Ali Mohammed Mansoor Alsahag
Lecturer in AI & Data Science, University of Amsterdam
Informatics Institute (IvI), Faculty of Science
Science Park 904, Amsterdam, The Netherlands
About me
I am a Lecturer in AI and Data Science at the University of Amsterdam, specialising in time-series modelling, forecasting and explainable machine learning. My work focuses on applications in energy demand, rail and mobility operations, climate-related variability, environmental monitoring and healthcare. I collaborate with public and industry partners to develop AI models and decision-support tools that are reliable, interpretable and directly useful in real operational settings. I hold a Ph.D. in Computer and Systems Engineering and have over 15 years of academic experience across Malaysia and the Netherlands.
Research Background & Interests
My research develops artificial intelligence methods for sustainable and climate-resilient socio-technical systems. I work at the interface of machine learning, infrastructure analytics and responsible AI, with the goal of enabling organisations to plan and operate critical systems—such as energy networks, rail and mobility services, and environmental monitoring under increasing climate and societal pressures.
A central theme in my work is spatio-temporal and graph-based modelling: I design forecasting and reliability models that integrate operational, environmental and climate signals to anticipate demand, disruption and maintenance risk. Alongside performance, I emphasise trustworthiness, developing approaches for explainability, uncertainty and fairness to ensure that AI systems can support transparent and equitable decisions.
This agenda builds on earlier research in energy-efficient communication systems and edge/IoT architectures, which shaped my long-term interest in sustainable computation and resource-aware modelling. Today, I collaborate with public and industry partners to build decision-support tools that translate advanced ML models into actionable insights with environmental, operational and social impact.
News
Dec 15–17, 2025 – Upcoming conference in Phuket, Thailand
I will present my work at the 19th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2025-Winter), held at M Social Hotel, Phuket, Thailand.
2025 – New article in Decision Analytics Journal
Our paper “An analytics framework for interpretable subseasonal forecasting under decadal climate variability” (Chen, J., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. M.) has been published in Decision Analytics Journal.
2025 – New article in Sustainability
Our work on hybrid Prophet–(Q) LSTM models for sustainable national energy demand forecasting in the Netherlands (Curiěl, R., Alsahag, A. M. M., & Mohammadi Ziabari, S. S.) has been published in Sustainability.
2025 – New article in Machine Learning for Computational Science and Engineering
Our paper “Task-adaptive debiasing with SCM for sentiment analysis” (Zhu, C., Mohammadi Ziabari, S. S., & Alsahag, A. M. M.) has been published in Machine Learning for Computational Science and Engineering.