I'm a first second third fourth year Ph.D. student at University of Notre Dame. I'm working in HCI@ND lab with advised by Ronald Metoyer. My broad research interests lie in HCI and NLP with an emphasis on text and visualization.
I design and develop interactive interfaces and tools to better mine and communicate stories in data.

I am doing an internship at Facebook Feed Integrity group in Seattle now. Previously, I interned at Fujitsu Laboratories of America (FLA) during 2018 summer at sunnyvale, where I worked on API Learning project. I also led seven volunteer groups at BUPT where we worked at various places and events such as Beijing Marathon, Beijing Olympic Park, and a boarding school for migrant kids.

Here is my Resume and email.

  • June.2019 - An co-authored ASONAM paper with Yue Zhang got accepted!
  • June.2019 - Start Facebook internship, catch me up in seattle!
  • June.2019 - Presented coupling paper in EuroVis'19
  • May.2019 - Served as a Student Volunteer in EuroVis!
  • May.2019 - Passed Ph.D proposal and earned a master!
  • March.2019 - One EuroVis paper got accepted, going to Portugal!
  • Feb.2019 - Will join Facebook as a summer intern, going to Seattle!
  • Dec.2018 - One CHI paper got accepted, going to England!
  • July.2018 - Oct.2018 Interned at Fujitsu Laboratories of America (FLA)


∙ Linking and Layout: Exploring the Integration of Text and Visualization in Storytelling

  Qiyu Zhi, Alvitta Ottley, Ronald Metoyer

  21st EG/VGTC Conference on Visualization (EuroVis’19)

coupling paper teaser
We seek to understand two text visualization integration forms: (i) different text and visualization spatial arrangements (layout), namely, vertical and slideshow; and (ii) interactive linking of text and visualization (linking). Through a crowdsourced study with 180 participants, we measured the effect of layout and linking on the degree to which users engage with the story (user engagement), their understanding of the story content (comprehension), and their ability to recall the story information (recall).

  pdf  I study website I preview video

∙ GameViews: Understanding and Supporting Data-driven Sports Storytelling

  Qiyu Zhi, Suwen Lin, Poorna Talkad Sukumar, Ronald Metoyer

  CHI’19 honorable mention, top 5% of all the papers

  Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

gameviews paper teaser
In this paper, we explore how these stakeholders construct data-driven sports stories. we implemented two exploratory prototypes: GameViews-Writers for sportswriters to quickly extract key game information and GameViews-Fans to support a real-time data-driven game- viewing experience for fans. We report insights from two user studies conducted with four professional sportswriters and eight sports fans, respectively.

  pdf I slides I preview video I video I GameViews-Writers Demo

∙ VisPod: Content-Based Audio Visual Navigation

  Qiyu Zhi, Suwen Lin, Shuai He, Ronald Metoyer, Nitesh V Chawla

  23rd International Conference on Intelligent User Interfaces (IUI'18) demo

vispod paper teaser
We present VisPod, a visual audio player that visually displays the main topics and keywords extracted from the transcript. VisPod supports (1) audio content browsing, (2) topic-based and keyword-based navigation, (3) communication of transcript and speaker information in real time, and (4) content-based query.

  pdf I Video I Demo

∙ Coupling Story to Visualization: Using Textual Analysis as a Bridge Between Data and Interpretation

  Ronald Metoyer, Qiyu Zhi, Bart Janczuk, Walter Scheirer

  23rd International Conference on Intelligent User Interfaces (IUI'18)

nba story and visualization paper teaser
We propose an approach to automatically integrate text and vi- sualization elements. We leverage natural language processing, quantitative narrative analysis, and information visualization to (1) automatically extract narrative components (who, what, when, where) from data-rich stories, and (2) integrate the supporting data evidence with the text to develop a narrative visualization.

  pdf I slides I Video I Demo

∙ Recognizing Handwritten Source Code

  Qiyu Zhi, Ronald Metoyer

  Proceedings of Graphics Interface 2017 (GI'17)

handwriting code recognition paper teaser
we explore handwriting recognition for source code. We collect and make publicly available a dataset of handwritten Python code samples from 15 participants. We present an approach to improve the recognition accuracy by aug- menting a handwriting recognizer with the programming language grammar rules. Our experiment on the collected dataset shows an 8.6% word error rate and a 3.6% character error rate which outperforms standard handwriting recognition systems and compares favorably to typing source code on virtual keyboards.

  PDF I Slides I Website

∙ Docio: Documenting API Input/Output Examples

  Jiang, S., Armaly, A., McMillan, C., Zhi, Q., Metoyer, R.

  Proceedings of the 25th IEEE International Conference on Program Comprehension, Tool Demo Track (ICPC'17)

docio paper teaser
We demonstrate a prototype toolset we built to generate I/O examples. our tool logs I/O values when API functions are executed, for example in running test suites. Then, our tool puts I/O values into API documents as I/O examples. our tool has three programs: 1) funcWatch, which collects I/O values when API developers run test suites, 2) ioSelect, which selects one I/O example from a set of I/O values, and 3) ioPresent, which embeds the I/O examples into documents.


∙ An combined sentiment classification system for SIGHAN-8

  Qiuchi Li, Qiyu Zhi, Miao Li

  Eighth SIGHAN Workshop on Chinese Language Processing at the Association for Computational Linguistics (ACL-IJCNLP'15)

sighan paper teaser
This paper describes our system (MSIIP THU) used for Topic-Based Chinese Message Polarity Classification Task in SIGHAN-8. In our system, a lexiconbased classifier and a statistical machine learning-based classifier are built up, followed by a linear combination of these two models. The overall performance of the proposed framework ranks in the middle of all terms participating in the task.