Iyan Eka Mulia’s work centers on tsunami modelling and hazard assessment. His research covers probabilistic tsunami hazard analysis (PTHA), tsunami inundation and economic loss in coastal tourism areas, landslide- and volcano-generated tsunamis such as the 2018 Anak Krakatau and Palu events, and transoceanic tsunami propagation. He also applies machine learning and generative AI to tsunami early warning, stochastic earthquake modelling, tropical cyclone intensity prediction, and chlorophyll-a forecasting. He supports community programs on tsunami preparedness, including the IOC-UNESCO “Tsunami Ready” program in Batukaras.

Contact: iyan.mulia@itb.ac.id

Qualifications

  • Ph.D. – PhD at Kagoshima University, Japan
  • M.T. – Master’s Degree in Engineering
  • S.Si. – Bachelor of Science

Research and Community Projects

  • Pemulihan Bencana Aspek Manajemen Risiko dan Kebencanaan (2026)
  • Probabilistic Tsunami Hazard Assessment (PTHA) for the Southern Coast of Java Using Updated Tsunami Source Data (2026)
  • Characteristics of transoceanic tsunamis: observation and modeling (2026)
  • SINERGI ALOR – Sinergi Edukasi dan Teknologi dalam Pengelolaan Lingkungan dan Wisata Desa Alor Besar di Pulau Alor (2026)
  • Pendampingan Penguatan Kapasitas Masyarakat terhadap Bencana Gempa dan Tsunami di Desa Liya One Melangka, Kecamatan Wangi-Wangi Selatan, Sulawesi Tenggara (2025)
  • Peningkatan Kapasitas Tsunami Ready Desa Batukaras menuju Rekognisi Internasional UNESCO-IOC (2025)
  • Simulasi dan Pemodelan Gelombang Tsunami Akibat Longsoran Aerial (2025)
  • Prediksi Intensitas Siklon Tropis Menggunakan Deep Learning (2025)
  • Analisis dan Prediksi Spasial-Temporal Klorofil-a di Perairan Indonesia dan Sekitarnya Menggunakan Algoritma Machine Learning (2025)
  • Penyediaan Informasi Prediksi Pasang Surut di Pulau Pramuka untuk Wisatawan dan Nelayan (2025)
  • Pengembangan Portal Data Kelautan Berbasis IHO S-100 untuk Mendukung Ekonomi Biru dan SDGs (2025)
  • DAPT-Equity2024 @ Pemodelan Gempa Stokastik Menggunakan Generative Artificial Intelligence dan Optimasi Posisi Stasiun Global Navigation Satellite System di Pulau Jawa (2024)
  • Pemodelan Dinamika Spasial dan Temporal Arus Laut untuk Pengembangan Kriteria Desain Turbin Pembangkit Listrik di Selat Alas Indonesia (2024)
  • Penerapan Prinsip Ekivalen untuk Penyelesaian Batas ZEE Indonesia-Malaysia di Selat Malaka (2024)
  • Pemetaan Daerah Potensi Rendaman Tsunami 3-Dimensi Resolusi Tinggi untuk Kajian Potensi Kerugian Ekonomi Bangunan di Daerah Wisata Pantai Pangandaran (2024)

Publications

  • Detecting Anak Krakatau tsunami with machine learning: Insights from Marina Jambu tide gauge data (2026).
  • AI-based ensemble tsunami inundation forecasting (2026).
  • Transoceanic propagation of the tsunami from the 2025 Mw 8.8 Kamchatka earthquake across the Pacific Ocean (2026).
  • Probabilistic tsunami hazard assessment in the Lesser Sunda Islands, Indonesia (2026).
  • Numerical investigation of tsunami inundation risk due to the 2018 Anak Krakatau volcano subaerial landslide: Study case Pandeglang, Indonesia (2026).
  • Long-period seismic waves from seawater disturbances during the 2018 Anak Krakatau volcanic island collapse (2026).
  • Multi-horizon prediction of tropical cyclone intensity and its interpretability with temporal fusion transformer (2025).
  • Analysis of tsunami economic loss in tourism areas using high-resolution tsunami run-up model (2025).
  • Tsunami hazards and risks from the Philippine Trench: The cases of 2012 and 2023 Mw 7.6 tsunamigenic earthquakes (2025).
  • Probabilistic tsunami hazard analysis of Batukaras, a tourism village in Indonesia (2025).
  • Machine learning approaches for tsunami early warning (2024).
  • Compounding impacts of the earthquake and submarine landslide on the Toyama Bay tsunami during the January 2024 Noto Peninsula event (2024).
  • Application of stress parameter from liquefaction analysis on the landslide-induced tsunami simulation: A case study of the 2018 Palu tsunami (2023).
  • Decision support system for predicting tsunami characteristics along coastline areas based on database modelling development (2011).