Tianyi Zhang is a Tenure-Track Assistant Professor in Computer Science at Purdue University. Prior to that, he was a Postdoctoral Fellow at Harvard University. He worked with Dr. Elena Glassman to build interactive systems that help domain experts explore and make sense of large collections of complex data, e.g., health records and code corpora. He received his Ph.D. from UCLA in 2019 under the supervision of Dr. Miryung Kim.

I am looking for PhD, Master’s and undergraduate students with strong motivations to join my research group. If you are interested, please contact me with your CV.


My research is in the intersection of Human-Computer Interaction, Software Engineering, and AI. I am broadly interested in building interactive systems that (1) augment human intelligence by abstracting and rendering a previously impenetrable pile of data to distill data-driven insights and (2) augment machine intelligence by eliciting and incorporating domain expertise from humans. Most of my work is designed for people in the programming domain, including software developers, novice programmers, and computer end-users.

  • My work on code mining and visualization helps programmers make more informed decisions by unveiling what other programmers have and have not done in similar contexts in GitHub and Stack Overflow (ICSE 2018, CHI 2018, ICSE 2019, CHI 2020, CHI 2021).
  • My work on interactive and interpretable program synthesis helps novices and end-users better communicate their intent and guide a synthesizer with enriched feedback loops and interpretability (UIST 2020, CHI 2021).

Beyond that, I am collaborating with psychiatrists at Harvard Medical School and Massachusetts General Hospital to help them explore massive amounts of health records and develop data-driven insights about disease progression and treatment trajectories. I also work on research topics including code search (ICSE 2015, ICSE 2019, FSE 2020 Industry), test reuse (ICSE 2017), software debloating (FSE 2020), and empirical studies on deep learning engineering (ISSRE 2019, PerCom 2020).


  • [Jun. 2022] Our paper about interactive synthesis of tensor transformation programs was accepted to UIST 2022! Congratulations to Zhanhui, Tiger, Qiping, and Shangyin!
  • [Jun. 2022] Our paper about concept-annotated examples for library comparsion was accepted to UIST 2022! Congratulations to Litao!
  • [Jun. 2022] I received the Ross-Lynn Research Scholar Fund to support my research on knowledge acquisition from Stack Overflow. Thanks Purdue!
  • [Jun. 2022] I was selected as a Societal Impact Fellow at Purdue!
  • [Jun. 2022] Our paper about test reduction and prioritization for multi-module autonomous driving systems was accepted to ESEC/FSE 2022! Congratulations to Yao!
  • [Jun. 2022] Our paper about the common practices and needs of testing autonomous driving systems was accepted to ESEC/FSE 2022! Congratulations to Guannan!
  • [Mar. 2022] Our paper about a dataset of Stack Overflow post summaries was accepted to the data/tool showcase track at MSR 2022! Congratulations to Bonan and Yifeng!
  • [Feb. 2022] Our paper about the usability of GitHub Copilot was accepted to CHI 2022 Late-Breaking Work! Congratulations to Priyan!
  • [Jan. 2022] Our paper about AI-based CPS was accepted to ICSE-SEIP 2022! Congratulations to Jiayang and Deyun!
  • [Oct. 2021] Our paper about interactive visual analytics for cohort analysis received an Honorable Mention Award from VAHC 2021!
  • [Aug. 2021] Our paper about interactive visual analytics for cohort analysis was accepted to VAHC 2021!
  • [Aug. 2021] I will teach a graduate seminar class on Human-AI Interaction this fall! Check the syllabus here!
  • [Apr. 2021] I will join Purdue CS as a tenure-track assistant professor this fall!
  • [Apr. 2021] I was recognized as a Distinguished Reviewer for ACM TOSEM!
  • [Mar. 2021] Our CHI 2021 paper “Visualizing Examples of Deep Neural Networks at Scale” received the Best Paper Honorable Mention Award from SIGCHI!
  • [Dec. 2020] Our paper about interpretable program synthesis was accepted to CHI 2021!
  • [Dec. 2020] Our paper about visualizing the distribution of design choices such as model structures and hyperparameter settings in a corpus of DNNs was accepted to CHI 2021! Congratulations to Litao!
  • [Aug. 2020] Our demo paper on debloating modern java applications was accepted to FSE 2020 Demonstration Track! Congratulations to Konner and Mihir!
  • [Aug. 2020] Our paper about example generation was accepted to FSE 2020 Industry Track! Congratulations to Celeste!
  • [Jun. 2020] Our paper about interactive program synthesis was accepted to UIST 2020!