Jie Yang

schoolDelft University of Technologybar_chart#4003 Global Rank

Total Papers

HCI Rank

#4003

Research Areas

Years Active

Recent Publications

``It Is a Moving Process'': Understanding the Evolution of Explainability Needs of Clinicians in Pulmonary Medicine

Clinicians increasingly pay attention to Artificial Intelligence (AI) to improve the quality and timeliness of their services. There are converging opinions on the need for Explainable AI (XAI) in healthcare. However, prior work considers explanations as stationary entities with no account for the temporal dynamics of…

CHI '233rd AuthorExplainable AI (XAI) +2

Faulty or Ready? Handling Failures in Deep-Learning Computer Vision Models until Deployment: A Study of Practices, Challenges, and Needs

Handling failures in computer vision systems that rely on deep learning models remains a challenge. While an increasing number of methods for bug identification and correction are proposed, little is known about how practitioners actually search for failures in these models. We perform an empirical study to understan…

CHI '224th AuthorExplainable AI (XAI) +1

How can Explainability Methods be Used to Support Bug Identification in Computer Vision Models?

Deep learning models for image classification suffer from dangerous issues often discovered after deployment. The process of identifying bugs that cause these issues remains limited and understudied. Especially, explainability methods are often presented as obvious tools for bug identification. Yet, the current practi…

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