R D Embedded Software

LY DUONG PHI

Embedded Software Engineer

Date of birth: March 5, 2001

Gender: Male

Phone: +84-384-***-***

OBJECTIVE

As a recent graduate with a degree in Automotive Engineering Technology and a basic foundation in embedded programming, I am eager to begin my career in the automotive software industry. I am passionate about leveraging my academic knowledge and project experience to contribute to the development of innovative and reliable embedded software solutions for automotive applications. Committed to continuous learning and professional growth, I am excited about collaborating with interdisciplinary teams to drive advances across multiple fields in embedded and automotive

EDUCATION

Sep 2019 – Dec 2024 VNUHCM-UNIVERSITY OF TECHNOLOGY Major: Bachelor of Engineering: Automotive Engineering Technology GPA: 7.55

English High Quality Program of OISP

Encouraging Study Scholarship of OISP 2020 – 2021

Rewarding outstanding students 201*-****-****

Email: **********@*****.***

Address: Ho Chi Minh, Viet Nam

WORK EXPERIENCE

Experience in Image Signal Processing Project

• Reading, writing, and displaying images.

• Changing color spaces from BGR to RGB.

• Image rotation and edge detection, which are essential for data augmentation and feature extraction .

Embedded Software Engineering Experience

My capstone project involves deploying YOLO (You Only Look Once) models on the Jetson Nano, a small AI computer designed for embedded systems. The experience covers:

• Basic Theories: Understanding OpenCV, PyTorch, TensorRT, and YOLO models.

• Deployment: Detailed guidelines on deploying YOLOv5 and YOLOv7 on Jetson Nano, including handling dependencies and versions of software like JetPack, Python, and CUDA.

• Performance Comparison: Evaluating the performance of YOLOv5(s) and YOLOv7(tiny) in terms of frames per second (FPS) for real-time detection. Scientific Papers : Evaluate the performance of using YOLOv5 and YOLOv7 in car speed monitoring applications

Responsibilities:

• Understanding OpenCV, PyTorch, TensorRT, and YOLO models

• Detailed guidelines for installation on deploying YOLOv5 and YOLOv7 on Jetson Nano.

• Optimizing neural network models trained on all major frameworks, calibrates them for lower precision with high accuracy, and deploys them to edge devices by TensorRT.

• Writing test reports and fixing related AIs.

• Evaluate the performance of YOLOv5 and YOLOv7 on hardware based on some criterias : FPS, inference time, confidences scores, etc. Hardware : Jetson Nano board

Software: YOLOv5 and YOLOv7

SKILL AND KNOWLEDGE SUMMARY

Programming Language: Strong knowledge in C and C++, basic knowledge in Python Image Library: Basic knowledge of OpenCV

Embedded Platform: Automotive electrics - electronics system, Computer Architecture, Microcontroller such as STM32F4

Version Control Tool:

Mathematical Foundation:

English:

Soft Skill:

Git

Linear algebra, CNNs and algorithms.

English (IELTS Certi cate with Overall Band Score 6.0 in 2022) Document writing, Time management, Teamwork, Problem solving, Presentation

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