Jianmo Ni

Welcome to my personal website!
I am a NLP researcher/engineer at Google. I graduated from the PhD program at University of California San Diego, advised by Prof. Julian McAuley.
I received my B.E. from Shanghai Jiao Tong University, M.E. from the Joint Waseda University-Shanghai Jiao Tong University Master Program.
My research interests include Natural Language Processing and Recommender System.

[2022/04] We open sourced T5X Retrieval, which is a JAX-based framework to build neural retrieval models.

[2020/08] I became a Noogler.

[2020/05] I successfully defended my thesis!

[2020/03] We provide colabs to help you parse metadata, find products and align product reviews. [colab notebook1] [colab notebook2]

[2019/09] We have released a new version of the Amazon review dataset [link] which includes more and newer reviews (i.e. reviews in the range of 2014~2018)! Welcome to do interesting research on this up-to-date large-scale dataset!

[2019/03] We have released the Endomondo workout dataset [link] that contains user sport records. The dataset includes multiple sources of sequential sensor data such as heart rate, speed, GPS as well as sport type, user gender and weather condition (i.e. temperature, humidity). Welcome to conduct personalization, fitness-aware, on-edge machine learning research on this dataset!

• Sentence-t5: Scalable sentence encoders from pre-trained text-to-text models
  Jianmo Ni, Gustavo Hernández Ábrego, Noah Constant, Ji Ma, Keith B Hall, Daniel Cer, Yinfei Yang.
  Findings of ACL 2022.
  [Paper] [Code]
  
• Learning visual-semantic embeddings for reporting abnormal findings on chest X-rays
  Jianmo Ni, Chun-Nan Hsu, Amilcare Gentili, Julian McAuley.
  Findings of EMNLP 2020.
  [Paper] [Code]
  
• Interview: Large-scale modeling of media dialog with discourse patterns and knowledge grounding
  Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley.
  Empirical Methods in Natural Language Processing (EMNLP) 2020.
  [Paper] [Code]
  
• Addressing Marketing Bias in Product Recommendations
  Mengting Wan, Jianmo Ni, Rishabh Misra, Julian McAuley.
  International Conference on Web Search and Data Mining (WSDM) 2020.
  [Paper] [Code]
  
• Justifying Recommendations using Distantly-Labeled Reviews and Fined-grained Aspects
  Jianmo Ni, Jiacheng Li, Julian McAuley.
  Empirical Methods in Natural Language Processing (EMNLP) 2019.
  [Paper] [Slides] [Code]
  
• Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation
  Liliang Ren, Jianmo Ni, Julian McAuley.
  Empirical Methods in Natural Language Processing (EMNLP) 2019.
  [Paper] [Code]
  
• Generating Personalized Recipes from Historical User Preferences
  Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley.
  Empirical Methods in Natural Language Processing (EMNLP) 2019.
  [Paper] [Code]
  
• Learning To Attend On Essential Terms: An Enhanced Retriever-Reader Model For Open-domain Question Answering
  Jianmo Ni, Chenguang Zhu, Weizhu Chen, Julian McAuley.
  Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) 2019.
  [Paper] [Code]
  Media: LinkedIn
• Modeling Heart Rate and Activity Data for Personalized Fitness Recommendation
  Jianmo Ni, Larry Muhlstein, Julian McAuley.
  The Web Conference (WWW) 2019.
  [Paper] [Code] [Data]
  Media: Nvidia, UCSD News, MobiHealth News, Science Times, Scitech Europa
• Personalized Review Generation By Expanding Phrases And Attending On Aspect-aware Representations
  Jianmo Ni, Julian McAuley.
  Annual Meeting of the Association for Computational Linguistics (ACL) 2018.
  [Paper] [Code]
• Estimating Reactions And Recommending Products With Generative Models Of Reviews
  Jianmo, Zachary Lipton, Sharad Vikram, Julian McAuley.
  International Joint Conference on Natural Language Processing (IJCNLP) 2017.
  [Paper] [Code]

• Research Intern, Google AI, Mountain View, CA, US.
  June 2019 - Sep 2019.
• Research Intern, Microsoft Research, Redmond, WA, US.
  Mentor: Chenguang Zhu , Weizhu Chen
  June 2018 - Sep 2018.
• Research Intern, WeChat AI, Tencent, Palo Alto, CA, US.
  Mentor: Cheng Niu
  Jun 2017 - Sep 2017.

• Teaching Assistant
  • CSE-291 Trends in Recommender Systems and Human Behavioral Modeling, Fall 2017.

• Reviewer
  • Journal: IEEE-TKDE, IEEE-TSG
  • Conference: NeurIPS 19', ICML 19'-20', ACL 19'-20', EMNLP 19'-20', NAACL 19', AAAI 20', SDM 19', INLG 19'-20', RecNLP 19'
• PC Member
  • ACL 19'-20', EMNLP 19'-20', NAACL 19', SDM 19', RecNLP 19'