Federated Learning Federated Learning and Privacy: Flower’s federated learning framework: Medium post: Federated Learning 101 with FEDn – Practical Federated Learning with Azure Machine Learning: AWS post: Applying Federated Learning for ML at the Edge – Synthetic Data What Privacy Officers Need to Know About Synthetic Data: a potential vendor service: Differential Privacy Code...
Writing – Knowns and Unknowns About China’s New Draft Cross-Border Data Rules (Nov 5, 2021), a collaboration piece analyzing the situation of China’s cross-border data transfer. Seven Major Changes in China’s Finalized Personal Information Protection Law (Sept. 15, 2021), a collaboration piece comparing the final version with the draft version of China’s PIPL to explore the...
Last week I was in San Francisco attending a privacy conference co-hosted by Berkeley Law and Peking University Law School. Having attended many privacy events, I still felt fresh this time seeing so many privacy scholars, experts and professionals from China, US and Europe together sitting in the same room to discuss their regional perspectives about privacy and cybersecurity, and I absorbed...
I once wrote a paper about data brokers during my third year at GW Law. From my research on that paper, I heard of the data brokerage industry for the first time and was surprised at how powerful it was (and still is). Data brokers hold massive volume of personal information about millions of people and sell their data services to a wide variety of clients including government agencies. In...
Last week I spent a few days at Harvard Kennedy School for the Public Interest Tech Summit, where I joined dozens of tech fellows and scholars from various backgrounds to explore and discuss around the concept of “public interest technology.” If you are interested, you can click here to watch the video recording of the opening session. A couple of ideas and inspirations I would like...
