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 at the intersection of machine learning, security, and systems. In the past, I was especially interested in attacks and defenses for multi-party machine learning systems such as Google's federated learning.
I finished my M.Sc. 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 helpful supervision of Ivan Beschastnikh.
Even more before that, I finished my B.A.Sc. Systems Design Engineering in 2016 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.
Email : clementf [at] andrew [dot] cmu [dot] edu
Physical : CIC 2223B
- 08/2019 [Misc]: Starting my PhD at CMU. The journey continues!
- 08/2019 [Paper]: "Brokered Agreements in Multi-Party Machine Learning" at APSys 2019. Had a great time in Hangzhou, China!
- 07/2019 [Work]: My last day at Oasis Labs. Thank you so much for a great 7 months in California, and I'm so excited to see more great work in privacy-preserving technology coming from the team!
- 06/2019 [Paper]: "GainForest: Scaling Climate Finance for Forest Conservation using Interpretable Machine Learning on Satellite Imagery" at the ICML 2019, Climate Change: How Can AI Help? workshop in Long Beach.
- 02/2019 [Poster]: "Biscotti: A Ledger for Private and Secure Peer to Peer Machine Learning" at NSDI'19.
- 01/2019 [Work]: 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!
- 11/2018 [Misc]: 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: Dec 31, 2019
Copyright © Clement Fung