Summary
Jaehun Kim is an audio and multimodal AI researcher with eight years of hands-on experience building speech and music deep-learning systems, from production-focused TTS and vocoder fine-tuning for Korean virtual humans to music detection and depression detection from voice. He has interned and researched at industry and academic labs including NAVER, INNERVERZ, KAIST, and Seoul National University, contributing to dataset curation, transfer learning for low-resource tasks, model compression, and deployment to web services. Currently pursuing advanced degrees in multimodal AI at KAIST, he blends electrical engineering fundamentals with applied ML to optimize inference speed and real-world robustness. An understated strength is his repeated focus on bridging research prototypes to deployable systems—balancing signal-level audio work with scalable model training and evaluation on messy, realistic data.
8 years of coding experience
1 year of employment as a software developer
American International School Chennai
Doctor of Philosophy - PhD, Multimodal AI, Doctor of Philosophy - PhD, Multimodal AI at Korea Advanced Institute of Science and Technology
English, Korean