I earned my Ph.D. degree from MIT in June 2023, under the mentorship of Prof. Regina Barzilay. My doctoral research focused on the extraction and utilization of knowledge from structured documents (check out my thesis defense). My research interests primarily lie in efficient and robust natural language processing, information extraction from literature, and AI for science.

During my doctoral journey, I had the opportunity to intern at Google Research, IBM Research, and BAAI. Prior to my time at MIT, I pursued my undergraduate studies at Tsinghua University, where I collaborated with Prof. Jie Tang.

Publications

^{(* indicates equal contribution)}

• From Structured Document To Structured Knowledge
  Yujie Qian
  Ph.D. Thesis, Massachusetts Institute of Technology, 2023
  [thesis]

• Predictive Chemistry Augmented with Text Retrieval
  Yujie Qian, Zhening Li, Zhengkai Tu, Connor W Coley, Regina Barzilay
  EMNLP 2023
  [paper] [arxiv] [code&data]

• RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing
  Yujie Qian, Jiang Guo, Zhengkai Tu, Connor W Coley, Regina Barzilay
  Journal of Chemical Information and Modeling (JCIM) 2023
  [paper] [arxiv] [code] [demo]

• MolScribe: Robust Molecular Structure Recognition with Image-To-Graph Generation
  Yujie Qian, Jiang Guo, Zhengkai Tu, Zhening Li, Connor W Coley, Regina Barzilay
  Journal of Chemical Information and Modeling (JCIM) 2023
  [paper] [arxiv] [code] [demo]

• Multi-Vector Retrieval as Sparse Alignment
  Yujie Qian*, Jinhyuk Lee, Sai Meher Karthik Duddu, Zhuyun Dai, Siddhartha Brahma, Iftekhar Naim, Tao Lei, Vincent Y Zhao*
  [paper]

• GPT Understands, Too
  Xiao Liu*, Yanan Zheng*, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, Jie Tang
  AI Open 2023
  [paper] [arxiv] [code]

• GLM: General Language Model Pretraining with Autoregressive Blank Infilling
  Zhengxiao Du*, Yujie Qian*, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, Jie Tang
  ACL 2022
  [paper] [code]

• FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding
  Yanan Zheng*, Jing Zhou*, Yujie Qian, Ming Ding, Jian Li, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, Zhilin Yang
  ACL 2022
  [paper] [code]

• Towards Efficient Discovery of Green Synthesis Pathways with Monte Carlo Tree Search and Reinforcement Learning
  Xiaoxue Wang, Yujie Qian, Hanyu Gao, Connor W Coley, Yiming Mo, Regina Barzilay, Klavs F Jensen
  Chemical Science 2020
  [paper]

• GraphIE: A Graph-Based Framework for Information Extraction
  Yujie Qian, Enrico Santus, Zhijing Jin, Jiang Guo, Regina Barzilay
  NAACL 2019
  [paper] [code]

• Trust Relationship Prediction in Alibaba E-Commerce Platform
  Yukuo Cen, Jing Zhang, Gaofei Wang, Yujie Qian, Chuizheng Meng, Zonghong Dai, Hongxia Yang, Jie Tang
  IEEE Transaction on Knowledge and Data Engineering (TKDE) 2019
  [paper] [code]

• Weakly Learning to Match Experts in Online Community
  Yujie Qian, Jie Tang, Kan Wu
  IJCAI 2018
  [paper] [software]

• A Probabilistic Framework for Location Inference from Social Media
  Yujie Qian, Jie Tang, Zhilin Yang, Binxuan Huang, Wei Wei, Kathleen M Carley
  [paper] [code]

• Feature Engineering and Ensemble Modeling for Paper Acceptance Rank Prediction
  Yujie Qian*, Yinpeng Dong*, Ye Ma*, Hailong Jin, Juanzi Li
  KDD Cup Workshop 2016 (2nd place)
  [paper]

Services

• Conference Reviewer: ACL (2019, 2020, 2023), EMNLP (2019, 2020, 2023), NAACL 2019, ACL Rolling Review (2021, 2022), NeurIPS (2021, 2022, 2023), ICML (2020, 2022, 2023), ICLR (2021, 2023), KDD 2022, AAAI 2019
• Journal Reviewer: Journal of Chemical Information and Modeling, Journal of Cheminformatics, Nature Communications

Awards

• Outstanding Graduate, Tsinghua University, 2017
• Outstanding Bachelor’s Thesis, Tsinghua University, 2017
• 2nd Place, KDD Cup Competition, 2016
• Comprehensive Excellence Scholarship, Tsinghua University, 2016
• National Scholarship, Ministry of Education of China, 2015
• Gold Medal, ACM/ICPC Asia Regional (Xi’an), 2014
• Gold Medal, China National Olympiad in Informatics, 2012