Dit-Yan Yeung

Hong Kong University of Science and Technology

Names

How do you usually write your name as author of a paper? Also add any other names you have authored papers under.

Dit-Yan Yeung (Preferred)
,
Dit-yan Yeung

Emails

Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.

****@cse.usk.hk
,
****@cse.ust.hk

Education & Career History

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Chair Professor
Hong Kong University of Science and Technology (ust.hk)
Present
 

Advisors, Relations & Conflicts

Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.

Coauthor
Abhinav Gupta
****@cs.cmu.edu
20152016
 
Coauthor
Naiyan Wang
****@gmail.com
20112016
 
Coauthor
Yi Zhen
****@cc.gatech.edu
20092016
 
Coauthor
Lin Sun
****@ust.hk
20152015
 
Coauthor
Lin Sun
****@lenovo.com
20152015
 
Coauthor
Jiaya Jia
****@cse.cuhk.edu.hk
20112015
 
Coauthor
Wu-jun Li
****@nju.edu.cn
20112015
 
Coauthor
Kui Jia
****@gmail.com
20082015
 
Coauthor
Hong Chang
****@ict.ac.cn
20042015
 
Coauthor
Jingdong Wang
****@microsoft.com
20112014
 
Coauthor
Xilin Chen
****@jdl.ac.cn
20112014
 
Coauthor
Eric Xing
****@cs.cmu.edu
20112014
 
Coauthor
Siyi Li
****@cse.ust.hk
20112014
 
Coauthor
Zhihua Zhang
****@cs.sjtu.edu.cn
20032014
 
Coauthor
Cheng-lin Liu
****@nlpr.ia.ac.cn
20102010
 
Coauthor
Guoqiang Zhong
****@gmail.com
20102010
 
Coauthor
James Kwok
****@cse.ust.hk
19952007
 
Coauthor
Albert Chung
****@cse.ust.hk
20062006
 

Expertise

For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing

Spatiotemporal models
Present
 
Generative models
Present
 
Graph neural networks
Present
 
Automated machine learning
Present
 
Adversarial learning
Present
 
Knowledge tracing
Present