• CV
  • Publications
  • Experience
  • Awards
  • Teaching
  • Service

About me

I am a final-year Ph.D. student in Department of Computer Science and Engineering (CSE), The Ohio State University (OSU), advised by Prof. Huan Sun. Before joining OSU, I received my B.E. in Communication Engineering from Beijing Univerity of Posts and Telecommunications (BUPT) in 2015. I have spent time interning in Microsoft Semantic Machines, Carnegie Mellon University, Microsoft Research, Fujitsu Lab of America, and Tsinghua University. I work in natural language processing (NLP) and artificial intelligence (AI), particularly building natural language interfaces that can reliably assist humans in knowledge acquisition and task completion. Some specific topics include:

  • Language and code: I seek to build natural language interfaces that allow humans to communicate with computers/machines easily. This requires modeling natural language, programming language, and their interplay. Applications of this research include semantic parsing, general-purpose code generation/search/summarization, and many other software engineering problems.
  • Human-AI interaction: I explore how machine learning systems can proactively collaborate with and learn from humans during decision making, as demonstrated in the setting of interactive semantic parsing. As the foundation, I also work on facilitating the dialogue between humans and AI systems.
  • Efficient NLP/AI: I study building machine learning models with limited supervision, especially for low-resource domains (e.g., healthcare).

I will be joining the CS Department at George Mason University as an Assistant Professor in Fall 2021! I am looking for highly self-motivated students. If you are interested in doing NLP/AI/machine learning/data mining research with me, see how to reach out!

Check out our workshop on Natural Language Processing for Programming (NLP4Prog), co-located with ACL 2021!


  • 05/2021: I will be interning in Microsoft Semantic Machines in this summer (virtually)!
  • 04/2021: I am awarded the Graduate Student Research Award by OSU, CSE department!
  • 01/2021: One paper accepted to ICLR'21! Thanks to my collaborators at CMU!
  • 11/2020: Super honored to receive the Presidential Fellowship from OSU Graduate School! ("The Presidential Fellowship is the most prestigious award given by the Graduate School. Recipients of this award embody the highest standards of scholarship in the full range of Ohio State's graduate programs.")
  • 10/2020: Honored to be selected to the Rising Stars in EECS workshop (hosted by UC Berkeley this year)!
  • 09/2020: Invited poster at Microsoft Research AI Breakthroughs Workshop (virtually).
  • 08/2020: Invited talk at VMware, Beijing (virtually).
  • 05/2020: Excited to start summer internship at CMU Language Technologies Institute with Prof. Graham Neubig!
  • 08/2019: Our work on a principled Interactive Semantic Parsing framework is accepted to EMNLP! See you in Hong Kong!
  • 07/2019: Attended ACL'19 in Florence.
  • 07/2019: Talk at ETH Zurich: "Towards Building Interactive and Collaborative Natural Language Interfaces".
  • 05/2019: One paper accepted to ACL'19 (my first ACL paper ever). Congrats to my collaborator Boyuan!
  • 01/2019: Our work exploring machine collaborations between Code Annotation and Code Retrieval is accepted by WWW'19!
  • 10/2018: We built an Interactive Semantic Parser: talk to your parser to resolve NL ambiguities (accepted by AAAI'19)!
  • 08/2018: To know more about StaQC? Check out our work "A Comprehensive Study of StaQC for Deep Code Summarization" (accepted by SIGKDD'18 Deep Learning Day)!
  • 05/2018: Feeling thrilled to start internship at Microsoft Research @ Redmond this summer!!
  • 04/2018: Attended WWW 2018 conference @ Lyon, France and present our work "StaQC: A Systematically Mined Question-Code Dataset from Stack Overflow". Check out the slides and quick StaQC examples!
  • 04/2018: Attended CRA Grad Cohort Workshop for Women (CRA-W) @ San Francisco.
  • 09/2017: Gave a talk about "Mining Code Answers to Natural Language Questions" at OSU CSE AI seminar.


  1. Ziyu Yao, Frank F. Xu, Pengcheng Yin, Huan Sun, Graham Neubig, "Learning Structural Edits via Incremental Tree Transformations", ICLR 2021. [Paper][Code]
  2. Ziyu Yao, Yiqi Tang, Scott Wen-tau Yih, Huan Sun, Yu Su, "An Imitation Game for Learning Semantic Parsers from User Interaction", EMNLP 2020. [Paper][Code][Slides]
  3. Xiang Yue, Xinliang Frederick Zhang, Ziyu Yao, Simon Lin, Huan Sun, "CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answering", ML4Health at NeurIPS 2020. [Paper][Code]
  4. Ziyu Yao, Yu Su, Huan Sun, Scott Wen-tau Yih, "Model-based Interactive Semantic Parsing: A Unified Formulation and A Text-to-SQL Case Study", EMNLP 2019. [Paper][Code]
  5. Boyuan Pan, Hao Li, Ziyu Yao, Deng Cai, Huan Sun, "Reinforced Dynamic Reasoning for Conversational Question Generation", ACL 2019. [Paper][Code]
  6. Ziyu Yao, Jayavardhan Reddy Peddamail, Huan Sun, "CoaCor: Code Annotation for Code Retrieval with Reinforcement Learning", The Web Conference (WWW) 2019. (Acceptance rate: 18%) [Paper][Code]
  7. Ziyu Yao, Xiujun Li, Jianfeng Gao, Brian Sadler, Huan Sun, "Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning", AAAI 2019. (Acceptance rate: 16.2%, SPOTLIGHT) [Paper][Appendix][Code][Slides][Poster]
  8. Ziyu Yao, Yizhe Zhang, Xiujun Li, Jianfeng Gao, Michel Galley, Chris Brockett, Huan Sun, Bill Dolan, "IEC: Towards Interest-Eliciting Neural Conversational Agents", Manuscript 2019. [Paper]
  9. Jayavardhan Reddy Peddamail, Ziyu Yao, Zhen Wang, Huan Sun, "A Comprehensive Study of StaQC for Deep Code Summarization", KDD 2018 Deep Learning Day. [Paper][*Update]
  10. Ziyu Yao, Daniel S. Weld, Wei-Peng Chen, Huan Sun, "StaQC: A Systematically Mined Question-Code Dataset from Stack Overflow", The Web Conference (WWW) 2018. (Acceptance rate: 14.8%) [Paper][Slides][Data&Code][Quick examples]
  11. Li Zhao, Minlie Huang, Ziyu Yao, Rongwei Su, Yingying Jiang, Xiaoyan Zhu. "Semi-Supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-Level Statistical Constraint", AAAI 2016. [Paper]
  12. Ziyu Yao, Shouzhong Tu, Minlie Huang, Xiaoyan Zhu. "A Semi-Supervised Method for Filtering Chinese Spam Tweets". Journal of Chinese Information Processing. 2016, 30(5):176-186. [Paper]



  • Graduate Student Research Award, OSU, CSE, 2021.
  • Presidential Fellowship, OSU, 2020
  • Selected to Rising Stars in EECS, UC Berkeley, 2020.
  • Graduate Students Poster Award (Honorable Mention), OSU, 2020.
  • NSF Student Travel Award for The Web Conference 2019 (WWW'19).
  • Graduate Students Poster Award (Honorable Mention), OSU, 2019.
  • Travel Grant for CRA-W Graduate Cohort for Women, San Francisco, 2018.
  • Beijing Outstanding Graduate Award, Beijing, 2015.
  • First-class Scholarship (top 3%), BUPT, 2012, 2014.
  • Second-class Scholarship (top 5%), BUPT, 2013.



  • Organizing Committee: NLP4Prog at ACL2021
  • Program Committee/Reviewer: MSR 2021, NAACL 2021, AACL-IJNLP 2020, EMNLP 2020, EMNLP-IntEx-SemPar 2020, NLPCC 2020, AAAI 2020, ACL-NLI 2020, CoNLL 2019, ACL SRW 2019, EMNLP 2018.
  • External/Secondary Reviewer: KDD 2020, ACL 2020, KDD 2019, KDDFeed Workshop 2019, NAACL 2019, ICDM 2018, ACL 2018, KDD 2017, WWW 2017, CIKM 2016, ICDM 2016.

Student Recruiting

For prospective students:

  • For prospective PhD students: I am looking for highly self-motivated PhD students with funding support. If you are interested in working with me, please email me with your CV, transcript, a description of your research interests, future career plan (e.g., research scientist or faculty), and your representative work (e.g., publication, thesis, research project). Please also let me know which semester (e.g., Spring/Fall 2022) you plan to apply for PhD. Please start your email subject with "[Prospective PhD Student - ${Your_Application_Semester}]".
  • For other interested students (at or outside GMU): I am also interested in advising passionate undergraduate and master students, especially if you plan to apply for graduate schools. I consider PhD students from other institutes for long-term collaboration as well. Funding can be provided to students with great records and performance. If you are interested in working with me, please email me with your CV, transcript, a description of your research interests, future plan after graduation (e.g., will you apply for Master or PhD), and your experience related to NLP/AI (if any). Please start your email subject with "[Prospective Intern Student]".

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