Longxiang Zhang

About Longxiang Zhang

I am an M.S. student in Data Science from Columbia University. My team research experiences makes me different from other data science candidates. As a student leader, I led a research project on adaptive activation functions in deep learning in 2021. In addition, I applied the results of this project to another program about maize leaf disease identification. Thanks to those experiences, I became familiar with Python language and its data science toolboxes, such as NumPy, Pandas, Matplotlib, Seaborn, and scikit-learn. Also, those research programs gave me chances to learn about the theories of most ML algorithms and apply the PyTorch framework to construct neural networks.My internship as an NLP research assistant in IFLYTEK taught me how to deal with dirty data got from people’s daily life. In that position, I also learned to become an eligible team member by fully contributing to tasks assigned to me. Besides, I extended my ML knowledge to solve real-life problems through this experience.My next focus areas will be causal inference and Bayesian machine learning, which I believe will add a degree of interpretability and robustness to machine learning models and thus improve the reliability of machine learning-based decision systems. I will take courses in Bayesian statistics, causal inference, and other related courses to prepare myself to explore these areas.

Experience

1. Machine Learning and Data Science Intern

   Meituan

   May 2023 — Present · Beijing, CN

   Applied Machine Learning, Statistical, and Causal Inference methods to improve the efficiency of the customer service system in Meituan.

Education

• Columbia Engineering

  Master of Science - MS, Data Science

• China Agricultural University

  Bachelor of Science - BS, Mathematics and Applied Mathematics

• China Agricultural University

  Bachelor of Science - BS, Data Science and Big Data Technology