Providence University

Computer Hardware and Embedded Systems Laboratory

Tzu-Chiang Tai
https://c060.pu.edu.tw/p/412-1110-3027.php?Lang=zh-tw

Research Field

Information Engineering (Information)

Introduction

Tzu-Chiang Tai received the Ph.D. degree in Electrical Engineering from National Cheng Kung University, Tainan, Taiwan.
He was with Philips Semiconductors and United Microelectronics Corporation (UMC). Currently, he is an Associate Professor with the Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan. His research interests include signal processing, deep learning, reconfigurable computing, and VLSI design.

Lab's Introduction:

FPGA prototype chip design, single-chip system, embedded system design and application, and other related research topics


Research Topics

Machine Learning, IC Chip Design, Embedded System


Honor

2022 Outstanding Research Award, Providence University
2021 Outstanding Research Award, Providence University
2019 Outstanding Research Award, Providence University
2018 Luking Research Award, Providence University
2017 Outstanding Research Award, Providence University
2016 Outstanding Research Award, Providence University
2014 Outstanding Research Award, Providence University
2013 Outstanding Research Award, Providence University

2019 Outstanding Department Teaching Award, Providence University
2015 Outstanding College Teaching Award, Providence University
2014 Outstanding Department Teaching Award, Providence University
2013 Outstanding Department Teaching Award, Providence University
2012 Outstanding Department Teaching Award, Providence University

2016 Outstanding Department Mentor Award, Providence University
2015 Outstanding Department Mentor Award, Providence University

2019 Silver Medal Award, Graduation Project Competition, College of Computing and Informatics, Providence University


Educational Background

Ph.D., Department of Electrical Engineering, National Cheng Kung University, Taiwan, R.O.C.


2 Vacancies

Job Description

Implement systems related to AI and Edge Computing

Preferred Intern Education Level

Undergraduate students, graduate students

Skill sets or Qualities

With good knowledge in AI and Edge Computing