Simin Chen

Ph.D. Candidate of Computer Science

The University of Texas at Dallas

Biography

I am a fourth-year Ph.D. candidate at the University of Texas at Dallas (UTD). I am fortunate to be advised by Prof.Wei Yang and Prof.Cong Liu. Before joining UTD, I received my master degree from Tongji University in May 2018. My research interest lies in machine learning, computer security, and program analysis.

I am actively looking for cooperation in the following topics: (1) deploying ML models safely and efficiently on edge/server platforms, (2) developing automatic tools to find the bugs in existing ML infrastructures, and (3) understanding the decision making of ML models and improving them.

Feel free to drop me an email if we share common research interests.

Download my resumé.

Interests

Machine Learning
Computer Security
Software Engineering

Education

Ph.D. Candidate, 2019 - Now

The University of Texas at Dallas
Master, 2015 - 2018

Tongji University
Bachelor, 2011 - 2015

Tongji University

News

April 2024 -- One paper is accepted to ESEC/FSE 2024 after major revision.

Jan 2024 -- One first authored paper is directly accepted to ESEC/FSE 2024.

Jan 2024 -- Serve as a PC member for the 24rd international conference on algorithms and architectures for parallel processing (ICA3PP 2024)

Jan 2024 -- Serve as the reviewer of the 17th Asian Conference on Computer Vision (ACCV 2024)

Jan 2024 -- Serve as the reviewer of the European Conference on Computer Vision 2024 (ECCV 2024)

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Publications

Simin Chen, Zexin Li, Wei Yang, Cong Liu (2024). DeciX: Explain Deep Learning Based Code Generation Applications. In ESEC/FSE 2024.

Simin Chen, Xiaoning Feng, Xiaohong Han, Cong Liu, Wei Yang (2024). PPM: Automated Generation of Diverse Programming Problems for Benchmarking Code Generation Models. In ESEC/FSE 2024.

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Yiming Chen, Simin Chen, Zexin Li, Wei Yang, Cong Liu, Robby Tan, Haizhou Li (2023). Dynamic Transformer Provide a False Sense of Efficiency. In ACL 2023.

Simin Chen, Hanlin Chen, Mirazul Haque, Cong Liu, Wei Yang (2023). The Dark Side of Dynamic Routing Neural Networks: Towards Efficiency Backdoor Injection. In CVPR 2023.

Zexin Li, Bangjie Yin, Taiping Yao, Junfeng Guo, Shouhong Ding, Simin Chen, Cong Liu (2023). Sibling-Attack: Rethinking Transferable Adversarial Attacks against Face Recognition. In CVPR 2023.

Simin Chen, Shiyi Wei, Cong Liu, Wei Yang (2023). DyCL: Dynamic Neural Network Compilation Via Program Rewriting and Graph Optimization. In ISSTA 2023.

Simin Chen, Mirazul Haque, Cong Liu, Wei Yang (2022). DeepPerform: An Efficient Approach for Performance Testing of Resource-Constrained Neural Networks. In ASE 2022.

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Simin Chen, Cong Liu, Mirazul Haque, Zihe Song, Wei Yang (2022). NMTSloth: Understanding and Testing Efficiency Degradation of Neural Machine Translation Systems. In ESEC/FSE 2022.

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Simin Chen, Hamed Khanpour, Cong Liu, Wei Yang (2022). Learning to Reverse DNNs from AI Programs Automatically. In IJCAI 2022.

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Simin Chen, Zihe Song, Mirazul Haque, Cong Liu, Wei Yang (2022). NICGSlowDown: Evaluating the Efficiency Robustness of Neural Caption Generation Models. In CVPR 2022.

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Simin Chen, Soroush Bateni, Sampath Grandhi, Xiaodi Li, Cong Liu, Wei Yang (2020). DENAS: automated rule generation by knowledge extraction from neural networks. In ESEC/FSE 2020.

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