📜 DeepC4: Deep Conditional Census-Constrained Clustering for Large-scale Multitask Disaggregation of Urban Morphology
🌐 lnkd.in/gC7Nby2n (arXiv preprint)

📜 A Data-Driven Probabilistic Approach to Regional Dynamics of Building Exposure and Physical Vulnerability Towards Global Disaster Risk Quantification Audit
🏢 AGU25, Progress, Ethics, and Accuracy in Bldg Stock Attribution (NH23D)
📍 New Orleans, LA, US
🗓 Dec 15-19, 2025

📜 Modernizing Quezon City's Building Risk Data with AI and Earth Observation
🏢 20th Assoc. of Pacific Rim Universities Multi-hazards Conference and Symposium (APRU-MH20)
📍 UP BGC, Philippines
🗓 Nov 26-29, 2025

📜 GraphCSVAE: Graph Categorical Structured Variational Autoencoder for Spatiotemporal Auditing of Physical Vulnerability Towards Sustainable Post-Disaster Risk Reduction
🏢 8th Int'l Disaster and Risk Conference (IDRC)
📍 Nicosia, Cyprus
🗓 Oct 22-24, 2025

using cluster-level constraints, multitask optimization, and multilabel conditionality, under a weak supervision setup.

#HelmholtzAI #AI4ER #DeepClustering #EO #UrbanMorphology #DisasterRisk #SpatialAudit #SpatialDisaggregation #Constraints

Our proposed novel DeepC4, a deep constrained clustering model, advances the existing classical spatial disaggregation techniques using deep learning and EO data to understand the distribution of various urban morphology characteristics at large scales, ...

✅ 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: apply.knight-hennessy.stanford.edu/register/?id...

some of our newest and exciting updates in how we align the use of AI with the practice of catastrophe modeling and disaster risk science!

#AI #DRR #EnvironmentalRisk #Cambridge #AI4ER #CDT #regional #disaster #risk #catastrophe #EO #ML #CAT #graphML #Bayesian

and physical vulnerability, regionally, given the vast amount of Earth Observation (EO) data and advanced machine learning (ML) techniques like spatiotemporal graph deep learning and Bayesian ML? That's what I will share high-level in our AI4ER CDT Showcase, including ...

When I began my journey in disaster risk science, it was fascinating to understand the mathematics behind probabilistic (seismic, tsunami, flood, blast, wildfire, etc.) hazard analysis. What if, in our risk equation, there's also probabilistic distribution of building exposure ...

Filipinos, Pinoy, or Philippines 🇵🇭 at #AGU24? We'll have a group dinner (hapunan) tomorrow. 📩 DM me for more details.

And, that's it! 4 hrs! #AGU24

Very thankful to our visitors who gave encouraging words on our proposed algorithm, have already expressed their intention in reading our preprint, & shared the same perspectives how AI should reasonably be used in DRR practice. Love y'all! ❤️

Applying AI 💻 & EO 🛰️ to exposure & vulnerability modelling, as my mentors also say, is indeed a "messy" one, yet it's widely recognized as a serious "data gap" in #DRR 🌍. Here's an online copy of our "very large" poster! 😄

✅ doi.org/10.5281/zeno...