جست‌وجوی استاد و پژوهشگر

• Power Systems
• Distributed Energy Resources
• Smart Grids
• +۳ مورد دیگر

Gustavo Valverde Mora is a Lecturer at ETH Zurich's Power Systems Laboratory in the Department of Information Technology and Electrical Engineering. His research focuses on distributed energy resources, smart grid technologies, and power system control, with expertise in behind-the-meter DER integration and hosting capacity analysis. His recent work addresses key challenges in renewable energy integration, including voltage control coordination between transmission and distribution networks, data-driven local control schemes for active distribution grids, and unsupervised load disaggregation techniques using smart meter data. He has developed novel methods for DER modeling, GIS-based system analysis, and distribution network planning. Recognized with multiple awards including the 2022 Costa Rican National Technology Award, he actively contributes to IEEE Task Forces on DER integration. His research demonstrates strong emphasis on practical grid applications, combining theoretical power systems knowledge with advanced data analytics. Dr. Valverde teaches Power System Analysis (227-0526-00L) and maintains collaborations with utilities worldwide on renewable integration challenges.

• IoT-Systems
• Smart Energy Management
• NILM (Non-Intrusive Load Monitoring)
• +۴ مورد دیگر

Andreas Rumsch is a Lecturer at the Lucerne School of Engineering and Architecture, heading the Research Group within the Institute of Electrical Engineering IET iHomeLab. He holds a Graduate Engineer degree from ETH Zürich (1990) and an Industrial Engineering degree from STV Kaderschule St. Gallen (1995). His professional experience spans over three decades in software development, product management, and R&D leadership across industries like healthcare, manufacturing, and energy. Teaching focuses on Business Administration for Engineers , IoT Systems , and Smart Energy Management . Research interests include IoT-systems, NILM (Non-Intrusive Load Monitoring), smart energy forecasting, and cybersecurity in IoT. Notable projects include SWEET RECIPE , WILSON , and EVFlex , addressing smart energy systems and building management. Publications emphasize cybersecurity in data spaces, energy-aware IoT, and NILM algorithms. He actively participates in industry forums and has contributed to reports on IoT standards and interoperability architectures.

• Internet of Things
• Smart Cities
• Digital Transformation
• +۷ مورد دیگر

Bocchi Yann serves as an Ordinary Professor at HES-SO Valais-Wallis' School of Management within the Economy and Services faculty. His primary appointment resides in the Computer Science Institute where he leads research in Internet of Things, Smart Cities, and Digital Transformation. His work bridges technical innovation with practical urban applications through multiple EU and Swiss-funded projects. His research focuses on IoT architecture design, context-aware systems, and human-centered smart environments. Key contributions include nomadic sensing platforms for cost-effective smart city implementation, geo-aware security protocols for cross-border data exchange, and semantic middleware for heterogeneous technology integration. His work demonstrates particular expertise in translating theoretical IoT concepts into deployable urban solutions through the SmartSantander testbed and other large-scale validations. His publication portfolio reveals consistent focus on IoT interoperability (2014-2017), evolving toward human-centric applications (2015-2016) and energy-aware systems (2020). The research trajectory shows progression from foundational protocol development toward practical smart city implementations with emphasis on data valorization and user experience. As principal investigator, he has secured significant research funding including 820,415 CHF for the EU IoT6 project and 50,000 CHF for GeoTrust from the Hasler Foundation. His collaborative approach spans academic institutions, Swiss cantons, and industry partners including Nokia Research Labs and PostAuto Schweiz AG. He directs the Management Information Technology program while teaching Systems Modeling in the BSc HES-SO in Management Information Systems. His industry partnerships demonstrate strong technology transfer capability, particularly in tourism management systems and cultural heritage applications.

• Smart Energy Management
• Assisted Living
• Nonlinear Control Systems
• +۵ مورد دیگر

Andrew Paice is a Professor and Head of the iHomeLab at Lucerne School of Engineering and Architecture (HSLU), Switzerland. His research focuses on smart energy management, assisted living for the elderly, and IoT applications in building intelligence. He leads a team exploring human-building interactions through projects like NILM (Non-Intrusive Load Monitoring) and Assisted Living systems. Prior roles include Head of R&D at Schindler Elevator and ABB Switzerland, where he managed teams in control systems and product development. Education includes a BSc (Hons) in Applied Mathematics from the University of Western Australia and a PhD in Systems Engineering from ANU. Professional training includes strategic innovation management at IMD Lausanne. Research emphasizes AI-driven solutions for energy efficiency, elderly care technologies, and smart home systems. Notable projects include the SmartNIALMeter dataset and security frameworks for international data spaces. Over 30 technical publications span journals like Energies and IEEE, with industry patents in power systems and automation. Awards include invitations to Salon Suisse and contributions to initiatives like the AAL4All project. Collaborations with institutions like ETH Zurich and industry partners drive applied research in smart cities and sustainable building technologies.

• Energy
• Demand Side Management
• Non-Intrusive Load Monitoring
• +۳ مورد دیگر

Pierre Roduit is a Professor and Head of the Institut Energie et environnement at HES-SO Valais-Wallis. His expertise spans Energy Systems, Demand Side Management, and Machine Learning applications in sustainability. He leads research on smart energy solutions, including grid flexibility, non-intrusive load monitoring, and hydropower maintenance. Current projects include the EU-funded domOS (H2020) for smart building OS and the Innosuisse-backed Industrialisation of energy services for small buildings. His work integrates IoT and data science to enhance energy efficiency in residential and industrial contexts. Key Projects: GOFLEX (H2020), SEMIAH (FP7), Cavitation Monitoring System Focus Areas: Thermal Energy Storage, Predictive Maintenance, Smart Grids His research bridges academic innovation with industrial applications, advancing technologies such as NILM and acoustic-based turbine monitoring. Over 20 years, he has authored over 30 publications and secured €16M+ in EU and industry funding.

• Data Science
• Energy Systems
• Thermal Energy Storage
• +۲ مورد دیگر

Andreas Melillo is a Lecturer and Researcher at the Lucerne University of Applied Sciences and Arts within the Lucerne School of Engineering and Architecture. He is affiliated with the Institute of Mechanical Engineering and Energy Technology and the Competence Center for Thermal Energy Storage. Melillo holds an M.Sc. in Physics with a specialization in theoretical physics from the University of Bern. His research focuses on Data Science applications in energy systems , particularly in simulation, modeling, and data collection for thermal energy optimization. He teaches courses on Python for Data Science and Data Collection, Integration, and Preprocessing. Research projects include SWEET DeCarbCH TES, Smart Decentralized DHW, and GIASES, focusing on renewable energy integration and grid optimization. His publications primarily explore energy demand forecasting, building characterization, and multi-energy system modeling.

• Structural Health Monitoring
• Wind Energy
• Graph Neural Networks
• +۳ مورد دیگر

Dr. Gregory Duthé is a researcher at the ETH Zürich in the Structural Mechanics and Monitoring department. His work bridges computational modeling and structural diagnostics with applications in renewable energy systems. Research contributions include: Development of Graph Neural Networks for aerodynamic flow reconstruction Advancements in wake-induced load estimation for wind farms Innovations in unsupervised fault detection for offshore turbine systems Key publication trends show focus on physics-informed machine learning (2025), multi-agent infrastructure decision support (2025), and leading edge erosion modeling (2021). He combines graph-based architectures with structural health monitoring techniques across wind energy applications. Contact: duthe@ibk.baug.ethz.ch