Joshua Dimasaka

Joshua Dimasaka is a PhD researcher with a professional background in civil & structural engineering, public policy, and data science. At the UKRI EPSRC Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER) and Cambridge University Centre for Risk in the Built Environment (CURBE), he leverages artificial intelligence methods and time-series Earth Observation data to audit regional spatiotemporal changes in exposure, physical vulnerability, and disaster risk profiles over time. His goal is to assess whether countries are making progress in reducing disaster risk, ultimately informing collective efforts under the Sendai Framework for Disaster Risk Reduction 2015–2030. Standing on the shoulders of giants, he aligns his work with the practice of regional disaster risk and catastrophe modeling, under the mentorship of Dr. Emily So (CURBE), Dr. Christian Geiß (DLR), Dr. Robert Muir-Wood (Moody’s RMS), and Dr. Fouad Bendimerad (EMI).

News

Aug 18, 2025 - Our short volunteering work to understand Myanmar-Thailand earthquake damage has been featured on the Department of Engineering website. Even though our volunteering capacities are sadly limited, we have truly learned a lot from this educational experience "what it's like in this very unique setting, very urgent, no data availability, and any other problems that we may have". Read more here.
Aug 5, 2025 - If "DeepC4" is for "spatial auditing" from our first year, we now present our efforts towards "spatiotemporal auditing" from our second year, with a non-peer-reviewed preprint "GraphVSSM: Graph Variational State-Space Model for Probabilistic Spatiotemporal Inference of Dynamic Exposure and Vulnerability for Regional Disaster Resilience Assessment" now available on arXiv! Across our three case studies ranging from city-level to multi-country scale, our proposed novel GraphVSSM tackles the equally important yet uniquely challenging aspect of modeling physical vulnerability at large spatiotemporal scales. It uniquely integrates graph deep learning, state-space modeling, and variational inference using time-series data and prior expert belief systems in a coarse-to-fine-grained manner, contributing to broader urban studies that require compositional data analysis in weakly supervised settings. Read the preprint here.
Jul 31, 2025 - Our non-peer-reviewed preprint "DeepC4: Deep Conditional Census-Constrained Clustering for Large-scale Multitask Disaggregation of Urban Morphology" is now available on arXiv! This work is the highlight contribution of my first-year PhD, which deals with "spatial auditing". 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, using cluster-level constraints, multitask optimization, and multilabel conditionality, under a weak supervision setup. Read the preprint here.
May 21, 2025 - Many thanks to our attendees in our AI4ER Annual Showcase 2025 yesterday! It's so motivating to see our community back again together, from the afternoon talks with interesting AI algorithmic tricks to our evening dinner filled with fun stories and delicious food + wine.
May 8, 2025 - Next week, it'll be Mental Health Awareness Week (May 12th-18th) and I hope you are all taking care, that your work is as equally important as what's affecting your work. This is not work-related news, but I'm very happy to share that I have successfully reached 10,000 push ups in 40 days. Did you know that there's a global and systemic mental-health crisis in academia?
May 6, 2025 - I will be presenting some of the newest and exciting updates of our PhD work (Probabilistic Regional Dynamics of Building Exposure & Physical Vulnerability) in our annual AI4ER CDT Showcase 2025 on Tuesday 20 May 2025 from 12.00 - 19.00 at the Department of Computer Science and Technology, William Gates Building, 15 JJ Thomson Ave, Cambridge, CB3 0FD. Join us and connect! RSVP here.
Apr 24, 2025 - I participated (and enjoyed) a roundtable discussion with other Cambridge CDT researchers and our EPSRC Executive Chair, Professor Charlotte Deane. I am very grateful to have shared our exciting research on using AI and Earth observation data in understanding large-scale disaster risk spatiotemporally here at the University of Cambridge.
Apr 21, 2025 - Our volunteering collaboration to understand the impact after Mw-7.7 earthquake in Myanmar and Thailand is now available on Zenodo and MapBox (a web map visualization). Many thanks to our volunteers (Shagun, Lisanne, Lorenzo, Grace, Fer, Han, Orlando, Shaomin, Andrea, and Sakthy) and many thanks for this leadership role.
Apr 18, 2025 - Due to many exciting developments in our research on spatiotemporal patterns of building exposure and physical vulnerability using probabilistic AI, geometric/graph deep learning, and geospatial datasets, our preprint for DeepC4 will most likely be available in the third quarter of 2025. Many thanks for patience! You may always check our DeepC4 work here and send me an email for any inquiries.
Dec 10, 2024 - I presented our poster presentation entitled "Deep Conditional Census-Constrained Clustering (DeepC4) for Large-scale Multitask Disaggregation of Urban Morphology" at American Geophysical Union Meeting 2024 in Washington, D.C. Many thanks for all those kind words and early requests for preprints! I also appreciate many fruitful conversations on AI and DRR. Many thanks to our AI4ER, Filipino attendees, Yue, Victor, Charlie, Robert, Sabine, Chenbo, and Susu's PhD students (who've been continuing our other AI and DRR work) for making this day a memorable one! We're still working on a preprint, which is expected to be shared publicly in the first quarter of 2025. Check my Bluesky posting here.
Nov 23, 2024 - The data and code repositories in Zenodo and GitHub of our "Deep Conditional Census-Constrained Clustering (DeepC4) for Large-scale Multi-task Disaggregation of Urban Morphology" are now available for public access. See you at AGU24 in Washington, D.C.!
Oct 18, 2024 - I attended 2024 UNDRR Asia-Pacific Ministerial Conference on Disaster Risk Reduction (APMCDRR) from 14 to 18 October 2024 at the Philippine International Convention Center in Manila. Check my post-event reflection here. Thankful for new connections and our EMI community gathering together!
Oct 2, 2024 - Our work "Spatial Disaggregation of Rwandan Building Exposure and Vulnerability via Weakly Supervised Conditional Census-Constrained Clustering (C4) using Earth Observation Data" has been accepted as a poster presentation at American Geophysical Union Meeting 2024 in Washington, D.C., on 10th of December 2024.
Sep 30, 2024 - New paper alert! My work with Andrea and Sakthy on "Enhancing assessment of direct and indirect exposure of settlement-transportation systems to mass movements by intergraph representation learning" in Environmental Research Letters has just been accepted.
Jun 30, 2024 - I started my research stay in DLR Earth Observation Center, Germany. Thankful for the Helmholtz Association. Let's explore Munich and Germany!
Jun 25, 2024 - I gave an invited presentation to the Innovations Group WG5 of LandAware, an international network on early warning systems. Many thanks for the good questions from our community. See their LinkedIn post here and Twitter/X post here.
May 22, 2024 - I delivered an oral presentation version of our ICLR ML4RS workshop poster at the Cambridge Hazard and Risk Research Day. Access the slides here.
May 11, 2024 - I presented our developing work "Global Mapping of Exposure and Physical Vulnerability Dynamics in Least Developed Countries using Remote Sensing and Machine Learning" at 2nd Machine Learning for Remote Sensing Workshop, 12th International Conference on Learning Representations (ICLR) in Vienna, Austria. Access the poster here, the 4-page paper here, the animated poster here, and the OpenSendaiBench Version 1 here.
Apr 29, 2024 - Joseph (University of Bath), Lois (Philippine Space Agency) and I (University of Cambridge) are building an online community PAIRL (Philippine AI Research and Learning Community) to democratize AI for the Philippine public and support PH AI researchers & learners to ignite meaningful collaborations and knowledge sharing. Follow us on a Twitter/X or join our growing community on Slack (free to join)!
Mar 4, 2024 - I won the Natural Hazards - Outstanding Student Presentation Award (OSPA) for my AGU 2023 presentation of "Near-real-time Country-wide Estimation of Susceptibility and Settlement Exposure from Norwegian Mass Movements via Inter-graph Representation Learning", which is now available here on Earth and Space Science Open Archive. Official press release and publication to follow.
Mar 3, 2024 - Our developing work "Global Mapping of Exposure and Physical Vulnerability Dynamics in Least Developed Countries using Remote Sensing and Machine Learning" has been accepted as a poster presentation at 2nd Machine Learning for Remote Sensing Workshop, 12th International Conference on Learning Representations (ICLR) in Vienna, Austria, on 11th of May 2024. More details to follow.
Feb 8, 2024 - I have been awarded a three-month fully-funded Helmholtz Visiting Researcher Grant to do an exciting summer research with the "Team Geo-risks" at the German Aerospace Center in July, August, and September 2024. If you'd be around and would like to chat about our work on the intersection of machine learning, disaster risk, and remote sensing, please feel free to send me an email.
Jan 12, 2024 - I have been accepted to attend the Bayesian Machine Learning as a tool for Climate Scientists Workshop at the Institute of Computing for Climate Science, University of Cambridge on March 25-27, 2024.
Jan 4, 2024 - I have been accepted to attend the Probabilistic Numerics Spring School 2024 at the University of Southampton on April 8-10, 2024.
Dec 14, 2023 - I led our Filipino community for a courtesy call on the Philippine Consulate General in San Francisco as we (20+ Filipino researchers) came together to share the Philippine stories of Earth sciences at the American Geophysical Union Annual Meeting 2023. Read more here.
Dec 13, 2023 - I presented "Near-real-time Country-wide Estimation of Susceptibility and Settlement Exposure from Norwegian Mass Movements via Inter-graph Representation Learning" at American Geophysical Union Meeting 2023 in San Francisco, California. Access here the YouTube recording.
Oct 5, 2023 - Our work "Near-real-time Country-wide Estimation of Susceptibility and Settlement Exposure from Norwegian Mass Movements via Inter-graph Representation Learning" has been accepted as an oral presentation at American Geophysical Union Meeting 2023 in San Francisco, California, on 13th of December 2023. Learn more about the presentation here.
Oct 1, 2023 - I officially began my PhD studies with Dr. Emily So (Cambridge University Centre for Risk in the Built Environment) and Dr. Christian Geiß (German Aerospace Center) and got my third master's degree MRes.
Jul 31, 2023 - I started an exciting remote summer research project at Bonn's Center for Remote Sensing of the Land Surface (ZFL) to collaborate with Dr. Emily So (Cambridge University Centre for Risk in the Built Environment) and Dr. Christian Geiß (German Aerospace Center) for a project about quantifying our global disaster risk. If you are also based in the Philippines seeing the possiblity of AI for DRR public policymaking, feel free to connect with me.
Jun 30, 2023 - Our MRes team (myself, Andrea, and Sakthy) ended our three-month research project on "Near-real-time Country-wide Estimation of Susceptibility and Settlement Exposure from Norwegian Mass Movements via Inter-graph Representation Learning". You may access the data and code in our Zenodo and GitHub repositories.
Jun 26, 2023 - I joined the UK Alliance for Disaster Research and the Disasters Research Group (DRG) to review and discuss current disaster research practice in the UK at Wellcome Trust, London.
Jun 21, 2023 - I presented my research on artificial intelligence and disaster risk assessment at Risk Management Solutions in London.
Mar 9, 2023 - I started working with Dr. Andrea Marinoni (Engineering) and Dr. Sakthy Selvakumaran (Engineering) to characterize human-environment factors for climate change adaptation and mitigation in the Arctic by causal graph inference.
Mar 1, 2023 - I co-authored "Seismic Impacts Report for M7.8 and M7.5 Turkey-Syria Earthquake Using Near Real-time Crowdsourcing and Remote Sensing Information".
Jan 27, 2023 - Our team's work on "Classifying sea ice in high-resolution SAR imagery using deep learning" has been accepted to EGU General Assembly 2023.
Jan 21, 2023 - EMI delivered 20 reports on updated climate and disaster risk assessment of Quezon City to the local government (read more).
Dec 17, 2022 - I co-authored a Nature Communications paper "Seismic multi-hazard and impact estimation via causal inference from satellite imagery".
Sep 26, 2022 - I started MRes+PhD in Application of Artificial Intelligence to the study of Environmental Risks at the University of Cambridge with a very generous full-funding studentship from UK Research & Innovation and Department of Earth Sciences. I will be part of Sidney Sussex College postgraduate community.
Aug 31, 2022 - I completed Global Urban Resilience Fellowship at EMI (Philippines). I am very grateful for the valuable mentorship from Dr. Fouad Bendimerad and for our hardworking team - Jaja, Mam Lourdes, Doc Renan, Laarni, Hector, Jom!
Aug 4, 2022 - I participated as part of the EMI expert observers for the Quezon City Public Service Continuity Plan Tabletop Exercise preparing for the "Big One" Mw-7.2 earthquake.
Jun 12, 2022 - I graduated MS Civil & Environmental Engineering (Sustainable Design and Construction - Structures) and MA Public Policy at Stanford University.