Yating Wu

Research Interests

• Discourse relationship (sentences relationship within document) and its application case like enhancing text accessibility through adding elaboration information to simplified text.
• Investigating patterns in monolingual and bilingual dialogue, and leveraging generative models on applications.

Education

Ph.D., (Aug. 2022 - Now) in Computer Enginnering

M.S., (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
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

Selected Publications

(^†Indicates equal contribution)

• QUDeval: The Evaluation of Questions Under Discussion Discourse Parsing [data]
  Yating Wu, Ritika Mangla, Greg Durrett and Junyi Jessy Li
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023, to appear.

• Elaborative Simplification as Implicit Questions Under Discussion [code and data]
  Yating Wu^†, William Sheffield^†, Kyle Mahowald, and Junyi Jessy Li
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023, to appear.

• 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.

Experience

Working Experience

• Amazon Prime Video, Summer 2023
  Software Develop Engineer Intern(received strong return incline).
  
  • Implemented an in-game notification system using a Rule Engine.
  • Set up Lambda to respond to external service notifications and fetch updates through API.
  • Designed a rule config table to store rules.
  • Automated the evaluation and execution of rules with Java Rule Engine.
  • Achieved two of three strech goals beside base logic within 9 weeks internship.

• 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, Spring 2023, Fall 2023
  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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