Malaysia AI, Research / AI news for Malaysia
UTM researcher applies AI to Malaysian rainfall and flood risk at Imperial
A UTM senior lecturer has finished year one of a two-year AI fellowship in London, working on rainfall modelling for Malaysian flood risk. No model results or agency partners have been published.
In brief
- Dr Uswah Khairuddin of Universiti Teknologi Malaysia (UTM) has completed the first year of the Eric and Wendy Schmidt AI in Science Global Faculty Fellowship at Imperial College London, according to UTM's 7 October 2026 newsroom article.[1]
- Her project applies AI to rainfall modelling, including downscaling and forecasting, to improve flood-risk prediction for extreme climate events in Malaysia.[1]
- UTM is the programme's only Malaysian partner. Year two returns to UTM with funded research time, but UTM reports no model results, accuracy figures or agency users yet.[1][2]
What UTM announced
Universiti Teknologi Malaysia says Dr Uswah Khairuddin, a senior lecturer at the Malaysia-Japan International Institute of Technology, has completed the first year of a two-year AI fellowship at Imperial College London. UTM published the account on 7 October 2026, written by Dr Uswah herself.[1]
Her research uses AI to improve rainfall modelling for flood-risk prediction during extreme climate events in Malaysia. This is a progress report on a fellowship, not a product launch or a published flood model.[1]
What the fellowship is
The Eric and Wendy Schmidt AI in Science Global Faculty Fellowship is run by Imperial's I-X Centre for AI in Science with support from Schmidt Sciences. Each fellow spends one year at Imperial, then continues the work at the home university in a second year. UTM says three annual cohorts of eight fellows began in September 2025.[1][2]
Imperial's own page lists UTM among six partner institutions, with the Indian Institute of Science, the National Centre for Biological Sciences, the University of Ghana, the University of Sao Paulo and Universitas Gadjah Mada. It says a deep knowledge of AI is not a precondition, and that most applicants will not come from computing departments.[2]
The flood-risk project
At Imperial, Dr Uswah works in the Department of Civil and Environmental Engineering with Professor Wouter Buytaert of Hydrology and Water Resources. UTM says the project examines how AI can support rainfall downscaling and forecasting, while keeping the scientific problem at the centre of model development.[1]
Downscaling means turning coarse weather-model output into finer local rainfall estimates. Our reading is that this is why the work matters for flood risk, because local rainfall intensity drives local flooding. UTM does not describe the method, the data or any test results.[1]
What the first year produced
UTM lists learning and networking outcomes rather than technical ones. Dr Uswah worked alongside AI postdoctoral researchers and fellows from other fields, served as a social coordinator at I-X and supported an I-X Women in AI career event.[1]
With other first-cohort fellows, she led a successful application to the Schmidt Community Initiative Fund. The group secured approximately USD 79,800 to organise an AI workshop in Brazil in 2027 and plans a Global Faculty Fellows conference straight afterwards.[1]
Year two and who else can apply
In the second year the work moves back to UTM. UTM says funding for a teaching buyout protects research time, and the remaining flexible research allocation is managed through its Research Management Centre. Dr Uswah plans to share new methods and international connections with students and colleagues.[1]
UTM says two of its academics joined the second full cohort in September 2026, and six others were selected for 2026 Mini Visits of two to six weeks. Imperial's page says applications for the 2026/27 intake are now closed.[1][2]
Why Malaysia should care
Flood-risk forecasting matters across Malaysia. UTM is the only Malaysian partner in this fellowship, but the work is early, and no model, accuracy figure or agency user has been announced.
UTM and other Malaysian researchers
A funded route to work with a hydrology group on AI methods, though UTM says the current round is closed.[1][2]
Practical move: Ask UTM's Research Management Centre about the next call.
Flood agencies and local councils
No operational tool exists yet, and UTM names no agency partner.[1]
Practical move: Treat it as research, and ask for validation results before use.
SMEs and property owners in flood-prone areas
No change to flood forecasts today.[1]
Practical move: Keep following official flood warnings from government channels.
What Malaysians can do now
- Researchers: ask UTM's Research Management Centre when the next fellowship and Mini Visit calls open, and how proposals are screened.
- Agencies and councils: ask the team what rainfall data, tests and accuracy measures its model will use before relying on any output.
- Residents and businesses in flood-prone areas: keep using official warnings for decisions, because this research has produced no public forecast.
What we still do not know
What we still do not know
- Which AI method, rainfall data and Malaysian locations the project uses, and how it will be tested.
- Whether any Malaysian agency or council will use the results, and when results will be published.
- How much of the programme's cost, such as stipend and allowances, UTM itself carries.
Sources
- 1.UTM researcher advances AI for flood risk at Imperial Universiti Teknologi Malaysia, 7 October 2026
- 2.Eric and Wendy Schmidt AI in Science Global Faculty Fellowships Imperial College London
- 3.File:Banjir Sandakan Januari 2025 01.jpg Wikimedia Commons, 16 January 2025
- 4.File:Queen's Lawn, Central Library and Sherfield Buildings, Imperial College London.jpg Wikimedia Commons, 5 November 2019
- 5.File:Ena Rain gauge station.jpg Wikimedia Commons, 3 June 2017
