🎓 I am on the job market and expect to graduate mid-2026.
I am a final-year Ph.D. candidate at the PLSE Lab, School of Computing, National University of Singapore, advised by Prof. Dong Jin Song. My research focuses on building trustworthy and reliable AI systems—making models robust, interpretable, and auditable.
Research Interests
- AI Safety & Robustness: Adversarial attacks and defenses, risk-aware optimization, with applications to GNNs, point clouds, and LLMs.
- Interpretability & Explainability: Explanation methods for model decisions, directionality-aware and risk-aware explanations, model debugging and auditing.
- Geometric Deep Learning: Graph neural networks, point clouds, structure-aware representation learning.
Education
- Doctor of Philosophy in Computer Science (2022 - 2026)
National University of Singapore
Thesis: Trustworthy Geometric Learning: From Structural Biases to Risk-Aware Robustness
Advisor: Prof. Dong Jin Song - Master of Computing in Artificial Intelligence (2020 - 2021)
National University of Singapore - Bachelor of Engineering in Computer Science (2015 - 2019)
Xidian University, Xi'an, China
Experience
- Research Assistant (July 2021 - Dec 2021)
NUS School of Computing, TrustDNN Project
Host: Prof. Dong Jin Song and Prof. Xiao Yan - Research Intern (Jan 2020 - June 2020)
NUS-Singtel Cyber Security R&D Lab
Host: Prof. David S. Rosenblum - Research Intern & Algorithm Engineer (Jan 2018 - June 2018)
JD Intelligent Cities Research, JD.com (MSRA Urban Computing Group)
Host: Prof. Yu Zheng and Dr. Junbo Zhang
Skills
Programming: Python, Bash/Shell Scripting, PyTorch
Systems: Linux/Unix, Git, Docker, Multi-GPU Training, ClickHouse, Spark, Ray
Research: Trustworthy AI, Graph Neural Networks, LLM Safety, Multi-Agent Systems
Language: English, Mandarin
Service & Awards
- Reviewer/Program Committee
- NeurIPS, ICML, AAAI, WWW, FSE, ASE, ISACE (2022-2026)
- Teaching Assistant
- CS5232 Formal Specification and Design Techniques (2024)
- CS4218 Software Testing (2023)
- CS4211 Formal Methods for Software Engineering (2022)
- Awards and Grants
- Graduate Student Travel Grant 2025: IEEE Security and Privacy 2025
- Graduate Student Travel Grant 2024: AAAI 2024
- Graduate Student Travel Grant 2022: 37th IEEE/ACM Automated Software Engineering (ASE)
- National University of Singapore Research Scholarship 2022-2026
- SoC Tuition Fee Support Award 2026
Publications
Under Review
Risk-Aware Robust Graph Network Explanation
Under Review
2026
From Attack Surfaces to Actual Operations: A Survey of Modern LLM Jailbreaks
Findings of the Association for Computational Linguistics (ACL Findings), 2026
2025
Ignoring Directionality Leads to Compromised Graph Neural Network Explanations
2025 IEEE Security and Privacy: Workshops (SPW)
2024
PointCVaR: Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification
Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024
2022
Repairing Failure-inducing Inputs with Input Reflection
The 37th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2022
PIANO: Influence Maximization Meets Deep Reinforcement Learning
IEEE Transactions on Computational Social Systems
2021
Self-Checking Deep Neural Networks in Deployment
The 43rd IEEE/ACM International Conference on Software Engineering (ICSE), 2021
2020
Digraph Inception Convolutional Networks
Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020
Preprints
Generalizing Neural Networks by Reflecting Deviating Data in Production
arXiv:2110.02718
Directed Graph Convolutional Network
arXiv:2004.13970
Disco: Influence Maximization Meets Network Embedding and Deep Learning
arXiv:1906.07378