About

Chuan Guo is a Research Scientist at FAIR/Meta, currently working on machine learning and security. With a PhD in Computer Science from Cornell University, Chuan's research interests revolve around test-time attacks against machine learning systems, differential privacy, and related notions. He has also worked on text classification, Bayesian optimization, and neural network calibration. Chuan's current role at Facebook involves working on large-scale text classification, with a focus on extreme multi-label classification and XML. His work in this area was accepted at NeurIPS 2019. In the past, he has worked as a research intern at Facebook AI, where he worked on certified data removal from a trained machine learning model. His work in this area was accepted at ICML 2020. He has also worked on defense against adversarial examples, with his work in this area being accepted at ICLR 2018. Chuan has a strong educational background, with a Bachelor of Mathematics in Computer Science, Combinatorics & Optimization, and Pure Mathematics, and a Master of Mathematics in Cryptography, both from the University of Waterloo. He also holds a PhD in Computer Science from Cornell University. Chuan's technical skills include research in machine learning, text classification, neural networks, and test. He has relevant experience of 2.78 years in the field.