AI/Machine Learning, Deep learning Electrical Engineering

Vũ Mạnh Hùng

ELECTRICAL ENGINEERING

SKILLS

TECHNICAL SKILLS

programing language Python, C++,

Matlab

Worked with libraries &

frameworks: TensorFlow, Scikit-

learn, Keras, Pandas, NumPy,

Matplotlib, PyTorch

experience with Google Colab,

Visual Studio, Jupyter Notebook,

Conda, Git

Hands-on experience with small-

scale models from Kaggle and

Hugging Face

SOFT SKILLS

teamwork and collaboration skills,

solid research and analytical

ability, time management

LANGUAGE

TOEIC - 670

PROFILE

093*******

*********@*****.***

https://sites.google.com/vie

w/vumanhhung

Hiệp Phú, tp.Thủ Đức, Vietnam

EDUCATION

ELECTRICAL ENGINEERING 9/2021 - 2025

VNU-HCM International University

GPA: 77.4

Currently in Senior year.

CAREER GOALS

• Seeking an internship in Artificial Intelligence with a focus on Computer Vision, Large Language Models (LLMs), and deep learning architectures such as CNNs and LSTMs.

• Eager to apply academic knowledge in model training, while open to expanding into Data Science, applying methods like Random Forest and exploring Signal Processing and Information Processing within the scope of Machine Learning.

• Aiming to develop practical experience, enhance analytical and teamwork skills, and grow professionally in a dynamic AI-driven environment. ACTIVITIES

VISUAL QUESTION ANSWERING (VQA) 2023 - 2024

Project subject

Developed a deep learning model combining CNN (ResNet) for image feature extraction and LSTM for question understanding, using the VQA COCO dataset. Focused on binary (Yes/No) answers. Built and trained the model with PyTorch, applied PIL for image preprocessing, and used spaCy and NLTK for text tokenization and linguistic processing. This project demonstrates integration of Computer Vision and NLP components in a real-world AI task. DOG BREED IDENTIFICATION 2022 - 2023

Project subject

Built an image classification model to identify 120 dog breeds from images. Used TensorFlow and Keras with pretrained CNN models (loaded via Kaggle) for transfer learning. Applied Matplotlib for dataset visualization and augmentation, and implemented structured dataset partitioning. Gained hands-on experience in image preprocessing, model tuning, and deployment-ready data handling. CERTIFICATIONS

2025 Complete A.I. & Machine Learning, Data Science Bootcamp ZTM course 2024 TOEIC Reading and Writting - 670

2019 Microsoft Office Specialist (MOS) - Word and Powerpoint

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