Guangyu (Noah) Shen

I am a Research Scientist at Google DeepMind. I work on identifying and mitigating misaligned behaviors in frontier models.

I earned my Ph.D. in Computer Science from Purdue University, advised by Prof. Xiangyu Zhang. My doctoral research spanned AI safety and security, from discovering attack vectors such as backdoors and jailbreaks to developing mitigations through safety alignment and guardrails. I also led efforts in real-world AI security challenges, achieving leading performances in the IARPA TrojAI Challenge and the Amazon Nova AI Challenge.

Guangyu (Noah) Shen

News

Sep. 2026 Our paper LensCT on fine-grained AI-involved text detection was accepted to NeurIPS 2026.

Sep. 2026 I joined Google DeepMind as a Research Scientist, working on Frontier Safety Mitigations.

Jul. 2026 I successfully defended my Ph.D. in Computer Science at Purdue University!

Selected publications All publications ↗

* Equal contribution

Awards & Honors

Fellowship

  • Bilsland Dissertation Fellowship, Purdue, 2025

Competition Record

  • 1st place for Amazon Nova AI Challenge ($250,000)
  • 1st place for TrojAI 14 out of 20 rounds
  • 2nd place for 2 tracks in Trojan Detection Competition (TDC2022)
    • Target Label Prediction
    • Trigger Synthesis
  • 3rd 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 Virginia Tech, CS 6804: AI Security and Privacy, invited by Prof. Shengwei An, Nov. 2025
  • Guest lecture at Rice University, COMP 620: Machine Learning System Seminar, invited by Prof. Yuke Wang, Nov. 2025
  • Guest lecture at University of Utah, CS 6958: Machine Learning Security, invited by Prof. Guanhong Tao, Oct. 2025
  • Guest lecture at University of Georgia, CSCI 8000: Red-Teaming for LLM Agents, invited by Prof. Zhen Xiang, Oct. 2025
  • Guest lecture at University of Utah, CS 6958: Machine Learning Security, invited by Prof. Guanhong Tao, Oct. 2024
  • Teaching Assistant 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

  • IEEE Conference on Secure and Trustworthy Machine Learning (SaTML): 2027
  • ACM Conference on Computer and Communications Security (CCS): 2025, 2026
  • 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

Experience

  • Research Scientist, Google DeepMind, Sep. 2026–present
  • 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 music. 🏂 is my new favorite sport. :p