Experience

Lunit Inc.

AI Research Scientist

Mar 2025 — Present

Designing and training large-scale vision foundation models for digital histopathology.
Developing scalable, distributed inference systems for clinical-scale workloads.
Crafting theory-grounded data curation strategies to improve model reliability and generalization.

KAIST, Graduate School of AI

Master's Student (Advisor: Prof. Ye Jong Chul)

Feb 2023 — Mar 2025

Thesis: Development of Foundation Models in the Context of Cell Painting [Thesis]
Developed foundation models for Cell Painting to automate phenotype profiling in drug discovery.
Designed bidirectional generative models for cross-modal translation between visual phenotypes and chemical structures.
Investigated methods to mitigate batch effects and improve data harmonization for large-scale bio-imaging.

Institut Pasteur Korea & Institut Pasteur Paris

Data Scientist (Part-time), Pasteur International Unit AI3D

Feb 2023 — Dec 2024

Continued core development responsibilities on a part-time basis (40 hours/month) after transitioning to full-time Master's studies.
Led the ongoing implementation and extension of the institute's primary AI analysis pipeline for high-content screening.

Institut Pasteur Korea & Institut Pasteur Paris

Data Scientist, Pasteur International Unit AI3D

Oct 2021 — Feb 2023

Worked within the Pasteur International Unit (PIU) AI3D, a joint initiative between Institut Pasteur Korea (lead: Dr. Spencer Shorte) and Institut Pasteur Paris (lead: Dr. Christophe Zimmer).
Designed and implemented the institute’s primary analysis pipeline for high-content screening, boosting throughput and reproducibility.
Applied computer vision models to Cell Painting assays to improve phenotypic profiling for drug discovery campaigns.

Institut Pasteur New Caledonia / ISEA

Research Intern, Undergraduate (Supervisor: Prof. Nazha Selmaoui-Folcher)

Oct 2020 — Oct 2021

Developed novel feature extraction and classification methods (CNNs, ML classifiers) for high-dimensional MALDI-TOF mass spectrometry data.
Created an interpretable deconvolution framework to identify discriminative biomarkers for pathogen detection.