Chia-Che Chang

MediaTek

Names

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

Chia-Che Chang (Preferred)

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.

****@gmail.com
,
****@mediatek.com

Education & Career History

Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.

Researcher
MediaTek (mediatek.com)
2018Present
 
MS student
National Tsing Hua University (nthu.edu.tw)
20162018
 
Undergrad student
National Chi Nan University (ncnu.edu.tw)
20122016
 

Advisors, Relations & Conflicts

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

Coauthor
yi-chen lo
****@mediatek.com
20202021
 
Coworker
chia-ping chen
****@mediatek.com
20202021
 
Coworker
yu-lin chang
****@mediatek.com
20202021
 
Coworker
hsuan-chao chiu
****@mediatek.com
20202021
 
Coworker
Yu-Hao Huang
****@mediatek.com
20202021
 
Coworker
Kevin Jou
****@mediatek.com
20202021
 
Coworker
Yu-Sheng Chen
****@cmlab.csie.ntu.edu.tw
20192020
 
Coworker
Li Su
****@iis.sinica.edu.tw
20182018
 
Coworker
Min-Xin Xue
****@gmail.com
20182018
 
Advisor
Hwann-Tzong Chen
****@cs.nthu.edu.tw
20172018
 
Coworker
Da-Cheng Juan
****@google.com
20172018
 
Coworker
Wei Wei
****@google.com
20172018
 
Coworker
Chieh Hubert Lin
****@gmail.com
20172018
 
Coworker
Wei-Chun Chen
****@gmail.com
20172018
 
Coworker
Chien-Yu Lu
****@gmail.com
20172018
 
Advisor
Che-Rung Lee
****@cs.nthu.edu.tw
20162018
 

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

Generative Adversarial Network
20172018
 
Computer Vision
20152018