Wenzhuo Huang

Wenzhuo Huang's work experience includes being a Quantitative Researcher at Citadel Securities since 2022. Prior to that, they worked as a Graduate Student Researcher and Graduate Teaching Assistant at UC San Diego Jacobs School of Engineering from 2016 to 2022, where they were involved in designing, simulating, and optimizing photonic nanostructures. In 2021, Wenzhuo Huang was a PhD Research Intern at Meta and a Quantitative Research Intern at Citadel Securities. They also have experience as an Undergraduate Student Researcher at Peking University from 2013 to 2015.

Wenzhuo Huang completed their education in a chronological order. Wenzhuo pursued a Bachelor of Science (B.Sc.) in Physics from Peking University, from 2012 to 2016. In 2015, they also had a brief academic experience in the field of Physics at The Hong Kong University of Science and Technology. Subsequently, they joined UC San Diego in 2016 to pursue a Master's degree in Electrical and Computer Engineering - Photonics, which they completed in 2018. Building on their master's degree, Wenzhuo Huang continued their academic journey at UC San Diego and is currently enrolled in a Doctor of Philosophy - PhD program, specializing in Electrical and Computer Engineering - Photonics.

In addition to their formal education, Wenzhuo Huang has also obtained several certifications. These include a Python and Machine-Learning for Asset Management with Alternative Data Sets certification from the EDHEC Business School in June 2022. Wenzhuo also completed an Introduction to Portfolio Construction and Analysis with Python certification from the same institution in October 2020. Furthermore, they hold a CFA Institute Investment Foundations™ certification from the CFA Institute, obtained in August 2020. Wenzhuo Huang has also completed a Micro-MBA Program from the University of California, San Diego - Rady School of Management in August 2020. In the field of Machine Learning, they have acquired certifications in areas such as Machine Learning from Stanford Online in June 2020 and Neural Networks and Deep Learning from deeplearning.ai in June 2020.