Vision-Based Holistic Scene Understanding for Context-Aware Human-Robot Interaction

   14 citations · 2022
2. 2
   Exploiting facial emotion recognition system for ambient assisted living technologies triggered by interpreting the user's emotional state

   6 citations · 2025
3. 3
   Human Attention Assessment Using A Machine Learning Approach with GAN-based Data Augmentation Technique Trained Using a Custom Dataset

   3 citations · 2022

Key Collaborators

Contact & Links