CV

Curriculum Vitae of Truong-Binh Duong - Computer Science graduate and AI researcher focusing on multi-modal systems.

Basics

Name Truong-Binh Duong
Label AI Researcher
Email duongtruongbinh2003@gmail.com
Phone +(84) 936212865
Url https://duongtruongbinh.github.io
Summary Recent Computer Science graduate from VNU-HCM, University of Science specializing in multi-modal AI and Vision-Language Models. Focused on rigorous experimentation, benchmarking, and deploying deep learning systems with PyTorch and Transformers.

Work

  • 2024.09 - Present
    Teaching Assistant
    AI VIETNAM
    Developing curriculum and teaching materials for the AIO program, covering fundamental Machine Learning, Deep Learning, and advanced topics such as AI Agents and LLM Reasoning.
    • Created comprehensive educational content for AI/ML courses
    • Designed exam questions for Linear Algebra, Probability, Statistics, ML, and DL
    • Teaching materials available at: https://drive.google.com/drive/folders/1JTLMNDsnOKD4Yo1e2x3CZVMUXkbP8KD2

Education

  • 2021.09 - 2025.08

    Ho Chi Minh City, Vietnam

    B.Sc. in Computer Science
    VNU-HCM, University of Science
    Computer Science (High-Quality Program)
    • Multi-modal AI
    • Deep Learning
    • Machine Learning
    • Data Science Programming

Awards

Publications

Skills

Programming
Python
C/C++
SQL
Data Science
Pandas
NumPy
Matplotlib
Seaborn
Scikit-learn
XGBoost
Deep Learning
PyTorch
Hugging Face
Transformers
CNN
RNN/LSTM
Vision-Language Models
MLOps & Tools
Docker
MLflow
Weights & Biases
FastAPI
Streamlit
Google Cloud (Vertex AI)

Languages

Vietnamese
Native speaker
English
Professional Working Proficiency (VSTEP B2)

Interests

Artificial Intelligence
Machine Learning Research
Computer Vision
Natural Language Processing
Technology
Open Source
DevOps
Sports & Entertainment
Football
Gaming
Anime
Traveling

Projects

  • 2025.01 - 2025.08
    Counterfactual Reasoning for Robust Visual Question Answering
    Graduation thesis proposing counterfactual training strategies, batch-contrastive losses, and curriculum learning to mitigate language bias in VQA.
    • Three-stage curriculum for stable optimization
    • Batch-contrastive loss with counterfactual samples
    • State-of-the-art performance on VQA-CP v2 (annotation-free methods)
  • 2024.07 - 2024.07
    Heineken Image Analysis Tool
    Backend and model engineering for a multi-model AI pipeline that automates brand compliance and safety analysis from images.
    • FastAPI inference service
    • Integrated YOLOv10, Owlv2, PaddleOCR, and CLIP
    • Delivered actionable reports for on-site audits
  • 2023.04 - 2023.05
    AI-Powered Math Solving Assistant
    Multi-modal chatbot that solves math problems through Gemini API fine-tuned on MetaMathQA-40K with OCR support for handwritten inputs.
    • Vertex AI fine-tuning workflow
    • OCR integration for image inputs
    • Web interface for interactive tutoring
  • 2022.01 - 2022.12
    Manga Popularity Prediction
    End-to-end data science pipeline for predicting manga scores using scraped metadata, exploratory analysis, and ensemble regression.
    • Automated web scraping and preprocessing
    • Compared Linear Regression, Random Forest, and XGBoost
    • Bayesian Optimization for hyperparameters