• Green and energy-efficient computing, energy informatics
• Parallel and distributed computing systems, cyber-physical systems
• Parallel programming, concurrent data abstractions, programming systems, runtime systems
• Dependable computing systems
• Intelligent systems

Chiara Bordin is Associate Professor with a focus on teaching and research within the Energy Informatics domain.

Her main research interests are related to mathematical optimization in the context of computer science applied to smart energy and power systems. This refers in particular (but is not limited) to: models for storage integration and storage technologies assessment; strategic network design, expansion and operation; power systems reliability oriented network restructuring and reconfiguration; multi-agent systems for microgrids coordination; stochastic multihorizon optimization; optimal management of electric vehicles and charging sites; integration of machine learning methodologies in the context of mathematical modelling.

Mathematical modelling and optimization is a strong interdisciplinary and versatile subject. By combining it with computer science, power systems engineering, economics, big data analytics and machine learning, it is possible to address many research questions within the energy and power systems field, enhance analyses and look at the studied systems from different perspectives. This can provide key methodological and analytical contributions to the young and dynamic research area of Energy Informatics, with particular regard to the two major research themes of “smart energy-saving systems” and “smart grids”. 

Member of the Arctic Centre for Sustainable Energy (ARC): ARC Website

Member of the Aurora Center MASCOT (Mathematical Structures in Computation): MASCOT Website

Projects: Smart Senja, TENORS

Interview for the Springer Nature Journal

Interview for the AIMMS community

Google Scholar

Linkedin

Member of the editorial board of the Energy Informatics Journal by Springer Open

Member of the editorial board of the Discover Applied Science Journal by Springer Nature

I was pleased to be one of the guest editors of the special issue titled “Smart and Sustainable Energy Hubs for a Future Integrated Energy System” published in the Energies Journal by MDPI.

Member of the technical program committee of the following conferences:

- Energy Informatics.Academy Conference (EI.A)

- DACH+ Energy Informatics Conference

- KES Sustainability in Energy and Buildings Conference

my research interest are exploiting high performance network comunication as well as emerging hardware to accelerate machine learning techniques.

• 5G, Networking & Communication, Network Function Virtualization (NFV), Network Slicing
• Cloud Computing, Edge Computing, Datacenter & Distributed System
• Green Computing, Energy Efficiency Optimization, Renewable Energy
• Machine Learning (especially Deep Reinforcement Learning)