Associate Researcher

Machine Learning Group, Microsoft Research Asia (MSRA)

jindong.wang (at) microsoft.com, jindongwang (at) outlook.com

Google Scholar | Zhihu Github Weibo | [CV] [中文简历]

I'm currently an associate researcher at machine learning group, Microsoft Research Asia (MSRA), where I directly report to Prof. Tie-Yan Liu. Before joining MSRA, I obtained by Ph.D degree from Institute of Computing Technology, Chinese Academy of Sciences in June, 2019. My Ph.D thesis is mainly about transfer learning algorithms. At MSRA, my research interest will be transfer learning based few-shot learning, meta learning, adaptive learning, and related applications.
My personal page on Microsoft Research

Artificial intelligence:

• Learning: transfer learning, data mining, machine learning, deep learning.
• Application: activity recognition, computer vision, and more.

• Associate Researcher. 2019.07 - Now
  Microsoft Research Asia (MSRA)
  Manager: Tie-Yan Liu
• Intern. 2019.06 - 2019.07
  Microsoft Research Asia (MSRA)
  Supervisor: Tao Qin
• Visiting student. 2018.04 - 2018.08
  Hong Kong University of Science and Technology (HKUST)
  Supervisor: Qiang Yang

• Ph.D in computer science. 2014 - 2019
  Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS)
  University of Chinese Academy of Sciences (UCAS)
  Supervisor: Yiqiang Chen
• B.Eng in computer science. 2010 - 2014
  North China University of Technology (NCUT), Beijing, China

Technical reports

1. 迁移学习简明手册 (First manual in transfer learning).
   Jindong Wang.
   Transfer Learning Tutorial 2018
   [Link] [PDF] [Github]

Conference papers

1. FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare.
   Yiqiang Chen, Jindong Wang, Chaohui Yu.
   IJCAI-19 Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (IJCAI (FML)) 2019
   [PDF coming soon]
2. Easy Transfer Learning By Exploiting Intra-domain Structures.
   Jindong Wang, Yiqiang Chen, Han Yu, Meiyu Huang, Qiang Yang.
   IEEE International Conference on Multimedia & Expo (ICME) 2019
   [PDF] [Code]
3. Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Prunning.
   Chaohui Yu, Jindong Wang, Yiqiang Chen, Zijing Wu.
   Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2019 Workshop
   International Joint Conference on Neural Networks (IJCNN) 2019 (Oral)
   [PDF] [Code]
4. Visual Domain Adaptation with Manifold Embedded Distribution Alignment.
   Jindong Wang, Wenjie Feng, Yiqiang Chen, Han Yu, Meiyu Huang, Philip S. Yu.
   ACM International Conference on Multimedia (ACMMM) 2018 (Oral, Top 10 papers)
   [PDF] [Code] [Supplementary] [Poster]
5. Deep Transfer Learning for Cross-domain Activity Recognition.
   Jindong Wang, Vincent W. Zheng, Yiqiang Chen, Meiyu Huang.
   The 3rd International Conference on Crowd Science and Engineering (ICCSE) 2018 (Best Paper)
   [PDF] [Link]
6. 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]
7. 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]
8. 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]
9. 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]
10. 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]
11. 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. Cross-position Activity Recognition with Stratified Transfer Learning.
   Yiqiang Chen, Jindong Wang, Meiyu Huang, Han Yu.
   Pervasive and Mobile Computing Volume 57, July 2019, Pages 1-13
   [Link] [PDF]
2. Deep Learning for Sensor-based Activity Recognition: A Survey.
   Jindong Wang, Yiqiang Chen, Shuji Hao, Xiaohui Peng, Lisha Hu.
   Pattern Recognition Letters Volume 119, 1 March 2019, Pages 3-11
   [Link] [PDF]
3. 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
   [Link] [PDF]
4. '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(JETAI) 2017
   [Link] [PDF]

Patents

1. 一种基于流形迁移学习的数据标定方法和系统.
   陈益强, 王晋东, 冯文杰, 忽丽莎.
   Chinese patent. No. CN108960270A. 2018
2. 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]
3. 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]
4. 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]
5. 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. See my Github rankings all over the world: [Link]
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

Awards and Honors

• Special scholarship of ICT (中科院计算所所长特别奖，计算所最高奖) 2019.
• Student Scholarship. AAAI Conference on Artificial Intelligence (AAAI) 2019.
• Student Travel Grant. ACM International Conference on Multimedia (ACMMM) 2018.
• Outstanding Reviewer. Neurocomputing. 2018.
• Best Paper. The 3rd International Conference on Crowd Science and Engineering (ICCSE) 2018.
• Merit Student, UCAS 2018.
• Student Travel Award. International Conference on Machine Learning (ICML) 2018.
• Student Scholarship. AAAI conference on Artificial Intelligence (AAAI) 2018.
• 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 City 2013.
• National Scholarship (3x), Ministry of Education 2012, 2013, 2014.

Reviewer | PC Member

• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
• ACM Computing Surveys (CSUR)
• ACM CHI Conference on Human Factors in Computing Systems (CHI) 2019
• Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)
• Knowledge-Based Systems
• Neurocomputing
• Pervasive and Mobile Computing (PMC)
• Journal of Experimental & Theoretical Artificial Intelligence
• IEEE Access
• Interactive Learning Environments (ILE)
• Journal of Electronic Images (JEI)
• European Signal Processing Conference (EUSIPCO) 2019
• Engineering Applications of Artificial Intelligence (EAAI) 2019
• Assembly Automation
• Annual International Conference on Information Technology and Applications (ITA) 2018 TPC member

Miscellaneous

• Publicity co-chair. International Joint Conference on Artificial Intelligence (IJCAI) 2019.
• Teaching assistant. Intelligent Pervasive Computing class. UCAS. Class ID: 251M6006H. 2017-2018, 2018-2019.
• CEO (Chief Experience Officer) of Jiqizhixin (机器之心)

• AI / data science: Python, Matlab, sklearn, Pytorch, Tensorflow.
• Development: C, C#, Java, Objective-C, C++, HTML, LaTex.
• Platform: PC, Android, iOS, Windows Phone, Spring MVC.
• Have passion to all the new things!

• 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.