Dr. Matthew Saffari
Dr. Matthew Saffari is a Principal Investigator at Dublin City University (DCU), Ireland, specialising in advanced sustainable, renewable, and energy-efficient energy systems for buildings and communities. His expertise spans hybrid thermal energy storage, heat pump integration, renewable energy systems, and AI-driven optimisation and intelligent control strategies for next-generation energy infrastructures. His research operates at the intersection of engineering, data science, and sustainability, with the overarching aim of accelerating the global transition towards net-zero, flexible, and resilient energy systems.
Dr. Saffari has an extensive international research portfolio, having contributed to high-impact multidisciplinary projects across Europe and beyond, including Spain, Germany, Australia, and Ireland. His work spans both fundamental research and applied innovation, addressing real-world challenges in building decarbonisation, renewable energy integration, and intelligent energy system design.
He leads pioneering research on hybrid thermal energy storage (TES), including phase change materials (PCM) and thermochemical storage, integrated with renewable technologies such as heat pumps and photovoltaic systems. His research advances intelligent control and optimisation frameworks - combining model predictive control (MPC), multi-objective optimisation, and machine learning- to enhance system performance, reduce carbon emissions, and unlock demand-side flexibility in buildings and district energy systems.
Dr. Saffari has played a leading role in several nationally and internationally funded research initiatives, including serving as DCU collaborator on the SEAI-funded GEONORM geothermal energy project and as Principal Investigator in the Horizon Europe-funded HYSTORE project. Through these initiatives, he works in close collaboration with leading academic institutions, industrial stakeholders, and R&D organisations across Europe to advance next-generation thermal energy storage technologies and integrated sustainable energy solutions. His research is supported by advanced modelling and simulation methodologies, including FMU-based co-simulation platforms and AI-enhanced optimisation frameworks, enabling high-fidelity performance analysis, predictive system modelling, and real-time intelligent control of complex multi-energy systems.
Beyond academia, Dr. Saffari is actively engaged in innovation and commercialisation. He is a selected participant in the ConceptionX Venture Programme, where he is developing an AI-driven platform designed to transform building retrofits through intelligent system design, predictive analytics, and techno-economic optimisation. His broader vision is to translate deep-tech research into scalable digital solutions that reshape how buildings are designed, retrofitted, and operated in a low-carbon future.
Dr. Saffari collaborates extensively with industry, policymakers, and international research networks, contributing to strategic EU funding initiatives and interdisciplinary programmes focused on clean energy transition. His work supports the electrification of heating, integration of renewable energy sources, and the advancement of smart, low-temperature district heating systems.
He has authored numerous peer-reviewed publications and continues to contribute to emerging research areas, including explainable AI in energy systems, hybrid optimisation methodologies, and AI-assisted building performance modelling.
His expertise and insights are also recognised beyond academia, contributing to public discourse on energy and sustainability. In an interview with The Irish Times, he highlighted Ireland’s strategic position as a hub for data centres and renewable energy innovation, emphasising the critical role of energy storage and engineering solutions in addressing growing energy demands and decarbonisation challenges. His broader philosophy underscores the role of engineering and innovation in transforming challenges into opportunities for sustainable development.
Dr. Saffari is also an active contributor to international knowledge exchange platforms. He has delivered invited presentations to global thermal energy storage (TES) networks, sharing advancements in modelling, simulation, and integration of innovative TES systems within the built environment. His contributions focus on enabling scalable, interoperable, and high-impact solutions that support grid balancing and energy flexibility - one building at a time.
Research Interests
Dr. Matthew "Mo" Saffari’s research focuses on advancing next-generation energy systems for buildings and districts, with an emphasis on integrating artificial intelligence, optimisation, and advanced thermal technologies to enable net-zero and flexible energy infrastructures.
His core research interests include:
- Hybrid Thermal Energy Storage (TES): Development and integration of advanced storage solutions, including phase change materials (PCM) and thermochemical storage, to enhance energy flexibility, efficiency, and renewable utilisation.
- AI-Driven Energy Systems & Optimisation: Application of machine learning, deep learning, and hybrid optimisation techniques (e.g., model predictive control (MPC), multi-objective optimisation) for intelligent control, forecasting, and decision-making in complex energy systems.
- Smart Buildings & Digital Twins:Design and implementation of physics-informed and data-driven digital twins for buildings, enabling real-time monitoring, predictive control, and performance optimisation.
- Heat Pump & Renewable Integration: Advanced modelling and control of heat pumps integrated with renewable energy sources (e.g., solar PV, geothermal), supporting electrification of heating and decarbonisation.
- Demand-Side Flexibility & Grid Interaction: Development of strategies to enhance building-to-grid interaction, peak load reduction, and energy flexibility through coordinated control of distributed energy resources.
- District Heating & Low-Temperature Networks: Optimisation and control of next-generation district heating systems, including low-temperature and renewable-integrated networks.
- FMU-Based Co-Simulation & Energy System Modelling: Development of high-fidelity simulation frameworks combining Modelica/FMU-based models with Python-based optimisation and AI algorithms.
- Explainable AI & Hybrid Modelling: Integration of physics-based models with interpretable AI techniques to improve transparency, reliability, and adoption of AI in energy systems.
- Techno-Economic Analysis & Decision Support: Multi-criteria evaluation of energy systems considering cost, emissions, and flexibility, supporting policy, design, and investment decisions.
Teaching Interests
Dr. Mohammad Saffari’s teaching focuses on bridging fundamental engineering principles with emerging digital and AI-driven approaches to energy systems. His teaching philosophy emphasises problem-based learning, real-world applications, and the integration of research-led content into the classroom.
His teaching spans both core engineering fundamentals and advanced energy system applications, including:
- Thermo-Fluid and Transport Processes – Fluid mechanics, heat and mass transfer, and their application in engineering systems
- Process & Systems Modelling – Mathematical modelling, system dynamics, and simulation of engineering and energy systems
- Sustainable Energy Systems for Buildings – Heat pumps, thermal energy storage, and renewable energy integration
- Sustainable Materials for Energy and Building Applications – Advanced materials including phase change materials (PCM), thermochemical storage materials, and smart materials for improving energy efficiency and flexibility
- Energy Systems Modelling & Simulation – Modelica, FMU-based co-simulation, and Python-based frameworks
- Optimisation & Control – Model predictive control (MPC), multi-objective optimisation, and decision-making under uncertainty
- AI in Energy Systems – Machine learning and data-driven methods for smart and adaptive energy systems
- Smart Buildings & Energy Flexibility – Digital twins, demand-side management, and building-to-grid interaction
Dr. Saffari is committed to equipping students with both strong theoretical foundations and practical, industry-relevant skills, preparing them to address real-world challenges in energy, sustainability, and climate innovation.