Bin Feng

Bin Feng is an accomplished research scientist and machine learning engineer currently at Meta, specializing in privacy-preserving conversion attribution models that deliver substantial value to advertisers and users. Prior experience includes serving as a graduate research assistant at the University of Illinois at Urbana-Champaign, an intern at Facebook focusing on ads and signal matching with a notable improvement to match rates, and a machine learning engineer at the Federal Reserve Bank of Chicago working on interpretable machine learning. Bin Feng has also achieved recognition as a top Kaggle competitions expert, earning silver medals in notable challenges. Educationally, Bin Feng holds a Ph.D. and M.S. in Transportation (Computational Physics) from the University of Illinois at Urbana-Champaign and a Bachelor's degree in Engineering from Zhejiang University.