Hi there, I'm Junyuan Hong 👋
I am a researcher on Machine Learning. My research centers around Privacy-Centric Trustworthy Machine Learning. My vision is to enhance trustworthiness (regarding fairness, robustness and security) under the privacy constraint, e.g., federated learning and differentially-private learning. My research highlights:
- [Privacy] in centralized learning with theoretic understanding, analysis tool and empirical algorithms and its financial application in distributed learning.
- [Trustworthiness] ⨉ Privacy: Federated Learning and Private Edge-Cloud Collaboration.
- Fair pre-training and federated learning📂.
- Robustness by efficient acquisition against adversarial samples📂 and OoD inference📂.
- Secure learning against backdoor attacks in private-data-free distillation.
- Inclusive learning by efficient on-device model adaptation📂, and private outsourcing training and customizable federated learning📂 for low-end devices.
See my homepage and CV for more information.