Jinyung Hong

Hello, I'm Jinyung Hong, a Ph.D. candidate in computer science at Arizona State University.

I belong to the BEET lab, supervised by Dr. Theodore P. Pavlic.

My research aims to apply principles and techniques from neuroscience, biology, and cognitive science to implement new interpretable Intelligence that can collaborate with humans and help them make decisions. To this end, I conduct research that spans the areas of neuro-symbolic computing, continual learning, and interpretable AIs, which are crucial components to building human-like AI systems with cognitive abilities.

Research Interests: Bio-inspired Computing, Neuro-symbolic Computing, Continual Learning, Explainable AI.

News

Dec 2 2024: Received the ASU School of Computing and Augmented Intelligence (SCAI) Conference Funding Award. 🎉

Spring 2024: Received an ASU School of Computing and Augmented Intelligence (SCAI) Doctoral Fellowship. 🎉

Recent Publications

Attribute-Centric Debiasing Network: Debiasing via Attribute Decomposition Learning

*Park, Keun Hee, *Hong, Jinyung, Jeon, Eun Som, Pavlic, Theodore P., Turaga, Pavan

*: equal contribution

Under review

Improved Knowledge Distillation Based on Global Latent Workspace with Multimodal Knowledge Fusion for Understanding Topological Guidance on Wearable Sensor Data

*Hong, Jinyung, *Jeon, Eun Som, Buman, Matthew P., Turaga, Pavan, Pavlic, Theodore P.

*: equal contribution

Under review

Bi-ICE: An Inner Interpretable Framework for Image Classification via Bi-directional Interactions between Concept and Input Embeddings

*Hong, Jinyung, *Kim, Yearim, Park, Keun Hee, Han, Sangyu, Kwak, Nojun and Pavlic, Theodore P.

*: equal contribution

arXiv.org (Under review)

arXiv

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