專家介紹
我是燁龍，一位生於1997年的27歲年輕專業人士，身處於這個快速發展的大數據時代。對於持續學習和探索新知識充滿熱情，我期待能在軟體工程師領域中充分發揮自己的潛能。
我曾就讀國立中山大學資訊工程所，這段學術旅程讓我獲得了豐富的理論知識和實踐經驗。我不僅參與了與我的職業目標相關的多門課程，還在實際的項目中取得了令人矚目的成就。我對科學方法和資料分析的興趣使我不斷地探索和學習，並在這方面取得了深入的專業知識。
作為一名經驗豐富的軟體工程師，我擅長系統架構設計和軟體開發，尤其在前後端串接和數據可視化方面具有深厚的專業知識。我在機器學習和製程參數分析領域也有豐富的經驗，能夠進行複雜的數據分析和根因分析。
我的技術技能涵蓋了多種程式語言，包括C/C++、Python和TypeScript，以及多種主流的前端和後端框架，如Django、Angular、React和Vue。近期，我主要參與了針對串製程查詢系統的開發，涉及系統架構設計和前後端的串接。
我期待能夠在未來的職業生涯中持續學習和成長，並將我的知識和技能應用於解決實際的問題，為企業創造價值。
我的專業技能範疇包括：
1.程式語言：
精通 Python 和 TypeScript。
熟練使用其他語言如 JavaScript、Java、C++ 和 C#。
2.資料庫技能：
熟悉資料庫管理，包括設計、優化和查詢資料庫，有經驗使用主流資料庫系統如 MySQL、PostgreSQL 或 Sqlite 也使用過 Oracle , RDB。
3.框架：
熟悉主流框架，包括 Django、Angular、React 和 Vue。
4.前後端分離：
具有開發前後端分離系統的經驗，並能夠設計並實現穩定的 API 接口。
5.可視化工具：
熟悉使用 Grafana 將數據可視化，呈現在網頁前端。
6.容器化部署：
熟悉使用 K8S 工具進行應用程式的容器化部署。
7.作業系統：
熟練使用 Linux 系統，包括 Ubuntu 和 CentOS，以及撰寫shell script達到自動化流程的能力。
8.版控工具：
熟悉使用 Git 進行版本控制，有能力管理和協作於專案的代碼庫。
9.機器學習領域：
具有機器學習方面的專業知識和經驗，包括神經網路、LGBM、KNN、決策樹等機器學習算法的應用。
10.平行運算設計:
在我最近的一個工作中，我有機會參與了一個與平行運算密切相關的專案。我負責設計並實現了一個基於基因演算法的超參數優化系統。這個系統旨在提升機器學習模型的預測能力。在這個過程中，我面臨了計算密集型任務，需要處理大量的計算，並優化運算速度。
我採用了Python的multiprocessing模塊，將計算平行化。這使我們能夠同時處理多個超參數組合，從而節省了大量的計算時間。這個專案的成功實施使我更深入地了解了平行運算的設計和實現。
工作經驗：
實習軟體工程師，2020年09月~2021年08月
工程師，震旦行股份有限公司 2022年02月~07月。
軟體工程師，燁聯鋼鐵公司，2022年07月至今。
曾任專案:
1.串製程查詢系統
2.危險區域警示系統
3. ESG碳盤查系統
4.日工作回報系統
5.公司系統入口網頁
6.碳足跡系統
7.基於機器學習模型與資料探勘的產品製程參數分析，解析缺陷根本原因
8.基於基因演算法優化機器學習模型之超參數，提升預測能力的有效策略
9.公司內部修繕表單系統
期待有機會能夠與您進一步交流，謝謝您的時間。
陳燁龍 敬上
外文自傳
My name is Chen Yelong, a 26-year-old professional born in 1997, currently navigating the rapidly evolving era of big data. I am deeply passionate about continuous learning and exploring new knowledge, aspiring to fully unleash my potential in the field of software engineering.
I pursued my graduate studies at the National Sun Yat-sen University, where I acquired a wealth of theoretical knowledge and practical experience. I not only engaged in numerous courses aligned with my career goals but also achieved remarkable results in various projects. My keen interest in scientific methods and data analysis has driven me to explore and learn continuously, leading to a profound understanding in this area.
As an experienced software engineer, I excel in system architecture design and software development, particularly in frontend-backend integration and data visualization. I also have extensive experience in the fields of machine learning and process parameter analysis, capable of conducting complex data analysis and root cause analysis.
My technical skills encompass a variety of programming languages, including C/C++, Python, and TypeScript, as well as mainstream frontend and backend frameworks such as Django, Angular, React, and Vue. Recently, I have been actively involved in the development of a query system for serial processes, which involves system architecture design and frontend-backend integration.
I look forward to continuing my learning and growth in my future career, applying my knowledge and skills to solve real-world problems and create value for businesses.
My areas of expertise include:
1. Programming language:
Proficient in Python and TypeScript.
Proficiency in other languages such as JavaScript, Java, C++ and C#.
2. Framework:
Familiarity with mainstream frameworks, including Django, Angular, React, and Vue.
3. Separation of front and rear ends:
Have experience in developing front-end and back-end separation systems, and be able to design and implement a stable API interface.
4. Visualization tools:
Familiar with using Grafana to visualize data and present it on the front end of the web page.
5. Containerized deployment:
Familiar with containerized deployment of applications using K8S tools.
6. Operating system:
Proficiency in using Linux systems, including Ubuntu and CentOS, and the ability to write shell scripts to automate processes.
7. Version control tools:
Familiarity with version control using Git, ability to manage and collaborate on project codebases.
8. Machine learning field:
Professional knowledge and experience in machine learning, including the application of machine learning algorithms such as neural networks, LGBM, KNN, and decision trees.
9. Database skills:
Familiar with database management, including designing, optimizing and querying databases, have experience using mainstream database systems such as MySQL, PostgreSQL or Sqlite, and have also used Oracle, RDB.
work experience:
Intern software engineer, September 2020~August 2021
Engineer, Zhendanhang Co., Ltd. February to July 2022.
Software engineer, Yulian Steel Company, from July 2022 to present.
Previous projects:
1. Hazardous area warning system:
In this project, I acted as the main software engineer and was responsible for developing a hazardous area warning system. The system combines infrared technology, video camera and RFID technology to perform portrait recognition and evaluate the count of people in the area, while recording the relevant information of people.
In terms of back-end development, I used Python language and Django framework to build a stable and reliable back-end system. I used the advantages of Python to develop a portrait recognition algorithm, and realized the real-time person recognition function through the camera and infrared technology. At the same time, I also use RFID technology to identify and record the information of personnel.
In terms of front-end rendering, I use the Django framework to handle web page rendering and data display. I designed an intuitive and easy-to-use user interface to display a count of people and related profiles in an area. Through Django's template language and HTML/CSS technology, I realized the dynamic update and interactive effects of data, providing a friendly user experience.
2. ESG carbon inventory system:
In this project, I served as the main software engineer responsible for developing an ESG carbon inventory system. The system is designed to monitor and manage the carbon emission data of enterprises and provide a visual presentation of relevant information.
In terms of back-end development, I used Python language and Django framework, and chose POSTGRESQL as the database. I designed and implemented a monitoring function for emission hotspots, using the advantages of Python to process large amounts of data. I developed a corresponding API interface to collect and store carbon emission data of enterprises. As a powerful and reliable relational database, POSTGRESQL can effectively store and manage data.
In terms of front-end development, I built a modern user interface using the Angular framework. Using HTML, CSS and TypeScript techniques, I designed an intuitive and easy-to-use interface. I work closely with the designers and UI team to make sure the interface is aesthetically pleasing and the user experience is good. At the same time, I used the powerful functions of Angular to realize the connection with the back-end API to obtain and display carbon emission data. In addition, I use the Grafana tool to visualize the data, providing users with an intuitive and easy-to-understand data presentation.
3. Daily work return system
4. Company system portal page
5. Carbon footprint system
6. Analysis of product process parameters based on machine learning models and data mining to analyze root causes of defects
7. An effective strategy to optimize the hyperparameters of LGBM and Neuron Network models based on genetic algorithms and improve the predictive ability.
Looking forward to having the opportunity to communicate with you further, thank you for your time.
Sincerely, Yelong Chen
