Papers
5
Total Citations
53
H-Index
4
About
George Cioroiu is a researcher at the intersection of human-computer interaction, affective computing, and social signal processing. His work focuses on enabling machines to understand and respond to human emotional and physical states, with a particular emphasis on multimodal emotion recognition and gesture-based control. Cioroiu’s most cited paper (28 citations) introduces a fast, accurate system for automatic hand gesture recognition using EMG signals and fully-connected neural networks, with applications spanning medical prosthetics, robot manipulation, and UAV control. He has also made significant contributions to multimodal emotion recognition, developing a lightweight, uncertainty-based learning model (2024, 10 citations) and an attention-based framework (2023, 6 citations) that advance the field’s ability to integrate diverse sensor data. Notably, Cioroiu contributed to the ROBIN project, creating language resources and a dialog manager for the Pepper robot to enable Romanian-language interaction in real-world scenarios. His work bridges deep learning, affective computing, and human-robot interaction, demonstrating impact through both methodological innovation and practical deployment.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Multimodal Emotion Recognition with Attention6 citations · 2023
- 4Making Pepper Understand and Respond in Romanian5 citations · 2019
- 5A Dialog Manager for Micro-Worlds4 citations · 2020