Joshua Paul L. Manalili
Papers
1
Total Citations
13
H-Index
1
About
Joshua Paul L. Manalili is a researcher at the forefront of affective computing, an interdisciplinary field bridging computer science, psychology, and cognitive science to create systems that can perceive, interpret, and respond to human emotion. His most cited work, "Expression Tracking with OpenCV Deep Learning for a Development of Emotionally Aware Chatbots" (2019, 13 citations), exemplifies his core contribution: integrating real-time facial expression analysis with conversational AI to simulate empathy. By leveraging OpenCV and deep learning, Manalili demonstrated how machines can move beyond rigid responses toward emotionally adaptive interactions, a critical step for human-centered technology. His research directly addresses the challenge of making chatbots not just functional, but emotionally intelligent—capable of recognizing user affect and tailoring responses accordingly. This work has implications for mental health support, education, and customer service, where empathetic engagement is paramount. Manalili’s focus on practical, deployable solutions marks him as a key voice in the growing movement to embed emotional awareness into everyday AI, showing that the future of human-computer interaction lies in machines that can truly understand how we feel.
Research Focus
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Top Papers
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