Sohee Yang (Preferred)
Sohee Yang
University College London, University of London
Names
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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.
****@navercorp.com
, ****@kaist.ac.kr
, ****@gmail.com
, ****@ucl.ac.uk
Personal Links
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Education & Career History
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PhD student
University College London, University of London (ucl.ac.uk)
2023 – Present
PhD student
Department of Computer Science, University College London, University of London (cs.ucl.ac.uk)
2023 – Present
Intern
DeepMind (deepmind.com)
2023 – Present
Intern
Google (google.com)
2023 – Present
MS student
Korea Advanced Institute of Science and Technology (kaist.ac.kr)
2021 – 2023
Research engineer
Clova AI, NAVER Corp. (navercorp.com)
2018 – 2021
Research intern
Kakao Corp. (kakaocorp.com)
2018 – 2018
Undergrad student
Handong Global University (handong.edu)
2014 – 2018
Advisors, Relations & Conflicts
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PhD Advisor
Sebastian Riedel
****@deepmind.com
2023 – Present
PhD Advisor
Pontus Stenetorp
****@stenetorp.se
2023 – Present
PhD Advisor
Minjoon Seo
****@kaist.ac.kr
2021 – Present
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
Large Language Models
2023 – Present
Natural Language Processing
2017 – Present
Open-Domain Question Answering
2020 – 2022
Task-Oriented Dialogue System
2017 – 2020