馮昱翔

My name is Yu-siang, Feng and I'm a master student at NCU, department of Communication Engineering now. My research topics are related to localization, SLAM, and Machine Learning.     What I did during my internship at Quanta Cloud Technology was to develop a DevOps system for the 5G core network.

Email: [email protected]  Cell Phone Number: 0966215203

  Taipei City, Taiwan  https://gitlab.com/yusiang_feng  

Education

2020 - 2022

National Central University

Department of Communication Engineering

2016 - 2020

National Taiwan Ocean University

Department of Communication, Navigation and Control Engineering

Work Experience

Intern Engineer  •  Quanta Cloud Technology

June 2020 - December 2020

Software R&D integration /5G core network system R&D, automated packaging, deployment, and testing mechanisms.

Project Experience

September 2020 - September 2021

Received Signal Strength Information (RSSI) Based Device-Free Localization with Machine Learning

NCU IPC LAB


We research and develop an RSSI-based Device-Free Localization System for smart wards. This project used Machine Learning to increase the accuracy of indoor localization, and I have compiled a paper and submitted it to ICCE-TW.

June 2020 - December 2020

Development of 5G core network code quality testing

Quanta Cloud Technology

We use GitLab CI/CD to do project control in this project. We designed a set of DevOps for the 5G core network and used various programming languages (Python, C, C++, Java) to test the Code Quality.

May 2021 - Now in progress

Develop a learning-based model for GBP bundle adjustment

NCU IPC LAB

This is a project in progress now. We use machine learning to accelerate the optimization part of SLAM, which is bundle adjustment. We have trained a model to increase the performance, and also make it 12 times faster. We are preparing a paper to submit to ICME.


Programming Skills


  • Python
  • C
  • C++

Skills


  • Gitlab-Ci/Cd
  • Machine Learning
  • 5G
  • Localization
  • SLAM

Language


  • English — Medium
  • Chinese — Native

Autobiography

My name is Yu-siang, Feng, and I come from Taipei City. Because I am the only child in my family, I have developed an independent character. I will find a way to solve problems by myself. Therefore, since I was young, I have liked to research and repair something, whether it is a computer or a mobile phone, hardware or software. I love research and finding a way to solve the problem.

I am currently studying a master's class at National Central University Department of Communication Engineering and doing research related to Machine Learning, Device-Free localization, and SLAM. In my spare time, I go to Quanta Cloud Technology as an intern engineer. And the project I do is about using GitLab CI/ CD to establish a set of DevOps designed for a 5G core network. These works let me know more about Machine Learning and DevOps. 

The first project I do at  National Central University is Received Signal Strength Information (RSSI) Based Device-Free Localization, which uses Machine Learning to increase the accuracy of indoor localization and test various Classification models, such as MSCNN, FCN, LSTM-MSCNN, etc. And I have compiled a paper and submitted it to ICCE-TW. During my internship in Quanta Cloud Technology, we use GitLab CI/CD to do project control. We design a set of DevOps for the 5G core network and use various programming languages (Python, C, C++, Java) to test the Code Quality. In the process of submitting the Code, the system will automatically detect whether there is a problem with the quality of the Code and show where it can be changed so that the engineer can quickly know where the problem is when submitting the code. The current research content is Spatial AI. We are developing some different models in SLAM (Simultaneous localization and mapping) to achieve good localization results at a faster speed. We are researching using machine learning to accelerate bundle adjustment with GBP, and have a better result that can make the GBP-based bundle adjustment 12 times faster. We compile a paper and submit it to ICME.

The programming languages I am good at are Python and C, and I have a certain degree of understanding of Machine Learning, DFL, bundle adjustment, and GitLab CI/CD.

During my university studies, I learned a lot of professional knowledge and skills, and in graduate school, I used a lot of this knowledge in my research. In order to be more proficient in these tools and techniques, I also read many online Courses, such as Machine Learning, Python, and C language courses. During the internship, I also read a lot of literature about GitLab and learned a lot. In the end, I can complete the project. When I am doing these projects, I can find my shortcomings, and then strengthen and learn, which makes me feel very happy. Therefore, I hope that in my future work, I can continuously explore my shortcomings, and improve my ability to do the job better.






























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