The research project focuses on using Natural Language Processing (NLP) to extract key highlighted words from data to create concise, readable abstractive highlights. By identifying the most important terms in the text, the project aims to present information more efficiently, helping users quickly grasp the main points without overwhelming details.

I'm collaborating with Professor Farhan Ali at NTU on a fascinating research project investigating the relationship between facial action units (FAUs) and epistemic emotions triggered by magic videos. Our goal is to develop predictive models that accurately identify key epistemic emotions and confusion across various age groups. By analyzing temporal data from FAUs and using advanced neural network architectures like hybrid RNN-CNNs, we aim to improve emotion classification accuracy and gain insights into the dynamic nature of emotional responses. This innovative research pushes the boundaries of computer vision and has potential applications in diverse fields like entertainment, education, and healthcare.