About Me

Hi there 👋 I am Xiaowei Yin, a senior undergraduate student at the School of Statistics, Renmin University of China (RUC), majoring in Statistics. You can download my CV here: CV

Research

My research interests includes:

• Learning theory (ML,RL,DL)

I find it interesting that learning theory can characterize the process of “learning” by leveraging concentration inequalities and several measures of complexity, including Rademacher Complexity, VC dimension, and Covering Numbers. Bridging them together is a satisfying intellectual pursuit! 😄 I hope to dig deeper into this field not only because I find it interesting but also because I believe insightful ideas can be born from this theoretical analysis into ML, RL, and DL. I hope to contribute meaningfully to this field.

• Causal Inference

My journey in causal inference began with Simpson’s paradox and the book Causal Inference: What If?, where I got to know the potential outcome framework, IPW estimator, doubly robust estimator, and how they deal with potential biases that may arise from analyzing observational data. I find that researchers in this field are addressing problems that are usually neglected by others, making it a meaningful pursuit for developing reliable, fair, and robust statistical methods. 😊 Fortunately, I have been working at the intersection of causal inference and machine learning, and I am amazed by how they can complement each other.

• Clinial Trial

My research experience has also introduced me to the field of clinical trials (online A/B testing), where I work on subgroup analysis and adaptive experiments. I am deeply fascinated by the topic of precision medicine, which demonstrates great humanity by taking individual situations into consideration. 💕 I also appreciate how adaptive experiments can boost the power of statistical analysis, allowing us to gather more information from a single clinical trial.