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About Us

Our group’s research interests broadly lie in Natural Language Processing, Data Mining, and Artificial Intelligence, with emphasis on various kinds of question answering systems, natural language interfaces, network analysis, and human behavior understanding.

We aim to develop advanced computational frameworks that enable users to easily query big data, write compute programs, collaborate with each other, and acquire knowledge for decision making in various domains such as healthcare, education, and business. Please check out the code/data we have released!

Group News

  • 12/2020: Congratulations to Xinliang (Frederick) Zhang for being awarded the highly competitive CRA Undergraduate Research Award (Honorable Mention)!
  • 11/2020: Congratulations to Ziyu Yao for being awarded the highly competitive Presidential Fellowship from OSU! (“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.”)!
  • 11/2020: My awesome Ph.D. student Jie Zhao has successfully defended his thesis! He will be our first Ph.D. graduate and will join Amazon Alexa Shopping team next!
  • 10/2020: Congratulations to Ziyu Yao for being selected into Rising Stars 2020!
  • 02-03/2020: We are thrilled to receive NSF CAREER award, Google Faculty Research Award, Lumley Research Award. 
  • 03/2020: Ph.D. student Ziyu Yao, Zhen Wang, and Xiang Deng will intern at Carnegie Mellon University, NEC labs, and Microsoft Research this summer. Congratulations!
  • 11/2019: Undergraduate research assistant Frederick Zhang was awarded a scholarship by CoE towards “Research Distinction” or “Honors Research Distinction”. Congratulations!
  • 10/2019: Our funded research project is selected to highlight by ARO and CoE@OSU.
  • 10/2019: Together with Ahmed Hassan Awadallah, Wen-tau Yih, and Yu Su, we are going to organize a workshop on Natural Language Interfaces: Challenges and Promises in ACL 2020! Please stay tuned.
  • 09/2019: Our work on biomedical network embedding (a systematic comparison of 11 advanced graph embedding methods for 4 biomedical prediction tasks) was accepted to Bioinformatics. Resources are available here!
  • 08/2019: A unified, principled formulation on Interactive Semantic Parsing, titled with “Model-based Interactive Semantic Parsing: A Unified Formulation and A Text-to-SQL Case Study”, was accepted to EMNLP’19 (long paper). Resources are available here!
  • 08/2019: Using Web Tables to improve the classic relation extraction task, titled with “Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction”, was accepted to EMNLP’19 (long paper). Resources are available here!
  • 05/2019: Our work on “Reinforced Dynamic Reasoning for Conversational Question Generation” was accepted to ACL’19 (long paper). Resources are available here!
  • 04/2019: Our work on “SurfCon: Synonym Discovery on Privacy-Aware Clinical Data” was accepted to SIGKDD’19 (research track, acceptance rate: ~14.2%, oral presentation). Resources are now available!
  • 04/2019: Our work on “Riker: Mining Rich Keyword Representations for Interpretable Product Question Answering” was accepted to SIGKDD’19 (research track, acceptance rate: ~14.2%, poster presentation). Resources are now available here!
  • 01/2019: Our work on “CoaCor: Code Annotation for Code Retrieval with Reinforcement Learning” was accepted to WWW’19 (acceptance rate: 18%, Oral + Poster). We explored using the code retrieval task performance to guide the learning of a code annotator (i.e., machine-machine collaboration between code retrieval and code annotation/summarization). Resources are now available here!
  • 11/2018: Our recent work on “Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning,”was accepted to AAAI’19 (acceptance rate: 16.2%)! Please check out our interactive semantic parser here!
  • 11/2018: Our work on “Answer Identification from Product Reviews for User Questions by Multi-task Attentive Networks” was accepted to AAAI’19 (acceptance rate: 16.2%)!
  • 07/2018: Our paper “A Comprehensive Study of StaQC for Deep Code Summarization,” an extension study of our <natural language question, code snippet> dataset mined from Stack Overflow in WWW 2018, was accepted in KDD 2018 Deep Learning Day (SPOTLIGHT)!
  • 12/2017: Work by Ziyu Yao on mining large-scale high-quality <natural language question, code snippet> pairs got accepted in WWW 2018. This is our very first work along the research line to facilitate Computer Science for All. Please check our datasets, code, and paper here!
  • 06/2017: Work by Jie Zhao on answer triggering got accepted in EMNLP 2017. Code is now available here. Please let Jie or me know if you have any suggestions!
  • 01/2017: Got tired of simple question answering? Try out our characteristic-rich question set! Any suggestions are welcome.
  • 12/2016: Our paper “Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts” was accepted in WSDM 2017
  • 09/2016: Our paper “An Augmented LSTM Framework to Construct Medical Self-diagnosis Android” was accepted in ICDM 2016
  • 07/2016: Our paper “On Generating Characteristic-rich Question Sets for QA Evaluation” was accepted in EMNLP 2016

Webpage construction credit to Ruoqi Liu