Cuong Dang
PhD Student at Virginia Tech
Electrical and Computer Engineering
Whittemore Hall
cuongdc@vt.edu
About
I am actively looking for an Internship position for Spring 2027.
Cuong Dang is a second-year Ph.D. student in the Department of Electrical and Computer Engineering at Virginia Tech, advised by Prof. Ruoxi Jia. His current research focuses on post-training for coding agents. He also has research experience in post-training, safety, uncertainty quantification, retrieval-augmented generation, interpretability, graph neural networks, and diffusion.
Click on keywords below to see papers organized by topics:
News
- [Feb 2026] Our paper "URAG: A Benchmark for Uncertainty Quantification in Retrieval-Augmented Large Language Models" has been released.
- [May 2026] Congratulations on our paper "The Confidence Trap: Calibration Attacks for Graph Neural Networks" accepted to KDD 2026.
- [Sep 2025] Yayyy, I'll start my PhD journey at Virginia Tech!
- [Apr 2025] Congratulations!!! I have received a PhD offer from Max Planck Institute and will visit MPI for Open House.
- [Feb 2025] Congratulations!!! I have received a PhD offer from NUS SoC and will visit NUS for Open House.
- [Aug 2024] I'll be at ACL 2024. Looking forward to seeing you all.
- [May 2024] Congratulations on our paper "A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models" accepted to ACL Findings 2024.
Education
Virginia TechSep. 2025 - June 2030 (Expected)
Ph.D. in Electrical and Computer Engineering
HCMUTSep. 2019 - June 2023
B.Eng. in Computer Science
Publications
Most recent publications on Google Scholar.
* indicates equal contribution.
URAG: A Benchmark for Uncertainty Quantification in Retrieval-Augmented Large Language Models
Vinh Nguyen*, *, Jiahao Zhang, Hoa Tran, Minh Tran, Trinh Chau, Thai Le, Lu Cheng, Suhang Wang
Arxiv
The Confidence Trap: Calibration Attacks for Graph Neural Networks
, Jiahao Zhang, Hieu Ta Quang, Dung Le, Lu Cheng, Suhang Wang
KDD 2026
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
,Dung D. Le,Thai Le
ACL Findings 2024
Score-based Diffusion Model for Conformer Generation
International Conference on Information Technology (ICIT), 2023
URAG: A Benchmark for Uncertainty Quantification in Retrieval-Augmented Large Language Models
Vinh Nguyen*, *, Jiahao Zhang, Hoa Tran, Minh Tran, Trinh Chau, Thai Le, Lu Cheng, Suhang Wang
Arxiv
The Confidence Trap: Calibration Attacks for Graph Neural Networks
, Jiahao Zhang, Hieu Ta Quang, Dung Le, Lu Cheng, Suhang Wang
KDD 2026
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
,Dung D. Le,Thai Le
ACL Findings 2024
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
,Dung D. Le,Thai Le
ACL Findings 2024
URAG: A Benchmark for Uncertainty Quantification in Retrieval-Augmented Large Language Models
Vinh Nguyen*, *, Jiahao Zhang, Hoa Tran, Minh Tran, Trinh Chau, Thai Le, Lu Cheng, Suhang Wang
Arxiv
The Confidence Trap: Calibration Attacks for Graph Neural Networks
, Jiahao Zhang, Hieu Ta Quang, Dung Le, Lu Cheng, Suhang Wang
KDD 2026
Vitæ
Full CV in PDF.
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Virginia Tech Sep 2025 - PresentPhD Student
Data-Driven Optimization for Machine Learning Systems -
FPT Software AI Center July 2023 - Aug 2025AI Research Resident
Constructing Diffusion Language Model for Code Generation -
HCMUT Sep. 2019 - June 2023Undergraduate Student
Undergraduate Student in Computer Science -
URA Research Group Mar. 2021 - July 2022AI Engineer
Constructing Chatbot for a Real Estate Company