Machine Learning Deep

Nguyễn Hoàng Vĩ

+ Go Vap, Ho Chi Minh # *****************@*****.*** 038*-***-***

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Objective

Computer Science graduate with a strong background in deep learning, machine learning, and AI-driven appli- cations. Experienced in research, model development, and MLOps. Passionate about applying state-of-the-art AI techniques to solve real-world problems and eager to contribute to innovative projects in AI and machine learning.

Education

BS University of Information Technology - VNUHCM, Computer Science

• GPA: 8.0/10 (3.5/4.0)

• Coursework: Computer Vision, Natural Language Processing, Rein- forcement Learning

Oct 2021 – Mar 2025

Experience

Bosch Global Software Technology Viet Nam, AI Engineer Intern

• Researched and implemented deep learning models for automation test.

• Developed and deployed an automation test system using Robot Framework, FastAPI, and deep learning models.

• Maintained and optimized a full ML pipeline using MLFlow, ensuring efficient model tracking and deployment.

• Developed a proof of concept (PoC) for a new AI-driven project. Nov 2024 – May 2025

University of Information Technology, Undergraduate Researcher

• Conducted in-depth literature reviews on deep learning and implemented models based on state-of-the-art research.

• Presented weekly progress updates and insightful analysis to the supervisor, refining research direction and methodologies.

May 2023 – Jan 2025

Graduate Thesis

Visual Place Recognition

• Proposed a novel approach for Visual Place Recognition by fusing hierarchical vision transformer features.

• Designed and implemented an efficient feature fusion strategy to enhance place recognition performance.

Sep 2024 - Jan 2025

Projects

3D Human Mesh Reconstruction

• Conducted an in-depth literature review on 3D human mesh reconstruction, reproduced and implemented state-of-the-art models.

• Tools Used: OpenGL, PyTorch

Aug 2023 - May 2024

Multiagent Deep Reinforcement Learning for Anatomical Landmark Detection

• Implemented a novel communicative multi-agent reinforcement learning sys- Apr 2023 - June 2023

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tem to automatically detect landmarks in 3D medical images. My system enables the agents to learn explicit communication channels, as well as im- plicit communication signals by sharing certain weights of the architecture among all the agents.

• Tools Used: PyTorch

Composed Image Retrieval

• Implemented a deep learning model to extract visual features from images and textual features from text queries.

• Designed a multimodal retrieval system that leverages both visual and textual features to retrieve relevant images based on combined text-image queries.

• Tools Used: PyTorch, JavaScript

Aug 2023 - Dec 2023

Document Assistant

• Crawl digital data from various social media platforms, such as LinkedIn, Medium, GitHub.

• Fine-tune an LLM using LoRA and track experiments with CometML.

• Create inference pipeline with LangChain.

• Tools Used: LangChain, CometML, HuggingFace

Jun 2024 - Oct 2024

Skills

Languages: Python, Java, C++

Framework: Pytorch, Tensorflow, Scikit learn, LangChain, FastAPI Technologies: MLFlow, DVC, Robot Framework, Docker, Git, OpenGL Soft Skills: Problem Solving, Critical Thinking, Teamwork Other: SQL, Linux, LaTeX

Language

English: TOEIC Certificate with score 800 - IIG

Certification

Google Advanced Data Analytics

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