Dang Nguyen
PhD Candidate
College Park, Maryland, United States
Summary
👤
Senior🎓
Top SchoolDang Nguyen is a PhD candidate in Computer Science at the University of Maryland with eight years of experience building and researching robust NLP systems. His current research focuses on making NLP models resilient to adversarial attacks, and he has practical ML engineering experience improving the popular TextAttack framework’s logging, evaluation, and error handling. He has held research-focused industry roles at VinAI, Adobe, and an Applied Scientist internship at Amazon, blending academic rigor with production-minded improvements. Dang’s background in computer engineering (9.22/10) and strong attention to detail show through contributions that span bug fixes, configurability enhancements, and tooling integrations like Weights & Biases. Based in College Park, MD, he brings a hands-on approach to defensive NLP research and open-source maintenance.
8 years of coding experience
1 year of employment as a software developer
Undergraduate, Computer Engineering, 9.22/10, Undergraduate, Computer Engineering, 9.22/10 at Ho Chi Minh University of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Maryland
vietnamese sign language, Vietnamese, English
Github Skills (8)
nlp10
adversarial-attacks10
python10
weight9
machine-learning9
debug9
weighting9
git7
Programming languages (13)
Github contributions (5)
QData/TextAttack
Sep 2021 - Jul 2022
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
Role in this project:
ML Engineer
ML EngineerContributions:6 commits, 5 PRs, 5 comments in 10 months
Contributions summary:Dang primarily focused on improving the TextAttack framework, specifically related to its logging and evaluation functionalities. Contributions include enhancing the configurability of the WandB logger, fixing bugs related to CLI evaluations with specific parameter settings, and improving exception handling. They also addressed minor issues like typos, demonstrating attention to detail and maintenance of the codebase.
pythonadversarial-machine-learningadversarialmodel-trainingtraining
dangne/tkllHDR
Feb 2019 - Oct 2019
DNN handwritten digit recognition system on Zedboard Zynq-7000 ARM/FPGA SoC
Contributions:24 PRs, 69 pushes, 29 branches in 8 months
fpga-socdigithandwritten-digit-recognitionrecognitionhandwritten
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