Image by Dennis Kummer

Hi, I'm Han

Han Fang 2019.JPG

👨🏻‍💻 📊 🐶 🧬

Han Fang is a Research Scientist Manager at Meta, building the world-class recommendation system​ with state-of-the-art AI on user understanding. Han supports and builds up a team of 30 research scientist and machine learning engineers that drive step-function change in recommendation outcome for priority surfaces across IG and FB, including Feed and Reels.


Han holds a PhD in Applied Mathematics and Statistics and has published highly influential papers in top-tier conferences and journals with 3000+ citations. 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. Han is a strong believer in giving back to the community by mentoring and growing future talents. In his spare time, he serves as an industry advisory board member for University of Washington.


Research @ Facebook

Screen Shot 2021-12-08 at 9.43.59 AM.png

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.

Screen Shot 2021-12-08 at 10.01.01 AM.png

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).

ai for hate speech.jpg

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

cell systems.png

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


nature protocols.png

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_