Yimeng (Damon) Zhang

Applied Scientist · Amazon · Multimodal AI Agents

Santa Clara, CA

01 — About

I received my B.Eng. degree in Electrical and Electronic Engineering from The University of Sheffield, UK, in 2018, and my M.Sc. degree in Electrical Engineering from Columbia University, USA, in 2020. I completed my Ph.D. in Computer Science at Michigan State University, USA under the supervision of Prof. Sijia Liu in 2025. I am currently an Applied Scientist at Amazon, where I work on multimodal AI agents.

02 — Research

My research centers on enhancing the efficiency of machine learning from multiple perspectives, including data optimization, model architecture, and parameter-efficient fine-tuning techniques. I aim to improve both the training and inference processes by reducing computational and resource demands while maintaining or enhancing performance. A key aspect of my work also involves ensuring model safety, with a focus on robustness against adversarial attacks. By integrating efficiency and safety, my research strives to create scalable, reliable, and secure AI systems that perform effectively in diverse real-world applications.

Deep Learning

Generative Models (LLMs, multi-modality, diffusion models), AI Safety (adversarial attack & defense)

Optimization

Zeroth-Order Optimization, Dataset/Model pruning

03 — Service

04 — Publications

Research Summary Google Scholar * equal contribution

2026

  1. SpanUQ: Span-Level Uncertainty Quantification for Large Language Model GenerationNeurIPS 2026

    Y. Zhang, Y. Zhuang, Z. Wang, Y. Lu, P. Chen, A. Gupta, Z. Su, M. Tan, Z. Zhang, Q. Liu, M. Ramanathan, R. Maragoud, E. Vul, J. Huang, D. Wang

    PaperCodeModelDataset
  2. SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model AgentsarXiv

    Z. Wang, Y. Lu, Y. Zhang, Q. Liu, C. Luo, J. Gesi, H. Lu, Y. Sang, M. Li, J. Huang, D. Wang

    Paper
  3. Firefly: Illuminating Large-Scale Verified Tool-Call Data Generation from Real APIsNeurIPS 2026

    Y. Lu, Z. Wang, Y. Lu, Y. Sang, J. Gesi, X. Tang, Y. Zhang, Z. Dai, H. Liu, H. Lu, C. Luo, Q. He, B. Dumoulin, J. Huang, D. Wang

    Paper
  4. Trajectory2Task: Training Robust Tool-Calling Agents with Synthesized Yet Verifiable Data for Complex User IntentsACL 2026

    Z. Wang, Y. Lu, Y. Zhang, P. Chen, Z. Dong, J. Huang, J. Gesi, X. Tang, C. Luo, Q. Liu, Y. Sang, H. Lu, M. Li, J. Lai, D. Wang

    Paper
  5. Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping via Reinforcement LearningICLR 2026

    Y. Zhang, T. Wang, J. Gesi, Z. Wang, Y. Lu, J. Lin, S. Zhan, V. Gao, R. Jiao, J. Liu, K. Qian, Y. Tang, R. Xue, H. Zhang, Q. Cui, Y. Guo, D. Wang

    PaperDataset
  6. Unlearning Isn’t Invisible: Detecting Unlearning Traces in LLMs from Model OutputsICLR 2026

    Y. Chen, S. Pal, Y. Zhang, Q. Qu, S. Liu

2025

  1. Customer-R1: Personalized Simulation of Human Behaviors via RL-based LLM Agent in Online ShoppingarXiv

    Z. Wang, Y. Lu, Y. Zhang, J. Huang, D. Wang

    Paper
  2. See, Think, Act: Online Shopper Behavior Simulation with VLM AgentsarXiv

    Y. Zhang, J. Gesi, R. Xue, T. Wang, Z. Wang, Y. Lu, S. Zhan, H. Zeng, Q. Cui, Y. Guo, J. Huang, M. Shah, D. Wang

  3. The Dual Power of Interpretable Token Embeddings: Jailbreaking Attacks and Defenses for Diffusion Model UnlearningarXiv

    S. Chen, Y. Zhang, S. Liu, Q. Qu

  4. ID-Patch: Robust ID Association for Group Photo PersonalizationCVPR 2025

    Y. Zhang, T. Zhi, J. Liu, S. Sang, L. Jiang, Q. Yan, S. Liu, L. Luo

    PaperCodeHF ModelSlidePosterDemo

2024

  1. Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion ModelsNeurIPS 2024

    Y. Zhang, X. Chen, J. Jia, Y. Zhang, C. Fan, J. Liu, M. Hong, K. Ding, S. Liu

    CodeHF ModelDemoPosterSlide
  2. To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images … For NowECCV 2024

    Y. Zhang*, J. Jia*, X. Chen, A. Chen, Y. Zhang, J. Liu, K. Ding, S. Liu

    CodeDemoPosterUnlearned DM BenchmarkSlide
  3. UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion ModelsNeurIPS 2024

    Y. Zhang, C. Fan, Y. Zhang, Y. Yao, J. Jia, J. Liu, X. Liu, S. Liu

    PaperPosterCodeBenchmarkDataset
  4. SOUL: Unlocking the Power of Second-Order Optimization for LLM UnlearningEMNLP 2024

    J. Jia, Y. Zhang, Y. Zhang, J. Liu, B. Runwal, J. Diffenderfer, B. Kailkhura, S. Liu

    CodePosterSlide
  5. Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A BenchmarkICML 2024

    Y. Zhang*, P. Li*, J. Hong*, J. Li, Y. Zhang, W. Zheng, P.-Y. Chen, J. D. Lee, W. Yin, M. Hong, Z. Wang, S. Liu, T. Chen

    CodePoster
  6. DeepZero: Scaling up Zeroth-Order Optimization for Deep Model TrainingICLR 2024

    A. Chen*, Y. Zhang*, J. Jia, J. Diffenderfer, J. Liu, K. Parasyris, Y. Zhang, Z. Zhang, B. Kailkhura, S. Liu

    CodeSlidePoster
  7. The power of few: accelerating and enhancing data reweighting with coreset selectionICASSP 2024

    M. Jafari, Y. Zhang, Y. Zhang, S. Liu

2023

  1. Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer LearningNeurIPS 2023

    Y. Zhang*, Y. Zhang*, A. Chen*, J. Jia, J. Liu, G. Liu, M. Hong, S. Chang, S. Liu

    PaperCodePosterSlide
  2. Text-Visual Prompting for Efficient 2D Temporal Video GroundingCVPR 2023

    Y. Zhang, X. Chen, J. Jia, S. Liu, K. Ding

    CodeHF ModelPosterSlide
  3. Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge DevicesASP-DAC 2023

    Y. Zhang*, A.K. Kamath*, Q. Wu*, Z. Fan*, W. Chen, Z. Wang, S. Chang, S. Liu, C. Hao

    Slide

2022

  1. How to Robustify Black-Box ML Models? A Zeroth-Order Optimization PerspectiveICLR 2022Spotlight · top 5%

    Y. Zhang, Y. Yao, J. Jia, J. Yi, M. Hong, S. Chang, S. Liu

    CodePosterSlide
  2. Reverse Engineering of Imperceptible Adversarial Image PerturbationsICLR 2022

    Y. Gong, Y. Yao, Y. Li, Y. Zhang, X. Liu, X. Lin, S. Liu

    Code

2020

  1. Video Synthesis via Transform-Based Tensor Neural NetworkACM MM 2020

    Y. Zhang, X. Y. Liu, B. Wu, A. Walid

  2. Tensor FISTA-Net for real-time snapshot compressive imagingAAAI 2020

    X. Han, B. Wu, Z. Shou, X. Y. Liu, Y. Zhang, L. Kong