Papers
5
Total Citations
142
H-Index
3
About
Ming-Che Lee is a leading researcher at the intersection of artificial intelligence, affective computing, and intelligent environments. His primary research areas include emotion recognition, human-computer interaction, and AI-driven virtual assistants, with a particular focus on applying deep neural networks to understand and respond to human emotional states. Lee’s most impactful work, “Study on emotion recognition and companion Chatbot using deep neural network” (2020, 65 citations), demonstrates his pioneering approach to creating emotionally aware conversational agents. His complementary study, “Enabling Intelligent Environment by the Design of Emotionally Aware Virtual Assistant: A Case of Smart Campus” (2020, 64 citations), extends this research into real-world applications, exploring how 5G and AIoT technologies can transform smart campuses through emotionally intelligent interfaces. Lee has also advanced Chinese speech emotion recognition (2022, 10 citations) and contributed to robotics with path planning algorithms and UI testing automation. With over 140 total citations, his work bridges the gap between technical AI innovation and human-centered design, making significant strides toward more empathetic and responsive intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1Study on emotion recognition and companion Chatbot using deep neural network65 citations · 2020
- 2
- 3
- 4
- 5