Kai Kang
Staff Machine Learning Engineer and Manager, Apple Inc.
Video Engineering Group
Email: myfavouritekk AT gmail DOT com
Site: kangk.ai
Computer Vision
Crowd Behavior Analysis
Video Object Detection
Deep Learning
Aug. 2013 - Sept. 2017
University: The Chinese University of Hong Kong (CUHK)
Department: Department of Electronic Engineering
Supervisor: Prof. Xiaogang Wang and Prof. Hongsheng Li
Degree: PhD
Sep. 2009 - July 2013
University: University of Science and Technology of China (USTC)
School: School of the Gifted Young
Department: Department of Optics and Optical Engineering
Degree: B.S. in Optics
Apple Inc.
Mar. 2021 - present
Staff Machine Learning Engineer & Engineering Manager. Video Engineering.
Apr. 2020 - Mar. 2021
Machine Learning Manager. Video Engineering.
Oct. 2018 - Apr. 2020
Senior Machine Learning Engineer. Video Engineering.
Technical lead for computer vision and machine learning algorithm development for camera related applications.
Oct. 2017 - Sept. 2018
Computer Vision/Machine Learning Engineer. Video Engineering.
Directly responsible for Face ID antispoofing algorithms since iOS 11.3 for iPhone X, iPhone XS, XS Max, XR and 2018 iPad Pros.
2021: Young Alumni Award. 50th Anniversary of the Department of Electronic Engineering, The Chinese University of Hong Kong.
2020: Outstanding Young Author Award, IEEE Circuits and Systems Society (CASS). "T-CNN: Tubelets With Convolutional Neural Networks for Object Detection From Videos", T-CSVT 2018.
2016: Winner (CUVideo), ImageNet: Large Scale Visual Recognition Challenge 2016 (ILSVRC2016), Task 3c: Object detection/tracking from video with provided training data. Official results page.
2015: Winner (CUVideo), ImageNet: Large Scale Visual Recognition Challenge 2015 (ILSVRC2015), Task 3a: Object detection from video with provided training data. Official results page.
2012: Best Software Tools Project (USTC-Software), International Genetically Engineered Machine (iGEM) Competition World Championship, MIT, Massachusetts, USA
2012: Gold Medal (USTC-Software), International Genetically Engineered Machine (iGEM) Competition Asia Jamboree, HKUST, Hong Kong
CUHK
Aug. 2013 - Sept. 2017
PhD candidate in Electronic Engineering, The Chinese University of Hong Kong
Supervisor: Prof. Xiaogang Wang and Prof. Hongsheng Li
Lab: Multimedia Laboratory, The Chinese University of Hong Kong
Research Areas: Object detection in videos, crowd behavior analysis, computer vision and deep learning
Details see publications.
Feb. 2012 - Nov. 2012
Team leader of USTC-Software team participating in iGEM competition (International Genetically Engineered Machine Competition)
Project Topic: Reverse Engineering for Biological Regulatory Networks (REBORN)
Medal: Gold Medal
Prize: Best Software Tools Project
The International Genetically Engineered Machine (iGEM) Competition is a worldwide synthetic biology competition aimed at building simple biological system from standard, interchangeable parts and operate them in living cells. This year, 191 teams from 21 countries were registered, and 71 teams advanced to the world championship, in which 12 software team were registered, and 9 of them advanced to world championship.
Visit the official iGEM 2012 page for more details, and be sure to visit our team wiki for more about the project
June, 2016: Object Detection from Video Tubelets with Convolutional Neural Networks, Computer Vision and Pattern Recognition (CVPR) Spotlight, Las Vegas, NV, USA. video
Dec, 2015: Object Detection in Videos with Tubelets and Multi-Context Cues, ImageNet and MS COCO Visual Recognition Challenges Joint Workshop, ICCV 2015, Santiago, Chile. slides poster video
Nov, 2012: Reverse Engineering for Biological Regulatory Networks, iGEM World Jamboree, MIT, Cambridge, MA, USA
Oct, 2012: REBORN: Synthetic Biology Tools for Hackers, iGEM Asia Jamboree, HKUST, Hong Kong
More projects on GitHub.