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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
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publications
Real-time mask detection on google edge TPU
Published in Arxiv, 2020
This paper introduces a new application for real-time mask detection on-device, utilizing Google Coral EdgeTPU
Recommended citation: Park, K., Jang, W., Lee, W., Nam, K., Seong, K., Chai, K. and Li, W.S., 2020. Real-time mask detection on google edge TPU. arXiv preprint arXiv:2010.04427.
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Federated semi-supervised learning with prototypical networks
Published in Arxiv, 2022
This paper proposes a federated semi-supervesed learning method, by sharing knowledge between cleints and server through prototypes.
Recommended citation: Kim, W., Park, K., Sohn, K., Shu, R. and Kim, H.S., 2022. Federated semi-supervised learning with prototypical networks. arXiv preprint arXiv:2205.13921.
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PointSplit: Towards on-device 3D object detection with heterogeneous low-power accelerators
Published in International Conference on Information Processing in Sensor Networks, 2023
This paper is about optimizing on-device 3D object detection on mobile devices equipped with CPU-GPU-NPU.
Recommended citation: Park, K., Choi, Y.R., Lee, I. and Kim, H.S., 2023, May. PointSplit: Towards on-device 3D object detection with heterogeneous low-power accelerators. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks (pp. 67-81).
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Unexplored Faces of Robustness and Out-of-Distribution: Covariate Shifts in Environment and Sensor Domains
Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
This paper is about covariate shift of AI models, caused by changes in environment or sensor parameters.
Recommended citation: Baek, E., Park, K., Kim, J. and Kim, H.S., 2024. Unexplored faces of robustness and out-of-distribution: Covariate shifts in environment and sensor domains. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 22294-22303).
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AI Should Sense Better, Not Just Scale Bigger: Adaptive Sensing as a Paradigm Shift
Published in NeurIPS, 2025
This position paper introduces a new direction for AI development: Adaptive sensing
Recommended citation: Baek, E., Park, K., Ko, J., Oh, M.H., Gong, T. and Kim, H.S., 2025. AI Should Sense Better, Not Just Scale Bigger: Adaptive Sensing as a Paradigm Shift. The Thirty-Ninth Annual Conference on Neural Information Processing Systems Position Paper Track.
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DistillSleep: Real-Time, On-Device, Interpretable Sleep Staging from Single-Channel EEG
Published in SLEEP, 2025
This paper is about automatic sleep staging AI model. We developed a lightweight AI model using knowledge distillation, while providing verifiability.
Recommended citation: Park, K., Hong, J., Lee, W., Shin, H.W. and Kim, H.S., 2025. DistillSleep: Real-Time, On-Device, Interpretable Sleep Staging from Single-Channel EEG. SLEEPJ, p.zsaf240.
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T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation
Published in ICLR, 2026
T1 is a CNN-Transformer hybrid that binds channels to attention heads for robust time series imputation, achieving 46% better performance than existing methods, especially under extreme missingness.
Recommended citation: Park, D., Ryu, H., Bae, S., Park. K., Kim. H.S., 2026., T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation., The Fourteenth International Conference on Learning Representations.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.