Find Academic Supervisors

Alberto Ferrante is a Lecturer and Researcher at the Faculty of Informatics of the Università della Svizzera italiana (USI), affiliated with the IDSIA (Dalle Molle Institute for Artificial Intelligence) USI/SUPSI. His work bridges cybersecurity, embedded systems, and AI applications, particularly in IoT and pest control. He holds a PhD from Università degli Studi di Milano (2006) and an MSc from Politecnico di Milano (2002). Research Interests: Ferrante focuses on Secure communication protocols and embedded systems security Malware detection and resource-optimized hardware solutions Machine learning applications for IoT, including agricultural pest monitoring and healthcare diagnostics Cyber-physical systems design and security-enhanced embedded systems His publications emphasize practical implementations, such as AI-driven UAVs for pest control and low-power drone systems for environmental monitoring. He actively contributes to tech transfer projects with industry partners and participates in major conferences like ICC and Globecom as a TPC member. He teaches the Master’s course Edge Computing in the IoT and collaborates on hardware-software co-design for security-critical systems. His work often integrates real-world constraints like energy efficiency and computational resource limitations. Key contributions include frameworks for dynamic security adaptation in wireless sensor networks and hardware-accelerated security for embedded systems.

• Communication Security
• Embedded Systems Security
• Design of Embedded Systems
• +4 more

Joseph Sifakis is an Emeritus Senior CNRS Researcher at the Verimag laboratory, University of Grenoble Alpes, and former Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) (2011-2016). He is renowned for his foundational contributions to formal verification, particularly in model checking and component-based system design. Sifakis is the founder of Verimag, a leading laboratory in embedded systems research, and the developer of the BIP framework for rigorous system design. His research focuses on system design methodologies, formal methods for embedded and cyber-physical systems, and the integration of correctness-by-construction principles. He pioneered the use of the Lustre language and SCADE tool for safety-critical systems, widely adopted in avionics and space applications. Key contributions include the BIP modeling language, the IF and Kronos verification tools, and advancements in system architecture modeling. His work bridges theoretical computer science with industrial applications, emphasizing safety, reliability, and scalability in complex systems. Awarded the Turing Award (2007) for model checking, Sifakis has held leadership roles in European research initiatives like the ARTIST Networks of Excellence. He served as President of the Greek Council for Research and Technology (2014-2016) and is a member of prestigious academies including the French Academy of Sciences and the National Academy of Engineering.

• Embedded Systems
• Formal Verification
• Component-Based Systems
• +3 more

Prof. Dr. Mario Trapp is a Full Professor and Chairholder of Engineering Resilient Cognitive Systems at the Technical University of Munich (TUM), within the TUM School of Computation, Information and Technology. He is also the Executive Director of the Fraunhofer Institute for Cognitive Systems IKS in Munich, leading a major research institute focused on the safe integration of artificial intelligence into critical systems. Education: PhD in Computer Science, TU Kaiserslautern, 2005 (with distinction) Habilitation in Computer Science, TU Kaiserslautern, 2016 Studied Technoinformatics / Computer Science, TU Kaiserslautern His research centers on resilient cognitive systems , where he combines expertise in model-based safety engineering with self-adaptive software systems. He advocates for safe intelligence , emphasizing that AI must be engineered to be both intelligent and safe, particularly in domains like autonomous driving and medical technology. His work addresses the challenge of ensuring dependability in open, adaptive systems where traditional safety methods fall short. The available publications reflect a consistent focus on dynamic safety assurance, adaptive certification, and runtime risk management for complex, open systems. His research trajectory shows a deep commitment to foundational methods that enable systems to maintain safety despite uncertainty and change. Scientific Affiliations and Recognition: Member, Bavarian State Government’s Council on AI (Bayerischer KI-Rat) Member, Bavarian State Ministry’s AI – Data Science Expert Panel Former Adjunct Professor, Department of Computer Science, TU Kaiserslautern Prof. Trapp is actively involved in technology transfer, advising numerous industrial partners on safety-critical software and AI assurance. He is a frequent speaker and author on the topics of AI safety, software engineering, and resilience. He leads a research team at Fraunhofer IKS focused on developing architectures and methods for dependable cognitive systems.

• Resilient Cognitive Systems
• Safety Assurance of AI-based Systems
• Self-Adaptive Software Systems
• +7 more

Akarsh Prabhakara is an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin–Madison, with an additional affiliation in the Department of Electrical and Computer Engineering. He earned his Ph.D. from Carnegie Mellon University in 2024, where he worked under Professors Anthony Rowe and Swarun Kumar. Ph.D., Electrical and Computer Engineering, Carnegie Mellon University, 2024 B.Tech, Electronics and Communication Engineering, National Institute of Technology Karnataka, 2018 His research focuses on building high-fidelity wireless systems for perception and communication, particularly in cyber-physical and robotic applications. He explores machine learning-driven RF systems, novel communication paradigms, wireless-robotics integration, and embedded wireless sensing. His work aims to enable robust perception in challenging environments such as smoke or fog using millimeter wave radar and deep learning. His recent publications in CVPR, ICRA, MobiCom, and ICCV demonstrate a strong trend in using neural methods for radar simulation, super-resolution, and wireless intelligence. Key themes include implicit neural rendering for radar, end-to-end learning for perception, and high-resolution point cloud generation from low-cost sensors. His scientific contributions have been recognized through publications in top-tier venues, though specific awards are not mentioned in the provided text. He is actively involved in mentoring and recruiting students for research in wireless and robotics. He teaches courses such as Intro to Computer Networks and Big Ideas in Wireless: Perception and Communication . He leads research projects like RadarHD, which enables lidar-like perception from mmWave radar, and is developing tools and datasets for community use. His lab emphasizes practical, real-world applications of wireless systems in robotics and autonomous systems.

• Wireless Systems
• Cyber-Physical Systems
• Machine Learning for RF
• +6 more

Muhamad Risqi U. Saputra (Risqi) is Associate Professor in Data Science at Monash University, Indonesia. He is actively involved in research, teaching, and interdisciplinary projects focusing on machine learning, computer vision, cyber-physical systems, and smart cities. His work contributes to UN Sustainable Development Goals, particularly in education, sustainable cities, and climate action. Education: DPhil/PhD in Computer Science, University of Oxford MEng in Information Technology, Universitas Gadjah Mada BEng in Electrical Engineering and Information Technology, Universitas Gadjah Mada Risqi's research focuses on applying deep learning and computer vision to real-world challenges such as navigation, environmental monitoring, and disaster management. His work integrates satellite imagery, IoT, and AI to solve problems in urban resilience and sustainable development. He is particularly interested in interdisciplinary applications in health, assistive technology, and smart cities. His recent publications highlight a strong trend in using deep learning for environmental monitoring—especially flood and mining footprint detection via satellite data. The integration of cross-attention networks, semantic segmentation, and multispectral imagery demonstrates technical innovation with societal impact. His work also extends into policy and social implications of AI, as seen in studies on energy transition and big data discourse in politics. Scientific Awards: Indonesia ICT Awards (INAICTA) International ICT Innovative Services Contest (InnoServe), Taiwan Asia Pacific ICT Alliance Awards (APICTA), Brunei Darussalam Risqi is a Chief Investigator on multiple active research projects such as Open Nutrition , Citarum Action Research Program , and MUST: Enabling Multi-species Transitions . These projects involve interdisciplinary collaboration across environmental science, public policy, and data science. He also contributes to public discourse through media engagement, including commentary on the misuse of 'big data' in politics. He teaches core units in data science, algorithms, and research methods at Monash University. He is currently accepting PhD students and leads research that bridges technical innovation with societal benefit, particularly in Southeast Asia’s urban and environmental contexts.

• Machine Learning
• Deep Learning
• Computer Vision
• +12 more

Prof. Adrian Filipescu is a full professor and PhD supervisor at the Department of Automation and Electrical Engineering, Dunărea de Jos University of Galati. He holds a PhD in Control Systems (1993) and has over 40 years of academic and research experience. His expertise spans numerical calculus, adaptive control, robotics, and Industry 4.0/5.0 applications. He has authored 12 books and over 110 indexed articles with an h-index of 11 (SCOPUS), and his work earned two UEFISCDI awards (2014, 2019). Education: Engineer diploma in Automatic Control (Polytechnic University of Bucharest, 1981) and PhD in Control Systems (Dunărea de Jos University, 1993). His research focuses on mechatronics systems integration, robotic control, digital twins, and industrial automation. Notable contributions include developing a mechatronics line with integrated autonomous robots, wheelchair systems for disabled users, and multidirectional autonomous vehicles. Research Themes: Digital twin frameworks, IoT-cloud robotics control, Industry 4.0/5.0 systems, inverse kinematics modeling, and autonomous robotic navigation. His recent work emphasizes cloud-based remote control, HIL simulation, and SCADA integration. Awards: Recipient of the 2014 and 2019 UEFISCDI 'Award for Research Results' for highly commended papers. He has led 10+ research projects, endowing labs with advanced robotic infrastructure and PLC-controlled systems. Advising & Grants: Supervised 7 completed PhD theses (including 1 international co-supervision). Projects focused on robotic-assisted manufacturing, autonomous systems, and mechatronics line optimization. Current lab facilities include mobile robots, industrial manipulators, and PLC-based control systems. Labs/Teams: Director of a research lab developing Industry 5.0-ready systems, including robotic assistants for elderly/disabled users and flexible assembly/disassembly technologies. Collaborations include NATO internships at Politecnico di Torino (Italy), INPG Grenoble (France), and ISR Coimbra (Portugal).

• Control Systems
• Robotics
• Mechatronics
• +5 more

Professor Nan Jiang is a Professor and Head of the Department of Computing and Informatics at Bournemouth University (BU), where he has been a faculty member since 2010. He leads research and teaching in Human-Computer Interaction (HCI), digital health, and usability engineering. He co-founded the Bournemouth University Human-Computer Interaction (BUCHI) research group in 2012, contributing significantly to the university’s research excellence in REF 2021. MSc in Advanced Methods, Queen Mary, University of London (2002) PhD in Web Usability, Queen Mary, University of London (2009) His research focuses on data-driven usability evaluation, with recent emphasis on digital health applications, explainable AI (XAI), and accessible technologies. He investigates how user interactions can be optimized for health services on mobile devices, particularly for chronic conditions like multiple sclerosis and mental health. His work bridges technical innovation with user-centered design principles. The 15 most recent publications reflect a strong trend in human-AI interaction, digital health interventions, and accessibility. Key themes include trust calibration in AI systems, co-design of health technologies, and the development of assistive tools using smartphone sensors. His research spans both technical AI modeling and deep user experience evaluation. Active reviewer for top HCI conferences and journals Reviewer for UKRI research councils and SBRI External Examiner at Kingston University and University of East London Member of W3C China Former public expert for W3C HTML Working Group Professor Jiang has secured significant research funding from the European Commission (H2020), ERDF, HEIF, and Innovate UK. He has supervised six PhD students to completion and continues to mentor graduate researchers. He has led major projects such as the FACETS digital toolkit for MS patients and Authentibility Pass for accessible authentication. He also contributes to public engagement through workshops and media appearances on digital addiction and CAPTCHA design. He co-founded and co-chaired the HCI Research Group at BU from 2015 to 2023 and has led initiatives in gamified learning, e-recruitment modeling, and intelligent interfaces. His team, often collaborating with Dr. Huseyin Dogan and Dr. Shamal Faily, focuses on real-world applications of HCI in healthcare, security, and social computing.

• Human-Computer Interaction
• Digital Health
• Explainable Artificial Intelligence
• +7 more

Shrideep Pallickara is a Professor in the Department of Computer Science at Colorado State University, where he also directs the Center for eXascale Spatial Data Analytics and Computing (XSD) . His research is funded by the National Science Foundation, Department of Homeland Security, Environmental Protection Agency, Department of Agriculture, and the UK's e-Science program. Research Interests: His research lies at the intersection of machine learning and large-scale systems, focusing on: Spatiotemporal data management and analytics Extreme-scale storage systems Stream processing for IoT and cyber-physical systems Deep learning over petabyte-scale, high-dimensional datasets Model construction for forecasting natural and urban phenomena His work addresses challenges in computational tractability, resource utilization, and convergence in distributed environments. Systems developed in his lab are deployed in domains such as urban sustainability, agriculture, epidemiology, environmental monitoring, healthcare, and defense. Research Trends in Publications: His recent publications demonstrate a strong focus on scalable analytics for geospatial and environmental data. Key themes include deep learning for soil moisture and salinity prediction, efficient visualization of massive satellite datasets, spatiotemporal search and summarization, and model performance profiling across spatial domains. The work integrates scientific domain knowledge with machine learning and systems innovation. Scientific Awards: NSF CAREER Award Board of Governors Award for Excellence in Undergraduate Teaching OLIE Award N. Preston Davis Award Monfort Professorship Best Paper Award at IEEE/ACM CCGrid 2019 Best Paper Award at BDCAT 2023 Best Paper Award at IEEE Cluster 2012 Best Student Paper Award at IEEE CloudCom 2010 Shortlisted for ACM DEBS-2015 Grand Challenge Award One of the Six Best Papers at ACM/IEEE GRID 2005 Advising and Grants: He advises numerous graduate students, many of whom are co-authors on his publications. His research is supported by major grants from NSF, DHS, EPA, USDA, and UK e-Science, enabling the development of open-source systems such as Granules, NaradaBrokering, Galileo, Funnel, and Spindle. Labs and Teams: He leads the XSD Center, which develops and maintains large-scale open-source software systems involving over 2500 classes and a million lines of code. These systems are used in academic, commercial, and defense applications.

• Machine Learning
• Deep Learning
• Large-Scale Systems
• +12 more

Andrés D. González serves as an Associate Professor in the Department of Industrial & Systems Engineering at the University of Oklahoma, applying interdisciplinary analytical frameworks to complex system dynamics across engineering and social domains. His educational foundation includes: Ph.D. in Civil Engineering from Rice University Ph.D. in Engineering from Universidad de los Andes, Colombia M.Eng. in Industrial Engineering from Universidad de los Andes, Colombia B.Sc. in Physics from Universidad de los Andes, Colombia Six Sigma Black-Belt certification from Arizona State University Research focuses on developing methodologies from systems dynamics, statistical physics, and operations research to model social-physical systems. Core contributions span infrastructure network resilience, supply chain optimization, and distributed control systems, with significant impact in Cyber-Physical-Social Systems and Aerospace/Defense engineering through novel analytical frameworks for interdependent critical networks. Professional recognition includes industry certification in process optimization, though formal scientific awards are not documented in this profile. Mentorship details and grant activities remain unspecified in current materials, with no laboratory or research team affiliations explicitly referenced.

• Interdependent infrastructure network resilience
• Supply chain performance
• Decentralized and distributed control and optimization models
• +2 more

Dr. Marwa Keshk is a Lecturer in Cyber Security at the School of Professional Studies, University of New South Wales (UNSW) Canberra. Her academic career focuses on the intersection of cybersecurity and artificial intelligence, with particular expertise in privacy preservation, anomaly detection, and threat intelligence. Her educational background includes: PhD in Cyber Security and Privacy Preservation (2021) from UNSW Master's degree in Evolutionary Computation (2017) from UNSW Bachelor's degree in Computer Science (2012) from the Faculty of Computers and Information at Helwan University, Egypt Dr. Keshk's research interests primarily center around the application of artificial intelligence and machine learning techniques to enhance cybersecurity measures. Her work explores how computational intelligence, statistical methods, and emerging technologies can be leveraged for privacy preservation, anomaly detection, and threat intelligence. She has made significant contributions to the security of Internet of Things (IoT) networks, cyber-physical systems, and critical infrastructure protection. Her research often combines theoretical advancements with practical applications, addressing real-world security challenges in increasingly connected digital environments. Analysis of Dr. Keshk's publication history reveals a strong focus on applying AI and machine learning to cybersecurity challenges, particularly in IoT environments. Her work demonstrates a progression from foundational research in evolutionary computation to specialized applications in cybersecurity. Recent publications show increasing emphasis on explainable AI for security applications, reflecting the growing need for transparency in security decision-making processes. Her research spans multiple domains including smart cities, industrial control systems, and power networks, demonstrating the versatility and wide applicability of her security frameworks. Dr. Keshk has received notable recognition for her academic work: UNSW Tuition Fee Scholarship for PhD Research (2018-2021) Data61/CSIRO Scholarship (2019-2021) During her PhD studies, Dr. Keshk was a research candidate at Data61-CSIRO in Australia, providing her with valuable industry experience alongside her academic pursuits. Her collaborative approach to research is evident in her extensive co-authorship with colleagues across various institutions, particularly with researchers from UNSW and other Australian universities. Dr. Keshk's work contributes significantly to several research teams and initiatives focused on cybersecurity and AI at UNSW Canberra. Her expertise complements broader efforts in secure systems development, particularly in the context of increasingly connected environments where traditional security boundaries are challenged by new technologies.

• Cyber Security
• Artificial Intelligence
• Privacy Preservation
• +5 more

Mohammad B Shadmand is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago (UIC). He currently serves as Director of the Intelligent Power Electronics at Grid Edge (IPEG) Research Lab and has a history of academic and research roles at Kansas State University and Texas A&M University. Research Focus : Smart photovoltaic inverters, energy storage systems, grid cybersecurity analytics, deep learning for cyber-physical energy systems, autonomous model predictive control, and photovoltaic-intensive grid modeling. Professional History : Assistant Professor at UIC (2020–present), Kansas State University (2017–2020); Research Engineer and Postdoctoral Research Associate at Texas A&M University. Scientific Recognition : Multiple IEEE Best Paper Awards (2019) IEEE Myron Zucker Student-Faculty Grant (2019) Keystone Research Faculty Scholar at Kansas State University (2017, 2020)

• Smart Grids
• Renewable Energy Systems
• Power Electronics
• +5 more

Paula Chanfreut Palacio is an Assistant Professor in the Control Systems Technology section of the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e). She joined TU/e in February 2023 after previously contributing to the ERC Advanced Grant project OCONTSOLAR (Optimal Control of Thermal Solar Energy Systems). Education: B.Sc. and M.Sc. in Industrial Engineering (University of Seville, 2017/2019) Ph.D. in Automation Engineering (University of Seville, 2018–2022) Visiting scholar at UC Berkeley (2021) and MIT (2022) Research Interests: Her work centers on decentralized and data-driven model predictive control (MPC) for large-scale interconnected systems. Key applications include renewable energy plants, traffic networks, and smart grids, with emphasis on scalability, cooperative multi-agent frameworks, and real-time optimization. She also investigates cyber-security in control systems and learning-based supervisory methods. Publications: Recent articles (2025) focus on advanced MPC techniques for safety-critical systems like vehicle platooning and power grids, highlighting themes such as cyber-attack resilience, nonlinear cooperative control, and invariant set design. Cross-cutting topics include distributed optimization, robustness, and machine learning integration. Projects: Active member of the Model Predictive Pandemic Control project (2023–2025), funded by an ERC Advanced Grant, focusing on control strategies for large-scale health crises. Affiliation: Part of the Cyber-Physical Systems and Systems Engineering research group at TU/e, contributing to interdisciplinary work in control theory and real-world engineering solutions.

• Model Predictive Control
• Distributed Control Systems
• Renewable Energy Systems
• +4 more

Saeed Ur Rehman serves as a Senior Lecturer in Cybersecurity and Networking within the College of Science and Engineering at Flinders University. He holds leadership positions as Course Leader for BIT and MIT (Networks and Cybersecurity) programs and Deputy Research Section Lead for Data and Information Sciences. His institutional affiliations include membership in the Centre for Defence Engineering Research and Training and the South Australia Cyber Security Innovation Node (SA Node) Advisory Board. Dr. Rehman's educational background includes: PhD in Electrical and Electronic Engineering from the University of Auckland (2015) Graduate Diploma in Higher Education from Unitec Institute of Technology (2016) Master of Engineering from the University of Auckland (2009) BSc Engineering from Pakistan (2004) His research spans cybersecurity, wireless communication, and network security with specific expertise in physical layer security, satellite communication, visible light communication, and fog computing. Dr. Rehman has developed innovative approaches in RF fingerprinting for device authentication and has contributed to vital sign monitoring technologies using radar systems. His work bridges theoretical security frameworks with practical applications in digital agriculture, vehicular networks, and energy harvesting systems. Analysis of his recent publications reveals a strong focus on emerging security challenges in next-generation networks, particularly addressing vulnerabilities in digital agriculture systems, privacy preservation in fog computing environments, and physical layer security enhancements for 6G networks. His research demonstrates consistent interdisciplinary collaboration across computer science, electrical engineering, and healthcare technology domains. Dr. Rehman has received significant recognition including: IEEE Senior Member status (2016) Fellowship from The Higher Education Academy, UK (2019) Cisco Networking Academy instructor certifications (2019, 2022) PhD Completion Award from University of Auckland (2014) As an active researcher and supervisor, he has secured substantial research funding including AUD$810,000 for the SmartSat CRC project (2020), AUD$150,000 from Defence Innovation Partnership (2023), and multiple grants from Flinders University and New Zealand institutions. He supervises PhD and Master's students in cybersecurity, with completed projects focusing on IoT security and privacy-preserving data aggregation, and current projects exploring intelligent reflective surfaces, RF emitter geolocation, and vehicular data communication frameworks. Dr. Rehman contributes extensively to the academic community as an IEEE Senior Member serving multiple societies, conference chair, journal editorial board member, and peer reviewer for numerous publications in his field.

• Cybersecurity
• Wireless Communication
• Network Security
• +7 more

Simone Vannuccini is a Teacher-Researcher and Junior Professor in the Economics of Artificial Intelligence and Innovation at the University Côte d'Azur's School of Economics and Management. He is affiliated with the Research Group in Law, Economics, and Management (GREDEG) and the Pole Innovation, Science and Technology (PIST) under the FIT (Firms, Innovation, Territories) team. His research focuses on innovation , artificial intelligence , and industrial policy , with particular emphasis on socioeconomic impacts, technological sovereignty, and global value chains. His recent publications explore themes like robot adoption , AI governance , and strategic autonomy in the European Union . His peer-reviewed articles and conference contributions span topics including multimodal AI systems , disruptive technologies , competition law enforcement , and cyber-physical dynamics . He actively contributes to interdisciplinary research bridging economics , law , and technology studies . Simone Vannuccini participates in collaborative projects such as AI3SD (Artificial Intelligence, Autonomous Systems, and Digital Innovation) and engages in policy discussions on green transitions , budgetary autonomy , and technological multiplier effects . His work integrates theoretical frameworks from Schumpeterian economics with empirical analyses of global innovation trends.

• Economics
• Artificial Intelligence
• Innovation
• +4 more

Professor Gareth Taylor is a Professor of Power Systems and Director of the Brunel Interdisciplinary Power Systems (BIPS) Research Centre at Brunel University London's College of Engineering, Design and Physical Sciences. He serves as Module Leader for the MSc Sustainable Electrical Power program and has been actively involved with the university since May 2000, progressing from National Grid Post-doctoral Scholar to his current position as Professor (appointed in 2012). He previously served as Head of the Department of Electronic and Electrical Engineering from May 2019 to June 2023 and holds a Visiting Professor position at Imperial College London (2023-2026). Professor Taylor earned his BSc in Applied Physics from Royal Holloway College, University of London (1987), followed by an MSc in Scientific and Engineering Software Technology from the University of Greenwich (1992), and completed his PhD in Computational Solid Mechanics at the University of Greenwich in March 1997. His doctoral research focused on finite volume methods for material non-linearity within multi-physics frameworks. His research spans power systems engineering with particular emphasis on smart grid technologies, renewable energy integration, and advanced computational methods. Professor Taylor has contributed to over 250 research publications in areas including power system operation and management, reactive power control, voltage regulation, and high-performance computing applications in electrical power systems. His work addresses critical challenges in modern power systems, particularly those related to the integration of renewable energy sources and the development of more resilient grid infrastructure. Analysis of his recent publications reveals a strong focus on addressing contemporary power system challenges, particularly the integration of renewable energy sources, smart grid technologies, and advanced computational methods. His work spans from fundamental power system analysis to practical applications in grid operation, with increasing emphasis on cybersecurity aspects of power system monitoring and the challenges posed by reduced system inertia in grids with high renewable penetration. Senior Member of IEEE Fellow of the Institute of Engineering and Technology (FIET) Chartered Engineer Fellow of the Higher Education Academy (FHEA) UK Regular Member for CIGRE Study Committee D2 (2016-2022) Member of Strategic Advisory Group for CIGRE Study Committee D2 (2023) Professor Taylor has led numerous significant research projects including TDX-ASSIST (€5.2M), e-HIGHWAY2050 (€8.2M), and HiPerDNO (€5.4M), with funding from EPSRC, European Commission, National Grid, and other major organizations. His current research portfolio includes projects on novel decoupled active/reactive power oscillation response, digitalization of power systems operation, and examining net zero policy in European energy markets. He also directs the BIPS Research Centre, which focuses on interdisciplinary power systems research with strong industry connections.

• Power Systems
• Smart Grids
• Renewable Energy Systems
• +7 more