Yun Jin

Yun Jin Email and Phone Number

건국대학교 겸임교수 adjunct professor @ 건국대학교
Yun Jin's Location
South Korea, Korea, Republic of
Yun Jin's Contact Details

Yun Jin work email

Yun Jin personal email

About Yun Jin

Experienced Senior Researcher with a demonstrated history of working in the research industry. Skilled in Natural Language Processing (NLP), Natural Language Understanding, Information Retrieval, Deep Learning, and Machine Translation. Strong research professional with a Ph.D focused in Information Retrieval and Natural Language Processing from Chungnam National University.

Yun Jin's Current Company Details
건국대학교

건국대학교

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건국대학교 겸임교수 adjunct professor
Yun Jin Work Experience Details
  • Dmt Labs
    대표
    Dmt Labs Mar 2018 - Present
    대한민국 서울 용산구
    다국어처리, 통번역서비스, 대화솔루션
  • 건국대학교
    겸임교수 Adjunct Professor
    건국대학교 Jun 2019 - Present
    대한민국 서울
    선형대수, 미적분학, 이산수학, 프로그래밍언어
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  • Peaceplus.Org
    Advisor
    Peaceplus.Org Sep 2019 - Oct 2019
    대한민국 서울 금천구
  • Etri
    Senior Researcher
    Etri Oct 2007 - Nov 2017
    Yuseong-Gu, Daejeon, Korea
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  • Information & Communication University (Icu)
    Postdoc
    Information & Communication University (Icu) Mar 2007 - Sep 2007
    Yuseong-Gu, Daejeon, Korea

Yun Jin Skills

Information Retrieval Natural Language Processing Machine Translation Machine Learning Natural Language Understanding Deep Learning

Yun Jin Education Details

Frequently Asked Questions about Yun Jin

What company does Yun Jin work for?

Yun Jin works for 건국대학교

What is Yun Jin's role at the current company?

Yun Jin's current role is 건국대학교 겸임교수 adjunct professor.

What is Yun Jin's email address?

Yun Jin's email address is wk****@****ail.com

What schools did Yun Jin attend?

Yun Jin attended Chungnam National University, Chungnam National University, Yanbian University.

What are some of Yun Jin's interests?

Yun Jin has interest in Multi Lingual Processing.

What skills is Yun Jin known for?

Yun Jin has skills like Information Retrieval, Natural Language Processing, Machine Translation, Machine Learning, Natural Language Understanding, Deep Learning.

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