Find Academic Supervisors

• Data Security and Privacy
• Privacy-Preserving Technologies
• Cyber-Physical Systems (CPS)
• +3 more

TASIDOU Aimilia is an Associate Professor at CESI, focusing on Security and Privacy by Design in Intelligent Infrastructures. She leads the Engineering and Numerical Tools research team, addressing challenges in privacy-preserving data extraction, CPS architecture, and decision-making systems. Her work aligns with EU regulatory standards and emphasizes practical applications in smart services and critical infrastructure. Education: PhD in Electrical and Computer Engineering (2015), Democritus University of Thrace MSc in Artificial Intelligence (2006), University of Edinburgh Diploma in Informatics (2005), University of Piraeus Research Interests: Aimilia explores privacy frameworks for smart infrastructures, including Privacy-by-Design principles, cybersecurity in microgrids, and data anonymization techniques. She also investigates the economics of personal data and its implications on fair data transactions. Her work bridges theoretical foundations with real-world implementations, such as privacy-preserving parking solutions and secure VoIP systems. Publications: Her recent work emphasizes privacy solutions compliant with EU legislation (e.g., GDPR), optimal allocation of privacy budgets in differential privacy, and enhancing security in telecommunication systems. Her 2021 paper on CPS architectures and 2022 study on microgrid networks highlight her contributions to resilient infrastructure design. Labs/Teams: As part of CESI’s Engineering and Numerical Tools team, she collaborates on projects like HArMoNICS (high-assurance microgrid systems) and PRISM (privacy safeguards for smart services). Past projects include myVisitPlanner GR , a personalized tourism platform, and studies on cultural heritage sustainability.

Eerika BorgentorpView profile

Researcher

• Smart Buildings
• Sustainability
• Real Estate Economics
• +5 more

Eerika Borgentorp is a Visitor (Faculty) in the Department of Built Environment and Real Estate Economics at Aalto University. Her academic background includes a Doctor of Science (Technology) from Aalto University School of Engineering (2023), a Master's degree in Engineering (2018), and earlier technical degrees. She has conducted extensive research on smart buildings, sustainability, energy efficiency, and real estate economics. Her research focuses on Smart Readiness Indicator (SRI) applications, green building performance, and low-carbon urban development. She has contributed to over 15 peer-reviewed publications and led the Smart Ready Buildings for People and Resource Flow in Sharing Cities project. She currently participates in the Green Asset Debt & Bond Platform (GADB) project exploring real estate markets' financial mechanisms. Professional activities include visiting research positions at Singapore University of Technology and Design (2023), University of California, Berkeley (2022-2023), and speaking engagements at international conferences. Her work bridges academic research with industry applications through studies on smart building profitability, EU policy implementation, and cold climate sustainability. Media coverage highlights her contributions to smart building advancements, including analysis of Europe's most intelligent buildings and energy transition strategies. Her research emphasizes practical solutions for achieving UN Sustainable Development Goals related to sustainable cities and climate action.

• Magnetic Field Engineering
• Magnetic Tunnel Junction Sensors
• Magnetoresistive Sensors
• +3 more

Wing Tat Pong is an Associate Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT). His research focuses on magnetic field engineering, magnetoresistive sensors, and low-frequency noise reduction in advanced materials. He has conducted extensive work on magnetic tunnel junction (MTJ) sensors and their applications in power systems and renewable energy. His research has been supported by two federal grants from the University Grants Committee, including studies on fault classification in power cables and improving MTJ sensor sensitivity through low-frequency noise analysis. Pong has co-authored over 200 publications, contributing to IEEE Transactions and other journals, with an h-index of 37 and 2,990+ citations. Key research areas include magnetic field sensing for wireless EV charging, anti-interference current sensing, and economic feasibility of community microgrids. His work bridges theoretical advancements in magnetic materials with practical applications in energy systems and power electronics. No lab or team affiliations were explicitly stated in the provided information.

Bamidele AdebisiView profile

Professor

• Smart Grids
• Internet of Things (IoT)
• Smart Cities
• +3 more

Professor Bamidele Adebisi is a Professor in Intelligent Infrastructure Systems and Head of the Smart Infrastructure and Industry Research (SIIR) Group at Manchester Metropolitan University's Department of Engineering. He has a PhD in Communication Systems from Lancaster University and holds roles such as Director of the African Hydrogen Partnership Trade Association and member of the Manchester Fuel Cell Innovation Centre. His research focuses on integrating sensing, communication, and data analytics into critical infrastructure like energy systems, transport, and smart cities. Awardees include the MBE for services to Knowledge Transfer and multiple industry collaboration awards. Education: B.Sc. Electrical Engineering (Ahmadu Bello University), M.Sc. and Ph.D. in Communication Systems (Lancaster University). Notable projects include leading the £29M EU-funded Triangulum smart cities project and the £10M CityVerve initiative. He has secured grants exceeding £45M across multi-country collaborations. Research interests span IoT, smart grids, peer-to-peer energy trading, and hydrogen energy. Board Member, African Hydrogen Partnership Visiting Professorships at University of Johannesburg and Afe Babalola University Editorial roles in IET Smart Cities, IEEE journals, and others Key contributions include innovations in cybersecurity for IoT, KTP award-winning projects, and academic leadership in smart infrastructure. His work bridges academia and industry, emphasizing sustainable energy and infrastructure solutions.

• Artificial Intelligence
• Reinforcement Learning
• Internet of Things (IoT)
• +4 more

Dr. Qingzhi Liu is an Assistant Professor in the Information Technology Group at Wageningen University & Research, Netherlands. He holds a Ph.D. from Delft University of Technology (2016) and completed postdoctoral research at Eindhoven University of Technology (2016-2019). His expertise spans artificial intelligence, reinforcement learning, IoT, precision agriculture, and smart greenhouse systems. He previously worked at NEC China in 2009. Research Interests: Liu’s work focuses on applying machine learning techniques to agricultural challenges, IoT infrastructure optimization, and energy-efficient computing. His projects include crop classification using drone imagery, smart greenhouse climate modeling, and blockchain-based IoT security. He also explores edge computing and containerized cloud resource management for real-time applications. Publications: Over 30 peer-reviewed articles in top venues like IEEE TPDS, TITS, and TVT. Recent work covers reinforcement learning applications in microgrids, privacy-aware cloud scheduling, and hyperspectral disease monitoring in crops. Teaching: Involved in courses such as Big Data (INF33806), Artificial Intelligence (INF36306), and Advanced Machine Learning (FTE40306). Labs/Teams: Active contributor to the Information Technology Group, focusing on AI-driven solutions for agriculture and IoT ecosystems.

Nimsiri AbhayasingheView profile

Senior Lecturer

• Inertial Measurement Unit (IMU) Applications
• Human Gait Modeling and Analysis
• Sensor Data Processing
• +3 more

Nimsiri Abhayasinghe is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computer and Mathematical Sciences. Their work focuses on inertial measurement units (IMUs), human gait modeling, and sensor-based systems for navigation, robotics, and biomedical applications. They are affiliated with the Faculty of Science and Engineering and contribute to the Office of the Provost's initiatives. Research interests include IMU calibration techniques, wearable sensor algorithms, and IoT-enabled assistive technologies. Notable contributions involve developing cost-effective IMU systems for navigation research, validating thigh angle estimation accuracy using optical motion capture, and creating gesture recognition systems for sign language. Publications span topics like human gait phase recognition, RPM detection using ignition pulses, and solar microgrid designs. Their work bridges mechanical engineering, computer science, and biomedical applications, emphasizing practical sensor integration and algorithmic innovation. No scientific awards are listed, but their research demonstrates expertise in sensor data analysis and interdisciplinary engineering solutions. Advising and grant details are not explicitly provided in the profile. They are based at Curtin Perth's New Technologies Building, Room 329.

Rosa KappertView profile

Researcher

• Energy Transition
• Sustainable Energy Systems
• Energy Data Analysis
• +3 more

Rosa Kappert is a researcher at Hanze University of Applied Sciences' Centre of Expertise Energy, specializing in system integration challenges within the energy transition. She holds a PhD in Nuclear and High Energy Physics from the University of Groningen (2022) and has additional degrees in Mathematics and Physics. Her work focuses on modeling complex energy systems, analyzing energy data, and addressing issues like network congestion and energy carrier synchronization. Education: Doctor of Philosophy (2017–2022), University of Groningen Master of Science in Physics (2013–2016), University of Groningen Bachelor of Science in Mathematics and Physics (2010–2013), University of Groningen Research Interests: Rosa combines her expertise in physics and mathematics to develop solutions for sustainable energy systems. Her work aligns with UN SDGs 7 (Affordable Clean Energy) and 13 (Climate Action), addressing topics like grid optimization, industrial energy hubs, and community-level energy management. Recent projects include the Groningen Stroomt Door pilot and the MODES market organization initiative. Key Projects (2022–2024): FLXPSTS: Flexposts (2022–2025) Groningen Stroomt Door (2022–2024) SMLLND - FS I: Regiodeal (2022–2024) Awards: 2024 recipient of the 'Pitch en poster met de meest helder impact' award for clear communication of energy system challenges. Grants & Activities: Co-principal investigator in multiple energy transition projects. Active in national and international conferences (e.g., 'Just and Inclusive Energy Transition' 2023) and community initiatives like the Stichting The Green Shift (Chair since 2018). Labs/Teams: Core member of the Hanze Centre of Expertise Energy, collaborating with academic and industry partners on pilot projects and data-driven solutions.

Marie-Cécile ALVAREZ-HERAULTView profile

Associate Professor

• Smart Grids
• Electrical Distribution Networks
• Renewable Energy Integration
• +3 more

Marie-Cécile ALVAREZ-HERAULT is an Associate Professor at Grenoble Institute of Technology, specifically at the National School of Energy, Water and Environment (ENSE3). She leads the Electrical Energy research master's degree and the Power Systems option of the Electrical Energy Engineering program. As a member of the SYREL research team at G2Elab laboratory, she conducts significant research on Smart Grids and electrical distribution networks. Education: Engineering degree from ENSIEG-INP (Grenoble Institute of Technology), 2007 Doctorate in Electrical Engineering from INPG (Institut National Polytechnique de Grenoble), 2009 Dr. ALVAREZ-HERAULT's research focuses on developing future electricity networks that are accessible, economical, and reliable. Her work specifically addresses Smart Grids as key solutions for integrating renewable energies while maintaining grid stability. She investigates new distribution network architectures, stochastic optimization of investment choices, and the impact of flexibility mechanisms on network planning. Her research has practical applications in both urban and rural contexts, with recent work emphasizing rural electrification in developing countries. Her extensive publication record from 2008-2025 demonstrates a clear evolution in focus from traditional distribution network architectures toward innovative solutions for high renewable penetration. Recent work shows strong emphasis on rural electrification, microgrid planning, and managing uncertainty in distribution system planning. Her research spans both AC and DC distribution systems, with case studies in Cambodia and Africa highlighting practical implementations of her theoretical work. Industrial Collaborations: KIC INNOENERGY (Smart Power project, Sweden, 2010-2014) Schneider Electric (patent development, since 2010) GEG (Greenlys Smart Grids demonstrator project, since 2011) ERDF (distribution network chair, since 2013) RWTH Aachen (EVOLVDSO European project, since 2013) Dr. ALVAREZ-HERAULT teaches various courses at ENSE3 covering electrical equipment implementation, network construction, transformers, and advanced smart grid functions. Her teaching directly reflects her research expertise, providing students with practical knowledge of modern power systems challenges and solutions. She is actively involved in the SYREL research team at G2Elab, which focuses on the integration of renewable energies into electrical networks. Her work bridges theoretical research with practical industry applications through multiple ongoing collaborations with major energy companies and participation in European research projects.

Qing-Chang ZhongView profile

Professor

• Power Electronics
• Smart Grids
• Renewable Energy Integration
• +2 more

Dr. Qing-Chang Zhong is the Max McGraw Endowed Chair Professor of Energy and Power Engineering and Management at Illinois Institute of Technology's Armour College of Engineering, with joint appointment in Electrical and Computer Engineering. As founder/CEO of Syndem LLC, he leads research in smart grid architectures, power converter control, and renewable integration, with seminal contributions to Virtual Synchronous Machine (VSM) technology cited in U.S. Congressional hearings. Education includes dual PhDs: Control and Power Engineering from Imperial College London (2004) and Control Theory from Shanghai Jiao-Tong University (2000), complemented by MSc (Hunan University, 1997) and engineering diploma (Xiangtan Institute, 1990). Research develops power-electronics-enabled autonomous power systems via the SYNDEM (Synchronized-and-Democratized) architecture. Core innovations include universal droop control, self-synchronized inverters, and bounded stability frameworks. Work fundamentally addresses grid stability in converter-dominated renewable-rich systems through novel control paradigms. Publications show consistent focus on grid-forming control strategies across 200+ papers. Recent works emphasize experimental validation and practical implementations, while foundational contributions established VSM architectures. The trajectory demonstrates evolution from theoretical frameworks to field-deployable solutions for next-generation grids. Honors include IEEE and IET fellowships, with inventions recognized as "game changers" for grid modernization. As IEEE Standard 2988-2024 chair, developed the first international VSM specifications. Student researchers received IET Dissertation Awards and Chinese National Outstanding Student awards under his mentorship. Entrepreneurial leadership includes commercialization through Syndem LLC, securing federal grants for VSM product development. Policy impact includes technical advisory roles for UK Grid Code changes and U.S. DOE initiatives on grid-forming technologies.

• Mathematical Optimization
• Power System Operation and Control
• Microgrids
• +3 more

Miguel Ángel Ríos Ocampo is a Researcher at Comillas Pontifical University’s Institute for Research in Technology (IIT), School of Engineering (ICAI). He is a Ph.D. candidate in electrical energy, focusing on energy systems modeling for sustainable transitions. His current role involves researching microgrids, power system operation, and renewable energy integration. He is also a member of the Energy and Poverty Chair. Education: B.Sc. and M.Sc. in Electrical Engineering from the Technological University of Pereira (UTP), Colombia. Ph.D. candidate in Electrical Energy at Comillas Pontifical University. Research Interests: Mathematical optimization of power systems, microgrid control, renewable energy integration, sustainable energy policies, and energy justice. His work bridges technical and societal aspects of energy transitions. Key Projects: "Assessment of Time and Cost Dynamics in Metropolitan Transport" (2025). "Indicators of Energy Poverty, Spain 2022" (2023). Professional Activities: Organized events like the "LivingLab Forum against Energy Poverty" (2025) and presented at conferences such as the European University Institute’s Climate, Energy and Environmental Justices workshop (2023). Labs/Teams: Active in the Energy and Poverty Chair, focusing on interdisciplinary solutions to energy poverty and sustainable transitions.

Udaya AnnakkageView profile

Professor

• Power System Control and Stability
• Electrical Energy Systems
• Power Systems
• +5 more

Dr. Udaya Annakkage is a Professor in the Department of Electrical and Computer Engineering at the University of Manitoba. He holds a PhD from the University of Manchester (UK) and has over 30 years of experience in teaching, research, and consulting. His research focuses on power system control and stability, electrical energy systems, and renewable energy integration. Dr. Annakkage has served as Head of the Department of Electrical and Computer Engineering (2008–2012 and 2020–2021) and was an editor of IEEE Transactions on Power Systems (2009–2012). He has supervised over 20 PhD students and has contributed extensively to IEEE and CIGRE working groups. Education: PhD, University of Manchester, UK (1987) MSc, University of Manchester, UK (1984) BSc (Eng.), University of Moratuwa, Sri Lanka (1982) Research Interests: Dr. Annakkage specializes in power system dynamics, stability analysis, renewable energy integration, grid-forming inverters, and advanced control strategies for power systems. His work emphasizes enhancing grid resilience, improving transient stability, and addressing challenges in inverter-dominated networks. Publications: His recent work explores topics such as grid-forming converter control, microgrid stability, and oscillation analysis in power systems. These contributions highlight advancements in renewable energy integration and dynamic system modeling. Grants & Advising: While currently not offering graduate student opportunities, Dr. Annakkage has a distinguished record of mentoring PhD and MSc students. His research has been supported by grants focusing on power system innovation and sustainability. Labs & Teams: Collaboration with IEEE and CIGRE underscores his involvement in industry-relevant research. Key projects include co-simulation platforms for real-time security assessment and stability analysis tools for large-scale power systems.

• Database Systems
• Software Engineering
• Data Integration
• +3 more

Roger King is a seasoned researcher with over 40 years of contributions to computer science, particularly in database systems, software engineering, and data integration. His work spans heterogeneous database management, semantic modeling, and distributed systems, often collaborating with leading institutions like University of Colorado and Springer. 1987: Co-authored foundational paper on semantic database modeling in ACM Computing Surveys 1992: Developed FaceKit database interface design toolkit 1994: Pioneered DIRECT query facility for multiple databases Research Interests: King's work focuses on database integration , semantic interoperability , and self-adaptive systems . Notable projects include Sybil for database evolution, Cactis for object-oriented databases, and COIL mediator definition language. Key Trends: His 15 most recent publications (2024-1999) address challenges in smart data systems , autonomous systems performance , and microgrid control , reflecting sustained expertise in data semantics and system architecture.

Jie XuView profile

Professor

• Artificial Intelligence
• Data Science
• Stochastic Optimization
• +6 more

Jie Xu is a Professor in the Department of Systems Engineering and Operations Research (SEOR) at George Mason University, with affiliations in the Department of Computer Science and Department of Statistics. His research focuses on algorithmic advancements in artificial intelligence, digital twin simulation, data science, stochastic optimization, and risk analytics, with applications in transportation, power systems, healthcare, and semiconductor manufacturing. He has led NSF-funded projects on bus fleet electrification, EV infrastructure, and human digital twin modeling. Previously, he served as President of the INFORMS Simulation Society (2022-2024) and as an Associate Editor for multiple journals. Education : PhD in Industrial Engineering (Northwestern University), MS in Computer Science (SUNY Buffalo), ME in Communications (Shanghai Jiao Tong University), BS in Electrical Engineering (Nanjing University). Research interests include digital twin-based optimization, Bayesian optimization, Monte Carlo tree search, and reinforcement learning. He has developed methodologies for cloud computing, EV grid integration, and cyber-physical systems resilience. Recent work emphasizes real-time simulation learning and DDDAS for energy systems. His NSF grants include the $1.5M CREATE project for transit electrification and FDT-BioTech for neurophysiological modeling. He teaches courses on stochastic simulation, predictive analytics, and optimization. Grants include funding from NSF, DOE, and ONR, totaling over $3M. Collaborations span universities, national labs, and industry partners.

Keigo HirakawaView profile

Professor

• Signal Processing
• Image Processing
• Digital Cameras
• +3 more

Keigo Hirakawa is a full-time Professor and Bernhard Schmidt Chair in Engineering Leadership at the University of Dayton's School of Engineering, Department of Electrical and Computer Engineering. He holds a joint appointment with the Electro-Optics and Photonics program. His academic journey includes a Ph.D. from Cornell University (2005), an M.S. from Cornell (2003), a B.S. from Princeton University (2000), and a Master of Music in Jazz Studies/Piano Performance from the New England Conservatory (2006). His research focuses on signal and image processing, statistical modeling, color image processing, and digital camera pipeline optimization. He is actively involved in professional activities such as serving as an Associate Editor for SPIE's Journal of Electronic Imaging and IEEE Transactions on Image Processing , and participates in the IEEE Image, Video, and Multidimensional Signal Processing Technical Committee. Recent work emphasizes event-based sensing, noise reduction in imaging systems, and advanced spectral imaging techniques. His research has led to innovations like Fourier multispectral imaging and Kalman filter-based particle velocimetry. He teaches courses such as ECE 203, 215, 340, 445, and graduate-level ECE 503 and 595. His laboratories focus on developing next-generation imaging systems and sensor technologies, with applications in aerospace, cybersecurity, and biomedical imaging. Collaborations span industry and academia to address challenges in real-time data processing and high-fidelity image reconstruction.

• Artificial Intelligence
• Reinforcement Learning
• Internet of Things (IoT)
• +5 more

Dr. Qingzhi Liu is an Assistant Professor at the Information Technology Group within Wageningen University & Research in the Netherlands. He holds a Ph.D. from Delft University of Technology (2016) and postdoctoral research experience at Eindhoven University of Technology (2016-2019). His research focuses on AI-driven solutions for precision agriculture, IoT systems, and edge computing. He teaches courses including Big Data (INF33806), Artificial Intelligence (INF36306), and Advanced Machine Learning (FTE40306). Research interests include reinforcement learning applications in microgrid energy management, deep learning-based crop classification using UAV imagery, and blockchain-enhanced IoT security frameworks. He has published in top venues like IEEE TPDS and IEEE TITS, addressing challenges in smart agriculture, distributed cloud scheduling, and energy-efficient computing. His work integrates computer vision techniques for agricultural monitoring (e.g., plant stem occlusion inpainting), low-code platforms for agri-tech development, and secure IoT data fusion methods. He actively contributes to interdisciplinary projects at the intersection of IT and life sciences.