Research

Research Statement

AI for understanding and anticipating complex environmental systems

I study how world models represent and anticipate change in complex hazard environments, supporting multi-hazard forecasting, risk warning, and intelligent decision-making in real settings.

01Current Research

Current Focus

Disaster Intelligence

Studying landslides, debris flows, and floods through remote sensing, geospatial information, spatiotemporal data, and machine learning for risk sensing, early warning, and decision support.

02Research Directions

Disaster IntelligenceCurrent Focus
World ModelsResearch Direction
Generative AIMethods and Exploration
Spatiotemporal ModelingOngoing
Computer VisionOngoing
Deployable Intelligent SystemsResearch Interest

03Published Research

Methods and Exploration

Generative AI

Exploring generative models for scientific data modeling, limited-data augmentation, cross-modal understanding, and dynamic process simulation.

JAMA Ophthalmology · 2025

04Methods and Capabilities

Python
PyTorch
Machine Learning
Computer Vision
Generative AI
Diffusion Models
Spatiotemporal Modeling
Data Processing
Data Visualization
Full-Stack Development
IoT & LoRaWAN

05Collaboration Interests

I welcome collaboration on multi-hazard early warning, rainfall modeling, world models for environmental systems, and generative approaches to scientific data — as well as conversations with researchers, students, and engineers from adjacent fields.

Get in Touch