In academia, my projects have focused on applying theoretical concepts to real-world challenges, particularly in the fields of artificial intelligence and computer science. These projects include developing innovative solutions through research collaborations, software development, and experimental analysis to advance knowledge and practical applications.

School Projects

Facial Emotion Recognition System

Developed and implemented a facial expression recognition model using deep learning techniques to classify emotions with high accuracy. Utilized convolutional neural networks (CNNs) and computer vision libraries (OpenCV, TensorFlow) to process and analyze facial landmarks. Enhanced model efficiency by optimizing data preprocessing and training, achieving good accuracy on benchmark dataset (FER2013).

Real-Time Detection Method for Small Traffic Signs Based on Yolov3

Developed a high-precision, real-time detection approach tailored for realistic scenes in driver assistance systems and autonomous driving. Designed and implemented a novel detection scheme, MSA_YOLOv3, to accurately achieve real-time localization and classification of small traffic signs, enhancing the reliability and responsiveness of traffic sign recognition in challenging environments.

Improve Profiling Bank Customer’s Behavior using Machine Learning

Conducted research on profiling bank customers to inform decision-making on granting banking facilities and setting credit limits. Integrated diverse data sources to enhance prediction accuracy and minimize risk, improving the effectiveness of customer profiling and credit assessments.

Community Complaint Management System

Engineered a web application for community residents to streamline communication with management, enabling residents to report issues and allowing staff to coordinate and manage community social activities efficiently.

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