Researching state-of-the-art AI methods in NLP and Multimodal Large Language Models at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
As a Computer Science graduate from Ho Chi Minh City University of Technology – Vietnam National University (HCMUT-VNU), I completed my degree in an accelerated 3.5 years and will soon join the prestigious Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) as a PhD student in Natural Language Processing (NLP).
Throughout my undergraduate journey, I developed strong programming proficiency in Python, Java, and C++, alongside a solid foundation in Machine Learning, Deep Learning, and Multimodal Analysis. My academic coursework and independent research cultivated my passion for state-of-the-art AI methods, particularly in NLP and Multimodal Large Language Models (MLLMs).
PhD in NLP at MBZUAI (2025-Present)
BSc in Computer Science at HCMUT-VNU (2021-2024)
Python, C++, Java, Machine Learning, Deep Learning
NLP, Multimodal AI, Large Language Models
Vietnamese (Native), English (IELTS 7.5)
Advanced techniques for learning across multiple modalities including text, image, audio, and video data for comprehensive AI understanding.
Development and optimization of large language models that can process and understand multiple data types simultaneously.
Research in LLM architecture, fine-tuning, retrieval-augmented generation, and explainable AI systems.
Practical applications of AI in healthcare, education, and sustainable development with focus on Vietnamese language and culture.
The 4th Italian Conference on Big Data and Data Science, Turin, Italy
Co-organized the XAI Challenge 2025 at IJCNN, focusing on explainable educational QA with hybrid LLM–symbolic models. Contributed to dataset construction using logic-based templates with Z3 validation, challenge design, and post-hoc analysis of participant solutions.
11th Intelligent Systems Conference 2025, Amsterdam, The Netherlands
Presented a TTS and VC framework that utilizes low-resource adaptable style transfer, enhancing speaker adaptation and synthesis quality with minimal data for both text-to-speech and voice conversion tasks.
International Conference on Computational Intelligence in Engineering Science, Ho Chi Minh City, Vietnam
Developed a voice- and text-based smart irrigation management system powered by a large language model (LLM), achieving 90% intent translation accuracy and 82% dialectal understanding—outperforming commercial tools—to enhance usability and sustainability in Vietnamese agriculture.
EAAI-24: The 14th Symposium on Educational Advances in Artificial Intelligence, Vancouver, Canada
Contributed to the preservation and dissemination of the Bahnar language, an ancient and culturally significant language of the minority ethnic group in Vietnam. Proposed innovative solutions to overcome practical hurdles in translating Vietnamese to Bahnar language, leveraging recent advances in Neural Machine Translation (NMT) and transfer learning techniques.
9th International Conference on Inventive Communication and Computational Technologies, Perambalur, India
Developed an AI-driven customer feedback analysis framework integrating four modules - Data Ingestion, Storage, Analysis, and Decision Making - optimized for small businesses. Validated using real-world Vietnamese datasets, the Claude 3.5 Sonnet model achieved 87.35% sentiment classification accuracy and 82.21% accuracy in department-involved identification.
The 13th International Symposium on Information and Communication Technology, Da Nang, Vietnam
Introduced a novel approach using Joint-Embedding Predictive Architecture for text-image alignment, improving multimodal fusion. Conducted experiment on sentiment analysis task with text and image.
Text-Image Joint-Embedding Predictive Architecture for multimodal fusion. Achieved 9.9/10 in Capstone Project Defense.
AI-powered healthcare application with agentic AI capabilities, integrating Google APIs and Redis for intelligent health management.
Advanced AI system showcasing cutting-edge machine learning and artificial intelligence implementations.
Innovative data generation system for creating synthetic datasets to enhance machine learning model training.
Multimodal framework based on CLIP adapted for medical healthcare, particularly on Low Back Pain (LBP) diagnosis.
Special Vietnamese tokenizer that breaks words into 5 components for enhanced NLP processing.
Multimodal CLIP model for Vietnamese text and image processing, enhancing performance for Vietnamese-specific tasks.
Advanced chatbot leveraging large language models and retrieval-augmented generation for university academic admission.
Open-source learning materials for Machine Learning and Natural Language Processing
Comprehensive Natural Language Processing laboratory materials and exercises, revised and enhanced for HCMUT students.
Practical machine learning laboratory exercises and implementations designed for HCMUT Computer Science students.
Featured in news articles, videos, and academic databases
Thanh Niên Newspaper
Featured for graduating early with a near-perfect thesis score from Bach Khoa International Program.
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Featured for developing v7, an AI-powered Vietnamese input method that revolutionizes typing experience.
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Recognized for winning the prestigious AmCham Scholarship 2024.
Read ArticleOISP HCMUT International
Featured for the remarkable journey from barely qualifying to becoming a top talented student.
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Featured for choosing to study at Bach Khoa over study abroad opportunities in New Zealand.
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Featured in a video highlighting the achievements of Bach Khoa International Program students.
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Featured in social media posts highlighting academic achievements and early graduation.
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Recognized for academic achievements and contributions to the university community.
View PostHo Chi Minh City, Vietnam
Abu Dhabi, UAE (PhD studies)