Yuqi Tang
Papers
1
Total Citations
19
H-Index
1
About
Yuqi Tang is a researcher at the forefront of human-computer interaction and explainable AI, with a focus on bridging the gap between complex algorithmic systems and non-expert users. Their most-cited work, "XAlgo: a Design Probe of Explaining Algorithms’ Internal States via Question-Answering" (2021), has garnered 19 citations and introduces a novel interactive approach that uses question-answering to demystify deterministic algorithms. This contribution challenges traditional explainable representations by prioritizing user-driven exploration, enabling non-experts to query and understand algorithmic internal states in an intuitive, conversational manner. Tang’s research is pivotal in making algorithms more transparent and accessible, addressing critical issues of trust and usability in everyday technology. By designing probes that empower users to engage with algorithmic logic, their work has implications for education, public policy, and user-centered system design. Tang’s innovative methodology stands out for its focus on real-world comprehension, marking them as a key voice in the movement toward inclusive and explainable AI.
Research Focus
Key Achievements
Top Papers
- 1