I am currently Ph.D student of Computer Science at North Carolina State University, where I am fortunately advised by Prof. Xiaorui Liu. Prior to that, I got my M.S. degree in Applied Mathematics at Academy of Mathematics and Systems Science, Chinease Academy of Sciences, advised by Lingyun Wu. I received my B.S. degree in Applied Mathematics at Beijing Normal University, where I was advised by Huajie Chen and Li Cui.
I have several research experiences in industry, including Automated Reasoning at AWS AI, Amazon GuardDuty, Baidu, Inc., and Tsinghua AIR.
I am a big fan of basketball and I idolize Chris Paul and Allen Iverson. Our team won two champions in basketball match in BNU.
💗 Research Interests
- Robust and Reliable Machine Learning
- Graph Machine Learning
- AI for Science
🔥 News
- 🎉 2026.01: Our papers on Scalabe Attack and Molecular Generation are accepted by ICLR 2026.
- 📖 2025.11: New preprint: Fine-Grained Iterative Adversarial Attacks with Limited Computation Budget.
- 💻 2025.05: I join Automated Reasoning Group at AWS AI as an Applied Scientist intern at NYC.
- 🎉 2025.05: Our paper "Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization." is accepted by ICML 2025.
- 🎉 2025.03: Our paper "Post-hoc Interpretability Illumination for Scientific Interaction Discovery." is accepted by ICLR 2025 Workshop XAI4Science.
- 🎉 2025.02: Our "Robustness Reprogramming for Representation Learning" is selected as a Spotlight paper (1.4% ≈ 162/11670) by ICLR 2025.
- 📖 2025.02: New preprint: Boosting Adversarial Robustness and Generalization with Structural Prior.
- 🎉 2025.01: Our paper "Robustness Reprogramming for Representation Learning" is accepted by ICLR 2025. See you in Singapore! It explores an intriguing and fundamental open challenge in Trustworthy AI: Given any well-trained deep learning model, can it be reprogrammed to enhance its robustness?
- 📖 2024.12: New preprint: Post-hoc Interpretability Illumination for Scientific Interaction Discovery. https://arxiv.org/abs/2412.16252
- 📖 2024.11: New preprint: Exploring the Potentials and Challenges of Using Large Language Models for the Analysis of Transcriptional Regulation of Long Non-coding RNAs. https://arxiv.org/abs/2411.03522
- 🎉 2024.10: One paper is accepted by IEEE BigData 2024.
- 💻 2024.10: I give a tutorial at DSAA about "Adversarial Robustness in Graph Neural Networks".
- 📖 2024.10: New preprint: Robustness Reprogramming for Representation Learning. https://arxiv.org/abs/2410.04577
- 🎉 2024.09: Three papers are accepted by NeurIPS 2024. See you in Vancouver!
- 📖 2024.08: I will serve as a reviwer of ICLR 2025.
- 🎉 2024.07: I receive the National AI Research Resource Pilot Award for our research on exploring and enhancing the robustness of LLMs and foundation models.
- 💻 2024.05: I join Amazon AWS GuardDuty as an Applied Scientist intern at NYC.
- 🎉 Our tutorial on "Adversarial Robustness in Graph Neural Networks" is accepted by DSAA 2024. See you in San Diego!
- 🎉 2024.05: I receive the Summer Graduate Merit Awards.
- 🎉 2024.03: One paper is accepted by ICLR 2024 Workshop on Reliable and Responsible Foundation Models.
- 🎉 2024.02: One paper is accepted by Briefings in Bioinformatics.
- 🎉 2023.09: One paper is accepted by NeurIPS 2023. See you in New Orleans!
- 🎉 2023.09: One paper is accepted by BMC Bioinformatics.
- 💻 2023.06: I join Big Search team in Baidu, Inc. as a research intern at Beijing.
- 💻 2022.03: I join Institute for AI Industry Research, Tsinghua University as a research intern.
📝 Publications
As a researcher with a background in both Mathematics and AI, I am deeply engaged in developing robustness-informed neural networks using robust statistics and optimization theories. Feel free to explore my publications contributing to this topic in various domains:
- Graph: [NeurIPS 2024] Robust Graph Neural Networks via Unbiased Aggregation
- Language: [NeurIPS 2024] ProTransformer: Robustify Transformers via Plug-and-Play Paradigm
- Vision: [ICLR 2025] Robustness Reprogramming for Representation Learning
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The International Conference on Learning Representations (ICLR), 2026
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Spotlight (1.4% ≈ 162/11670)The International Conference on Learning Representations (ICLR), 2025
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Neural Information Processing Systems (NeurIPS), 2024
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Neural Information Processing Systems (NeurIPS), 2024
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International Conference on Machine Learning (ICML), 2025
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ICLR Workshop XAI4Science, 2025
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MABM, 2025
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Neural Information Processing Systems (NeurIPS), 2024
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IEEE International Conference on Big Data (IEEE BigData), 2024
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Briefings in Bioinformatics, 2024
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Neural Information Processing Systems (NeurIPS), 2023
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BMC Bioinformatics, 2023
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Preprint, 2025
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Preprint, 2024
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Preprint, 2023
🎖 Honors and Awards
- 🏀 2018.12 Champion of Mingyue Cup Basketball Match of BNU
- 🏆 2017/2018/2019 First-class scholarship of Beijing Normal University
📖 Educations
2023.06 - (now), PhD in Computer Science, North Carolina State University, Raleigh
2020.09 - 2023.06, MS in Mathematics, Academy of Mathematics and Systems Science, Beijing
2016.09 - 2020.06, BS in Mathematics, Beijing Normal University, Beijing
💬 Invited Talks
- 2024.10, Tutorial: “Adversarial Robustness in Graph Neural Networks: Recent Advances and New Frontier”, DSAA 2024, San Diego
- 2024.03, Robustify Transformers via Plug-and-Play Paradigm, MSU
- 2024.01, Research Lightning Talk on Large Language Models and AI Security, NCSU
💻 Internships
2025.05 - 2025.08, Automated Reasoning Group at AWS AI, New York. Mentor: Ferhat Erata- 2024.05 - 2024.08, Amazon GuardDuty, New York. Mentor: Ali Torkamani
2023.06 - 2023.09, Baidu, Inc., Beijing. Mentor: Xiaochi Wei
2022.03 - 2022.09, Institute for AI Industry Research, Tsinghua University, Beijing. Mentor: Wenbing Huang
2021.08 - 2021.10, AiQuant, Beijing. Mentor: Ge Wang
🏀 Basketball is Life
