Welcome to my personal blog, a curated space where I delve into the SOTA research in machine learning and deep learning. I start a post each Saturday, aiming to distill an academic paper into a more digestible format. Recent updates can be found here. A list of more structured long term surveys can be found here.

I created this blog as a means to deepen my grasp of the research papers I read. I found that attempting to clarify a paper compels me to delve into the underlying 'why': Why does a particular method or architecture stand out? How can I effectively communicate its core concepts? It's also about piecing together the broader context, such as recognizing how new ideas are built upon previous works and questioning why some significant contributions were overlooked in the past.

I am Martin Jiang, a graduate student in Computer Science at Columbia University. I previously worked as a research engineer in a AI lab and a desk strats in an investment bank.

Should you encounter any inaccuracies or wish to discuss further, I welcome your insights at yj2577 $AT$ columbia $DOT$ edu.

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