I am a Ph.D. student in Computer Science at Purdue University, advised by Prof. Raymond A. Yeh. I received my B.Sc. in Data Science from Shanghai University of Finance and Economics, where I worked with Prof. Yixuan Qiu.

I am currently a Research Scientist Intern at Meta Superintelligence Lab, working with Dr. Xi Yin and Dr. Lu Liu, building world-class video generation and editing models. Previously, I worked with Dr. Chen Chen at Apple Camera, and with Dr. David Wipf and Tong He at AWS AI Lab.

My research interests span video and image generation and editing, as well as model safety and immunization. I am passionate about building scalable, controllable generative systems that achieve both high fidelity and robust safety guarantees. Please feel free to reach out via email!

Experience

May 2025 - Present Meta Superintelligence Lab
Research Scientist Intern
Apr. 2024 - Sept. 2024 Apple Camera
Research Intern
Feb. 2022 - Apr. 2024 Amazon Web Services
Applied Scientist Intern

Education

Aug. 2022 - present Purdue University
Ph.D. Student in Computer Science
Sept. 2018 - Jul. 2022 Shanghai University of Finance and Economics
B.sc. in Data Science

Publications

2025

Knowledge Distillation Detection for Open-weights Models

Knowledge Distillation Detection for Open-weights Models

Qin Shi*, Amber Yijia Zheng*, Qifan Song, Raymond A. Yeh (* equal contribution)
NeurIPS 2025
DarkDiff: Advancing Low-Light Raw Enhancement by Retasking Diffusion Models for Camera ISP

DarkDiff: Advancing Low-Light Raw Enhancement by Retasking Diffusion Models for Camera ISP

Amber Yijia Zheng, Yu Zhang, Jun Hu, Raymond A. Yeh, Chen Chen
arXiv, 2025
Model Immunization from a Condition Number Perspective

Model Immunization from a Condition Number Perspective

Amber Yijia Zheng*, Site Bai*, Brian Bullins, Raymond A. Yeh (* equal contribution)
ICML 2025 Oral presentation (Top 1%)
CFG-Zero*: Improved Classifier-Free Guidance for Flow Matching Models

CFG-Zero*: Improved Classifier-Free Guidance for Flow Matching Models

Weichen Fan, Amber Yijia Zheng, Raymond A. Yeh, Ziwei Liu
arXiv, 2025
Multi-concept Model Immunization through Differentiable Model Merging

Multi-concept Model Immunization through Differentiable Model Merging

Amber Yijia Zheng, Raymond A. Yeh
AAAI 2025

2024

Learning to obstruct few-shot image classification over restricted classes

Learning to obstruct few-shot image classification over restricted classes

Amber Yijia Zheng*, Chiao-An Yang*, Raymond A. Yeh (* equal contribution)
ECCV 2024
IMMA: Immunizing text-to-image Models against Malicious Adaptation

IMMA: Immunizing text-to-image Models against Malicious Adaptation

Amber Yijia Zheng, Raymond A. Yeh
ECCV 2024
AI4CC Workshop in CVPR, 2024 (Best paper Runner-up)
Graph Machine Learning through the Lens of Bilevel Optimization

Graph Machine Learning through the Lens of Bilevel Optimization

Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf
AISTATS 2024

2022

Learning Manifold Dimensions with Conditional Variational Autoencoders

Learning Manifold Dimensions with Conditional Variational Autoencoders

Amber Yijia Zheng, Tong He, Yixuan Qiu, David Wipf
NeurIPS 2022