About

Hello, I am a student has been working on many problems:

• Detecting natural selection
• Estimating selective pressures
• Quantifying time-varying selective pressures
• Inferring the distribution of fitness effects
• Detecting archaic admixture

Inspired by the story of Prof. Wen-Hsiung Li, who was encouraged by Dr. Masatoshi Nei, one of the founding editors of Molecular Biology and Evolution, to apply mathematics to genetics—a time when those who understood mathematics in genetics were few and far between—I boldly chose the less-traveled path.

Currently, I am interested in applying machine learning, particularly deep learning, to population genetics—an approach still dismissed by some as a minority perspective in this field, even though population genetics is not fundamentally different from other disciplines, and machine learning has already achieved undeniable success in fields like computer vision and natural language processing.

The recent recognition of pioneers like John J. Hopfield and Geoffrey E. Hinton, who were awarded the 2024 Nobel Prize in Physics for their foundational work on artificial neural networks, further affirms how once-dismissed ideas can revolutionize entire fields. This serves as a reminder that even minority perspectives, when pursued with persistence and rigor, can ultimately transform the landscape of science.