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Jin-Jun Lee

Korea Advanced Institute of Science and Technology · Neuroscience

About the Lab

Professor Jin-Jun Lee's research lab at KAIST specializes in the intersection of media art, artificial intelligence, and embodied interaction, focusing on creating immersive, multisensory experiences through innovative technologies. The lab explores AI-driven artistic expression, including data mosaicing, sonification, and interactive projection systems, to address social and cultural narratives—particularly the voices of marginalized communities. Their work bridges traditional East Asian literati aesthetics with contemporary digital media, using computational systems to translate inner emotional and mental states into multimodal artistic outputs. The lab emphasizes ethical and aesthetic implications of AI in art, challenging dominant representations through palimpsestic, layered computational artworks.

media artAI artinteractive systemssonificationdata mosaicing

Research Overview

Papers
5
Total Citations
1
Papers (5y)
5
Primary Field
Neuroscience

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
5total
2022
2023
2024
2025
Citations per year (5y)
1total
2022202320242025

Selected Papers

5
1
Article|1 citations·2024
EMPop: Pin Based Electromagnetic Actuation for Projection Mapping
Sungbaek Kim, Doyo Choi, Jinjoon Lee
OA

As interactive media arts evolve, there is a growing demand for technologies that offer multisensory experiences beyond audiovisual elements in large-scale projection mapping exhibitions. However, traditional methods of providing tactile feedback are impractical in expansive settings due to their bulk and complexity. The EMPop system is the proposed solution, utilizing a straightforward design of electromagnets and permanent magnets making projection mapping more interactive and engaging. Our sy

Cognitive NeuroscienceNeuroscience
2
Article|0 citations·2023
gOd, mOther and sOldier: A Story of Oppression, Told through the Lens of AI
Andrew Gambardella, Meeyung Chung, Doyo Choi, Jinjoon Lee
SJR Q1Leonardo

Abstract The authors present gOd, mOther and sOldier—Nowhere in Somewhere Series 2022, a work that was conceptualized and created by artist Jinjoon Lee and his TX Creative Media Lab at KAIST, realized through the remote cooperation of eight local collaborators across Southeast Asia. The authors used artificial intelligence–based object detectors and sonification techniques in a work of media art to symbolize the voicelessness of those at the margins of society in Southeast Asia. These algorithms

Computer Vision and Pattern RecognitionComputer Science
3
Preprint|0 citations·2022
Efficient Data Mosaicing with Simulation-based Inference
Andrew Gambardella, Young‐Jun Choi, Doyo Choi, Jinjoon Lee
arXiv (Cornell University)OA

We introduce an efficient algorithm for general data mosaicing, based on the simulation-based inference paradigm. Our algorithm takes as input a target datum, source data, and partitions of the target and source data into fragments, learning distributions over averages of fragments of the source data such that samples from those distributions approximate fragments of the target datum. We utilize a model that can be trivially parallelized in conjunction with the latest advances in efficient simul

Signal ProcessingComputer Science
4
Article|0 citations·2025
Toward Diffused Multiplicity: Palimpsestic Characteristics in AI Art
Y W Choi, Jinjoon Lee
OA

This paper examines diffused multiplicity as an emergent characteristic of AI art, analyzing how multiple temporal, cultural, and aesthetic layers are embedded within these computational systems. Unlike traditional artistic production that maintains coherent aesthetic identities, AI artworks function as palimpsestic objects that contain multiple potential interpretations simultaneously. Through analysis of neural networks as synthetic media and examination of related artworks, this paper demonst

Cognitive NeuroscienceNeuroscience
5
Article|0 citations·2025
Audible Garden : Transcoding Literati Traditions in Landscape Representation Through a Multimodal Approach
Youngjun Choi, H. Lee, Jinjoon Lee
SJR Q1LeonardoOA

Abstract This paper analyzes the integration of East Asian literati traditions with contemporary multimedia through two artworks. It proposes a multimodal transcoding framework converting video frames into multisensory outputs via data-driven visualization and sonification. Using a modified turntable, the system interprets an artificial marble disc, created from the artist’s daily creation, to depict mental space using sumi ink. This aligns with literati traditions of expressing inner worlds thr

Food ScienceAgricultural and Biological Sciences

Research Areas

Cognitive NeuroscienceSignal ProcessingFood ScienceComputer Vision and Pattern Recognition

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