Group leader

Eunchai Kang

Developmental neuroscientist ยท University of Aberdeen

Eunchai leads research in the Kang/Berg Lab on human cortical development, neurogenesis and stem cell-derived brain models, with a particular focus on how environmental and inflammatory signals influence the developing brain.

Eunchai Kang

Research

Eunchai studies the cellular and molecular mechanisms that shape human brain development, with a particular interest in cortical neurogenesis and the response of developing neural tissue to environmental and inflammatory signals.

Her work combines human stem cell-derived organoids and assembloids with ex vivo human fetal brain models to investigate how neural stem cells build organised tissue and how interactions among neural and non-neural cell types influence developmental outcomes.

Research interests

  • Human cortical development and neurogenesis
  • Brain organoids, cerebroids and assembloids
  • Maternal inflammation and IL-17A signalling
  • Neuroimmune interactions during development
  • Human experimental models of neurological disease

Lab
Kang/Berg Lab

Institution
Institute of Medical Sciences
University of Aberdeen

Email
Eunchai.Kang(at)abdn.ac.uk

Profile
Google Scholar

Background

Training

Eunchai completed her undergraduate studies at KAIST in South Korea, followed by a PhD at Johns Hopkins University and postdoctoral training at the University of Pennsylvania.

Outside the lab

Outside the lab, Eunchai enjoys playing the piano and cello.

Kang/Berg Lab group event

Selected publications

Research highlights

Assir et al. Modeling maternal immune activation in 3D ex vivo human fetal brain cerebroids reveals IL-17A-driven disruption of cortical development. Nature Neuroscience, 2026. View publication

Gim et al. Deciphering Cell-Type and Temporal-Specific Matrisome Expression Signatures in Human Cortical Development and Neurodevelopmental Disorders via scRNA-Seq Meta-Analysis. Nature Communications, 2025. View publication

Qian et al. Brain-region-specific organoids using mini-bioreactors for modeling ZIKV exposure. Cell, 2016. View publication