Find Academic Supervisors

• Big Data Analytics
• Machine Learning in Oil and Gas Industry
• Signal Processing for Patient Monitoring
• +3 more

Mario Palendeng is an Adjunct Professor at Charles Darwin University's Faculty of Science and Technology, affiliated with the North Australian Centre for Oil and Gas (NACOG) and Energy and Resources Institute. He holds a PhD in Electrical and Electronics Engineering from the University of Queensland (2016). His research focuses on big data analytics, machine learning applications in energy sectors, and signal processing for healthcare monitoring. He leads projects like the 'Residential Inverter Testing Services at CDU Microgrid' (2022), addressing microgrid stability and renewable energy integration. Education: PhD, Electrical and Electronics Engineering, University of Queensland (2016) Research interests span cybersecurity in IoT smart cities, distributed microgrid control systems, and livestock age estimation via spectroscopy. His work contributes to UN Sustainable Development Goals related to affordable energy and sustainable agriculture. Recent publications explore smart city cyber attack prevention, inverter testing methodologies, and cattle age determination using reflectance measurements. Collaborations include interdisciplinary projects with industry partners.

Mohsen AziziView profile

Associate Professor

• Decentralized Control Systems
• Power Systems
• Renewable Energy
• +5 more

Mohsen Azizi is an Associate Professor at the New Jersey Institute of Technology (NJIT), with a primary appointment in the School of Applied Engineering and Technology and a secondary appointment in the Department of Electrical and Computer Engineering. He joined NJIT in 2018 after serving as an Assistant Professor at Michigan Technological University and as an R&D engineer at Pratt & Whitney Canada, where he designed control systems for jet engines. His research focuses on decentralized control, fault diagnosis, and renewable energy systems, including microgrids and power systems. He holds a Ph.D. in Electrical and Computer Engineering from Concordia University (2010), an M.S. from the same program (2005), and a B.S. in Electrical Engineering from Sharif University of Technology (2003). Dr. Azizi's research interests span decentralized control strategies, fault detection in power systems, and the integration of renewable energy solutions. He has developed innovative approaches for microgrid stability, solar energy systems, and machine learning applications in grid diagnostics. His work on the Renewable Energy Systems Training (REST) project emphasizes industry-aligned curriculum development and laboratory design for solar PV installation and troubleshooting. His contributions include advancements in hardware-in-the-loop simulation platforms and portable solar-powered systems. He actively collaborates with industry partners like Nucor Steel Corporation, reflecting his commitment to bridging academic research and practical applications. His IEEE senior membership highlights his engagement with the broader engineering community.

• Smart Grids
• Distributed Energy Resources
• Power System Dynamics
• +3 more

Panagiotis Kotsampopoulos is a Principal Researcher at the Institute of Communication and Computer Systems (ICCS) and an Adjunct Lecturer at the School of Electrical and Computer Engineering (ECE-NTUA), National Technical University of Athens (NTUA). He leads the Smart RUE research group at ICCS-NTUA since 2009 and is a founding member of the international DERlab association. His work focuses on smart grids, distributed energy resources (DER), and microgrid technologies, with significant contributions to hardware-in-the-loop (PHIL) laboratory development and real-time simulation methodologies. Education includes a Diploma (2010) and PhD (2017) in Electrical and Computer Engineering from NTUA, and a graduate degree in Education from the University of Athens (2020). He has coordinated major EU projects like RE-EMPOWERED (H2020) and APEX, securing over €10M in research funding. His teaching roles include lecturing on power system analysis and developing hands-on laboratory exercises for ECE-NTUA courses. Research interests span power system dynamics, microgrid control, and engineering education innovation. He chairs the IEEE PES Task Force on 'Innovative Teaching Methods' and contributes to IEEE standards development (e.g., P2004). He has authored 36 journal articles, 9 book chapters, and over 37 conference papers, delivering 50+ invited lectures globally. Professional activities include membership in CIGRE, IEEE (Senior Member), and the Technical Chamber of Greece. He co-founded the energy community 'Collective Energy' (COEN) and leads initiatives promoting energy communities and green transitions in EU geographical islands.

• Energy Storage Systems
• Optimization Algorithms
• Energy Management Systems
• +3 more

FERAHTIA Seyd-Ali is a Researcher-Lecturer at CESI, affiliated with the LINEACT research team. His expertise lies in energy storage systems, optimization algorithms, and renewable energy integration. He holds a PhD in Automation from the University of M'sila (2022), focusing on microgrid energy management. His research includes lithium-ion battery diagnostics, AI-driven energy optimization, and control strategies for multi-source systems. Education: PhD in Automation (University of M'sila, 2022), Master's in Automation & Industrial Computing (2018), and Bachelor's in Electrical Engineering (2016). Research activities span battery modeling, offshore wind turbine control, and smart grid technologies. He contributes to journals like Applied Energy and IEEE Transactions. As an editorial member of 'Smart Grids and Sustainable Energy', he promotes sustainable energy solutions. He is part of international networks such as IREENA (Saint-Nazaire) and the International Federation of Automatics (IFAC).

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.

Fawad KhanView profile

Research Fellow

• Cyber Security
• Healthcare Security
• Cryptography
• +4 more

Fawad Khan is a Postdoctoral Research Fellow at the Centre for Intelligent Healthcare, Coventry University, UK. He previously served as an Assistant Professor at the National University of Sciences and Technology (NUST), Islamabad, Pakistan. He holds a PhD in Information & Communication Engineering from Xidian University (2018), and worked as a Lab Engineer at FAST-NUCES from 2011-2015. His research focuses on Cyber Security, Healthcare Security, Cryptography, Privacy Preservation, and Blockchain. Key areas include Homomorphic Encryption, Authentication, Searchable Encryption, and Privacy-Preserving Machine Learning. He has contributed to projects like secure telemedicine systems, smart airport security, and IoT healthcare solutions. He has authored over 30 publications, including works on blockchain in healthcare, homomorphic encryption for deep learning, and privacy-preserving data analytics. Awards include Senior Membership of IEEE. His professional roles include Technical Program Committee member for conferences and journals. His lab contributions include developing multistatic radar sensing for healthcare monitoring and datasets on activity tracking. He emphasizes interdisciplinary research at the intersection of AI, cybersecurity, and healthcare technologies.

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.

Mahmoud SalamatiView profile

Research Fellow

• Formal Methods in Control
• Learning in Control Systems
• Cyber-Physical Systems
• +2 more

Dr. Mahmoud Salamati is a Research Fellow at the Max Planck Institute for Software Systems, working in the Rigorous Software Engineering group under Professor Rupak Majumdar. His research bridges formal methods, control theory, and machine learning with applications in cyber-physical systems, energy grids, and autonomous vehicles. Salamati's work develops formal verification techniques for stochastic systems and data-driven control synthesis methods. Recent publications focus on regret-free reinforcement learning for temporal logic specifications, metastable failure analysis in distributed systems, and abstraction-based controller synthesis. His research addresses fundamental questions about decidability and scalability in formal control synthesis while maintaining practical applications in energy management and autonomous systems. Key contributions include novel approaches to time-bounded reachability problems in continuous-time Markov chains, symbolic control methods for multi-agent systems, and hybrid optimization techniques for power plant control. Salamati's work demonstrates consistent integration of theoretical computer science foundations with practical engineering challenges in critical infrastructure systems.

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.

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

Goras Tecla Castelia is a Researcher at the Department of Energy within the College of Electrical Engineering at Technical University of Iasi . With a focus on modernizing power distribution systems, their work integrates advanced technologies like artificial intelligence, data mining, and clustering algorithms to address challenges in voltage control, renewable energy integration, and electric vehicle (EV) charging infrastructure optimization. Research Interests Power Systems Analysis Smart Grid Implementation Wind Energy Integration Machine Learning Applications Grid Automation Prosumer Management Key Publications Trends Recent articles (2024-2025) emphasize AI-driven optimization, smart SCADA systems, and clustering methodologies for improving voltage quality, renewable energy modeling, and EV charging station placement. These works often address technical challenges in low- and medium-voltage networks, with case studies in Romania.

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.