In this session, Saman will explore how AI-based tools and methods, including deep learning, explainable AI, digital twins, and AI-integrated simulation, can improve disaster preparedness, response, and recovery. The lecture will highlight how geospatial data, machine learning, and socio-economic modelling can provide deeper insights into disaster vulnerability and resilience, offering new approaches to reducing disaster risks. In addition to his research, Saman teaches across both undergraduate and postgraduate programmes at the Department of Risk and Disaster Reduction (RDR). He leads IRDR0047: Geospatial Data Science and IRDR0010: Advanced Hazards at the postgraduate level, focusing on the application of geospatial data and AI in understanding and managing complex disaster risks. At the undergraduate level, he teaches IRDR0021: Social and Geospatial Data Analysis, equipping students with the skills to analyse and apply geospatial data in disaster and social risk contexts.

16

4/16/2025

Who really holds the power in international humanitarianism? In this thought-provoking taster lecture, Dr Philip Cunliffe explores the political and historical context of humanitarian aid, examining how decisions are shaped by national interests and state power. Using the recent quest to disband USAID by the new administration as a case study, Dr Cunliffe challenges common assumptions about the role of aid in global governance and international relations. He discusses the origins of USAID during the Cold War, the political motivations behind aid distribution, and the rise of new geopolitical dynamics shaping humanitarianism today. The lecture also examines key failures in Western humanitarianism — from Afghanistan to Haiti — and explores how state sovereignty, political legitimacy, and global power structures intersect with humanitarian practice.

12

4/15/2025

This module introduces students to a range of engineering and data-science methods that are currently used in humanitarian action and human welfare. This module covers the fundamentals of data-driven engineering solutions and digital data science in the era of big data. Students will be learning about the application of digital data, their limitations, and ethical considerations of using them in humanitarian and development contexts.

46

4/11/2025

Technology has always played an important role in humanitarian action. The emerging technologies, data and digital humanitarianism are transforming the way the global humanitarian and development sectors are currently preparing for and responding to humanitarian crisis and development needs. This module introduces students to a range of physical and digital technologies that are commonly used in humanitarian action. These technologies include the application of earth observation satellites, unoccupied aerial systems (i.e., drones), geospatial techniques, predictive analytics, use of social-media big data, mobile surveillance technology for digital health, and crowdsourcing of digital data for humanitarian action. Students will be learning about the application of various technologies, their limitations, and ethical considerations of technology and digital data use in humanitarian and development contexts. This module covers a wide-ranging variety of digital data and provides basic int

6

4/11/2025

The module aims to take a modelling and statistical approach to geophysical and hydro-meteorological hazards. Students will understand statistical, modelling, observational and data science approaches to assessing hazards such as earthquakes, floods and landslides. Students will have the opportunity to apply the knowledge gained from lectures using real-world data during weekly computer practicals.

6

4/6/2025

This skills development module is designed to provide students with the essential tools required for analysing quantitative and geospatial data in the context of risk and disaster reduction, humanitarian crises, and public health emergencies. As a participant in this module, you will acquire foundational knowledge in statistical methods tailored for survey design and quantitative data analysis. Moreover, the module includes hands-on programming exercises, which will enhance your ability to conduct independent research in risk and disaster science. These exercises focus on data analysis using an example programming language. You will also develop fundamental skills in geospatial data analysis through an introduction to Geographic Information Systems (GIS) and Remote Sensing (RS) techniques. Utilising industry-standard software, you will engage in the analysis of geospatial data, thereby strengthening both your scientific understanding and practical abilities in this field.

10

3/12/2025

This module provides students with practical, field-based learning that enables them to apply theory to practice through problem-based and experiential learning. The module delivery is on UCL campus and includes a partially-funded field trip. The module equips students with skills for research and future fieldwork or deployment related to disaster risk reduction. Central themes to the module are operational risk management, travel risks, fieldwork, and health geography. Module leader: Dr Myles Harris

8

3/12/2025

This module enables students to develop foundational skills needed to progress in the global humanitarian studies. Topic examples included in the module are critical thinking, professionalism, secondary data analysis, and communicating evidence. This module will equip students with learning opportunities that underpin their higher education and link to their future career, thus provide a strong scholarly foundation for further study and relevant skills for employment. https://www.ucl.ac.uk/module-catalogue/modules/interdisciplinary-skills-IRDR0049

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3/12/2025