Victor Xiaohui Li

Well met and welcome to my virtual abode!

I presently serve as a quantitative researcher within an esteemed equity strategy group of an investment bank in New York. My academic credentials include a master of science degree from Columbia University, and an MSc in Machine Learning at Imperial College London.

I possess an ardent devotion towards the domains of data science and quantitative finance, with a particular interest in harnessing data-driven approaches for investment strategy. My past pursuits have encompassed conducting a diverse research on deep leanring empowered Natural Language Process (NLP) and Deep Reinforcement Learning at Columbia, plus more statistics flavoured causal inference, and applied probability within the context of random graph theory at UC Berkeley.

Should you desire a more comprehensive overview of my background, kindly refer to my curriculum vitae or LinkedIn profile.

During my leisure time, I am an avid programming enthusiast and an ardent learner and instructor of data science. I achieved first prize in a global hackathon hosted by SP Global, by using cutting-edge NLP language models. Furthermore, I have honed my pedagogical skills by serving as a teaching assistant for ORCAE4500 Foundations of Data Science at Columbia. As an online mentor for the University of Michigan's applied machine learning program on Coursera, I have helped students from overseas to achieve their goals in the data field.

I regularly participate in academic webinars and conferences related to data science and quantitative investment, and I maintain close ties with my academic peers, including several PhDs who are both my wonderful collaborators and good friends. My passion lies in the intersection of computer science, statistics, and finance, which is precisely where financial data science operates.

If you have any research ideas involving machine learning in finance, I would be delighted to hear from you and please do not hesitate to reach out.

With a presence integrated into the vibrancy of the Wall Street, I serve as an equity quantitative strategist with a full-stack specialization in alternative data, factor construction, Machine Learning/NLP, and systematic equity strategies.

I feel privileged to be part of a team led by esteemed senior quants from the Wall Street, and our team shares the same energy and record as our market-neutral alpha strategies, emphasizing sustainable long-term growth. The team has a history spanning over a decade, and if you're interested, please feel free to learn more in the official website.

Although I find myself in a fiercely competitive industry, my personal philosophy is centered around the pursuit of a poetic way of life and living a multidimensional existence. The likes of Su Shi, a classical Chinese scholar, and the French literary artist Marcel Proust (while my favourite French author is Victor Hugo) are more akin to my ideal state and texture of being. Consequently, I devote a great deal of time elevating my personal hobbies and leisure pursuits.

Undoubtedly, I relish the city life more, where I often visit museums, art exhibitions, and West End operas in London, while I have an equal fondness on the similar places like MoMA or Whitney in New York.

I have a deep passion for French, Japanese, and classical Chinese culture, including poetry, music, literature, film, food, and anime. Additionally, I have a profound appreciation for Russian literature, particularly my youthful love for Gogol and Dostoevsky. Traveling abroad is consequently a regular occurrence for me.

My preferred sport is football, and I have served as a midfield player on my school team. I am a lifelong fan, ardently supporting Real Madrid and Beijing Guoan - my hometown team - for almost twenty years, and my passion for them remains the same.