- AI-driven Automated Attack Response Strategy Generation System
- Development of Value-Added Resource Conversion Technology for Waste Plastic Pyrolysis Products
- Development of Wearable Neuromorphic Heterogeneous Integration Platform for SPAD-fNIRS-Based Pain Signal Quantification
- Identification of Novel Disease Markers Using Depression Patient-Derived iPSCs
- Development of Sustainable and Highly Functional Polymer Synthesis and Application Technologies for Future Mobility Regulatory Compliance
- AI-driven Discovery of Targeted Protein Degraders — CRBN-based Molecular Glue Degraders
- Ultra-Low-Latency Storage-Driven I/O Subsystem for Large Language Models
- Intelligent E-Skin Foundry Platform
- Korea Sustainable Hybrid Intensification for Fractionation Technology (K-SHIFT)
- kaist_prj10
- ARC-H2: Autonomous Robotics-driven Catalysts for Hydrogen with High Durability
- PFAS-free Research Initiative for Macromolecular Energy materials (PRIME)
- Center for Divertor Science and Innovation in Fusion Energy (D-SINE)
- Quantum teleportation with quantum dot photons of different colors using a system of PIC and ASIC
- Development of AI-Based Super-Gap Core Technology for Next-Generation Eco-Friendly Free-Form Displays
- Net-zero Seawater Refinery; An AI-Based Integrated Refinery Platform for Carbon Capture and Resource Recovery from Seawater
- Transcendent Material Innovation of Phase Transition Artificial Muscles for Soft Robotics
- Development of an AX-based Intelligent Disaster Prevention Platform for Ultra-Safe SMR Construction Against Extreme External Hazards
- nEAR-LINK Initiative: In-Ear Affective BCI-AI Research Network
- Center of AI-BASE (Brain Architecture, Simulation & Engineering)
- Spin-based Neuromorphic/Quantum Hardware Platform
- Green Carbon Capture via AI-assisted Chloroplast DNA Editing
- Digital Health Technologies for Prediction and Intervention in Neurodegenerative Diseases
- Development of AI-Biofoundry Integrated Platform for Rapid On-Site Detection of Polycarbonate Microplastics and BPA Upcycling
Center of AI-BASE (Brain Architecture, Simulation & Engineering)
KEYWORDKeyword
OBJECTIVE Objective
We will fundamentally advance the field of AI-neuroscience by building the world's first multimodal brain foundation model (BrainFM) integrating ultra-high-resolution functional and structural brain imaging data, elucidating the disease mechanisms of intellectual disability, depression, and Parkinson's disease, and developing an AI-driven preclinical evaluation platform that predicts the efficacy of therapeutic interventions.
INTRODUCTION Director's Message
Brain disease therapeutics suffer from a significantly lower clinical success rate compared to other disease areas, underscoring the urgent need for a new AI-driven approach that integrates structural and functional understanding of brain circuits and validates treatment efficacy in advance.
The AI-BASE Research Center directly addresses this challenge by combining world-class imaging technologies with cutting-edge AI, while nurturing the next generation of researchers at the frontier of AI-neuroscience convergence.
IMPACT Impact
Through open-source release of the Brain Foundation model and multimodal brain datasets, this project will establish a foundational infrastructure for AI-driven neuroscience research, while the AI-based preclinical simulation platform will enhance the objectivity and success rate of brain disease drug development. Furthermore, the outcomes of this project will lay the groundwork for expansion to a broader range of brain diseases, catalyzing a paradigm shift in preclinical evaluation, and strengthen global competitiveness in the field through the training of convergent AI-neuroscience talent.
TALENT Ideal Talent
A proactive researcher who bridges AI and experimental neuroscience, leads an independent research group, and aspires to grow within a global scholarly network