Taipei Tech AIoT Lab

Artificial Intelligence of Things


  • 2019/10/10 - Our paper "AnyCharge: An IoT Wireless Charging Service for the Public" has been accepted by IEEE IOT Journal!
  • 2018/10/24 - Our paper "VIVID: Virtual Environment for Visual Deep Learning" won the ACM MM 2018 Best Open Source Software Award!


Prof. Kuan-Ting (K. T.) Lai 賴冠廷

Dr. Kuan-Ting Lai received bachelor's degree in Electric Engineering and master's degree in Computer Science from National Taiwan University in 2003 and 2005. After graduation, he joined Quanta Computer as a video ASIC engineer for 4 years, and started to pursue Ph.D. in 2009, under supervision of Prof. Ming-Syan Chen. During 2012-2013, Dr. Lai visited Prof. Shih-Fu Chang’s DVMM lab at Columbia University, and co-developed a large-scale video event detection system with IBM T. J. Watson Research Center. He received his Ph.D. degree in Feb. 2015 and became the VP of technology at Arkados Group. He also co-founded AnyCharge, a wireless charging service provider in Asia. In 2018, Dr. Lai joined the Department of Electronic Engineering at National Taipei University of Technology (臺北科技大學電子工程系) as an Assistant Professor. His research interests include computer vision, machine learning, deep learning and Internet of Things. His habit is traveling around the world by joining conferences and making new friends.


Year 2018

Chi-Jen Chen

  • Intelligent System Research Center Sofeware Engineer Intern

Guo-Wei Wu

  • Coding 365 Teaching Assistant

Jung-Cheng Tsai

  • Coding 365 Teaching Assistant

Tsan-Lun Yang

  • Exchange student at University of Cincinnati to study industrial big data analysis

Year 2019

Chi-Hung Tian

  • Exchange student at Osaka Prefecture University for studying Computer Science

Chao-Yu Siao

  • Coding 365 Teaching Assistant

Jun-Jia Su

  • Arima Communications Corp Intern
  • AU Optronics Corp Intern

Yung-Chin Hsu

  • Google Taiwan Engineering Limited Intern
  • HTC Corporation Intern

Wei-Chuan Chiang

  • Institute for Information Industry Intern

Chun-Hsien Yu

  • PROV Technology Corporation, software engineer
  • shuttle computer, Android BSP engineer


VIVID - Virtual Environment for Visual Deep Learning

VIVID is a photo-realistic simulator that aims to facilitate deep learning for computer vision, which supports different characters: robot, drone, and automobile. The platform can be used for many research fields including deep reinforcement learning, semantic segmentation object recognition and human action recognition. For more details please visit the project's github page.

AnyCharge - An IoT-based Public Charging Service

AnyCharge is a public wireless charging service based on IoT technology. All the chargers are controllable by our cloud. We have deployed around 70 charging spots in Taiwan, Thailand, and Singapore (website).

Drone Action Recognition

In this project, we develop a large-scale action detector of drone that can recognize numerous complex human actions such as running, eating, smoking, photo shooting, and create a large-scale dataset to evaluate our algorithm.

Mining Telecom Fraud using Social Network Analysis

Telecom fraud is one of the most prevalent crimes today and causes most property loss. To identify the roles of the fraudsters, we cooperate with Criminal Investigation Bureau of Taiwan and propose a Telecom Fraud Analysis Model (TFAM). For more details, please refer to our paper "Mining the Networks of Telecommunication Fraud Groups using Social Network Analysis", ASONAM, 2017.


The table is created by Google Scholar on September 12, 2019. For latest information, please visit My Google Scholar Profile.

Title Cited by Year
An Efficient and Resource-Aware Hashtag Recommendation Using Deep Neural Networks
D Kao, KT Lai, MS Chen
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 150-162, 2019
VIVID: Virtual Environment for Visual Deep Learning
KT Lai, CC Lin, CY Kang, ME Liao, MS Chen
2018 ACM Multimedia Conference on Multimedia Conference, 1356-1359, 2018
The privileged sensing framework: A principled approach to improved human-autonomy integration
AR Marathe, JS Metcalfe, BJ Lance, JR Lukos, D Jangraw, KT Lai, ...
Theoretical Issues in Ergonomics Science 19 (3), 283-320, 2018
7 2018
Mining the Networks of Telecommunication Fraud Groups using Social Network Analysis
YC Chang, KT Lai, SCT Chou, MS Chen
Advances in Social Networks Analysis and Mining (ASONAM), 2017
2 2017
Learning sample specific weights for late fusion
KT Lai, D Liu, SF Chang, MS Chen
IEEE Transactions on Image Processing 24 (9), 2772-2783, 2015
15 2015
Recognizing complex events in videos by learning key static-dynamic evidences
KT Lai, D Liu, MS Chen, SF Chang
European Conference on Computer Vision, 675-688, 2014
38 2014
Video Event Detection by Inferring Temporal Instance Labels
KT Lai, XY Felix, MS Chen, SF Chang
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, 2014
94 2014
Sample-specific late fusion for visual category recognition
D Liu, KT Lai, G Ye, MS Chen, SF Chang
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, 803-810, 2013
54 2013
Human action recognition using histogram of oriented gradient of motion history image
CP Huang, CH Hsieh, KT Lai, WY Huang
Instrumentation, Measurement, Computer, Communication and Control, 2011 …, 2011
39 2011
Orientation histogram of SIFT displacement for recognizing actions in broadcast videos
KT Lai, MS Chen, CH Hsieh, MF Lai
Visual Information Processing (EUVIP), 2011 3rd European Workshop on, 286-291, 2011
3 2011
Human action recognition using key points displacement
KT Lai, CH Hsieh, MF Lai, MS Chen
International Conference on Image and Signal Processing, 439-447, 2010
8 2010
Player detection and tracking in broadcast tennis video
YC Jiang, KT Lai, CH Hsieh, MF Lai
Pacific-Rim Symposium on Image and Video Technology, 759-770, 2009
13 2009

Contact Us

Office Address

Complex Building (綜科館), Room 406-1. No. 1, Sec. 3, Zhongxiao E. Rd., Taipei City, 10643, Taiwan (臺北科技大學)

Phone Number

(+886-2) 2771-2171 Ext. 2275