I am a passionate and driven computer science enthusiast exploring the depths of AI and machine learning. With a solid foundation in cognitive science, my curiosity for understanding intelligent systems led me to dive into machine learning algorithms, practical AI applications, and deep learning projects. I’ve developed strong skills in Python data analysis, and web development, working with tools like Pytorch, Numpy, and the Pandas.
I’m continuously pushing the boundaries of my technical abilities through hands-on projects, such as building a context-based GPT using Langchain and FastAPI; Transfer architecture based on the paper "Attention is all you need". My problem-solving mindset is complemented by my interest in real-world applications, like developing software solutions for different organizations such us EUFS(Edinburgh formula student), and enhancing my expertise in C and MIPS assembly during my computer system coursework.
My involvement in Formula Student projects has provided me with practical experience in collaborative, high-pressure environments, where I’ve contributed to developing efficient and innovative software solutions for autonomous systems.
Currently, I am focused on pursuing deeper knowledge in AI/ML to further expand my technical expertise. I am participate a LLM deployment open source project "Serverless LLM", which will boost my understanding in LLM inference system with efficient checkpoint loading mechanisms.
Outside of my academic pursuits, I am dedicated to my personal fitness, consistently hitting the gym and enjoying running. I’ve also taken on leadership roles, having acted as the captain of a badminton team. In my downtime, I love reading books across a wide range of genres, with a particular focus on productivity, psychology, and science fiction.