Hi there! I’m Qilin Xu (许琪林), a senior pursuing my degree in Electrical Engineering at Chongqing University and the University of Cincinnati Joint Co-op Institute. As I embark on my final year, I am grateful for the incredible opportunities I’ve encountered, including achieving a GPA of 3.94/4.0 and being honored with a National Scholarship! ✨
Currently, I’m thrilled to serve as a Research Assistant at the MARS Lab at Wuhan University, where I delve into the fascinating world of multimodal machine learning. My research focuses on harmonizing diverse data sources, like images and text, to significantly enhance how machines understand and interact with our world. This enriching role has deepened my knowledge of machine learning algorithms and polished my research skills. 🤖
My co-op experiences have been instrumental in shaping my approach to AI research. At Chongqing University, I was excited to lead a team analyzing energy consumption through self-supervised learning techniques. This experience honed my analytical and communication skills—critical elements for fruitful collaboration in research! ⚡
At the Tsinghua Sichuan Energy Internet Research Institute, I explored the impact of renewable energy on power grid frequency responses by applying Graph Neural Networks (GNNs). This hands-on experience sharpened my problem-solving skills and logical thinking, essential for tackling the complex challenges in AI. ⚙️
These experiences have ignited my passion for furthering AI research and innovation. I am excited to apply for a Ph.D. in Electrical Engineering and Computer Science (EECS), with the aspiration of developing cutting-edge AI methodologies and exploring their transformative real-world applications. The chance to contribute to the thriving field of machine learning, particularly in multimodal machine learning, truly excites me! 💡
I am eager to collaborate with fellow researchers in machine learning and multimodal AI, as collective insights often lead to the most impactful and innovative solutions. I am committed to learning and making meaningful contributions to this dynamic field. Let’s work together to push the boundaries of the way machines understand and interact with the world! 🌏