Biography
I am an MC2 Postdoctoral Fellow at the Maryland Cybersecurity Center (MC2) at the University of Maryland, College Park. I received my Ph.D. degree in Computer Science from the University of Virginia, advised by Prof. David Evans and Prof. Yuan Tian at UCLA. I am interested in machine learning for security and the trustworthy aspects of machine learning, especially in malicious training environments.
I am seeking tenure-track faculty positions. Feel free to reach out if you find a match.
Materials:
Interests
- Trustworhy Machine Learning
- Poisoning Attacks
- Machine Learning for Security
Education
Ph.D. in Computer Science, 2017-2023
University of Virginia
Ph.D. in Computer Science (discontinued due to advisor relocation), 2015-2017
Arizona State University
B.Eng. (Honors) in Electrical Engineering, 2010-2014
China Agricultural University
Selected Publications
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(2023).
SoK: Pitfalls in Evaluating Black-Box Attacks.
In arXiv.
(2023).
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?.
In NeurIPS 2023.
(2023).
Manipulating Transfer Learning for Property Inference.
In CVPR 2023.
(2022).
Poisoning Attacks and Subpopulation Susceptibility.
In VISxAI 2022 (Best Paper Award).
(2022).
Stealthy Backdoors as Compression Artifacts.
In TIFS 2022.
(2021).
Model-Targeted Poisoning Attacks with Provable Convergence.
In ICML, 2021.
(2019).
Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries.
In Usenix Security 2020.
Experience
MC2 Postdoctoral Fellow
Research on machine learning for security and poisoning for beneficial outcomes.
Graduate Research Assistant
Research on trustworthy machine learning at SRG.
Interim Engineering Intern
Robust federated learning against backdoor attacks.
Applied Scientist Intern
Worked on GNN based anomaly detection on extremely large graphs.
Research Intern
Worked on query efficient black-box attacks on vision classifiers.