謝泓廷 (Vincent Hsieh)

My dream is to be one of the contributors of world-class software which really facilitate people's daily life. When I graduate from NTHU, I learn android starting from a famous smart phone manufacture. In that period, in addition to the android framework, I further have experience to co-work with product manager and UX designer to come up with great software that million of user need. Moreover, I have experience in the past two year to co-work with oversea team in Europe to develop the world-class navigation software which is now the leading automative navigation system in cars around the Europe. 

java、Kotlin、C++、Android、machine learning、computer vision、python
[email protected]


HsinChu City, R.O.C ; Master in Information System and Application, National Tsing-Hua University — 2011 ~ 2013

  • GPA: 4.21
  • TOEIC: 790 

Taoyuan City, R.O.C ; B.S in Information Management, Yuan-Zen University — 2007 ~ 2011

  • GPA: 3.71, School Year Rank (1/55)


  • Senior Engineer @ TSMC - 2021/04 - 2021/10
    • Java-based equipment automation system (Java, Kubernetes, SpringBoot)
  • Software Engineer @ TomTom - 2018/08 - 2021/04
    • Android-based user interface (Kotlin, Java)
    • Automated end-to-end testing (Cucumber, Espresso)
    • Cross platform navigation engine (C++)
    • Work with oversea team
    • Scrum team member
  • Senior Software Engineer @ AMACS (AI Machine learning And Cloud Software) Center, ASUS— 2017 ~ 2018
    • Computer Vision related projects
      • Face Recognition System in ASUS
  • Android Software Developer @ AMAX( ASUS Mobile Application eXperience Center), ASUS — 2014 ~ 2017 


  • TomTom GO Navigation - GPS Maps & Traffic Alerts: an onboard navigation software that provide route planning with real-time traffic.

    • An on board navigation software that provide route planning with real-time traffic. In addition to route planning, it's functionalities includes providing timely voice and visual guidance, searching for rich POIs and warning for speed cameras so that guide the driver to the destination safely.
    1. Design and implement features
    2. End-to-end automation test, unit-test
    3. Co-work with UX designer, engineer with oversea team in Europe.
    1. Kotlin, Java, C++
    2. e2e automation test
  • Kids Mode: an easy and customized launcher  for kids in ZenFone 2 (https://goo.gl/QBMJTy)

An Android launcher that design for kids between 5 to 10 years old. It's a safe playground for kids to use. Parents can pick applications their kids can access under Kids Mode . Moreover they could set play time for their kids to use, preventing them from playing smart phone for a long time.


  1. Design and implement features 
  2. unit test

  • ZenUI Launcher: a highly customized launcher which preloaded in Zenfone series (https://goo.gl/vBQkv1)

This launcher is pre-loaded in ASUS zenfone and its download and update counts has been over 10,000,000 in Google Play Store. It’s a highly customised launcher for users. In this application, I have involved in developing features including the following ones:

  • ZenUI Now: a widget in Android home screen that show various news according to your favourite publisher. With this feature, user can read online news directly without opening browser or even downloading news apps. For more detailed content about this feature, please reference to this (https://goo.gl/4DhXoh). 
  • ZenUI Show: User can share their customized home screen as screenshot to social network.
  • Badge: Unread badge count at icons such as Facebook, Gmail
  1. Develop the above features
  2. Developing difference size of layouts for Android tablet or phone.
  3. Improving memory usage in ZenUI Launcher using Android Studio or LeakCanary (https://goo.gl/TkxGuE).

  1. Java 
  2. LeakCanry, Lint, Android hierarchy viewer, MAT, Fresco, Infer


  • 機器學習基石 (Machine Learning Foundations) -Hsuan-Tien Lin
  • 機器學習技法 (Machine Learning Technique)- Hsuan-Tien Lin
  • Deep Learning Specialization (Coursera) - Prof.  Andrew Ag.
    • Neural Networks and Deep Learning 
    • Structuring Machine Learning Projects 
    • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
    • Convolutional Neural Networks
  • CS231n: Convolution Nerual Networks (Stanford University) 
    • course website : http://cs231n.stanford.edu/2017/
    • assignment : https://github.com/vincent732/cs231n 


  • Face Recognition System: A real-time face classification using deep learning approach

In order to solve the problem that if we forgot to bring our identification card, we cannot enter the office. We implement a face recognition system (Face Detection、Face Embedding Generation、Classification) in front of the entry in our office. 


    1. Collect training images
    2. Reading paper to explore new idea 
    3. Improve the flow and performance of system
    4. Try various experiments to validate our idea 
    1. Python 
    2. Tensorflow 
    3. SVM, FaceNet, MobileNet  
    4. Docker

  • Face Recognition in Raspiberry pi with Intel Movidius NCS

In the second stage of face recognition, in order to reduce the cost of setting up network or pc (with GPU), we move the system from PC to Raspberry pi with Intel Movidius NCS, which is used to speed up the inference speed on embedded system.


  1. Tranform tensorflow model to NCS graph
  2. Improve the performance of system
  1. NCS sdk
  2. Python
  3. Docker

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Academic Silver Medal

Awarded by Yuan Ze University (2009)

Yu-Hsiang Scholarship

Awarded by Yuan Ze University (2009)

Wan-Lin Tsai Scholarship

Awarded by Cathay Charity Foundation (2013) 


  • Hung-ting Hsieh, Chung-chi Huang, Mei-hua Chen, Mingling Bai, Jason S. Chang, and Keh-jiann Chen, 2012, An In-Page Computer- Assisted Translation Tool for Specific Domain, In Proceeding of the 10th Biennial Conference of the Association for Machine Translation in the Americas, Demo session (AMTA 2012) 

  •  Shih-ting Huang, Mei-hua Chen, Hung-ting Hsieh, Tinghui Kao and Jason S. Chang. 2012. FLOW: A First- Language-Oriented Writing Assistant System. In Proceeding of the 50th Annual Meeting of the Association for computational Linguistics: Systems Demonstrations (ACL 2012) 

  •  Chung-Chi Huang, Ping-Che Yang, Mei-Hua Chen, Ting- Hui Kao, Hung- Ting Hsieh and Jason S. Chang. TransAhead: A Writing Assistant for CAT and CALL, In Proceeding of the 13th European Chapter of the Association for computational Linguistics (EACL 2012) 

  • Chung-Chi Huang, Mei-Hua Chen, Shih-Ting Huang, Hung-Ting Hsieh, Ting-Hui Kao, Hsien-Chin Liou, Jason S. Chang. Automatically Generating Grammar Patterns and Lexical Bundles for Assisting Language Learners’ collocation learning, In Proceeding of the 15th International CALL Research Conference (CALL 2012)

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