PhD student, University of Catania, Italy
Sarah Di Grande is a driven researcher and data scientist currently pursuing a PhD in Systems, Energy, Computer, and Telecommunications Engineering at the University of Catania, Italy. With expertise in machine learning and a focus on sustainable water-energy optimization, she has contributed extensively to data science applications in renewable energy and smart city initiatives.
Profile
Orcid
Education š
Sarah completed a Masterās in Data Science for Management at the University of Catania in 2022, graduating summa cum laude with a thesis on unsupervised machine learning for photovoltaic systems. She also holds a Bachelorās degree in Business Economics from the same institution and graduated from Liceo Megara with top honors in 2017. Her studies have centered on advanced machine learning, big data, and data security.
Experience š¼
Currently, Sarah is a PhD student and researcher at the University of Catania, working in collaboration with Darwin Technologies on machine learning-based water-energy optimization. She previously interned as a data scientist at BaxEnergy, where she applied predictive maintenance techniques for photovoltaic panels, gaining hands-on experience in industrial data science applications.
Research Interests š¬
Her research is dedicated to leveraging artificial intelligence for sustainable energy systems, focusing on machine learning applications in hydropower forecasting, urban traffic prediction, and water distribution network optimization. Sarahās work aims to enhance resource management and promote sustainability in smart cities.
Awards š
Sarah has received recognition for her innovative contributions, winning the Start-Cup Sicilia 2023 for her work on the āSmart Knee Project,ā a device aimed at diagnosing knee osteoarthritis. She also secured second place in the University of Cataniaās Start-Cup competition for the same project.
Publications Top Notesš
Sarah has contributed numerous papers to international conferences and journals, exploring AI in hydropower, water distribution, and urban traffic management. Some key publications include:
“A Proactive Approach for the Sustainable Management of Water Distribution Systems” (2023) in 12th International Conference on Data Science, Technology and Applications – DATA [cited by 10 articles].
“Detection and Prediction of Leakages in Water Distribution Networks” (2023) in DATA 2023 [cited by 7 articles]
“A Machine Learning Approach for Hydroelectric Power Forecasting” (2023) in 14th International Renewable Energy Congress – IREC [cited by 5 articles].
“Data Science for the Promotion of Sustainability in Smart Water Distribution Systems” (2024) in Communications in Computer and Information Science, Springer [cited by 12 articles].