Introducing Jiaqi Zeng, a senior studying Mathematics at the University of Illinois. This is Jiaqi’s first semester at ATLAS, but she has already found it incredibly rewarding. She first learned about ATLAS through department emails and newsletters, and the Artificial Intelligence & Machine Learning (AI/ML) group caught her attention. She saw it as an incredible opportunity to work on cutting-edge machine learning projects, collaborate with experts, and apply her knowledge to real-world challenges. As an intern in the ATLAS AI/ML group, Jiaqi worked on a Movie Recommender System while also taking advantage of ATLAS’s learning environment. She participated in Kaggle courses, including the Titanic Competition and a Time Series Course, further expanding her skills. Through her internship, Jiaqi gained deeper insight into advanced machine learning techniques and front-end web development. She also improved her presentation and communication skills. Her biggest takeaway from the experience was the importance of continuous learning—especially in the rapidly evolving field of AI and machine learning. Staying up to date with the latest advancements, exploring new methodologies, and refining her skills proved essential to staying relevant and making meaningful contributions. Looking ahead, Jiaqi aims to enter the Quantitative Investment industry, where she can leverage her expertise in AI and machine learning to develop data-driven trading strategies and analyze complex market patterns. She is fascinated by the intersection of finance, mathematics, and machine learning and is eager to apply her skills to solve real-world investment challenges in the future.