Taehwan Kim

ORCID: 0009-0000-9670-4667
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Welding Techniques and Residual Stresses
  • Machine Learning in Materials Science
  • Recommender Systems and Techniques
  • Greenhouse Technology and Climate Control
  • Additive Manufacturing Materials and Processes
  • Smart Agriculture and AI
  • Privacy-Preserving Technologies in Data
  • Remote Sensing in Agriculture
  • Caching and Content Delivery

Ulsan National Institute of Science and Technology
2025

Virginia Tech
2024

Federated Learning (FL) is an emerging distributed machine learning (ML) technique that enables in-situ model training and inference on decentralized edge devices. We propose Totoro, a novel scalable FL engine, massive applications to run simultaneously networks. The key insight explore hash table (DHT)-based peer-to-peer (P2P) re-architect the centralized system design into fully one. In contrast previous studies where many shared one parameter server, Totoro assigns dedicated server each...

10.1145/3627703.3629575 article EN 2024-04-18
Coming Soon ...