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About Me

My name is Bingyin Zhao (赵秉崟). I am a Research Fellow at the National University of Singapore, working with Dr. Biplab Sikdar. I earned my Ph.D. in Computer Engineering from Clemson University in the United States under the supervision of Dr. Yingjie Lao.

I worked as a Deep Learning Software and Research Intern at NVIDIA under the supervision of Dr. Jose M. Alvarez and Dr. Zhiding Yu. I received a full-time offer as a Senior System Software Engineer from NVIDIA after the internship but could not return to the U.S. due to an unexpected visa issue when I came back to visit my family in China. I then relocated to Singapore. Thank you Singapore for having me and I love this great place!

My research interests include Generative AI, Trustworthy AI and Computer Vision. I have authored, co-first-authored and co-authored several research papers in CVPR, ICCV, AAAI, TCAD, DAC, etc. I also serve as a reviewer for multiple computer vision, artificial intelligence and machine learning conferences, including CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, AAAI, etc.

I hope for world peace and that human beings live long and prosper.


🧑‍🎓Education Background



📮News and Updates

[03/2025] I developed a simple tool to download and summarize CVPR2025 accepted papers with user-defined keywords using vibe coding. The link is here.
[02/2025] Our paper
UIBDiffusion: Universal Imperceptible Backdoor Attack for Diffusion Models is accepted by 2025 Conference on Computer Vision and Pattern Recognition (CVPR). We will release the final paper and code soon. Stay tuned!
[10/2024] I joined the National University of Singapore as a Research Fellow, working on synthetic tabular data and the security of generative models.
[05/2024] I'm Dr. Zhao now.
[02/2024] I passed my PhD defense.
[01/2024] I received the full-time offer as a Senior Systems Software Engineer (Gen AI) from NVIDIA but could not join due to an unexpected visa issue.
[07/2023] Our paper Fully Attentional Networks with Self-emerging Token Labeling is accepted by International Conference on Computer Vision (ICCV) 2023. The code and models can be found at NVlabs.
[03/2023] Our paper
Data-Driven Feature Selection Framework for Approximate Circuit Design is accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD).
[02/2023] Our paper
NNTesting: Neural Network Fault Attacks Detection Using Gradient-Based Test Vector Generation is accepted by 60th Design Automation Conference (DAC).
[05/2022] I will join NVIDIA as a Deep Learning Software and Research Intern.
[12/2021] Our paper
CLPA: Clean-Label Poisoning Availability Attacks Using Generative Adversarial Nets is accepted by Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22). [Code]
[10/2021] Our paper
Towards Class-oriented Poisoning Attacks against Neural Networks is accepted by Winter Conference on Applications of Computer Vision (WACV) 2022.