Email : clementf [at] andrew [dot] cmu [dot] edu
Physical : CIC 2223B
I am a 1st year Societal Computing PhD student in the School of Computer Science at
Carnegie Mellon University, advised by
I am a member of CyLab, the security and privacy institute at CMU.
My research interests are in attacks and defenses for multi-party machine learning systems. In the past, I was especially interested in privacy and security vulnerabilities in federated learning.
I finished my MSc in computer science in 2018 at the University of British Columbia, where I was a member of the Networks, Systems and Security (NSS) Lab. I built systems for private and secure multi-party machine learning under the great supervision of Ivan Beschastnikh.
In 2016, I finished my BASc Systems Design Engineering at the University of Waterloo, where I spent several work terms across on a wide variety of projects, from developing bioinformatics research tools to building online recommender systems infrastructure at scale with Linkedin.
- Aug 2019: Starting my PhD at Carnegie Mellon. The journey continues!
- Aug 2019: Paper: "Brokered Agreements in Multi-Party Machine Learning" at APSys 2019. Had a great time in Hangzhou, China!
- June 2019: Paper: "GainForest: Scaling Climate Finance for Forest Conservation using Interpretable Machine Learning on Satellite Imagery" at the Climate Change: How Can AI Help? workshop at ICML 2019.
- Feb 2019: Poster: "Biscotti: A Ledger for Private and Secure Peer to Peer Machine Learning" at NSDI'19.
- Jan 2019: My first day working at Oasis Labs, a Berkeley blockchain startup founded by Professor Dawn Song. Excited to build technology that enables privacy-preserving data computation on the blockchain!
- Nov 2018: Successfully defended my masters thesis: "Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting". The thesis has also been reformatted and posted on arXiv.
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Last Updated: Sept 15, 2019
Copyright © Clement Fung