Information

✉️ [email protected]

✉️ [email protected]

📍 Seoul , Korea

🌐 www.linkedin.com/in/taehwan-yoon-4418272a7

Language

🇰🇷 Korean

🇬🇧 English

Motto

Stay desired, modest, honest, and responsible. Effort does not betray me, even if it does not lead to success. Do my best in the present, and don’t be disappointed by the past.

Personal Statement

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I am a PhD student at Soongsil University in Korea. My major are artificial intelligence (AI) , privacy-preserving machine learning (PPML), Healthcare AI (HAI), Federated Learing (FL). I have experiences of bio and medical data analysis and colaboratively AI training system preserving privacy (FL). I am looking foward to get good job or co-work opportunity about AI and PPML. If you have any suggestions for me, please let me know by email. Sincerely, appreciate reading my resume.

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Interesting Topic

• How do we improve fine-tuning performance under federated learning scenarios using a Bayesian transfered learning approaches.
• How do we mitigate heterogeneity and data diversity and catastrophic forgetting under Federated Learning scenarios.
• In the medical domain, How do we sum up and generate patient chart information using tiny language model trained by patient information including privacy as for preserving the privacy. (Muti-modal Federated Learning scenarios)

Keywords: Federated Learning, Preserving-Privacy Machine Learning, Medical Analysis, Fine-Tuning, Bayesian Transfered Learning, Adaptive Resonance Theory, Tiny Language Model, Text Generation, Multi-Modal.

Experience

AI engineer intership

2022.2~2023.2

Collected optimal coherence tomography (OCT) data at Konkuk University hospital and patients meta information. And developed U-Net based segmentation AI model. Fine-tuning and connceting AI to platform for clinicians.

Distributed Intelligence Lab (DILab)

2023년 3월~continue

Research PPML and Medical AI using FL.

Education

Bachelor, Computer software, Graduated

2017년 3월~2023년 2월

MSc and PhD, Computer science and engineering, Continue

2023년 3월~continue

Publication

프로젝트

Awards & Scholarships

• (2024) Best Paper Award / ASK conference best paper award- KIPS (Korea Information Processing Society)
• (2025) Winning a Prize / Industry-Academic Challenge- KIAT (Korea)

Patent

• Federated Learning System based on Bayesian Fine-Tuning.
• Federated Learning based on Sub-Network for Global Model Protection.

Conference

conf-list

Skill

역량