Amber Yijia Zheng

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

I've had pleasure to work with Chen Chen at Apple, David Wipf and Tong He at AWS AI Lab.

My research interests lie in generative models and their applications across diverse tasks. Currently, I am interested in leveraging language models for vision. My past works include model editing, model immunization, image restoration, and manifold learning. Please feel free to reach out via email!

Curriculum Vitae
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Education
  • Purdue University
    Purdue University
    Ph.D. Student in Computer Science
    Aug. 2022 - present
  • Shanghai University of Finance and Economics
    Shanghai University of Finance and Economics
    B.sc. in Data Science
    Sept. 2018 - Jul. 2022
Experience
  • Apple
    Apple
    Research Intern
    Apr. 2024 - Sept. 2024
  • Amazon Web Services
    Amazon Web Services
    Applied Scientist Intern
    Feb. 2022 - Apr. 2024
News
2024
Our paper Multi-concept Model Immunization through Differentiable Model Merging is accepted by AAAI 2025!
Dec
I will join Meta Logo Meta GenAI as a Research Scientist Intern in 2025 summer.
Dec
IMMA and LTO are accepted by ECCV 2024!
Jul
Invited keynote speaker of T2MM @ICME 2024.
Jul
IMMA is selected as an oral presentation and awarded 🥈 Best Paper Runner-up 🥈 at AI4CC @CVPR 2024!
Jun
I will join  Apple as a Research Intern in 2024 summer.
Feb
Our paper Graph Machine Learning through the Lens of Bilevel Optimization is accepted by AISTATS 2024!
Jan
2023
Invited speaker for Rising Star Lecture Series of ASTAR Center for Frontier AI Research (CFAR)
Mar
2022
I get NeurIPS 2022 Scholar Award.
Oct
Our paper Learning Manifold Dimensions with Conditional Variational Autoencoders is accepted by NeurIPS 2022!
Sep
I'm on boarding at Purdue as a PhD student. Boiler up!!
Aug
I'm awarded Shanghai Outstanding Graduate and Honours Degree at Shanghai University of Finance and Economics.
Jun
Invited Talks
2024
Invited keynote speaker - T2MM @ICME (link)
Jul
Oral presentation - AI for Content Creation Workshop @CVPR / slides
Jun
2023
CFAR Rising Star speaker - Centre for Frontier AI Research, Singapore (link) / slides
Mar
Selected Publications (view all )
Multi-concept Model Immunization through Differentiable Model Merging
Multi-concept Model Immunization through Differentiable Model Merging

Amber Yijia Zheng, Raymond A. Yeh

AAAI 2025

[Project Page] [arXiv] [Code]

Multi-concept Model Immunization through Differentiable Model Merging
Multi-concept Model Immunization through Differentiable Model Merging

Amber Yijia Zheng, Raymond A. Yeh

AAAI 2025

[Project Page] [arXiv] [Code]

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

[Paper] [Project Page] [arXiv] [Code]

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

[Paper] [Project Page] [arXiv] [Code]

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)

[Paper] [Project Page] [arXiv] [Code]

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

[Paper] [Project Page] [arXiv] [Code]

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

[Paper] [arXiv] [Code]

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

[Paper] [arXiv] [Code]

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

[Paper] [arXiv] [Code]

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

[Paper] [arXiv] [Code]

All publications
Services

Conference reviewer: NeurIPS, ICLR, CVPR

Awards
  • Best paper Runner-up in AI4CC at CVPR 2024
  • NeurIPS Scholar Award 2022
  • Shanghai Outstanding Graduate 2022
  • First-class People's Scholarship 2020, 2021, 2022