Q. Vera Liao

4.4k total citations · 1 hit paper
62 papers, 1.8k citations indexed

About

Q. Vera Liao is a scholar working on Artificial Intelligence, Safety Research and Sociology and Political Science. According to data from OpenAlex, Q. Vera Liao has authored 62 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 21 papers in Safety Research and 13 papers in Sociology and Political Science. Recurrent topics in Q. Vera Liao's work include Ethics and Social Impacts of AI (21 papers), Explainable Artificial Intelligence (XAI) (21 papers) and Artificial Intelligence in Healthcare and Education (10 papers). Q. Vera Liao is often cited by papers focused on Ethics and Social Impacts of AI (21 papers), Explainable Artificial Intelligence (XAI) (21 papers) and Artificial Intelligence in Healthcare and Education (10 papers). Q. Vera Liao collaborates with scholars based in United States, Canada and China. Q. Vera Liao's co-authors include Wai‐Tat Fu, Justin D. Weisz, Mohit Jain, Michael Müller, Zahra Ashktorab, Yunfeng Zhang, Jennifer Wortman Vaughan, Rachel Bellamy, Stephanie Houde and Casey Dugan and has published in prestigious journals such as Journal of Machine Learning Research, Cognitive Science and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Q. Vera Liao

61 papers receiving 1.7k citations

Hit Papers

1 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Investigating Explainability of Generative AI for Code through Scenario-based Design

2022 116 citations Q. Vera Liao, Michael Müller et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Q. Vera Liao United States	24	951	397	301	255	201	62	1.8k
Mihaela Vorvoreanu United States	15	554 0.6×	256 0.6×	275 0.9×	233 0.9×	217 1.1×	47	1.7k
Besmira Nushi United States	13	1.0k 1.1×	501 1.3×	132 0.4×	382 1.5×	315 1.6×	19	2.1k
Jina Suh United States	19	1.1k 1.1×	352 0.9×	203 0.7×	207 0.8×	292 1.5×	58	2.2k
Dakuo Wang United States	28	1.0k 1.1×	310 0.8×	225 0.7×	410 1.6×	305 1.5×	95	2.4k
Adam Fourney United States	18	636 0.7×	252 0.6×	159 0.5×	264 1.0×	210 1.0×	54	1.5k
Carrie J. Cai United States	20	1.2k 1.2×	331 0.8×	179 0.6×	308 1.2×	209 1.0×	38	2.5k
Haiyi Zhu United States	24	537 0.6×	519 1.3×	541 1.8×	266 1.0×	143 0.7×	84	1.8k
Todd Kulesza United States	11	1.0k 1.1×	314 0.8×	92 0.3×	194 0.8×	121 0.6×	18	1.6k
Stefan Morana Germany	19	844 0.9×	185 0.5×	374 1.2×	162 0.6×	403 2.0×	57	1.7k

Countries citing papers authored by Q. Vera Liao

Since Specialization

Citations

This map shows the geographic impact of Q. Vera Liao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Q. Vera Liao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Q. Vera Liao more than expected).

Fields of papers citing papers by Q. Vera Liao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Q. Vera Liao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Q. Vera Liao. The network helps show where Q. Vera Liao may publish in the future.

Co-authorship network of co-authors of Q. Vera Liao

This figure shows the co-authorship network connecting the top 25 collaborators of Q. Vera Liao. A scholar is included among the top collaborators of Q. Vera Liao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Q. Vera Liao. Q. Vera Liao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Peng, Yuyang, Q. Vera Liao, Bohan Chen, et al.. (2025). BizGen: Advancing Article-level Visual Text Rendering for Infographics Generation. 23615–23624. 1 indexed citations

2.

Liao, Q. Vera, et al.. (2025). Canvil: Designerly Adaptation for LLM-Powered User Experiences. 1–22. 1 indexed citations

3.

Liao, Q. Vera, et al.. (2025). As Confidence Aligns: Understanding the Effect of AI Confidence on Human Self-confidence in Human-AI Decision Making. 1–16. 4 indexed citations

4.

Li, Haotian, et al.. (2025). Why is AI Not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling. IEEE Transactions on Visualization and Computer Graphics. 31(10). 7598–7613. 1 indexed citations

5.

Ehsan, Upol, Q. Vera Liao, Samir Passi, Mark Riedl, & Hal Daumé. (2024). Seamful XAI: Operationalizing Seamful Design in Explainable AI. Proceedings of the ACM on Human-Computer Interaction. 8(CSCW1). 1–29. 5 indexed citations

6.

Ehsan, Upol, Samir Passi, Q. Vera Liao, et al.. (2024). The Who in XAI: How AI Background Shapes Perceptions of AI Explanations. 1–32. 26 indexed citations

7.

Bansal, Gagan, et al.. (2024). Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions. ACM Transactions on Computer-Human Interaction. 4 indexed citations

8.

Liao, Q. Vera & Long He. (2024). Lightweight key generation circuits for CRYSTALS-Kyber. 209–213. 1 indexed citations

9.

Xiao, Ziang, Michelle S. Lam, Motahhare Eslami, et al.. (2024). Human-Centered Evaluation and Auditing of Language Models. 1–6. 11 indexed citations

10.

Lai, Vivian, Chacha Chen, Alison Smith, Q. Vera Liao, & Chenhao Tan. (2023). Towards a Science of Human-AI Decision Making: An Overview of Design Space in Empirical Human-Subject Studies. 1369–1385. 61 indexed citations

11.

Müller, Michael, Lydia B. Chilton, Anna Kantosalo, et al.. (2023). GenAICHI 2023: Generative AI and HCI at CHI 2023. 1–7. 16 indexed citations

12.

Kulkarni, Chinmay, Tongshuang Wu, Kenneth Holstein, et al.. (2023). LLMs and the Infrastructure of CSCW. 408–410. 1 indexed citations

13.

Russell, Daniel M., Q. Vera Liao, Chinmay Kulkarni, Elena L. Glassman, & Nikolas Martelaro. (2023). Human-Computer Interaction and AI. 1–3. 1 indexed citations

14.

Lai, Vivian, et al.. (2023). Selective Explanations: Leveraging Human Input to Align Explainable AI. Proceedings of the ACM on Human-Computer Interaction. 7(CSCW2). 1–35. 19 indexed citations

15.

Fan, Mingming, et al.. (2022). Human-AI Collaboration for UX Evaluation: Effects of Explanation and Synchronization. Proceedings of the ACM on Human-Computer Interaction. 6(CSCW1). 1–32. 32 indexed citations

16.

Arya, Vijay, Rachel Bellamy, Pin‐Yu Chen, et al.. (2020). AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. Journal of Machine Learning Research. 21(130). 1–6. 37 indexed citations

17.

Arya, Vijay, Rachel Bellamy, Pin‐Yu Chen, et al.. (2020). AI Explainability 360 Toolkit. 376–379. 19 indexed citations

18.

Liao, Q. Vera, Wai‐Tat Fu, & Markus Strohmaier. (2016). #Snowden. MADOC (University of Mannheim). 3352–3363. 9 indexed citations

19.

Liao, Q. Vera, Victoria Bellotti, & G. Michael Youngblood. (2016). Improvising Harmony. 2. 159–169. 4 indexed citations

20.

Liao, Q. Vera & Wai‐Tat Fu. (2011). Effects of Aging and Individual Differences on Credibility Judgment of Online Health Information. Cognitive Science. 33(33). 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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