Find Academic Supervisors

Mikael EklundView profile

Professor

• Autonomous Systems
• Nonlinear System Identification and Control
• Health Informatics
• +3 more

Dr. Mikael Eklund is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, within the Faculty of Engineering and Applied Science. He holds a PhD (2003), MSc (1996), and BSc (1989) in Electrical and Computer Engineering from Queen’s University. His research focuses on Autonomous Systems , Nonlinear System Identification and Control , Health Informatics , and Pervasive and Mobile Computing . He has expertise in medical image processing, robotic vehicles, and smart sensors for assisted living. Education and Work Experience : - PhD (Electrical and Computer Engineering), Queen’s University (2003) - MSc and BSc from Queen’s University (1996, 1989) - Visiting Postdoctoral Scholar at UC Berkeley (2003–2006) - Adjunct Assistant Professor at Queen’s University (2003) - Former Teaching Fellow at Queen’s University (1996–2001) - Industrial experience in flight control system engineering (CAE Inc., 1989–1996) Research Contributions : - Developed SensorNet, a wireless infrastructure for assisted living. - Advanced methods for nonlinear system identification in chemical processes and aerospace systems. - Pioneered real-time UAV safety protocols and model predictive control algorithms for aerial pursuit-evasion games. - Explored EMG signal processing for hand force estimation and MEG signal source localization in neuroscience. Teaching and Outreach : - Teaches courses like Medical Image Processing and Electric Circuits. - Active in interdisciplinary projects like the ITALH initiative for elder tech integration. - Presented at conferences such as IEEE EMBC, ACC, and CDC, emphasizing healthcare IT and autonomous systems.

Jennet DickinsonView profile

Assistant Professor

• High Energy Physics
• Particle Physics
• Higgs Boson Physics
• +4 more

Jennet Dickinson is an Assistant Professor in the Department of Physics at Cornell University, affiliated with the College of Arts and Sciences. Her research focuses on high-energy particle physics, particularly the study of the Higgs boson and its interactions using data from the Large Hadron Collider (LHC). She contributes to the CMS experiment and collaborates with the ATLAS collaboration. Education: PhD in Physics from the University of California, Berkeley (2020); BA in Physics from Columbia University (2014). Her research interests include: Investigating new physics phenomena through Higgs boson production at the HL-LHC Developing advanced silicon pixel detectors for the CMS Phase 2 upgrade (TFPX system) Integrating machine learning into detector readout electronics for efficient data processing Publications highlight her work on boosted Higgs signatures, Higgs-top quark interactions, and smart pixel sensor technologies. She is actively involved in the High Luminosity LHC upgrade project and contributes to multidisciplinary research at the intersection of particle physics and artificial intelligence.

Yujia ZhangView profile

Assistant Professor

• Bioiontronics
• Microengineering
• Synthetic tissues
• +3 more

Yujia Zhang is a Tenure Track Assistant Professor at the School of Engineering , École Polytechnique Fédérale de Lausanne (EPFL), leading the Laboratory for Bio-Iontronics (BION) since January 2025. His work focuses on developing iontronic biointerfaces and hybrid intelligent systems for biomedical applications. Academic Affiliations: EPFL School of Engineering, STI-SMT SMT-ENS PhD program committee Research Themes: Droplet-based iontronics, synthetic tissues, advanced manufacturing Research Trends from his publications emphasize microscale droplet iontronics , soft energy systems , and biohybrid interfaces , with applications in neurostimulation , tumor modeling , and biomedical devices . Scientific Awards : 2023: Early-career Research Scientist Representative, UK Parliamentary & Scientific Committee 2022: Excellent Doctoral Dissertation, Chinese Academy of Sciences 2021: Outstanding Doctoral Thesis, Chinese Institute of Electronics 2020: Special Prize for President Scholarship, Chinese Academy of Sciences Academic Contributions include mentoring PhD students and teaching microfabrication technologies. His lab develops 3D-printed synthetic tissues and droplet networks for interactive biological communication.

Javier IrizarryView profile

Professor

• Unmanned Aerial Systems (Drones) in Construction
• Construction 4.0
• Reality Capture Technology
• +3 more

Javier Irizarry is a Professor and Interim Chair in the School of Building Construction at Georgia Tech's College of Design. He also serves as Associate Dean for Academic Affairs and Outreach , overseeing academic programs, diversity initiatives, and recruitment efforts. As Director of the CONECTech Lab, he pioneers research in Construction 4.0 and UAV applications for infrastructure challenges. Education : Ph.D. (Civil Engineering), Purdue University Masters in Engineering Management, Polytechnic University of Puerto Rico B.S. (Civil Engineering), University of Puerto Rico, Mayagüez Research Focus : Irizarry’s work integrates cutting-edge technologies into construction, including Unmanned Aerial Systems (UAS), Reality Capture, Virtual/Augmented Reality, and Human Factors in Robotics. His lab develops frameworks for Construction 4.0 , emphasizing technology-driven solutions for safety and efficiency. Lab & Impact : The CONECTech Lab focuses on Construction 4.0 , advancing drone-based inspection systems, digital twins, and safety analytics. His research has led to over 100 publications, with applications in infrastructure monitoring, safety management, and educational tools. Leadership : As Associate Dean, Irizarry drives academic innovation and outreach, including pre-college programs and diversity strategies. He is a licensed Professional Engineer (PE) and FAA-licensed drone pilot, bridging academia and industry.

Steven KosierView profile

Research Professor

• Microelectronics
• Radiation Effects on Semiconductors
• Power Device Reliability
• +5 more

Steven Kosier is a Research Professor of Electrical and Computer Engineering at Vanderbilt University's School of Engineering . His research focuses on microelectronics reliability, particularly radiation effects on power devices and advanced CMOS technologies. He explores semiconductor applications for space and military systems, emphasizing interdisciplinary solutions. Education: Ph.D., Electrical Engineering, University of Arizona M.S., Electrical Engineering, University of Arizona B.S., Electrical Engineering, University of Minnesota Research Interests: Radiation Effects on Semiconductors SiC Power MOSFET Reliability High-Voltage Device Design Space and Military Electronics Multi-disciplinary Engineering Solutions Publications Trends: His recent work emphasizes radiation-hardened power devices, trench-based semiconductor architectures, and hybrid sensor systems. Key themes include SiC MOSFET degradation under heavy-ion irradiation, TID effects in nanoscale MOSFETs, and high-voltage trench device optimization. Awards: No specific scientific awards were listed in the provided text. Grants and Labs: No grants or lab affiliations were explicitly mentioned. His research appears to focus on device physics and semiconductor reliability without noted collaborative lab structures.

• Cloud Computing
• Fog Computing
• Edge AI
• +7 more

Sukhpal Singh Gill is an Assistant Professor (Lecturer) in Cloud Computing at the School of Electronic Engineering and Computer Science, Queen Mary University of London (UK). He holds a PhD, ME, and BE in Computer Science and is a Fellow of the Higher Education Academy (FHEA). His roles include Programme Director for MSc Advanced Computer Science and MSc Business Analytics, as well as Deputy Chair of the Main Misconduct Panel. He leads the GillNet Research Lab and is the Editor-in-Chief of the International Journal of Applied Evolutionary Computation (IJAEC) , with editorial roles in IEEE IoT, Nature Scientific Reports, and other journals. Education: PhD in Computer Science ME in Computer Science BE in Engineering Research Interests: Focus on Cloud Computing, Edge AI, IoT, Energy Efficiency, and Quantum Computing. His work bridges theoretical advancements with practical applications in healthcare, smart cities, and sustainable computing. Notable projects include AI-driven frameworks for carbon-neutral cloud resource management, blockchain-empowered healthcare systems, and quantum cloud computing models. Teaching: Teaches modules such as Cloud Computing (Postgraduate), Fundamentals of Web Technology (Undergraduate), and Semi-structured Data and Advanced Data Modelling (Postgraduate/Undergraduate). He emphasizes inclusive curriculum design and innovative teaching tools like the Q-Module-Bot for AI-supported learning. Awards & Grants: Recipient of 12,500+ citations and an H-index of 54 (Google Scholar). Secured grants for projects on edge AI, federated learning, and sustainable cloud computing. Winner of awards including the IEEE IT Professional Magazine Outstanding Reviewer Award (2024) and Elsevier's Best Paper Award (2023). Labs & Teams: Leads the GillNet Research Lab , focusing on cutting-edge research in cloud-edge computing, AI, and quantum systems. Collaborates with industry partners on projects like HealthEdgeAI and AIoT-driven smart healthcare systems .

Emanuele CrisostomiView profile

Associate Professor

• Smart Grids
• Electric Vehicles
• Control Systems
• +2 more

Emanuele Crisostomi is Associate Professor of Electrical Systems at the University of Pisa's Department of Energy, Systems, Territory and Constructions Engineering. He holds PhD and graduate degrees in Automation Engineering from the University of Pisa, with research visits to University of Cambridge, University of Leicester, and Hamilton Institute. His research bridges control theory, energy systems, and smart mobility. His research integrates: Smart grid control and renewable energy integration Electric vehicle charging infrastructure and routing algorithms Urban traffic modeling and optimization Nonlinear system dynamics and Lyapunov stabilization Machine learning applications in energy systems Crisostomi's publications demonstrate consistent innovation in electric vehicle-grid integration, with recent focus on predictive charging control, highway EV circulation patterns, and hydropower monitoring. His work shows increasing application of deep reinforcement learning for multi-regional power systems and hybrid network models for infrastructure monitoring. He leads research on IoT-enabled energy efficiency in buildings and contributes to epidemic modeling through network science. Current projects examine battery sizing optimization, charging station scheduling under uncertainty, and synergetic building management systems integrating environmental monitoring with energy conservation.

Yan Kyaw TunView profile

Assistant Professor

• Edge Computing
• Multi-Access Edge Computing
• Resource Allocation
• +12 more

Yan Kyaw Tun is a Tenure Track Assistant Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design, located in Copenhagen, Denmark. His research lies at the intersection of wireless communications, edge computing, and artificial intelligence, with a strong focus on next-generation networks (5G/6G), UAV-assisted systems, and intelligent resource management. His educational background includes a Ph.D. in Computer Engineering from Kyung Hee University, South Korea, where he was awarded the Best Ph.D. Thesis Award in 2021, and a Bachelor of Engineering in Marine Electrical Systems and Electronic Engineering from Myanmar Maritime University. Dr. Tun's research interests span Edge Computing , Multi-Access Edge Computing (MEC) , Resource Allocation , Unmanned Aerial Vehicles (UAVs) , Reinforcement Learning , Energy Efficiency , and Integrated Sensing and Communication (ISAC) . His work leverages AI and optimization techniques to enhance the performance of wireless networks, particularly in space-air-ground integrated systems and satellite-HAP environments. The recent publications highlight a clear trend toward intelligent and sustainable networking: the integration of STAR-RIS (Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces), Federated Learning for satellite-HAP systems, and AI-driven optimization for UAV trajectories and beamforming. These works are published in high-impact venues such as IEEE Transactions on Mobile Computing and IEEE ICC , showcasing his leadership in cutting-edge communication technologies. His scientific accolades include: IEEE ComSoc Outstanding Young Researcher Award for EMEA Region (2024) Best Ph.D. Thesis Award (2021) Student Best Paper Award at APNOMS 2019 Korea Network Operation and Management Conference Award (2020) Korea Computer Congress 2018 Award Dr. Tun is actively engaged in the academic community as an advisor and grant participant. Though no direct advisees are listed, his involvement in large collaborative projects—evidenced by co-authorship with senior researchers like Prof. Choong Seon Hong—indicates mentorship and team leadership. He has served on the editorial boards of IEEE Internet of Things Journal , IEEE Open Journal of the Communications Society , and IEEE Network , and has secured research support through participation in IEEE-organized workshops and special issues. He is a key organizer of upcoming workshops, including the 'Sustainable AI for Next-Generation Wireless Communications and Networking' at IEEE GLOBECOM 2025 and the 'Digital Twin Networks' workshop at IEEE/CIC International Communications in China 2025, reflecting his role in shaping future research directions in intelligent and green networking.

Georgios KavallieratosView profile

Associate Professor

• Cybersecurity
• Maritime Cybersecurity
• Cyber-Physical Systems
• +3 more

Georgios Kavallieratos is an Associate Professor at the University of Oslo's Institute of Transport Economics, specializing in the Section for Autonomous Systems and Sensor Technologies. His research focuses on cybersecurity in maritime systems, cyber-physical systems, and risk management. He actively contributes to the DESSI project on energy system security infrastructure. His research interests include maritime cybersecurity, cyber-physical system security, and the intersection of safety and security in autonomous systems. His work addresses threats to navigation systems, smart farming, and satellite communications, with a focus on developing risk assessment frameworks and robust cybersecurity controls. Recent publications emphasize maritime cybersecurity trends, integrated navigation system protection, and threat analysis in emerging technologies like Dairy Farming 4.0. He co-authored foundational papers on cyberattack defenses for autonomous ships and cybersecurity requirements for Shipping 4.0. Current projects involve enhancing societal awareness of cybersecurity risks and improving incident response strategies for critical infrastructure. His work bridges theoretical cybersecurity principles with practical applications in transportation and industrial systems.

Renato NegraView profile

Professor

• High Frequency Electronics
• Cyber-Physical Systems
• Neuromorphic Computing
• +7 more

Prof. Dr. Renato Negra is a faculty member at RWTH Aachen University, serving as the Chair of High Frequency Electronics within the Faculty of Electrical Engineering and Information Technology. His research is centered on advanced electronic systems with a focus on reconfigurable and low-power architectures for real-time applications. Research Interests: His work spans high frequency electronics, neuromorphic computing, embedded systems, and cyber-physical systems. He develops FPGA-based and edge-computing solutions for computer vision, robotics, and smart infrastructure, particularly in elderly monitoring and autonomous navigation. His research integrates deep learning with hardware optimization for energy efficiency and real-time performance. The recent publications highlight a strong trend toward event-based vision , neuromorphic sensors , and low-power embedded AI , applied in domains such as smart cities, healthcare, and robotics. There is a consistent emphasis on real-time processing, reconfigurable systems, and the deployment of neural networks on constrained hardware platforms. Scientific Awards: No awards or honors were mentioned in the provided text. Advising and Grants: While no specific students or advising roles are listed, the volume and depth of publications suggest active supervision or collaboration within research projects. Although no grants are explicitly named, involvement in EU-level initiatives (e.g., FitOptiVis ECSEL Project) and national R&D programs (e.g., BIO-PERCEPTION) can be inferred from the research topics and publication contexts. Labs and Teams: Prof. Negra leads the research activities in High Frequency Electronics at RWTH Aachen. While not directly linked to the Computer Vision and Robotics Lab (CVR-Lab) mentioned in the text, his work aligns closely with neuromorphic and CPS research themes, suggesting potential interdisciplinary collaboration.

Dipanwita ThakurView profile

Assistant Professor

• Green Artificial Intelligence
• Federated Learning
• Smart Healthcare
• +4 more

Dr. Dipanwita Thakur serves as Assistant Professor at the Department of Computer Engineering, Modeling, Electronics and Systems (DIMES) at the University of Calabria, Italy since July 2023. She is an active member of the European Cooperation in Science & Technology (COST Action CA22104) focusing on cybersecurity and serves in the IEEE Future Networks Working Group for Artificial Intelligence/Machine Learning. Previously, she held a 15-year Assistant Professor position at Banasthali University, Rajasthan, and has industry experience at TechMahindra and C-DAC. Education: Ph.D. in Smart Healthcare from West Bengal University of Technology, Kolkata M.Tech. in Software Engineering from Banasthali Vidyapith MCA from NIELIT, Government of India B.Sc. from University of Calcutta Her research pioneers Green Artificial Intelligence with emphasis on energy-efficient federated learning and smart healthcare applications. She develops privacy-preserving human activity recognition systems using multimodal data fusion, focusing on performance evaluation and environmental sustainability. Her work bridges theoretical machine learning with practical healthcare solutions, optimizing AI systems for reduced carbon footprint while maintaining clinical efficacy through hardware-algorithm co-design and quantization techniques. Recent publications reveal a strong trajectory toward sustainable AI, with increasing focus on energy-aware federated learning frameworks, multimodal medical segmentation, and non-IID data handling. Her work consistently addresses the critical balance between model accuracy, convergence speed, and energy consumption across edge devices, with growing emphasis on quantization techniques and hardware-algorithm co-design for real-world deployment. Scientific Awards: Elevated to IEEE Senior Member (2024) Dr. B.C. Roy Memorial Scholarship for outstanding 10th Board results (1992) Student Science Seminar Award by West Bengal Government (1990) Dr. Thakur actively mentors students as evidenced by her congratulations to advisee Farwa for paper acceptances. She serves as Associate Editor for Information Fusion (Elsevier) and IEEE Sensors Journal, and holds editorial roles at Scientific Reports. Her research is advanced through COST Action CA22104 and IEEE working groups, though specific grant details aren't listed in the source material. She has organized key workshops including Green-Aware AI 2024 and Green Federated Learning at IJCNN 2025. She leads research within the MONAI community on data quality and federated learning, and contributes to IEEE IoT and Future Networks initiatives. Her work with the COST Action CA22104 Behavioral Next Generation in Wireless Networks connects cybersecurity with sustainable AI development, while her Missouri S&T visiting scholar position focuses on energy optimization for federated learning systems.

• Phase-change heat transfer
• Surface Engineering
• Thermal Management
• +12 more

Dr. Ali Sadaghiani is an Associate Professor in Surface Engineering and an Anniversary Fellow at the University of Birmingham, affiliated with the Department of Mechanical Engineering in the School of Engineering. He leads the Smart Research Group, focusing on advancing phase-change heat transfer and interfacial transport phenomena for sustainable energy and water solutions. PhD in Thermofluidics, Sabanci University, 2019 MSc in Mechatronics Engineering, Sabanci University, 2015 BSc in Mechanical Engineering, Iran University of Science and Technology, 2012 His research lies at the intersection of thermal-fluid engineering and material science, with a strong emphasis on boiling, condensation, evaporation, and freezing. He develops advanced engineered surfaces to enhance heat transfer efficiency in applications such as electronic cooling, battery thermal management, solar desalination, and anti-icing systems. His work integrates experimental methods (e.g., micro-PIV, Raman spectroscopy), multiscale modeling (CFD, MD), and surface modification techniques. His recent publications and projects reflect a consistent focus on sustainable technologies, including solar-driven interfacial evaporation, hydrogen-powered propulsion systems, and solid-state battery thermal regulation. He has led and contributed to multiple Horizon Europe and national research initiatives such as Triathlon, ARISE, MicroFlowTec, and BioAFC, demonstrating strong interdisciplinary collaboration and innovation. ERC Starting Grant laureate Anniversary Fellow Dr. Sadaghiani actively supervises PhD students and welcomes applicants interested in phase-change heat transfer, surface engineering, AI-driven material design, and sustainable thermal systems. He has secured significant research funding and continues to develop scalable solutions for next-generation energy and water technologies.

• Signal Processing
• Image Processing
• Wireless Sensor Networks
• +12 more

Professor Tariq Durrani is a Research Professor in the Department of Electronic and Electrical Engineering at the University of Strathclyde, UK. He is also recognized as a Visiting Professor and Honorary Professor at other institutions, reflecting his international academic engagement. His research spans signal and image processing with applications in sensor networks, UAVs, and intelligent communication systems. Research Interests: Signal and Image Processing Integrated Sensing and Communication (ISAC) Unmanned Aerial Vehicle (UAV) Networks Wireless Sensor Networks Big Data Analytics for Energy and Infrastructure Cognitive Neuroscience-Inspired Systems His recent publications highlight a strong trend in leveraging deep learning and optimization techniques for next-generation wireless systems, particularly in intelligent transportation, secure communications, and IoT. The integration of sensing, communication, and computing in UAV-enabled environments is a dominant theme. His work contributes to UN Sustainable Development Goals in clean energy, smart cities, and climate action. Scientific Awards and Honors: Thales Scottish Technology Prize 2009 (Third Place) Elected Honorary Member, Eta Kappa Nu (2010) Honorary Professor, University of Stirling (2010) Visiting Professorial Fellow (2012) Vice President (International Activities) Recipient (2012) Research Leadership: He has led and co-led multiple funded research projects, including those supported by the Royal Society of Edinburgh and the British Council, focusing on geological disaster monitoring, microseismic detection in oil exploration, and cognitive information integration in heterogeneous networks. His collaborative network spans the UK, China, and other international partners. Laboratories and Research Teams: His work is associated with advanced research in intelligent systems and sensor networks at the University of Strathclyde, contributing to the Fingerprint research profile in areas such as Unmanned Aerial Vehicles, Algorithms, and Optimization.

Anthony GachaganView profile

Professor

• Ultrasonics
• Non-Destructive Evaluation (NDE)
• Ultrasonic Transducer Design
• +13 more

Professor Anthony Gachagan is a leading academic at the University of Strathclyde, serving as Head of Department and Research Director in the Department of Electronic and Electrical Engineering (EEE) within the Faculty of Engineering. He has been Director of the Centre for Ultrasonic Engineering (CUE) since 2010, leading a multidisciplinary team of around 55 researchers with over £5M in active funding. He also holds leadership roles in RCNDE as Academic Chair and Management Board member, and participates in BINDT committees. His research spans ultrasonic transducer design, non-destructive evaluation (NDE), robotics, high-power ultrasound, and industrial process control. His work is highly collaborative, involving national and international partnerships with industry and academia, and contributes to sectors such as energy, aerospace, nuclear, and healthcare. He is actively involved in major research initiatives aimed at net zero, structural integrity, and advanced manufacturing. Recent publications highlight his focus on robotic ultrasonic inspection, adaptive signal processing, phased array techniques, and in-process monitoring of additive manufacturing. These works demonstrate a strong trend toward automation, real-time defect detection, and integration of ultrasonic systems in industrial and safety-critical applications. Scientific Awards: The BINDT Annual Conference Award (2019) Prof Gachagan has secured significant grants from EPSRC, Innovate UK, and industry partners, including projects on future ultrasonic engineering, lightning impulse testing, and robotic inspection for offshore wind. He supervises numerous research students and leads large collaborative teams. He also contributes to research commercialization through IAA projects. He leads the Centre for Ultrasonic Engineering (CUE), a vibrant research unit integrating electronic, mechanical, and biomedical engineers, physicists, and material scientists. The centre focuses on next-generation ultrasonic technologies, robotics integration, and industrial deployment.

• Non-Destructive Evaluation
• Ultrasonic Testing and Imaging
• Eddy Current Testing
• +9 more

Dr. Ehsan Mohseni is a Senior Lecturer in the Department of Electronics and Electrical Engineering at the University of Strathclyde, Faculty of Engineering. He is a key member of the Centre of Ultrasound Engineering (CUE) research group and supports the Royal Academy of Engineering and Spirit AeroSystems research chair led by Professor Gareth Pierce. His work focuses on advancing robotic and intelligent Non-Destructive Evaluation (NDE) systems for industrial applications. B.Sc. in Materials Science and Metallurgical Engineering, University of Tehran, 2006 M.Sc. in Metal Forming Processes, University of Tehran Ph.D. in Automated Defect Detection using Electromagnetic NDE, École de Technologie Supérieure (ETS), Montreal, Canada Dr. Mohseni’s research is centered on NDE 4.0, integrating advanced sensing, multi-physics modeling, and machine learning. His expertise spans ultrasonic and eddy current testing, multi-sensor data fusion, and probability of detection studies. He focuses on applications in additive manufacturing, welding, composites, and metal processing, aiming to overcome current technological barriers in industrial inspection. The recent publications highlight a strong trend toward intelligent, automated, and robotic NDE systems. Key themes include self-supervised learning for ultrasonic segmentation, human-machine collaboration in data analysis, and advanced signal processing for weld and composite inspection. The integration of AI, flexible sensor arrays, and embedded navigation systems reflects a shift toward smart, adaptive inspection platforms aligned with Industry 4.0. Scientific Awards: The BINDT Annual Conference Award (2019) Dr. Mohseni is actively involved in research funding and knowledge transfer. He serves as Principal Investigator on KTP projects with ETHER NDE LIMITED and NATIONAL OILWELL VARCO UK LIMITED, focusing on in-process inspection for additive manufacturing and field calibration for ultrasonic testing. He contributes to large-scale collaborative projects funded by Innovate UK and industry partners, emphasizing practical deployment of NDE solutions. He also supervises research staff and collaborates with global aerospace firms including Pratt & Whitney Canada, Safran, and Bell Helicopter. He is a core member of the Centre of Ultrasound Engineering (CUE), a dynamic research group developing next-generation ultrasound technologies. The team works on advanced robotic sensing hubs, flexible transducer arrays, and AI-driven data interpretation tools, often in collaboration with the Royal Academy of Engineering research chair and industrial partners.