Fernando Bruno Dovichi Filho | Engineering | Best Researcher Award

Prof. Fernando Bruno Dovichi Filho | Engineering | Best Researcher Award

Professor, UNIFEI/UFSCAR, Brazil

Fernando Bruno Dovichi Filho 🇧🇷 is a Brazilian Mechanical Engineer with a Ph.D. in Mechanical Engineering, specializing in energy systems, renewable energy, and thermal modeling. With a rich blend of academic and research experience, he is currently a Substitute Professor at the Federal Institute of São Paulo (IFSP – Piracicaba campus). His work focuses on computational modeling, biomass energy, and sustainability-driven technologies, actively contributing to Brazil’s bioenergy development. Fernando’s background includes hands-on research in high-precision machining, hybrid propulsion, and energy conversion systems.

Profile

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Education 🎓

Fernando completed his Ph.D. in Mechanical Engineering (2017–2022) at the Federal University of Itajubá (UNIFEI), where he analyzed the technical and economic potential of electricity generation from biomass in Minas Gerais 🌱⚡. He earned his Master’s degree (2013–2015) at the same institution, refining thermal property estimation methods. His Bachelor’s in Industrial Mechanical Engineering (2008–2012) from ETEP Faculdades included a project on optical glass machining 🔧📐, showcasing his early inclination toward precision engineering and energy systems.

Experience 💼

With teaching and research roles across premier institutions, Fernando’s career spans from academia to aerospace research. Currently a full-time Substitute Professor at IFSP – Piracicaba (2023–present), he develops curricula, teaches engineering courses, and guides research and extension projects 🧑‍🏫📊. He previously served as a Substitute Professor at IFMS in 2016. As a PBIC/CNPq Research Fellow, he contributed to advanced propulsion research at both IAE and IEAv from 2009 to 2012, specializing in hybrid rocket engines, high-voltage discharges, and detonation studies using NASA CEA software 🚀💻.

Research Interest 🔍

Fernando’s research integrates renewable energy, thermal systems, and decision-making methodologies. His main focus is on biomass-based electricity generation, thermophysical property modeling, and multi-criteria decision analysis (MCDA) with GIS integration 🌍🧪. He is also keen on advancing thermal estimation techniques, applying hybrid modeling tools like MATLAB and EES, and evaluating the technology readiness of green energy solutions in Brazil and globally.

Awards 🏆

Fernando’s research integrates renewable energy, thermal systems, and decision-making methodologies. His main focus is on biomass-based electricity generation, thermophysical property modeling, and multi-criteria decision analysis (MCDA) with GIS integration 🌍🧪. He is also keen on advancing thermal estimation techniques, applying hybrid modeling tools like MATLAB and EES, and evaluating the technology readiness of green energy solutions in Brazil and globally.

Publications 📄

📖 Evaluation of TRL for biomass electricity technologies, Journal of Cleaner Production, 2021
DOI LinkCited in renewable energy feasibility studies worldwide.

📖 GIS-MCDM methodology for biomass selection, Agriculture, 2025
DOI LinkA key reference for geo-spatial biomass planning.

📖 An approach to technology selection, Energy, 2023
DOI LinkCited in works addressing clean technology prioritization.

📘 Book Chapter: From Crops and Wastes to Bioenergy, Woodhead Publishing, 2025

Publisher LinkCited by authors in sustainable agriculture and energy.

Conclusion

Based on his research achievements, publications, and experience, Fernando Bruno Dovichi Filho is a suitable candidate for the Best Researcher Award. His contributions to sustainable energy solutions and his expertise in thermal systems optimization and renewable energy systems demonstrate his potential to make a significant impact in the field. With some further emphasis on international collaborations and publishing in top-tier journals, he is well-positioned to continue making meaningful contributions to research.

Sarah Di Grande | Analytics | Best Researcher Award

Ms. Sarah Di Grande | Analytics | Best Researcher Award

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.

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Education 🎓

Sarah completed a Master’s 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 Bachelor’s 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 💼

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 🔬

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. Sarah’s work aims to enhance resource management and promote sustainability in smart cities.

Awards 🏆

Sarah has received recognition for her innovative contributions, winning the Start-Cup Sicilia 2023 for her work on the “Smart Knee Project,” a device aimed at diagnosing knee osteoarthritis. She also secured second place in the University of Catania’s Start-Cup competition for the same project.

Publications Top Notes📚

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].