Yating Wu

Research Interests

Discourse Relationship, Text Elaboration, Speech Disfluency, Multilinguality and Grammatical Error Correction.

Education

Ph.D., (Jan. 2020 - Now) in Computer Enginnering

Department of Electrical and Computer Engineering,

University of Texas at Austin.
Advisors: Prof. Jessy Li, Prof. Alex Dimakis
Group: UT NLP Group, Wireless Networking and Communications Group(WNCG)

B.Eng., (Spt. 2014 - Jul. 2019) in Computer Science and Technology

B.A., (Spt. 2014 - Jul. 2019) in Japanese

Department of Computer Science; Department of Foreign Languages
Dalian University of Technology.

Undergraduate Exchange Student, (Spt. 2017 - Aug. 2018) in Computer Science

Department of Information & Communication Engineering,
The University of Tokyo.
Advisor: Prof. Toshihiko Yamasaki
Group: Aizawa Yamakata Matsui Laboratory

Publication

• Elaborative Simplification as Implicit Questions Under Discussion [code and data]
  Yating Wu^†, William Sheffield^†, Kyle Mahowald, and Junyi Jessy Li
  arXiv(^†Indicates equal contribution)

• Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion [code]
  Wei-Jen Ko, Yating Wu, Cutter Dalton, Dananjay Srinivas, Greg Durrett and Junyi Jessy Li
  Findings of the Association for Computational Linguistics (ACL), 2023 (To appear)

• longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks [bib]
  Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan, Jifan Chen, Eunsol Choi, Gabriella Chronis, Anubrata Das, Katrin Erk, Matthew Lease, Junyi Jessy Li, Yating Wu and Kyle Mahowald
  In Proceedings of the First Workshop on Dynamic Adversarial Data Collection (DADC) at the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), pages 41--52, 2022.
  

Experience

Working Experience

• Amazon Prime Video, Summer 2021
  Software Develop Engineer Intern(received return offer). [The project got launched in prime video offical site]
  
  • Implemented a Ranking System for ranking the events based on its popularity. I wrote over 10,000 lines java code and assured over 97% coverage.
  • Designed and Implemented a Ranking Data DynamoDB table for saving viewership data and filter events.
  • Set up Lambda to automatically pulling and putting latest information to Database.
  • Contributed to the main team repository to sort events based on viewership data.
  • Ingested with inner service to create two new carousals to provide this service for new customers.

Teaching Experience

• University of Texas at Austin, Fall 2021, Spring 2022, Summer 2022, Fall 2022
  CS391L: Machine Learning(TA)
  • Hold office hours and prepare materials for CS391L. It is a graduate level course for machine learning. Professor: Adam Klivans, Qiang Liu.
  
  
• University of Texas at Austin, Summer 2020, Fall 2020, Spring 2021
  EE422C: Software Design & Implementation II(TA)
  
  • Hold Recitations and office hours for EE422C Software Design & Implementation II. It is a course teaching Java Data Structures and Algorithm Analysis. Professor: Vallath Nandakumar, Edison Thomaz.

Awards

• VMware Codehouse Palo Alto 1st place, Jul. 2021[post]
• Outstanding graduates, Jun. 2019

Links

Department of Electrical and Computer Engineering

The University of Texas at Austin

The University of Tokyo

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