I am a fifth-year Ph.D. student in Computer Science at Purdue University. I am fortunate to work with Prof.Xiangyu Zhang.

My research is centered on enhancing the security of a broad spectrum of AI models, with a particular focus on defending against malicious attacks, such as backdoor attacks. I serve as the team leader and core member of the Perspecta-PurdueUMass team, which competes in the TrojAI Program, an AI backdoor detection competition held by IARPA. Over the past four years, our team has achieved top-tier performance, securing leading positions in 14 out of 20 rounds. In the course of this competition, I have developed and refined a suite of scanning methodologies for detecting backdoors across a variety of machine learning models, including object detection systems, malware detectors, and large language models. I also participate in the Amazon Nova AI Challenge as the co-leader of the PurCL team, where we develope advanced red-teaming tools to help build trustworthy AI coding systems.

📢: I am always open to discussions and collaborations. If you are interested in exploring ideas related to AI safety and security, please feel free to contact me via email.

News

🎉 Oct. 2024: Our paper on LLM backdoor scanning got accpeted to S&P 2025.

🎉 Sep. 2024: Our paper on detecting machine generated text got accepted to NeurIPS 2024.

🎉 Aug. 2024: Our paper on FL gradient inversion got accepted to NDSS 2025.

Selected Publications [Full List] (* equal contribution)

• BAIT: Large Language Model Backdoor Scanning by Inverting Attack Target
  Guangyu Shen^*, Siyuan Cheng^*, Zhuo Zhang, Guanhong Tao, Kaiyuan Zhang, Hanxi Guo, Lu Yan, Xiaolong Jin, Shengwei An, Shiqing Ma, Xiangyu Zhang
  Proceedings of the 46th IEEE Symposium on Security and Privacy (S&P 2025)
  

• ODSCAN: Backdoor Scanning for Object Detection Models
  Siyuan Cheng^*, Guangyu Shen^*, Guanhong Tao, Kaiyuan Zhang, Zhuo Zhang, Shengwei An, Xiangzhe Xu, Yingqi Liu, Shiqing Ma, Xiangyu Zhang
  Proceedings of the 45th IEEE Symposiums on Security and Privacy (S&P 2024)
  

• UNIT: Backdoor Mitigation via Automated Neural Distribution Tightening
  Siyuan Cheng^*, Guangyu Shen^*, Kaiyuan Zhang, Guanhong Tao, Shengwei An, Hanxi Guo, Shiqing Ma, Xiangyu Zhang
  The 18th European Conference on Computer Vision (ECCV 2024)
  

• Django: Detecting Trojans in Object Detection Models via Gaussian Focus Calibration
  Guangyu Shen^*, Siyuan Cheng^*, Guanhong Tao, Kaiyuan Zhang, Yingqi Liu, Shengwei An, Shiqing Ma, Xiangyu Zhang
  Proceedings of 37th Conference on Neural Information Processing Systems (NeurIPS 2023)
  

• PICCOLO: Exposing Complex Backdoors in NLP Transformer Models
  Yingqi Liu^*, Guangyu Shen^*, Guanhong Tao, Shengwei An, Shiqing Ma, Xiangyu Zhang Proceedings of the 43rd IEEE Symposiums on Security and Privacy (S&P 2022)
  

• Constrained Optimization with Dynamic Bound-scaling for Effective NLP Backdoor Defense
  Guangyu Shen^*, Yingqi Liu^*, Guanhong Tao, Qiuling Xu, Zhuo Zhang, Shengwei An, Shiqing Ma, Xiangyu Zhang
  Proceedings of the 39th International Conference on Machine Learning (ICML 2022)
  

• Complex Backdoor Detection by Symmetric Feature Differencing
  Yingqi Liu^*, Guangyu Shen^*, Guanhong Tao, Zhenting Wang, Shiqing Ma, Xiangyu Zhang
  IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022 (CVPR 2022)
  

• Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
  Guangyu Shen^*, Yingqi Liu^*, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng, Shiqing Ma, Xiangyu Zhang
  Proceedings of Thirty-eighth International Conference on Machine Learning (ICML 2021)
  

Awards & Honors

Fellowship

• Bilsland Dissertation Fellowship, Purdue, 2025

Competition Record

• 1st place for TrojAI 14 out of 20 rounds
• 2nd place for 2 tracks in Trojan Detection Competition (TDC2022)
  • Target Label Prediction
  • Trigger Synthesis
• 3nd place and most efficient method award for Track II: Backdoor Trigger Recovery for Models in The Competition for LLM and Agent Safety (CLAS2024)

Teaching

• Guest lecture at University of Uath, CS 6958: Intro to Machine Learning, invited by Prof. Guanhong Tao, Oct, 2024
• Teaching Assistance at Purdue University, CS 59200 - AI and Security, Aug. 2024
• Guest lecture at University of Massachusetts, Amherst, COMPSCI 360: Introduction to Computer and Network Security, invited by Prof. Shiqing Ma, Feb. 2024

Services

Competition Co-chair

• IEEE Trojan Removal Competition, 2022

Program Committee

• ACM Conference on Computer and Communications Security (CCS): 2025
• 8th Deep Learning Security and Privacy Workshop(DLSP): 2025
• Workshop on Backdoors in Deep Learning: The Good, the Bad, and the Ugly(BUGS), NeurIPS 2023
• Workshop on Secure and Trustworthy Deep Learning Systems (SecTL), AsiaCCS 2023

Reviewer

• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR): 2022,2023
• International Conference on Machine Learning (ICML): 2022,2023,2024,2025
• European Conference on Computer Vision (ECCV): 2022
• International Conference on Computer Vision (ICCV): 2023
• Conference on Neural Information Processing Systems (NeurIPS): 2022,2023
• International Conference on Learning Representations (ICLR): 2025

Experiences

• Applied Scientist Intern, Amazon AWS AI Lab, May.2024-Aug.2024, May.2023-Aug.2023
• Research Assistant, working with Prof.Baijian Yang, Purdue University, Aug.2019-Jan.2020
• Summer Research Intern, working with Prof.Junfeng Yang and Prof.Baishakhi Ray, Columbia University, May.2019-Aug.2019

Personal

I love movies and Hip-Hop music. 🏂 is my new favorite sport. :p