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| awards = [[Forbes 30 Under 30]]
| awards = [[Forbes 30 Under 30]]
| website = {{URL|https://www.cc.gatech.edu/~dyang888/index.html}}
| website = {{URL|https://nlp.stanford.edu/~diyiy/}}
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'''Diyi Yang''' is a Chinese computer scientist and assistant professor of computer science at [[Stanford University]] and [[Georgia Institute of Technology]] [[Georgia Institute of Technology School of Interactive Computing|School of Interactive Computing]]. Her research combines [[linguistics]] and [[social science]]s with [[machine learning]] to address social problems like [[Cyberbullying|online harassment]], as well as user-centered [[Natural language generation|text generation]] and [[Data augmentation|learning with limited data]].
'''Diyi Yang''' is a Chinese computer scientist and assistant professor of computer science at [[Stanford University]]. Her research combines [[linguistics]] and [[social science]]s with [[machine learning]] to address social problems like [[Cyberbullying|online harassment]], as well as user-centered [[Natural language generation|text generation]] and [[Data augmentation|learning with limited data]].


== Biography ==
== Biography ==
Diyi Yang attended [[Shanghai Jiao Tong University]] for her undergraduate studies, earning a [[Bachelor of Science]] degree in [[Computer Science]] in July of 2013. She received an [[Master of Science|M.S.]] (May 2015) and [[Doctor of Philosophy|Ph.D.]] (February 2019) degrees from [[Carnegie Mellon University]] [[Language Technologies Institute]]. For her [[dissertation]] work, Yang developed algorithms for understanding computational social roles by bringing together [[machine learning]] techniques with [[sociology]] and [[social psychology]]. Upon completing her PhD, Yang became an assistant [[professor]] at the [[Georgia Tech]] [[Georgia Institute of Technology College of Computing|College of Computing]] where she now leads the Social and Language Technologies (SALT) Lab.<ref>{{Cite web|last=Yang|first=Diyi|title=SALT Lab|url=https://www.cc.gatech.edu/~dyang888/group.html|url-status=live|archive-url=https://web.archive.org/web/20200814101949/https://www.cc.gatech.edu/~dyang888/group.html |archive-date=2020-08-14 }}</ref>
Diyi Yang attended [[Shanghai Jiao Tong University]] for her undergraduate studies, earning a [[Bachelor of Science]] degree in [[Computer Science]] in July of 2013. She received an [[Master of Science|M.S.]] (May 2015) and [[Doctor of Philosophy|Ph.D.]] (February 2019) degrees from [[Carnegie Mellon University]] [[Language Technologies Institute]]. For her [[dissertation]] work, Yang developed algorithms for understanding computational social roles by bringing together [[machine learning]] techniques with [[sociology]] and [[social psychology]]. Upon completing her PhD, Yang became an [[assistant professor]] at the [[Georgia Tech]] [[Georgia Institute of Technology College of Computing|College of Computing]]. In 2022, Yang moved to [[Stanford University]] where she now leads the Social and Language Technologies (SALT) Lab.<ref>{{Cite web|last=Yang|first=Diyi|title=SALT Lab|url=https://nlp.stanford.edu/~diyiy/group.html|url-status=live}}</ref>


== Recognition ==
== Recognition ==
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== External links ==
== External links ==
*[https://www.cc.gatech.edu/~dyang888/index.html Official Website] at Georgia Tech
*[https://nlp.stanford.edu/~diyiy/ Official Website]
*{{Google Scholar id|id=j9jhYqQAAAAJ}}
*{{Google Scholar id|id=j9jhYqQAAAAJ}}


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[[Category:Year of birth missing (living people)]]
[[Category:Year of birth missing (living people)]]
[[Category:Living people]]
[[Category:Living people]]
[[Category:Georgia Tech faculty]]
[[Category:Stanford University Department of Computer Science faculty]]
[[Category:Chinese expatriates in the United States]]
[[Category:Chinese expatriates in the United States]]
[[Category:Shanghai Jiao Tong University alumni]]
[[Category:Shanghai Jiao Tong University alumni]]

Revision as of 17:35, 1 September 2022

Diyi Yang
Alma materCarnegie Mellon University (Ph.D., 2019),
Shanghai Jiao Tong University (B.S., 2013)
AwardsForbes 30 Under 30
Scientific career
FieldsNatural Language Processing, Computational Linguistics, Computational social science, Social computing
InstitutionsStanford University (2022-),
Georgia Tech (2019-)
Doctoral advisorRobert E. Kraut,
Eduard Hovy
Websitenlp.stanford.edu/~diyiy/

Diyi Yang is a Chinese computer scientist and assistant professor of computer science at Stanford University. Her research combines linguistics and social sciences with machine learning to address social problems like online harassment, as well as user-centered text generation and learning with limited data.

Biography

Diyi Yang attended Shanghai Jiao Tong University for her undergraduate studies, earning a Bachelor of Science degree in Computer Science in July of 2013. She received an M.S. (May 2015) and Ph.D. (February 2019) degrees from Carnegie Mellon University Language Technologies Institute. For her dissertation work, Yang developed algorithms for understanding computational social roles by bringing together machine learning techniques with sociology and social psychology. Upon completing her PhD, Yang became an assistant professor at the Georgia Tech College of Computing. In 2022, Yang moved to Stanford University where she now leads the Social and Language Technologies (SALT) Lab.[1]

Recognition

In 2020, Yang was named one of IEEE AI's 10 To Watch,[2] and in 2021, she was awarded Samsung AI Researcher of the Year,[3] Intel Rising Star,[4] and was listed in the Forbes 30 Under 30 for Science.[5]

References

  1. ^ Yang, Diyi. "SALT Lab".{{cite web}}: CS1 maint: url-status (link)
  2. ^ Subrahmanian, V.S. (2020-11-01). "The Future of AI: AI's 10 To Watch". IEEE Intelligent Systems. 35 (6): 3–6. doi:10.1109/mis.2020.3033683. ISSN 1541-1672.
  3. ^ "[Samsung AI Forum 2021] Day 1: AI Research for Tomorrow". Samsung. Archived from the original on 2021-11-01.
  4. ^ "Intel® 2021 Rising Star Faculty Award Recognizes 10 Leading Early-Career Professors". Intel. Archived from the original on 2021-09-14.
  5. ^ Knapp, Alex; Jennings, Katie; Rosenbaum, Leah (eds.). "Science - Forbes 30 Under 30 2021". Forbes. Archived from the original on 2020-12-01.
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