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<h2 class="section-title">Experience</h2>
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<div class="timeline-item">
<div class="timeline-date">August 2025 - January 2026</div>
<h3>
MedMAS: Multi-agent System for Pre-intake Clinical Note
Generation in Conversation
</h3>
<p style="color: var(--accent); font-weight: 600">
BioInfomatic Laboratory, Feng Chia University, Taiwan
</p>
<p class="timeline-content">
Building a multi-agent system that extracts patient information
through conversations, generates targeted follow-up questions to
gather comprehensive patient data, and creates detailed
pre-visit clinical reports. This streamlines the examination
process, saving physician time and improving patient experience
during medical consultations. The system is evaluated across
three core tasks: Named Entity Recognition (NER), Question
Generation (QG), and Summarization, achieving state-of-the-art
results on both MTS-Dialog and CliniKnote benchmark datasets,
demonstrating the superiority of multi-agent architectures over
conventional approaches such as in-context learning and
instruction-tuning in the medical domain.
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<p
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<strong>Advisor:</strong> Prof. Fang-Rong Hsu
</p>
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<div class="timeline-item">
<div class="timeline-date">September 2024 - January 2026</div>
<h3>ViLegalLM: Language Models for Vietnamese Legal Text</h3>
<p style="color: var(--accent); font-weight: 600">
NLU Laboratory, Hung Yen University of Technology and Education
</p>
<p class="timeline-content">
ViLegalLM comprises one representation model (135M) and two
generation models (1.54B, 1.72B) specifically for Vietnamese
legal text through continual pretraining on newly 16GB of
high-quality legal documents. ViLegalLM achieves
state-of-the-art performance across 10 benchmarks spanning four
main tasks: Information Retrieval (IR), Question Answering (QA),
Natural Language Inference (NLI), and Syllogism Reasoning,
outperforming 7 state-of-the-art Vietnamese models and
establishing new strong baselines for Vietnamese legal text
processing. The project also contributes three large-scale
synthetic training datasets to address the shortage of
high-quality legal training data in Vietnam.
</p>
<p
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>
<strong>Advisor:</strong> Assoc. Prof. Minh-Tien Nguyen
</p>
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<div class="timeline-item">
<div class="timeline-date">August 2025 - September 2025</div>
<h3>Adaptive Weighted Ensemble for Legal Text Processing</h3>
<p style="color: var(--accent); font-weight: 600">
NLU Laboratory, Hung Yen University of Technology and Education,
Vietnam
</p>
<p class="timeline-content">
Designed a framework combining multiple bi-encoders through
query-specific confidence calculation, advanced dynamic
weighting, and ensemble score fusion with cross-encoder
reranker. Achieved 3rd place in Legal Information Retrieval task
(F2-score: 0.8482, 7.51% improvement) and 2nd place in Legal
Question Answering (97.56% accuracy) in ALQAC 2025 Competition.
Paper accepted at 17th International Conference on Knowledge and
System Engineering (KSE 2025).
</p>
<p
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>
<strong>Advisor:</strong> Assoc. Prof. Minh-Tien Nguyen
</p>
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<div class="timeline-item">
<div class="timeline-date">February 2024 - September 2025</div>
<h3>
IntelliChat - Question Answering System for Vietnam Legal
Documents
</h3>
<p style="color: var(--accent); font-weight: 600">
NLU Laboratory, Hung Yen University of Technology and Education,
Vietnam
</p>
<p class="timeline-content">
Built a demo legal question-answering system for Vietnamese,
integrating information retrieval with answer
extraction/generation optimized for the legal domain.
IntelliChat outperforms GPT-3.5 and state-of-the-art open-source
LLMs (~7B parameters) in both automatic and human evaluations,
and is deployed online to enable Vietnamese citizens to
independently access and understand legal documents.
</p>
<p
style="
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>
<strong>Advisor:</strong> Assoc. Prof. Minh-Tien Nguyen
</p>
</div>
<div class="timeline-item">
<div class="timeline-date">February 2024 - June 2025</div>
<h3>QACTune - Advanced Legal Information Retrieval Framework</h3>
<p style="color: var(--accent); font-weight: 600">
NLU Laboratory, Hung Yen University of Technology and Education,
Vietnam
</p>
<p class="timeline-content">
Developed a novel fine-tuning framework leveraging
Question-Context-Answer relationships for enhancing legal
information retrieval in low-resource settings. Average
improvements of 3.9% and 4.8% in MAP@100. Published in
Engineering Applications of Artificial Intelligence (WoS-SCIE,
Q1, IF: 8.0).
</p>
<p
style="
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>
<strong>Advisor:</strong> Assoc. Prof. Minh-Tien Nguyen
</p>
</div>
<div class="timeline-item">
<div class="timeline-date">July 2023 - January 2024</div>
<h3>
ViEduQAG - Vietnamese Question and Answer Generation in
Education
</h3>
<p style="color: var(--accent); font-weight: 600">
NLU Laboratory, Hung Yen University of Technology and Education,
Vietnam
</p>
<p class="timeline-content">
Pioneered Vietnamese Question-Answer Generation research in
education domain by creating ViEduQA - the first comprehensive
Vietnamese educational QAG dataset with 12,618 QA pairs across
319 lessons from 4 high school subjects. Published in SOICT 2024
(Springer CCIS).
</p>
<p
style="
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>
<strong>Advisor:</strong> Assoc. Prof. Minh-Tien Nguyen
</p>
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<div class="timeline-date">February 2025 – July 2025</div>
<h3>
NLP Fresher @ Artificial Intelligence Institute JSC, Hung Yen,
Vietnam
</h3>
<p style="color: var(--accent); font-weight: 600">
SmartChat - Smart AI Assistant for Vietnamese
</p>
<p class="timeline-content">
Led comprehensive evaluation of large language models for
production chatbot system, focusing on optimizing performance
across multiple NLP tasks including document reranking, question
rewriting, and content generation. Conducted systematic
benchmarking of state-of-the-art models including GPT-4o-mini,
Amazon Nova Lite, Amazon Nova Micro, and Amazon Nova Pro.
</p>
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style="color: var(--accent); font-weight: 600; margin-top: 1rem"
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AI Assistant for Vietnam Ministry of Agriculture
</p>
<p class="timeline-content">
Developed a comprehensive domain-specific chatbot system
enabling intelligent question-answering capabilities over legal
document collections and regulatory text corpora. Built
innovative text-to-analytics functionality and designed a novel
document chunking mechanism combining Depth-First Search (DFS)
algorithms with advanced Regular Expression patterns.
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<div class="timeline-item">
<div class="timeline-date">October 2024 – January 2025</div>
<h3>AI Intern @ Viettel Telecom Corporation, Hanoi, Vietnam</h3>
<p style="color: var(--accent); font-weight: 600">
Per-Title Encoding
</p>
<p class="timeline-content">
Developed and optimized per-title encoding algorithms for video
compression on the TV360 streaming platform. Implemented
advanced analysis techniques to assess video complexity and
dynamically adjust encoding parameters, achieving optimal
balance between visual quality and file size.
</p>
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style="color: var(--accent); font-weight: 600; margin-top: 1rem"
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Video Frame Interpolation
</p>
<p class="timeline-content">
Designed and implemented advanced video frame interpolation
systems to enhance motion smoothness for TV360 platform content
delivery. Developed sophisticated interpolation algorithms using
deep learning techniques to generate high-quality intermediate
frames.
</p>
<p
style="color: var(--accent); font-weight: 600; margin-top: 1rem"
>
Video Quality Assessment for User Generated Content
</p>
<p class="timeline-content">
Built comprehensive video quality assessment frameworks for
evaluating and enhancing user-generated content on the TV360
platform using computer vision and machine learning techniques.
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<h3>Natural Language Processing - Teaching Assistant</h3>
<p style="color: var(--accent); font-weight: 600">
CS19TN, Hung Yen University of Technology and Education
</p>
<p class="timeline-content">
Assisted in teaching Natural Language Processing course, guiding
students through fundamental and advanced NLP concepts, helping
with assignments and projects.
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<div class="timeline-item">
<div class="timeline-date">April 2024 – July 2025</div>
<h3>Natural Language Processing - Key Mentor</h3>
<p style="color: var(--accent); font-weight: 600">
UTEHY-NLU Lab
</p>
<p class="timeline-content">
Mentored students in NLP research projects, guiding them through
literature review, experimental design, and paper writing.
</p>
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<div class="timeline-item">
<div class="timeline-date">December 2023 – July 2025</div>
<h3>Deep Learning - Key Mentor</h3>
<p style="color: var(--accent); font-weight: 600">
UTEHY-NLU Lab
</p>
<p class="timeline-content">
Guided students in deep learning fundamentals and applications,
covering neural networks, CNNs, RNNs, and Transformers.
</p>
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<div class="timeline-item">
<div class="timeline-date">June 2023 – July 2025</div>
<h3>Machine Learning - Key Mentor</h3>
<p style="color: var(--accent); font-weight: 600">
UTEHY-NLU Lab
</p>
<p class="timeline-content">
Mentored students in machine learning concepts and practical
applications, covering supervised and unsupervised learning
algorithms.
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