Biography

Hello! This is Jianing “Jed” Yang (杨佳宁). I am a first-year Ph.D. student in Computer Science and Engineering at University of Michigan. I am a member of SLED lab, advised by Prof. Joyce Chai. I do research on natural language understanding, particularly those grounded to robots and physical world. I am interested in building NLP algorithms and systems that enables human-robot communication and collaboration through natural language.

Before joining UMich, I obtained my Master’s in Machine Learning from Carnegie Mellon University where I worked with Prof. Louis-Philippe Morency and Prof. Matt Gormley on Multimodal Natural Language Understanding, Dataset Bias Analysis, and Machine Learning. I got my Bachelor’s in Computer Science from Georgia Tech.

Before I delved fully into research, I had worked as a Software Development Engineer at  Amazon Web Services, intern and full-time.

Outside of work, you will find me skiing/cooking/baking/photographing.

Interests
  • Robot NLP
  • Interactive Task Learning
  • Multimodal Machine Learning
Education
  • Ph.D. in Computer Science and Engineering, 2025 (expected)

    University of Michigan

  • M.S. in Machine Learning, 2020

    Carnegie Mellon University

  • B.S. in Computer Science, 2018

    Georgia Institute of Technology

News

  • [Aug. 2021] I started my Ph.D. at University of Michigan!
  • [Mar. 2021] 🎉 Our paper MTAG was accepted to NAACL 2021! The code is available here.
  • [Dec. 2020] 🎉 I finished my Master’s and graduated from CMU! 🎉 I will continue to stay as a Research Assistant at CMU’s MultiComp lab until my PhD starts in Fall 2021.
  • [Nov. 2020] I’m attending EMNLP 2020 virtually. Happy to chat there!
  • [July 2020] I’m attending ACL 2020 virtually. Check out our video presentation on QA bias analysis!

Academia Experience

 
 
 
 
 
CMU MultiComp Lab
Graduate Researcher
Aug 2019 – Aug 2021 Pittsburgh, PA
  • Designed a graph neural network (GNN) algorithm for fusion of multimodal temporal data
  • Analyzed language artifacts in video QA datasets
  • Built pipeline for multimodal question answering about social situations
  • Coordinated annotation of dataset
  • Advisor: Prof. Louis-Philippe Morency
 
 
 
 
 
CMU ML/NLP Research Group
Graduate Researcher
Aug 2019 – Aug 2021 Pittsburgh, PA
  • Designed new algorithms to improve scheduled sampling training for seq2seq models
  • Validated effectiveness of the method on NER, Machine Translation and Text Summarization tasks
  • Advisor: Prof. Matt Gormley
 
 
 
 
 
Georgia Tech Machine Learning for Healthcare (SunLab)
Undergraduate Research Assistant
Aug 2017 – Dec 2018 Atlanta, GA
  • Built cardiac arrest prediction pipeline using multimodal temporal data collected from ICU patients
  • Advisor: Prof. Jimeng Sun

Industry Experience

 
 
 
 
 
Amazon
Software Development Engineer
Amazon
Feb 2019 – Aug 2019 Seattle, WA
  • Led a load balancing project to decrease system latency from 20 seconds to milliseconds.

  • Received award for technical soundness and leadership at 2019 Q2 AWS Identity organization meeting.

 
 
 
 
 
Amazon
Software Development Engineer Intern
Amazon
May 2018 – Jul 2018 Seattle, WA
Extended AWS Microsoft Active Directory to support multiple Availability Zones to increase service availability
 
 
 
 
 
Amazon
Software Development Engineer Intern
Amazon
May 2017 – Jul 2017 Seattle, WA
Designed and implemented a backup mechanism for AWS Simple Active Directory to enhance system reliability

Contact