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Andrea VinciView profile

Researcher

• Quantum Computing
• Edge-Cloud Computing
• Internet of Things (IoT)
• +5 more

Andrea Vinci is an accomplished researcher with 66 publications and 1,261 citations, specializing in the intersection of quantum computing, edge-cloud architectures, and Internet of Things (IoT) systems. His work demonstrates significant contributions to solving complex computational problems through innovative approaches that bridge theoretical quantum algorithms with practical distributed computing applications. His research interests span quantum computing applications for resource management, multi-density clustering techniques for urban analytics, and platform-independent IoT application development. Vinci has pioneered work in variational quantum algorithms for cloud/edge resource allocation, quantum kernels for IoT data classification, and distributed AI for cognitive building systems. His research demonstrates a consistent focus on addressing NP-hard problems through quantum-classical hybrid approaches. Analysis of Vinci's publication trends reveals a strategic research trajectory moving from foundational work in smart city analytics and crime prediction toward cutting-edge quantum computing applications for IoT and edge-cloud systems. His recent publications (2023-2025) show increasing focus on quantum machine learning techniques specifically tailored for IoT data processing, with significant attention to practical implementation challenges. Vinci maintains an extensive collaborative network, frequently publishing with researchers including Fabrizio Marozzo, C. Mastroianni, J. Settino, and Antonio Guerrieri across multiple high-impact venues including IEEE Transactions, ACM conferences, and specialized journals in quantum computing and distributed systems. His technical contributions include the development of the COGITO platform for cognitive buildings, novel approaches to multi-density crime prediction, and significant advancements in quantum kernel methods for IoT data analysis. Vinci's tutorial publications indicate his role in educating the broader research community about emerging quantum computing applications for distributed systems.

• Heat Network Optimization
• Additive Manufacturing
• Heat Exchanger Design
• +5 more

Maarten Blommaert is an Assistant Professor at the Department of Mechanical Engineering, Faculty of Engineering Technology at KU Leuven. He leads the Applied Mechanics and Energy conversion (TME) unit at the Geel Campus and heads the Subdivisie EnergyVille TME. His research focuses on numerical optimization of thermal systems, particularly district heating networks, additive manufactured heat exchangers, and plasma-facing components for nuclear fusion reactors. Assistant Professor, KU Leuven Head, Subdivisie EnergyVille TME Member, KIES Institute Member, Leuven.AM Institute Member, EnergyVille Blommaert's research explores three main areas: heat network optimization through automated design tools like PATHOPT, additive manufacturing of high-performance heat exchangers, and thermally resistant wall modules for nuclear fusion reactors. His work combines computational modeling with advanced manufacturing techniques to enhance energy efficiency and reduce carbon emissions. Scientific awards include collaborative research contributions in: Optimizing district heating networks for renewable energy integration Developing next-generation heat exchangers Advancing nuclear fusion reactor technology Blommaert actively supervises research projects in thermal-fluid systems and collaborates with institutions like VITO and EnergyVille. His research team IDEAL (Innovative Design for Energy Applications Lab) specializes in free-shape and topology optimization techniques for energy components and systems.

• Power Systems Engineering
• HVDC Grid Technology
• Renewable Energy Integration
• +2 more

Hakan Ergun serves as an Associate Professor at KU Leuven's Faculty of Engineering Science within the Department of Electrical Engineering (ESAT). He leads the Subdivisie EnergyVille Electa - Ergun and holds key roles in EnergyVille initiatives, including membership in the Division EnergyVille and the Council of the Faculty of Engineering Science. His research focuses on power systems engineering with specialization in HVDC grid technology, renewable energy integration, and stochastic optimization. Current projects include predictive maintenance for wind farms, congestion management for offshore HVDC grids, and development of hybrid AC/DC grid software tools. His work addresses critical challenges in grid resilience, uncertainty modeling, and multi-national offshore grid coordination. Recent publications demonstrate strong trends in hybrid AC/DC grid optimization under uncertainty, with emphasis on stochastic programming, polynomial chaos expansion, and risk-based operational models. Key themes include offshore grid protection, frequency stability with energy storage, and spatio-temporal variability in power system planning. Ergun actively supervises doctoral candidates including K. Phillips and C.K. Jat. His research portfolio includes significant EU-funded projects such as CROCODILE (Cross-border Coordination of Offshore Grids) and advanced HVDC grid development initiatives with multi-year funding through 2028-2029. He directs the EnergyVille Electa subdivision focused on electrical energy systems applications, collaborating with industry partners on real-world grid implementation challenges. Current work emphasizes practical solutions for multi-GW offshore energy hubs and resilient power systems leveraging HVDC transmission flexibility.

• Additive Manufacturing
• Materials Science
• Metallurgy
• +22 more

Jean-Daniel Penot is a Researcher at CESI's Research and Innovation Department , with expertise in additive manufacturing, materials science, and industrial integration. His work bridges advanced manufacturing technologies with environmental sustainability and educational innovation. Doctorate in Materials Physics (2010) Engineering Degree in Physics (2007) Research Master in Optoelectronics (2007) Penot's research spans Additive Manufacturing and its applications in automotive, nuclear, and construction sectors. He focuses on Laser-Material Interaction , Machine Learning for process optimization, and Sustainable Engineering through life cycle assessments and geopolymer applications. His recent publications emphasize BIM , AM Modular Plants , and Defect Analysis in 3D-printed metals. Penot leads France Additive initiatives and contributes to International Standards as a board member. Penot supervises PhD students including Maryam Houhou and Amal Khabouchi , with a focus on Industrial Security and Energy Transitions . His projects integrate Thermal Comfort , Ultrasonic Inspection , and Quality Assurance in additive manufacturing systems.

Sajjad Fattaheian DehkordiView profile

Researcher

• Power Systems Engineering
• Smart Grids
• Renewable Energy Integration
• +3 more

Sajjad Fattaheian Dehkordi is a Postdoctoral Researcher in the Department of Electrical Engineering and Automation at Aalto University, Espoo, Finland. His research focuses on advanced energy management systems for modern power grids, with emphasis on distributed and transactive control approaches for resilient and efficient grid operations. His core research interests include: Power system resilience under high renewable penetration Microgrid and energy community optimization Distributed energy resource integration Electric vehicle-grid interaction and V2G systems Real-time congestion and ramping management Analysis of his 2022-2024 publications reveals a dominant trend toward multi-agent transactive frameworks addressing grid stability challenges. His work consistently targets voltage regulation, asymmetrical power flows, and ramping events in distribution systems, leveraging optimization techniques like MILP while incorporating flexibility concepts for renewable integration. Key innovations include distance-driven P2P/P2G transactions and incentive-based congestion management. No scientific awards are documented in the available records. Information regarding student advising, research grants, or leadership roles is not provided in current documentation.

Valentina CecchiView profile

Associate Professor

• Electric power systems modeling and analysis
• Transmission and distribution system optimization
• Grid-enhancing technologies
• +4 more

Valentina Cecchi is Associate Professor of Electrical and Computer Engineering and Associate Director of the same department at the University of North Carolina at Charlotte (UNC Charlotte), where she has been a faculty member since 2010. She previously served as Graduate Program Director and Associate Chair of the department from 2019 to 2024. Education background: Ph.D. in Electrical Engineering, Drexel University, Philadelphia, PA Research interests center on electric power systems modeling and analysis, with particular emphasis on optimization of transmission and distribution system planning and operation, grid-enhancing technologies, dynamic line rating of transmission lines, and the integration of renewable and distributed energy resources. Her work spans power system protection, resilience, data-driven analytics, and pedagogical innovation in power engineering education. A consistent thread in her recent publications (2023-2025) is the application of advanced analytics and machine learning to improve real-time monitoring, protection, and restoration of active distribution networks. A complementary focus is the development and evaluation of modern educational methodologies to prepare students for emerging challenges in power and energy systems. Scientific awards: William States Lee College of Engineering Graduate Teaching Excellence Award (2022) Advising & grants narrative: While specific PhD/Master’s students are not listed in the provided text, Dr. Cecchi’s service as Graduate Program Director and her active publication record with student co-authors suggest significant mentoring activity. She has led NSF-supported curriculum updates and educational research efforts, and her work on distribution system resilience, renewable integration, and protection coordination has been funded by multiple agencies and industry partners. Laboratory & teams: Dr. Cecchi is affiliated with the EPIC building (Energy Production and Infrastructure Center) at UNC Charlotte, specifically office 1224, and contributes to the university’s power and energy systems research infrastructure.

Vassilios AngelidisView profile

Professor

• Power Electronics
• Renewable Energy Sources
• Electrical Power Systems
• +1 more

Professor Vassilios Angelidis is a distinguished academic in the field of Electrical Engineering, currently serving as a Professor at the Department of Electrical and Computer Engineering of Democritus University of Thrace. He joined the university in June 2024, bringing with him extensive international experience from prestigious institutions including the University of Glasgow, University of Sydney, University of New South Wales (UNSW), and the Technical University of Denmark. Professor Angelidis received his educational foundation with a degree in Electrical Engineering from Democritus University of Thrace, followed by a Master of Applied Science from Concordia University in Canada, and a PhD from Curtin University in Western Australia. He further enhanced his expertise with an MBA from Curtin Graduate School of Business. His research interests span Power Electronics, Renewable Energy Sources, Electrical Power Systems, and Autonomous Electricity Networks. Professor Angelidis has made significant contributions to the development of advanced power conversion techniques, grid integration of renewable energy sources, and the application of artificial intelligence in power system analysis and prediction. His work has been instrumental in advancing the field of smart grid technologies and sustainable energy systems. An analysis of his recent publications reveals a strong focus on power electronics applications in renewable energy integration, particularly in photovoltaic systems and electric vehicle charging infrastructure. His research demonstrates expertise in developing advanced algorithms for power system monitoring and control, with particular emphasis on frequency estimation, phase angle calculation, and power quality enhancement in modern grids with high penetration of distributed energy resources. Among his notable scientific achievements, Professor Angelidis has been recognized as an IEEE Fellow for his significant contributions to power electronics and the conversion and integration of renewable energy sources into power grids. He has also received the prestigious Advanced Research Fellowship for young researchers from the Engineering and Natural Sciences Council of the United Kingdom. Throughout his career, Professor Angelidis has secured research funding from various organizations across Australia, the United Kingdom, Denmark, China, India, and Malaysia, as well as industry partners with global reach. He has served on the International Councils of Beijing Jiaotong University and Universiti Tenaga Nasional (UNITEN), and currently holds the position of Vice President-elect of the IEEE Power Electronics Community. At Democritus University of Thrace, Professor Angelidis is affiliated with the Electrical Machines Laboratory within the Energy Systems Sector, where he leads research on Control and Diagnostic Methods of Electrical Machines. His current work focuses on advancing the integration of renewable energy sources into electrical power systems while maintaining grid stability and reliability.

Vigdis VandvikView profile

Professor

• Plant and vegetation ecology
• Biodiversity
• Ecosystem responses to climate change
• +7 more

Professor Vigdis Vandvik at the University of Bergen (Department of Biological Sciences) is a leading community ecologist studying global change impacts on plants, biodiversity, and ecosystem functions. Her research spans three key areas: local-regional process interactions, environmental change scaling from individuals to ecosystems, and human land-use impacts. She directs the Between The Fjords Lab using macroecological experiments across Norway's Vestland Climate Grid and global networks. Key research systems: Alpine, grassland, heathland ecosystems Methodological focus: Experimental macroecology, field-lab integration Policy engagement: IPBES assessments, Norwegian Council on Ethics Her 15 most recent articles reveal trends in climate-vegetation interactions, functional trait analysis, and nature-climate policy linkages. Studies range from Arctic nutrient dynamics to alpine grazing mitigation and heathland carbon fluxes, emphasizing cross-scale ecological modeling and experimental frameworks. Current PhD/MSc projects include climate budget integration (ECOBUDGETS), mycorrhizal responses (FUNDER/DURIN), range expansion impacts (RangeX), and carbon flux dynamics (ThreeD/INCLINE). She actively promotes open science through GBIF ambassadorship and FAIR data initiatives. Labs/teams: Between The Fjords Lab, CeSAM Centre for Sustainable Area Management, Ecological and Environmental Change Research Group, bioCEED Center of Excellence in Biology Education. International collaborations span Norway, Europe, US, Uganda, Nepal, China, and Peru.

• Control Engineering
• Process Control
• Optimal Control
• +11 more

Torsten Wik is a Professor in Control Engineering at Chalmers University of Technology. He leads the Control Engineering research group and focuses on process control with theoretical and applied methodologies. Institution: Chalmers University of Technology Department: Control Engineering His research spans optimal control, model reduction, and systems with model uncertainties. Applications include energy-saving systems, environmental improvement, biological systems (water purification, recirculating fish farms, LED greenhouse lighting), and battery estimation/modeling/control. Recent work emphasizes battery degradation diagnosis, state estimation, fast charging, and reconfigurable systems. Key methodologies include physics-informed frameworks, machine learning integration, entropy-based predictive algorithms, and hypergraph modeling. Applications extend to electric vehicles, photovoltaic systems, fuel cells, and biofilm reactors. Publications highlight collaborations across engineering domains, focusing on control theory, electrochemical modeling, and real-time optimization. His work bridges theoretical advancements with industrial applications in energy systems, transportation, and sustainable agriculture.

• Construction Engineering
• Discrete-Event Simulation
• Industrial Construction
• +6 more

Yasser Mohamed is a Professor in the Civil and Environmental Engineering Department at the University of Alberta . His academic and professional focus revolves around construction engineering, discrete-event simulation, and process optimization for industrial and tunneling operations. He has also explored knowledge engineering techniques and the application of TRIZ (Theory of Inventive Problem Solving) to construction processes. Email: yaly@ualberta.ca Location: 7-269 Donadeo Innovation Centre For Engineering, Edmonton, AB Courses Taught: CIV E 603 (Construction Informatics), CIV E 606 (Design and Analysis of Construction Operations) His research emphasizes modeling construction processes using discrete-event simulation to optimize performance and develop synthetic environments for construction operations. Recent publications, however, indicate a shift toward power systems, focusing on DC microgrids , grid-forming converters , and renewable energy integration . Scientific Awards: None explicitly mentioned in the provided data. Advising and Grants: No formal advisees listed. A co-applicant on a CRD grant (2007–present) for synthetic environments in construction simulation.

Emily JensenView profile

Assistant Professor

• Control Systems
• Power Systems
• Robotics
• +3 more

Emily Jensen is an Assistant Professor in the Department of Electrical, Computer & Energy Engineering at the University of Colorado, Boulder. She specializes in the analysis and control of spatially-distributed systems with applications in power grids, satellite constellations, and bio-inspired robotics. Her work focuses on developing theoretical frameworks to optimize system performance under constraints such as communication limitations and nonlinear dynamics. Education: B.S. in Engineering Mathematics & Statistics, UC Berkeley, 2015 M.S./Ph.D. in Electrical & Computer Engineering, UC Santa Barbara, 2020 Professional Appointments: Postdoctoral Researcher at UC Berkeley (2022-2023) Postdoctoral Researcher at Northeastern University (2021) Her research interests center on optimal distributed control, system-level synthesis, and the interplay between system structure and controller design. Key projects include multi-timescale power network control, nonlinear wave dynamics in engineering systems, and distributed parameter systems with limited communication. Dr. Jensen has delivered invited talks at high-profile venues such as the International Symposium on Mathematical Theory of Networks & Systems (2024) and the System Level Synthesis Workshop (2022). She currently advises a team of graduate and undergraduate researchers, including Addie McCurdy, Andy Gusty, and Matt Baughman (co-advised with Prof. Hodge). Awards: UC Regents’ Graduate Fellowship (2016) Zonta Amelia Earhart Fellowship (2019) IFAC Conference Young Author Award Honorable Mention (2022) She teaches ECEN 3300 (Linear Systems) and ECEN 5738 (Nonlinear Control Systems) at CU Boulder. Her work has been published in IEEE journals and conferences, emphasizing theoretical contributions with practical engineering relevance.

Sai Mounika ErrapotuView profile

Assistant Professor

• Cybersecurity
• Privacy Preservation
• Smart Grid Security
• +6 more

Sai Mounika Errapotu is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). She leads the Cyber Physical Systems Privacy and Security Enhanced Computing (CyPSEC) Lab, focusing on developing practical security and privacy solutions for hardware and software systems in distributed networks, IoT, and smart grids. Her research integrates cryptography, differential privacy, and optimization to address emerging challenges in cyber-physical systems. Education: Ph.D. in Electrical and Computer Engineering (University of Houston, 2018), B.Tech. in Electronics and Communication Engineering (Jawaharlal Nehru Technological University, 2013). Postdoctoral work: AI, Networking Technologies, and Security Lab, University of Houston (2018–2019). Her research interests span cybersecurity, privacy-preserving protocols, trust modeling, and optimization in smart grids, IoT, and wireless networks. She emphasizes application-specific solutions that balance security, privacy, and scalability. Recent articles highlight advancements in intrusion detection via GANs and neural networks, smart home IoT security protocols, and privacy-preserving techniques in healthcare and transportation systems. Major Grants: $782,500 ARL grant for GAN-based intrusion detection, $1.1M DOE NNSA consortium for power systems, and $140K PNNL grant for healthcare synthetic data. Awards: Miguel Izquierdo Teaching Excellence Award (2021), Rising Stars Award, and Best Dissertation Award (2018). Advising highlights include mentoring students like Humaira (CPS Rising Star), Nicholas Lopez (M.S. grad in IoT security), and Ismael Holguin (LLNL intern). The CyPSEC Lab actively publishes in IEEE and NAPS conferences, addressing vulnerabilities in protocols like DNP3 and smart home IoT systems. Labs/Teams: CyPSEC Lab focuses on bridging theory and practice in CPS security, collaborating with industry partners and national labs.

• Scientific computing
• Computational mathematics
• Numerical methods
• +6 more

Christina C. Christara is a Professor in the Department of Computer Science at the University of Toronto, specializing in scientific computing and numerical methods. Her research focuses on numerical solutions of partial differential equations, high performance computing, parallel computation, and financial mathematics applications. She holds a Ph.D. in Computer Science from Purdue University (1988), an M.Sc. from Purdue (1986), and a B.Sc. in Mathematics from Aristotle University (1982). She has taught courses such as Numerical Methods for Optimization Problems (CSC466/2305), High-Performance Scientific Computing (CSC456-2306), and Numerical Algorithms (CSC436), emphasizing both theoretical and computational aspects. Her research interests span numerical weather prediction, computational finance, and advanced numerical techniques like spline collocation and penalty methods. She has supervised over 20 graduate students in topics ranging from GPU-accelerated PDE solvers to XVA pricing models. Her work often addresses challenges in computational efficiency and accuracy, with applications in engineering, finance, and environmental science. She is affiliated with the Numerical Analysis and Scientific Computing Group and actively contributes to high-performance computing methodologies.

• Applied Analytics
• Statistical Inference
• Time Series Analysis
• +7 more

Dr. Laleh Tafakori is a Senior Lecturer in the Department of Statistics and Analytics at RMIT University's School of Science. Her research focuses on the intersection of statistical modeling, machine learning, and their applications in healthcare, finance, and environmental science. She is affiliated with the university's City Campus and can be contacted at laleh.tafakori@rmit.edu.au . Her teaching interests include Applied Analytics , Statistical Inference , Time Series Analysis , Mathematical Statistics , Stochastic Processes , and Probability Theory . She actively supervises research projects in areas such as: Healthcare modeling (e.g., diabetes onset prediction, maternal risk assessment) Environmental data analysis (e.g., extreme precipitation estimation via satellite data) Financial risk analysis (e.g., Value-at-Risk forecasting, credit portfolio management) Machine learning applications in complex networks and smart grids Her recent research trends emphasize predictive modeling for public health challenges, leveraging advanced statistical techniques (copula models, functional volatility) and machine learning (CNNs, random forests). She collaborates with institutions worldwide, addressing issues like Saudi Arabia's healthcare indicators and European financial systemic risk. While no formal awards are listed, her work demonstrates impactful contributions to interdisciplinary data science. Dr. Tafakori has advised over 16 students on topics ranging from diabetes epidemiology to edge computing optimization. Her research outputs include 28+ peer-reviewed articles, with a focus on methodological innovation and real-world problem-solving. She maintains active engagement in collaborative projects without explicitly listed grants.

• Network Protocols Engineering
• Cybersecurity
• Distributed Systems
• +3 more

Klaus Wehrle is a Professor of Computer Science and Head of the Communication and Distributed Systems Group (Informatik 4) at RWTH Aachen University. He holds a diploma (1999) and doctorate (2002) from the University of Karlsruhe (now KIT). His research focuses on network protocols, cybersecurity, and distributed systems, funded by DFG, ERC, EU, and industry. He leads the DFG Priority Program on Cyber-Physical Networking and holds ERC grants. Awards include Südwestmetall and FZI Dissertation Prizes. He serves on IEEE, ACM, and DFG committees. His work spans protocol engineering, network simulation, and reliable communication software. He advises the Department of Computer Science at RWTH and collaborates on projects like In-Network Computing and Industrial IoT security. His research addresses industrial systems, smart grids, and privacy-preserving data sharing.