Ph.D candidate | student member of AAAI / ACM / IEEE / CCF

Institute of Computing Technology, Chinese Academy of Sciences

Research Center for Ubiquitous Computing Systems
Beijing Key Laboratory of Mobile Computing and Pervasive Device

jindongwang (at) outlook.com Weibo Zhihu Github [CV] [CV(Chinese)]

• Artificial intelligence, transfer learning, machine learning, data mining and deep learning.
• Zhihu Live speaker: machine learning starter, feature engineering, research articles.
• Ph.D supervisor: Prof. Yiqiang Chen; With Prof. Qiang Yang from HKUST: photo, signature on my algorithm.

• 2018.04-2018.08 Postgraduate visiting intern in Hong Kong University of Science and Technology (HKUST). Supervisor: Prof. Qiang Yang.
  At the same time, I will also be a research intern at Artificial Intelligence Department of WeBank (微众银行).
• 2014.09-present Ph.D candidate in computer science, Institute of Computing Technology, Chinese Academy of Sciences.
• 2010.09-2014.06 B.S in computer science, North China University of Technology (NCUT), Beijing, China.

Technical reports

1. 迁移学习简明手册. [Link] [PDF] [Github]
   Jindong Wang. Transfer Learning Tutorial. Technical report 2018.

Conference papers

1. Stratified Transfer Learning for Cross-domain Activity Recognition.
   Jindong Wang, Yiqiang Chen, Lisha Hu, Xiaohui Peng, Philip S. Yu.
   IEEE International Conference on Pervasive Computing and Communications (PerCom). 2018 [PDF] [Code and dataset]
2. Balanced distribution adaptation for transfer learning.
   Jindong Wang, Yiqiang Chen, Shuji Hao, Wenjie Feng, Zhiqi Shen.
   The IEEE International Conference on Data Mining (ICDM). 2017 [Link] [PDF] [Code]
3. Weak multipath effect identification for indoor distance estimation.
   Xiaohai Li, Yiqiang Chen, Zhongdong Wu, Xiaohui Peng, Jindong Wang, Lisha Hu, Diancun Yu.
   The 14th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC). 2017 [PDF]
4. OCEAN: A new opportunistic computing model for wearable activity recognition.
   Yiqiang Chen, Yang Gu, Xinlong Jiang, Jindong Wang.
   The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp). 2016 [PDF] [Link]
5. Less Annotation on Personalized Activity Recognition Using Context Data.
   Lisha Hu, Yiqiang Chen, Shuangquan Wang, Jindong Wang, Jianfei Shen, Xinlong Jiang, Zhiqi Shen.
   The 13th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC). 2016 [PDF] [Link]
6. A Study of Players' Experiences during Brain Games Play.
   Faizan Ahmad, Yiqiang Chen, Shuangquan Wang, Zhenyu Chen, Jianfei Shen, Lisha Hu, Jindong Wang.
   The 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI). 2016 [PDF] [Link]

Journal articles

1. Deep Learning for Sensor-based Activity Recognition: A Survey.
   Jindong Wang, Yiqiang Chen, Shuji Hao, Xiaohui Peng, Lisha Hu.
   Pattern Recognition Letters. 2018 [Link] [PDF]
2. OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition.
   Lisha Hu, Yiqiang Chen, Jindong Wang, Chunyu Hu, Xinlong Jiang.
   International Journal of Machine Learning and Cybernetics (IJMLC). 2017 [PDF] [Link]
3. 'BrainStorm': A Psychosocial Game Suite Design for Noninvasive Cross-generational Cognitive Capabilities Data Collection.
   Faizan Ahmad, Yiqiang Chen, Lisha Hu, Shuangquan Wang, Jindong Wang, Zhenyu Chen.
   International Journal of Experimental and Theoretical Artificial Intelligence(IJETAI). 2017 [PDF] [Link]

Patents

1. 用于大规模数据标定的迁移学习方法及系统.
   陈益强, 王晋东, 沈建飞, 胡春雨, 王记伟, 张宇欣, 忽丽莎.
   Chinese patent. No. CN106599922A. 2017 [Link]
2. 人‑机器人运动数据映射的方法及系统.
   陈益强, 王晋东, 张宇欣, 胡春雨, 忽丽莎, 沈建飞.
   Chinese patent. No. CN106600000A. 2017 [Link]
3. 一种交通模式行为识别方法及相应的识别模型构建方法.
   陈益强, 忽丽莎, 谷洋, 王晋东, 王双全.
   Chinese patent. No. CN105447504A. 2015 [Link]
4. 运动行为和认知能力的关联分析方法及系统.
   陈益强, 胡春雨, 忽丽莎, 谢涛, 王晋东.
   Chinese patent. No. CN107016233A. 2017 [Link]

Book chapters

1. 保研一本通. 2014 [JD Link] [PDF]

1. My Matlab repos on Github rank top 3 in China, and top 8 worldwide. Cool! [Link] [Screenshot]
2. Leading the transfer learning tutorial (迁移学习简明手册) on Github: Tutorial
3. Leading a pupular transfer learning resource projects on Github: Transfer Learning
4. I'm also leading other popular research projects: Machine Learning, Activity Recognition
5. Numberconverter: a simple wox plugin to convert numbers into certain systems. 2015
6. My BMI & 2048 : a simple BMI app, while 2048 is a modified 2048 game about study. Available at Apple's App Store. 2015
7. I started a software studio Pivot Studio with a group of talented people, and we made many applications. 2010-2014

• AAAI-18 Student Scholarship. AAAI conference on Artificial Intelligence. 2017
• National Scholarship for PhD students, Ministry of Education. 2017
• Merit Student, UCAS. 2017
• Second prize of Bewinner Innovation scholarship. 2017
• Merit Student, UCAS. 2015
• Excellent Graduate, NCUT. 2014
• Excellent Bachelor's Graduation Thesis, NCUT. 2014
• Beijing Merit Student, Beijing. 2013
• National Scholarship (3x), Ministry of Education. 2012-2014

• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2018
• Neurocomputing 2018

• Teaching assistant. Intelligent Pervasive Computing class. UCAS. Class ID: 251M6006H. 2017-2018.

• Artificial intelligence: Python, Matlab, sklearn, Pytorch, Tensorflow.
• Development: C, C#, Java, Objective-C, C++, HTML, LaTex.
• Platform: PC, Android, iOS, Windows Phone, Spring MVC.
• I know something about mobile phone programming as well as server programming, making me capable of creating apps solely from 0 to 1.

• Learned Latte art recently!
• I like to share experience and lessons on social networks.
• Except for hiking and badminton, I do not like sports.
• I read every night. History, novel, economics, philosophy...
• I write a lot. Poetry, sketch, drama...
• I like watching any movies with good stories and devotions.