Luofeng Liao
Research Scientist at Meta
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolLuofeng Liao is a research scientist at Meta with eight years of experience at the intersection of machine learning, econometrics, and optimization. Currently a PhD student at Columbia specializing in operations research, statistics, and game theory, he focuses on causal inference, theoretical reinforcement learning, personalized and federated learning, and distributed optimization. His background includes an MS in Statistics from the University of Chicago and software engineering experience at Meta alongside industry exposure at Goldman Sachs. Luofeng blends rigorous theoretical training with practical engineering—shipping research-driven solutions in production settings. Based in New York, he brings a global academic pedigree from Fudan and an exchange at the University of Melbourne, reflecting a breadth of perspectives that informs his work on scalable, data-driven decision systems. Notably, he bridges econometric rigor with systems thinking to drive robust personalized and federated learning methods.
8 years of coding experience
BS computer science, BS computer science at Fudan Universityphd student operations research statistics and game theory, phd student operations research statistics and game theory at Columbia UniversityMS Statistics, MS Statistics at University of ChicagoThe University of Melbourne
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
r-package9
pretty-print7
printing7
r6
meta-analysis3
hypothesis-testing2
Programming languages (2)
Github contributions (5)
DataSlingers/MoMA
May 2018 - Aug 2019
MoMA: Modern Multivariate Analysis in R
Contributions:274 commits, 4 PRs, 46 comments in 1 year 3 months
r-packagerstatsmultivariate-analysismultivariate
luofengliao/luofengliao.github.io
Nov 2021 - Mar 2025
A beautiful, simple, clean, and responsive Jekyll theme for academics
Contributions:78 pushes in 3 years 4 months
responsive-jekyll-themeacademicscleanjekylljekyll-theme
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