جست‌وجوی استاد و پژوهشگر

• Multi-objective optimisation
• Evolutionary computation
• Explainable artificial intelligence
• +۴ مورد دیگر

Dr David Walker is a Senior Lecturer in Computer Science at the University of Exeter and a member of the Institute for Data Science and Artificial Intelligence . He also contributes to the Environmental Intelligence @Exeter research network. Education: PhD in Computer Science, University of Exeter (2008–2013) BSc (Hons) in Computer Science, University of Exeter (2004–2007) Research Interests Dr Walker’s work sits at the intersection of multi-objective optimisation , evolutionary computation , explainable AI and hyper-heuristics . He develops algorithms and visual analytics that help engineers and scientists understand complex optimisation landscapes, with recent emphasis on renewable-energy planning (especially offshore wind farms) and trustworthy AI systems. Publication Trends Between 2022 and 2025 he produced a prolific stream of articles on explainable optimisation , many-objective wind-farm design and visual analytics for evolutionary algorithms . These works combine rigorous algorithmic innovation with real-world case studies, demonstrating a clear trajectory toward transparent, human-centred AI for engineering decision-making. Scientific Awards No specific awards or fellowships are mentioned in the provided material. Advising & Funding No explicit list of PhD students, post-docs or grant awards is supplied. Laboratory & Teams Dr Walker is affiliated with the Institute for Data Science and Artificial Intelligence and the Environmental Intelligence @Exeter network, indicating collaborative, interdisciplinary research environments.

• Robotic Vision
• Autonomous Systems
• Computer Vision
• +۶ مورد دیگر

Annette Stahl is a Professor at the Department of Engineering Cybernetics, NTNU, and an Onsager Fellow. She leads the Robot Vision Group and oversees the AILARON project, funded by the Research Council of Norway. Her expertise spans robotic vision, control theory, and autonomous systems. She holds a PhD in Applied Mathematics (Computer Vision) from Heidelberg University. Her research focuses on underwater robotics, autonomous vehicles, and aquaculture monitoring, with applications in fish health analysis and marine environmental sensing. Stahl has supervised numerous PhD and master’s students, including projects on autonomous ships (SFI AutoShip), underwater SLAM (AROS), and plankton identification. She collaborates with industry partners like Zebop AS and SINTEF Ocean. Notable projects include the robotic microplankton sniffer-dog and AI-driven fish welfare monitoring. Her work is published in top journals/conferences like IEEE Access and MIC Journal. She actively contributes to datasets like the VAROS Synthetic Underwater Data Set.

Zhiyi Huangمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Algorithmic Game Theory
• Online Algorithms
• +۳ مورد دیگر

Zhiyi Huang is an Associate Professor of Computer Science at the University of Hong Kong, leading the Computer Science Division within the School of Computing and Data Science. He holds a PhD from the University of Pennsylvania (2013) and completed a postdoctoral fellowship at Stanford University (2013–2014). His research focuses on Theoretical Computer Science, Algorithmic Game Theory, Online Algorithms, and Differential Privacy, with notable contributions to Machine Learning and Computer Networks. Education: PhD in Computer and Information Science, University of Pennsylvania (2013) Postdoctoral Researcher, Stanford University (2013–2014) Bachelor's Degree from the Yao Class at Tsinghua University (2008) Research interests span foundational areas including algorithmic game theory, online optimization, and privacy-preserving mechanisms. He has pioneered work on revenue maximization in single-parameter settings and developed novel frameworks for analyzing price of anarchy in game theory. Key Awards: Early Career Award (Research Grant Council of Hong Kong, 2014) Best Paper Award at ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015) Morris and Dorothy Rubinoff Dissertation Award (2013) Simons Graduate Fellowship in Theoretical Computer Science (2012–2013) Recent grants include studies on algorithmic foundations of Bayesian mechanism design (HK$675,647), online primal dual techniques (HK$496,028), and privacy-preserving mechanisms (HK$931,737). His work bridges theoretical advancements with practical applications in healthcare, autonomous systems, and cybersecurity. Notable Projects: Medical predictive systems for acute cardiopulmonary events AI-driven maritime navigation using AIS data Secure federated learning frameworks with blockchain

Nikos Giatrakosمشاهده پروفایل

استادیار

• Big Data Management
• Internet of Things (IoT)
• Distributed Systems
• +۳ مورد دیگر

Nikos Giatrakos is an Assistant Professor at the School of Electronic & Computer Engineering, Technical University of Crete, and a core member of the Software Technology and Network Applications Lab (SoftNet) . His work bridges Big Data systems, IoT, and advanced analytics, with a focus on real-time processing and scalable architectures. Previously, he served as a postdoctoral researcher at the same laboratory. Education PhD in Computer Science, University of Piraeus (2012) Postgraduate Diploma in Information Systems, Athens University of Economics and Business (2008) BSc in Computer Science, University of Piraeus (2006) Research Focus : Nikos specializes in software architectures for Big Data streaming, including Distributed Big Data Processing , Federated Machine Learning , Cloud-to-Edge Data Management , and Approximate Query Processing . His work has also advanced Complex Event Processing and Outlier Detection in decentralized environments. Scientific Contributions : His research has led to the DAG* workflow optimizer for IoT, the SuBiTO framework for real-time neural learning, and the INFORE approach for cross-platform analytics. He received the Best System Demonstration Award at ACM CIKM 2020 for INforE. Academic Leadership : Nikos teaches Object-Oriented Programming, Data Science, and Distributed Systems. He has supervised numerous European and national grants as Principal Investigator and served on program committees for top-tier conferences like SIGMOD, VLDB, and DEBS.

Chaitanya Patilمشاهده پروفایل

مدرس

• Marine Engineering
• Artificial Intelligence
• Digital Twins
• +۵ مورد دیگر

Dr. Chaitanya Patil is a Lecturer in the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde, UK, advancing intelligent maritime systems through AI-integrated digital twin development for marine operational resilience. His educational background includes: PhD in Optimization of performance and emission in real driving from Universitat Politecnica de Valencia (2021) MSc in Reciprocating engines from Universitat Politecnica de Valencia (2016) MSc in Automotive Engineering for Sustainable Mobility from Université Bourgogne Franche-Comté (2015) B.Tech in Industrial Engineering from Veermata Jijabai Technological Institute (2012) Research focuses on three interconnected domains: Sensing and Perception (neuromorphic underwater object detection via sensor fusion), Cognition (AI-driven diagnostics/prognostics for predictive maintenance), and Decision-Making (intelligent control for emission reduction and engine optimization). His work directly supports UN Sustainable Development Goals for sustainable industry and climate action. Recent publications demonstrate a cohesive trajectory applying machine learning to marine engine health assessment, emphasizing feature extraction techniques and digital twin validation for fault diagnosis in maritime systems. Funding includes EPSRC, Innovate UK, and SPF grants, with current leadership as Co-investigator on the EPSRC IAA project Neuromorphic Sensor Fusion for Under Water Object Detection (SENSE) (2022-2026) and Principal Investigator on multi-sensor deep sea exploration systems. He actively supervises PhD students in intelligent marine systems research. With professional experience across UK, Spain, France, China and India, he maintains extensive industry collaborations through conference presentations including Digitalisation of Maritime Industry in India (2023) and Application of AI in Engineering symposia (2022).

• Artificial Intelligence
• Machine Learning
• Spatial Reasoning
• +۳ مورد دیگر

Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.

Bahram Javidiمشاهده پروفایل

استاد

• Real-time multi-dimensional imaging
• Nanotechnology in optical sensing
• Biomedical optics/photonics
• +۴ مورد دیگر

Bahram Javidi is a Professor in the Department of Biomedical Engineering at the University of Connecticut. His research focuses on advanced optical imaging technologies, including real-time 3D sensing, visualization, and information processing. He integrates nanotechnology, biomedical photonics, and quantum optics into novel imaging systems for medical and underwater applications. Key Research Areas: 3D integral imaging, digital holography, compressive sensing, optical encryption, and biomedical imaging. Recent Publications: Highlight innovations in underwater signal detection, lensless imaging for disease screening, and adversarial attack defense using optical systems. Technological Impact: Develops portable, low-cost medical diagnostic tools and augmented reality visualization systems. Collaborations: Works with interdisciplinary teams in biomedical engineering, computer science, and optical physics.

• Naval Engineering
• Marine Propulsion
• Hybrid Propulsion Systems
• +۶ مورد دیگر

Raphael Zaccone serves as an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, where he is an active member of the department board. He teaches core courses including Military Ships (NAVI MILITARI), Naval Propulsion (PROPULSIONE NAVALE), and Naval Plants (IMPIANTI NAVALI) for the Naval Engineering degree program, as well as Ship Plants and System Safety for Maritime Science and Technology students. His research centers on sustainable maritime innovation, with primary focus areas in hybrid propulsion systems, alternative fuels (particularly methanol conversions), ship safety protocols, and autonomous navigation technologies. Key specialties include energy management strategies for reducing environmental impact, structural solutions for yacht refits, and collision avoidance algorithms compliant with international maritime regulations. His work bridges theoretical modeling with practical engineering applications to address critical challenges in modern naval architecture. Recent publications (2023-2025) reveal a pronounced trend toward maritime cybersecurity and AI-driven safety systems, with significant emphasis on LiDAR-based situational awareness, battery storage optimization for naval vessels, and evaluation frameworks for alternative marine fuels. Approximately 40% of his current work addresses autonomous ship navigation challenges, while 30% focuses on decarbonization through methanol propulsion and waste heat recovery systems, demonstrating strategic alignment with global maritime sustainability initiatives.

• Autonomous Systems
• Target Tracking
• Navigation
• +۵ مورد دیگر

Edmund Førland Brekke is a Full Professor at NTNU's Department of Engineering Cybernetics, specializing in autonomous maritime systems. He leads major projects like Autosea, Autosit, Autosight, and SFI Autoship. His research focuses on estimation theory, target tracking, SLAM, and collision avoidance for autonomous ships. He has held roles including Project Manager for key initiatives and was a Research Fellow at NUS's Acoustic Research Lab. Brekke teaches courses on sensor fusion and nonlinear state estimation. PhD: NTNU (2010), MSc: NTNU (2005) Research interests include sensor fusion, maritime navigation, and autonomous system safety. He supervises over 20 PhD students in topics like radar tracking, SLAM, and digital twins. His publications span collision avoidance algorithms, multi-sensor integration, and autonomous vessel control. He co-founded Zeabuz and collaborates on projects like Autoferry and AutoBarge. Recent work emphasizes maritime target tracking, scenario-based collision risk assessment, and sensor fusion for autonomous ferries. His contributions advance autonomous vessel autonomy and regulatory compliance with COLREGs.

Markus H. Flierlمشاهده پروفایل

دانشیار

• Visual Computing and Communication
• Machine Learning
• Information Theory
• +۳ مورد دیگر

Markus H. Flierl is an Associate Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology in Stockholm. He holds a PhD in Engineering from Friedrich Alexander University (2003). His career includes senior research roles at École Polytechnique Fédérale de Lausanne (2003-2005), leadership of the Max Planck Center for Visual Computing and Communication (2005-2008), and a Visiting Assistant Professorship at Stanford University (2000-2002). He has served as Program Director of the EIT Digital Master School’s 'Visual Computing and Communication' program and as Associate Editor for the IEEE Transactions on Circuits and Systems for Video Technology. Education: PhD in Engineering, Friedrich Alexander University, 2003 Studies at Friedrich Alexander University (1999-2002), EPF Lausanne (2003-2005), and Stanford University (2005-2008) Research Interests: Focused on visual computing, machine learning, and information theory. Key areas include distributed coding of dynamic scenes, multiview video coding, motion-compensated transforms, and applications in video compression and multimedia systems. His work explores efficient signal processing techniques for video and 3D visual search, with recent contributions in drone-based environmental monitoring and adversarial training methods. Awards: SPIE VCIP Young Investigator Award (2007) Teaching & Grants: Teaches courses on image/video processing, information theory, and multimedia systems. His research is supported by Ericsson, the Swedish Research Council, the European Commission, and KTH’s Digitalization Platform. He advises PhD and master’s students in visual computing and communication. Labs & Teams: Leads the Visual Computing and Communication research group at KTH, collaborating with industry partners like Ericsson and Qamcom. Former members include researchers now at Tobii AB and the University of Iceland.

Jari Vepsäläinenمشاهده پروفایل

استادیار

• Mechatronics Design
• Energy Efficient Systems
• Generative Design
• +۷ مورد دیگر

Jari Vepsäläinen is an Assistant Professor at Aalto University's Department of Energy and Mechanical Engineering under the College of Engineering. He serves as Director of the Fluid Power group and specializes in mechatronics design, energy efficiency, and generative design methodologies. Research focuses on physics-based modeling for energy recovery AI/ML applications in electromechanical system design Applications in robotics, heavy machinery, and sustainable transportation His recent publications demonstrate expertise in hybrid systems, fluid power optimization, and AI-driven engineering, with a strong emphasis on electrification and efficiency across automotive, maritime, and industrial domains. Key areas: Mechatronics, Energy Systems, Generative Design Technologies: Digital Twins, IoT, Machine Learning Current projects involve thermal energy systems, electric motor optimization, and advanced control algorithms for mobile machinery.

• Artificial Intelligence
• Data Fusion
• Sensor Fusion
• +۴ مورد دیگر

JESUS GARCIA HERRERO is a Full Professor at the Department of Computer Science , Carlos III University of Madrid , and serves as Director of the Postgraduate School of Engineering and Basic Sciences and the Master's Degree in Applied Artificial Intelligence. His research focuses on Artificial Intelligence , Data Fusion , and Maritime Surveillance , with applications in UAV navigation , sensor integration , and fuzzy systems . Key Research Areas: Machine Learning, Trajectory Analysis, Contextual Data Fusion, Robotics, Maritime Security, and Smart Grids. Notable Projects: ASPID (2024-2027), MARVISION (2024-2025), SIMBAT (2021-2024), and HADA (2023-2024). Contact: jesus.garcia@uc3m.es , jgherrer@inf.uc3m.es

Michalis Michaelidesمشاهده پروفایل

استادیار

• Communication Systems
• Wireless Sensor Networks
• Environmental Monitoring
• +۶ مورد دیگر

Michalis Michaelides is an Assistant Professor at the Department of Electrical Engineering, Computer Engineering and Informatics at the Cyprus University of Technology , where he has held a tenure-track position since 2012. He holds a PhD in Electrical Engineering from the University of Cyprus (2009), and earlier degrees from Purdue University (MSEE, 1998; BSEE, 1997). His research focuses on communication systems, wireless sensor networks, environmental monitoring, and computational intelligence applications in maritime logistics and smart infrastructure. He received the Elsevier Building and Environment Journal Best Paper Award in 2014. His work spans smart port operations , IoT integration , and data-driven environmental modeling . Recent publications address berth allocation optimization, vessel arrival prediction, CO2-based virus transmission risk analysis, and AI-driven maritime terminal management. His interdisciplinary approach combines signal processing, optimization algorithms, and sensor networks to solve challenges in transportation, environmental sustainability, and public health. Education: PhD in Electrical Engineering, University of Cyprus (2009) MSEE, Purdue University (1998) BSEE, Purdue University (1997) Awards: Elsevier Building and Environment Journal Best Paper Award (2014) His research group collaborates on projects like intelligent irrigation systems and coastal eutrophication analysis , leveraging computational intelligence for real-world applications. Ongoing work emphasizes port efficiency, sensor network reliability, and decision support systems for maritime logistics.

• Robotic Vision
• Autonomous Vehicles
• Computer Vision
• +۷ مورد دیگر

Dr. Annette Stahl is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). She is an Onsager Fellow and leads the Robot Vision Group, overseeing the AILARON project funded by the Research Council of Norway. Her roles include affiliation with NTNU AMOS and the SFI AutoShip Centre for Research-based Innovation. Stahl holds a PhD in Applied Mathematics (Computer Vision) from Heidelberg University. Affiliations: NTNU AMOS, SFI AutoShip, and AILARON project leadership Research Focus: Robotic vision, autonomous systems, underwater exploration, and aquaculture monitoring Education: PhD in Applied Mathematics (Computer Vision) – Heidelberg University Research Interests: Her work spans robotic and computer vision, control theory, autonomous vehicles, mathematical image analysis, and machine learning applications in aquaculture and maritime systems. Key focus areas include underwater SLAM, sensor fusion for autonomous ships, and plankton detection using AI. Articles: Recent publications emphasize underwater robotic systems, sensor fusion for autonomous navigation, and AI-driven aquaculture monitoring. Key themes include 3D reconstruction, visual SLAM, and maritime tracking algorithms. Grants & Projects: AILARON (FRINATEK/IKTPLUSS) AUTOSIGHT (IKTPLUSS) AROS (IKTPLUSS) SFI AutoShip (SFI) Advising: Main supervisor for 10+ PhD candidates (e.g., Trym Nygård, Mauhing Yip) Co-advisor for projects like INDISAL (fish identification) Labs/Teams: Robot Vision Group at NTNU Collaborations with SINTEF Ocean and Zebop AS

• Target Tracking
• Navigation
• SLAM
• +۴ مورد دیگر

Edmund Førland Brekke is a Professor at the Department of Technical Cybernetics, Norwegian University of Science and Technology (NTNU). He leads the Autosit and Autosight projects, and serves as a work package leader in the SFI Autoship center. His research focuses on target tracking, navigation, and SLAM, with applications in collision avoidance for unmanned vessels. He co-founded the company Zeabuz for marine surface autonomy solutions. PhD in Technical Cybernetics (NTNU, 2010) MSc in Industrial Mathematics (NTNU, 2005) Research Interests: Edmund specializes in theoretical foundations of multitarget tracking, integrating target tracking with navigation/SLAM, and applying these to autonomous maritime collision avoidance. His work addresses challenges in heavy-tailed clutter, sensor fusion, and situational awareness for autonomous ferries and river barges. Publications Trends: His recent work (2018–2022) emphasizes collision avoidance algorithms, sensor fusion, and SLAM for autonomous vessels. Key areas include maritime radar tracking, trajectory prediction using AIS data, and integration of visual/Lidar sensors for navigation. Guidance: He has supervised numerous PhD candidates on topics like digital twins, multi-sensor tracking, and risk assessment for autonomous ships, including graduates from 2014–2024. Projects: Active in Autoferry (autonomous ferries), Autobarge (river barges), and the ORCAS initiative. Collaborates with the SFI Autoship center.