Motivated Machine Learning Enthusiast Seeking Undergraduate Studies

During my graduation thesis project, I was fortunate to be a part of Professor Sun Yu's lab, where I actively participated in weekly group meetings. Our research focused on exploring the application of distributed machine learning in the communication field. My thesis topic involved delving into the intricacies of encrypted traffic recognition algorithms based on federated learning.

Throughout this research journey, I acquired a wealth of knowledge in machine learning, deep learning, and distributed learning. I became proficient in various model structures such as LeNet, AlexNet, and ResNet, which I implemented using Python with the assistance of Tensorflow and Keras libraries. This project allowed me to immerse myself in the entire machine learning process, from constructing robust datasets to designing models, algorithms, evaluation metrics, and even publishing papers.

As a result of my dedicated efforts, I achieved an impressive 94% accuracy rate in identifying VPN encrypted traffic. This accomplishment not only solidified my understanding of the fundamental algorithms and theoretical foundations of machine learning but also sparked my passion to pursue further studies in this field.

Applying for college, I am eager to continue expanding my knowledge and skills in machine learning. I am excited to be a part of an academic community where I can collaborate with esteemed professors and fellow students to further explore the frontiers of this captivating discipline.