Thermal reliability in advanced packaging
We study thermal phenomena across scales, from standard cells to architecture, to inform thermal-aware design and reliability.
What we study
Three connected questions: how heat moves through packages, how to remove it, and how to manufacture the structures reliably.
AI-designed liquid cooling
We explore microchannel geometries for efficient cooling and more uniform temperatures across chiplets.
Panel-level manufacturing
We investigate AI-guided printing processes for redistribution layers and polymer dielectrics, with uniformity and scalability in mind.
Research in print
Selected papers from the IDAS publication record. Full bibliographic details are listed on the Publications page.
- 2026Functional Nano-to-Microstructures by Jet Printing and Direct Ink WritingChemical Reviews
- 2025Reinforcement Learning-Based Dynamic Optimization of Driving Waveforms for Inkjet Printing of Viscoelastic FluidsLangmuir
- 2025Evaluating inkjet printability of viscoelastic ink through Deborah number analysisPhysics of Fluids
- 2022The design of an inkjet drive waveform using machine learningScientific Reports
Work with IDAS
We welcome enquiries from students interested in AI-driven engineering design and advanced packaging research.
seongju@hanbat.ac.krLaboratory / Hanbat National University, N13-604Professor's office / Hanbat National University, N13-802
125 Dongseo-daero, Yuseong-gu, Daejeon, Republic of Korea
Tel. +82-42-828-8804