Publication
We are committed to advancing disaster resilience in the Philippines by integrating machine learning and physics-based modeling for earthquake-induced landslide prediction.
Predictive Resilience
We leverage advanced machine learning and physics-based models to predict earthquake-induced landslides with precision. Our research enhances early warning systems, empowering communities, local governments, and scientists with real-time hazard assessments to mitigate risks and safeguard lives.
People and Partnership
We are dedicated to fostering interdisciplinary collaboration between earth sciences and artificial intelligence to bridge knowledge gaps and drive innovative disaster risk reduction solutions.
About Us
"Empowering Disaster Resilience Through AI and Earth Science"
We are a dedicated team of researchers, engineers, and AI specialists committed to advancing earthquake-induced landslide prediction. By integrating machine learning, remote sensing, and geophysical modeling, we develop data-driven solutions to enhance disaster preparedness and risk reduction. Our mission is to equip communities, local governments, and scientists with the technology and knowledge needed to mitigate landslide hazards and protect lives.
Our Mission
Bridging Earth Science and AI to develop innovative landslide prediction models, enhancing disaster resilience in vulnerable communities.
Our Plan
Fostering collaboration between scientists, engineers, and AI specialists to train and empower stakeholders in disaster preparedness.
Our Vision
A future where AI-driven hazard mapping and prediction safeguard lives, infrastructure, and communities against earthquake-induced landslides.
Services
Places and Partnerships
Strengthening Collaboration Between AI, Earth Science, and Government for Safer Communities
Seismic Insights
Utilizing AI and Physics-Based Models to Enhance Earthquake-Induced Landslide Prediction
Call To Action
Be part of the ML-PREP movement in advancing AI-powered landslide prediction and disaster preparedness!
Call To ActionOur Portfolio
- All
- Research
- Extension
- Instruction
- Production
Research 1
MOA Signing for the 2024 approved projects
Instruction 3
2024 GEO Sciences Lecture
Research 2
Ground breaking ceremony
Extension 2
Remote Sensing
Instruction 2
Landslide and Earthquake Prediction
Research 3
2025 DOST Call Conference
Extension 1
Geographic information system(GIS)
Extension 3
Resilient Solutions
Instruction 1
CSU Partnership
Our Partners
Testimonials
Saul Goodman
Disaster Risk Reduction Specialist
This project is a game-changer for disaster preparedness. The integration of AI and geophysical models provides accurate, real-time landslide predictions, helping local governments create safer communities.
Sara Wilsson
Researcher
The combination of Earth Science and AI in this initiative sets a new standard for hazard mapping. The use of machine learning to refine landslide prediction models is a major step forward in disaster risk reduction.
Jena Karlis
Engineer / AI Specialistr
As an engineer, I’ve seen firsthand how this project enhances seismic hazard assessment. The AI-driven approach not only increases accuracy but also improves efficiency in early warning systems.
Matt Brandon
Local Government Unit (LGU) Representative
This initiative equips our community with vital knowledge and tools to prepare for potential landslides. The technology empowers us to make informed decisions and protect our residents.
John Larson
Community Member
Knowing that advanced AI and scientific research are being used to predict landslides gives me peace of mind. This project is a beacon of hope for communities like ours living in high-risk zones.
Team
Our team is composed of experts in Earth Science, Artificial Intelligence, and Disaster Risk Reduction (DRR), working together to develop an advanced landslide prediction and warning system.
Jayrold Arcede, PhD
Project Leader
Loreniel Anonuevo, MSc
Project Technical Specialist IV
Karl Malcolm N. Cordova, MSc
Project Technical Specialist I (CSU-based)
Ken Adrian C. Villarias
Project Technical Assistant IV (CSU-based)
Paolo L. Pacaldo, MSIT
Project Technical Assistant IV (CSU-based)
Lolly Jade T. Rosil
Project Administrative Assistant I
Loyd John M. Gonzales
Project Technical Aide V
Jay Melvin Segales
Project Technical Aide VContact Us
We’d love to hear from you!
Whether you have questions, need collaboration opportunities, or want to learn more about our project, feel free to reach out.