I am a Lecturer (US Assistant Professor equivalent) at the School of Computing Technologies, RMIT University. I earned my Ph.D. degree in Computer Science from RMIT University. My research pivots on building and researching secure systems to address data privacy and security issues in machine learning.
I am always looking for self-motivated students aiming for strong research! Please email me your CV, transcript, research statement, English test score.
- [Aug 24] I am serving as the TPC member for EuroS&P'25
- [Jul 24] I am serving as the TPC member for USENIX Security'25
- [Jul 24] I am serving as the TPC member for AsiaCCS'25
- [Apr 24] Our paper "OblivGNN: Oblivious Inference on Transductive and Inductive Graph Neural Network" has been accepted by USENIX Security'24.
- [Mar 24] I am serving as the Senior PC member for CIKM'24
- [Nov 23] Our course Security Testing 2023 has received STEM College Top Five Courses Award 2023
- [Jul 23] I am deeply honored to be the awardee of STEM College Higher Degree by Research Prize, RMIT University, 2023
- [Jul 22] Our course Cloud Security 2022 has received STEM College Top Five Courses Award 2022
- [Oct 21] Our paper "MediSC: Towards Secure and Lightweight Deep Learning as a Medical Diagnostic Service" has received the Best Paper Award of ESORICS 2021.
Research
My current research focuses on secure multi-party computation and its applications in privacy-preserving machine learning. My goal is to build impactful work that is expected to push forward the deployment of PPML on practical usages like medical diagnostics and mobile image classification. My design philosophy is:
- Devising lightweight and fundamental secure computation protocols resort to advanced cryptographic techniques. I am particularly interested in secure multiparty computation, function secret sharing, zero knowledge proof.
- Building secure and practical PPML systems that harness the insights from computer systems, cryptography, machine learning. I conduct interdisciplinary research empowering versatile real-world service scenarios, like MLaaS (MediSC, CryptMed, OblivGNN), outsourced cloud computation (Sonic, EncSIM), mobile-edge computing (Leia), collaborative computation over distributed data ([ESORICS'19], [TDSC'20]).
Prospective Students
- I am always looking for self-motivated Ph.D. students. If you are interested in AI/Machine Learning Privacy and Security, Secure Computation, please do not hesitate to contact me.
- Please email me your CV, transcripts, research experience (e.g. minor thesis, RA, publications), IELTS/TOEFL score.
- Information on RMIT Ph.D. admission and scholarships can be found here, and here.
Useful Links
- MPC Papers, Tutorials, and Frameworks
- Quality Research
- Computer Security Conference Ranking and Statistic
- Security and Privacy Conference Deadline
Last update: 2022/08