Education

Indiana University Bloomington | Fall 2024
Ph.D. in Computer Science

• Advisor: Thai Le

Hanoi University of Science and Technology (HUST) | 2014-2020
Bachelor and Master in Computer Science

• Bachelor Thesis: Neural Poisson Matrix Factorization for Collaborative Filtering
• Thesis advisor: Khoat Than
• Best Presentation Award, Graduated with Very Good Degree

Publications

NoMatterXAI: Generating “No Matter What” Alterfactual Examples for Explaining Black-Box Text Classification Models
Tuc Nguyen, James Michels, Hua Shen, Thai Le
AAAI 2025

ADAPTERS MIXUP: Mixing Parameter-Efficient Adapters to Enhance the Adversarial Robustness of Fine-tuned Pre-trained Text Classifiers
Tuc Nguyen, Thai Le
EMNLP 2024 [Oral: 7.94%]

Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning
Tuc Nguyen, Thai Le
ACL 2024

Learning Weighted Product Spaces Representations for Graphs of Heterogeneous Structure
Tuc Nguyen, Dung D.Le, Anh Ta
ICLR on Geometrical and Topological Representation Learning (2022)

Pruning deep equilibrium models
Hoang Pham*, Tuc Nguyen*, Anh Ta, Dung D.Le, Long Tran-Thanh
ICML on Sparsity in Neural Network (2022)

Modeling the sequential behaviors of online users in Recommender System
Tuc Nguyen, Linh Ngo, Khoat Than
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications (2019)

Research experience

FPT AI Resident | 2021 - 2023
FPT AI Center, Vietnam - website: https://fpt-aicenter.com/

Research Student | 2018 - 2021
Data Science Lab (DSLab), HUST - website: ds.soict.hust.edu.vn/

• Supervisor: Khoat Than

Selected Honors and Awards

Jetstream2 AI Fellow | 2024
UITS Research Technologies, Pervasive Technology Institute (PTI)

FNC Founders Graduate Fellowship | 2023
Department of Computer and Information Science, University of Mississippi

Scholarship for Master Student | 2021
School of Information and Communication Technology, HUST

Best Presentation Award | 2019
School of Information and Communication Technology, HUST

Academic Services

Reviewer
PAKDD (2023), AAAI (2023), KSE (2022)

Teaching Assistant | 2019
Data Science Laboratory (DSLab) – HUST

• Run a seminar on fundamental machine learning models such as linear regressions, k-nearest neighbors, support vector machines and neural networks for new students
• Help new students get hands-on experience with Tensorflow – a deep learning framework

Travel

NAACL 2024: Mexico City, Mexico

EMNLP 2024: Miami, Florida, USA

Technical Skills

• Programming Languages: Python, C/C++, Java, JavaScript
• Libraries: Pytorch, Tensorflow, Numpy, Matplotlib
• Developer Tools: Git