Fanbo Meng

Fanbo Meng's work experience begins in 2014 as a Graduate Teaching Assistant at the University of Notre Dame. From 2014 to 2019, Meng worked as a Research Assistant at the university, where they designed analysis strategies and implemented Boosted Decision Trees for physics data analysis. They also co-designed packages in C++ and Python for terabyte-scale data analysis. In 2014, Meng also started working as a Visiting Research Assistant at CERN, where they contributed to a million-dollar sub-detector upgrade and improved data collection efficiency at the CMS particle detector.

In 2020, Meng co-founded The AI Institute and took on multiple roles, including Co-founder, Data Scientist, Content Director, and Teaching Director. In this position, Meng provided training on data science-related topics and skills to graduate students and acted as a consultant for data science projects. They also designed and prepared data science study materials and analyses.

In December 2020, Meng joined Professorbob.ai as the Deputy Chief in Data Science. Professorbob.ai is a virtual assistant developed by The AI Institute team to answer users' questions in a specific knowledge domain after undergoing artificial intelligence training.

Overall, Meng's work experience showcases their expertise in data science, physics data analysis, and algorithm optimization.

Fanbo Meng completed their education with a Bachelor of Science (BS) degree in Physics from Wuhan University in 2012. Fanbo then pursued a Doctor of Philosophy (PhD) degree in Elementary Particle Physics from the University of Notre Dame between 2012 and 2019. Additionally, Fanbo Meng obtained several certifications in various machine learning subjects from Coursera. These certifications include "Sequence Models" (obtained in January 2019), "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" (obtained in September 2018), "Structuring Machine Learning Projects" (obtained in September 2018), "Neural Networks and Deep Learning" (obtained in August 2018), and "Machine Learning" (obtained in February 2018).