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Chung-Yeon LEE

Biointelligence Lab
Department of Computer Science and Engineering
Seoul National University

Postal Information
Rm.#417, Bldg.#138, Seoul National University
1 Gwanak-ro, Gwanak-gu, Seoul 151-742

Contact Information:
Phone: + 82 2 880 5890 Message: + 82 10 7510 7150 Email: cylee@bi.snu.ac.kr

Curriculum Vitae


Research Interests

img Learning and Memory

Understanding neuronal information processing principles underlying human learning and memory.

img Machine Learning

Developing innovative computational models and algorithms for building synthetic intelligence systems solving practical problems.

img Virtual Reality

Understanding human perception and development of super-realistic virtual environments.

img Robot Learning

Developing mobile cognitive robots that actively perceive information by multimodal sensors and interacting with the real-world environment.

Selected Papers

Effective EEG Connectivity Analysis of Episodic Memory Retrieval (CogSci-2014)

Episodic memory formation is associated with large-scale neuronal activity distributed across the cortex. Decades of neuroimaging and patient lesion studies demonstrated the correlation between the roles of specific brain structures in episodic memory retrieval. Distributed, coordinated and synchronized activities across brain regions have also been investigated, however, neuronal mechanisms based on effective connectivity underlying the coordination of this anatomically distributed information processing into introspectively coherent cognition have remain largely unknown. Here we investigate the information flow network of the human brain during episodic memory retrieval. We have estimated local oscillation amplitudes and asymmetric inter-areal synchronization from EEG recordings in individual cortical anatomy by using source reconstruction techniques and effective connectivity method during episodic memory retrieval. The strength and spectro-anatomical patterns of these inter-areal interactions in sub-second time-scales reveals that the episodic memory retrieval involves increase of information flow and densely interconnected networks between the prefrontal cortex, the medial temporal lobe, and some subregions of the parietal cortex. In this network, interestingly, the SFG acted as a hub, globally interconnected across broad brain regions. [Full Article] [Presented Slides]

Neural Correlates of Episodic Memory Formation in Audio-Visual Pairing Tasks (CogSci-2012)

Understanding episodic memory formation of real-world events is essential for the investigation of human cognition. Most studies have stressed on delimiting the upper boundaries of this memory by using memorization tasks with conditional experimental paradigms, rather than the performance of everyday tasks. However, naturally occurring sensory stimuli are multimodal and dynamic. In an effort to investigate the encoding and retrieval of episodic memory under more naturalistic and ecological conditions, we here demonstrate a memory experiment that employs audio-visual movies as naturalistic stimuli. Electroencephalography measurements were used to analyze neural activations during memory formation. We found that oscillatory activities in the theta frequency bands on the left parietal lobe, and gamma frequency bands on the temporal lobes are related to overall memory formation. Theta and gamma power of the frontal lobes, and gamma power of the occipital lobes were both increased during retrieval tasks. Furthermore, subjects’ memory retrieval performance on the query task was used to clarify our experimental results. Correlation between behavioral differences and neural activation was observed in the same regions. Our results extend the previous results of neurocognitive studies on memory formation via naturalistic stimuli, neural oscillations, and behavioral analysis combined. [Full Article] [Presented Poster]

Place awareness learned by mobile vision-GPS sensor data (NIPS-2012 Workshop)

Context awareness is necessary for diverse user-oriented services. Especially, place awareness (logical location context awareness) is an essential method for a location-based service (LBS) that is widely provided to smartphone users. However, GPS-based place awareness is only valid when not only a user is located at outdoor positions where a GPS signal is strong enough but also the information on the relation between a physical location and a symbolic place is available. Here we propose a novel place awareness method using visual information as well as GPS data. The proposed method predicts the current place of a user from GPS-tagged scene photographs taken by the digital camera equipped in a smartphone. Our method uses a modified support vector machine (SVM) where scene images and GPS coordinates are given as the instances and the weight parameters of the model, respectively, for classifying the place from the scene. We evaluate our method on the place awareness from approximately 4,000 photographs of four places including hallway, classroom, restaurant, and outdoor. Experimental results show that the proposed method can precisely recognize the place with scene photos only when GPS information is not available and the awareness accuracy is improved in the GPS-available case. Furthermore, we demonstrate a smartphone application using the proposed place awareness method based on vision-GPS data. [Full Article] [Presented Poster]

Multi-layer structural wound synthesis on 3D face (Journal of CAVW, 2011)

In this paper, we propose multi-layer structural wound synthesis on a 3D face. The fundamental knowledge of the facial skin is derived from the structure of tissue, being composed of epidermis, dermis and subcutis. The approach first defines the facial tissue depth map to measure details at various locations on the face. Each layer of skin in a wound image has been determined by hue-based segmentation. In addition, we have employed disparity parameters to realise 3D depth in order to make a wound model volumetric. Finally, we validate our methods using 3D wound simulation experiments. [Full Article] [Presented Slides]