Yanying Chen

Papers

Total Citations

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About

Yanying Chen’s research lies at the intersection of computer vision, affective computing, and intelligent systems, with a focus on how machines can interpret and respond to human context and emotion. In her highly cited 2015 work on the Assistive Image Comment Robot, Chen introduced a novel mid-level concept-based representation to predict viewers’ affective responses to images posted on social media. This framework moved beyond low-level features to capture the intended emotional impact of an image, offering a practical system for automated, context-aware commentary. Building on this, her 2018 paper on ContextualNet leveraged Long Short-Term Memory (LSTM) networks to exploit contextual information for improved image-based localization. By integrating sequential spatial cues into convolutional neural networks, Chen addressed key limitations in single-image localization, enhancing accuracy without increasing data dimensionality. With over 36 combined citations, her contributions demonstrate a clear trajectory from affective image understanding to robust spatial reasoning. Chen’s work is notable for bridging emotional intelligence and geometric perception, offering tools that are both socially aware and technically precise—a rare and valuable combination in modern AI research.