Image by Dennis Kummer

Hi, I'm Han

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👨🏻‍💻 📊 🐶 🧬

Han Fang is a Research Scientist Manager at Meta AI, building the world-class recommendation system. Han's team carries out research in the following topics: few-shot learning, multi-modal content understanding, self-supervised user understanding, large-scale modeling, and reinforcement learning.

Han holds a PhD in Applied Mathematics and Statistics from Stony Brook University (2017). In his PhD, he developed a set of graphical and machine learning algorithms for large-scale genomics data. He is a recipient of the President’s Award to Distinguished Doctoral Students, the Woo-Jong Kim Dissertation Award, and the Excellence in Research Award. 


Research @ Facebook

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Harmful content can evolve quickly. Our new AI system adapts to tackle it

We’ve built and recently deployed a new AI technology called Few-Shot Learner (FSL) that can adapt to take action on new or evolving types of harmful content within weeks instead of months. It not only works in more than 100 languages, but it also learns from different kinds of data, such as images and text, and it can strengthen existing AI models that are already deployed to detect other types of harmful content.

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Training AI to detect hate speech in the real world

We’ve built and deployed an innovative system called Reinforcement Integrity Optimizer (RIO). RIO is an end-to-end optimized reinforcement learning (RL) framework. It’s now used to optimize hate speech classifiers that automatically review all content uploaded to Facebook and Instagram.


Supporting  economy recovery and vaccine distribution across the world

We develop the first micro-estimates of wealth and poverty that cover the populated surface of near 100 low and middle-income countries. Together with UC Berkeley, Facebook’s Data for Good team released the Relative Wealth Index data to support COVID-19 economic recovery and equitable vaccine distribution across the world using AI (paper).

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AI advances to better detect hate speech

We have a responsibility to keep the people on our platforms safe, and dealing with hate speech is one of the most complex and important components of this work. To better protect people, we have AI tools to quickly — and often proactively — detect this content.



Tetris Planner: Optimizing Facebook Data Warehouse Data Placement

Facebook's data warehouse has 9+ data centers around the world, which hosts exabytes of data for analytics and machine learning. Planner was deployed to all Facebook's data centers and successfully rebalancing petabytes of data daily.

Research from PhD

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Cell Systems

Scikit-ribo enables accurate estimation and robust modeling of translation dynamics at codon resolution

Scikit-ribo, an open-source analysis package for accurate genome-wide A-site prediction and translation efficiency (TE) estimation from Ribo-seq and RNA sequencing data


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Nature Protocols

Indel variant analysis of short-read sequencing data with Scalpel

Scalpel is an open-source software for reliable indel detection based on the microassembly technique

Contact me


Twitter: @han_fang_