Find Academic Supervisors

Simon LarssonView profile

Researcher

• Social Anthropology
• Anthropology of Religion
• Colonial History
• +8 more

Simon Larsson is a Researcher in Social Anthropology at the Center for Multidisciplinary Research on Religion and Society (CRS), Department of Theology, Uppsala University. His work bridges colonial history, Christianity, and the social implications of emerging technologies including AI, nanotechnology, and cybersecurity, with a strong focus on governance frameworks in natural resource management. His research interests reveal a distinctive interdisciplinary trajectory examining how technological systems intersect with religious practices and colonial legacies. Key themes include the anthropology of Christianity in legal-historical contexts (evident in Congo mission studies), digital technology's societal impacts (particularly machine learning's parallels with traditional oracles), and collaborative governance models in environmental conflicts across Sweden and sub-Saharan Africa. Fieldwork spans diverse geographical settings from New Mexico's geological landscapes to Côte d'Ivoire's ritual practices, emphasizing local knowledge systems. Recent publications demonstrate a pronounced shift toward analyzing technology's ethical dimensions through anthropological frameworks, while maintaining continuity in environmental governance research. His 2024-2025 works particularly highlight comparative studies of contingency reduction mechanisms across magical, religious, and algorithmic systems, alongside practical applications in maritime logistics and wildlife management. Larsson's research is primarily funded by the Swedish Research Council, Formas, Mistra, and the Swedish Transport Administration, with additional support from multiple foundations. His collaborative projects frequently involve cross-institutional teams addressing real-world governance challenges in conservation, transportation, and human-technology interaction. As a core member of the Center for Multidisciplinary Research on Religion and Society (CRS), he contributes to an integrated research environment that connects theological studies with anthropological fieldwork and policy-oriented governance analysis, facilitating dialogue between religious traditions and contemporary technological societies.

• Machine Learning
• Environmental Risk Modeling
• Marine Technology
• +2 more

Jarl Gunnar Taxerås Flaten is an Associate Professor at the Norwegian Fisheries College, part of UiT The Arctic University of Norway. His academic work focuses on interdisciplinary research at the intersection of marine technology and computational methods. Institution: UiT The Arctic University of Norway College: Norwegian Fisheries College Email: jarl.g.flaten@uit.no Research interests include: Development of machine learning models for environmental risk assessment Long-term forecasting systems for Arctic maritime conditions Data-driven approaches to marine safety and climate adaptation Recent publications demonstrate his focus on computational methods applied to polar engineering challenges, particularly ice risk prediction in Norwegian Arctic waters. His work combines algorithmic innovation with practical maritime applications.

Martin MasekView profile

Associate Professor

• Computer Vision
• Image Processing
• Artificial Intelligence
• +9 more

Martin Masek is an Associate Professor of Computer Science in the School of Science at Edith Cowan University (ECU), where he leads the Centre for Artificial Intelligence and Machine Learning (CAIML). He has been with ECU since 2005, having completed his PhD at The University of Western Australia in 2004. His academic journey began with a Bachelor of Engineering with 2nd Class Honours in IT from The University of Western Australia in 1998. Dr. Masek's research spans multiple domains of computer science with a focus on artificial intelligence and its applications. His primary research interests include computer vision and image processing, artificial intelligence and machine learning (particularly Evolutionary Algorithms and Neural Networks), and applications of games technology for modeling, simulation, and visualization. His work demonstrates significant interdisciplinary reach, connecting computer science with health, education, and defense applications. His recent publications reveal a strong trend toward applying AI techniques to solve real-world problems across diverse domains. A significant portion of his work focuses on serious games and virtual reality for health education and training, including applications for meningococcal disease education, clinical leadership development, and aggression de-escalation training. Another major theme involves maritime traffic analysis and anomaly detection, often incorporating seasonal context. His research also includes medical imaging applications, particularly for diabetic foot osteomyelitis detection and radiology report generation, as well as military applications involving strategy discovery and virtual training environments. Dr. Masek has successfully secured numerous competitive research grants totaling millions of dollars, with recent projects including "Immersive Violence and Aggression De-escalation Experience (IVADE)" funded by the Department of Health WA ($408,928), "AI-driven virtual character simulation for aggression and violence de-escalation training in virtual reality" ($499,660), and "Virtual-reality-enhanced advanced tactical parachute training" funded by the Department of Jobs, Tourism, Science and Innovation ($346,145). He has supervised numerous research students to completion, including doctoral candidates working on topics such as "Evolving gameplay elements into virtual terrains," "A Cooperative Co-evolutionary Approach to the Automated Discovery of Team Behaviour in Real-time Strategy Games," and "Detecting diabetic foot osteomyelitis in plain radiographic images using deep learning." His current supervision includes projects on "Anomaly Detection of Seasonal Vessel Activity" and "Representation Learning for Asychronous Data Streams." Dr. Masek leads the Centre for Artificial Intelligence and Machine Learning (CAIML) at ECU, which appears to focus on interdisciplinary AI research with applications across health, defense, and other sectors. His work demonstrates a strong commitment to translating theoretical AI research into practical applications that address real-world challenges.

Marco LübbeckeView profile

Professor

• Operations Research
• Mixed Integer Programming
• Branch-and-Price Algorithms
• +3 more

Marco Lübbecke is a Professor at the Faculty of Business and Economics of RWTH Aachen University , Germany. He serves as the chairholder of the Lehrstuhl für Operations Research and holds the position of Studiendekan (Dean of Studies) for his faculty. His professional contact is marco.luebbecke@rwth-aachen.de, with additional administrative contact at luebbecke@or.rwth-aachen.de. Current academic rank: Professor Faculty: Business and Economics Department: Operations Research Marco Lübbecke's research focuses on Operations Research and Mixed Integer Programming . He develops and analyzes algorithms like Branch-and-Price , Dantzig-Wolfe Reformulation , and Decomposition Methods to solve complex optimization problems in industrial, transportation, and political science applications. Core research areas: Combinatorial Optimization, Mathematical Programming Application domains: Logistics, Rail Transport, Redistricting, Manufacturing Systems Methodological interests: Column Generation, Cutting Planes, Algorithm Engineering His recent publications highlight advancements in optimization software frameworks like the SCIP Optimization Suite and algorithmic techniques for solving large-scale linear and integer programs. Key research trends include automated decomposition methods, structural analysis of MIPs, and hybrid approaches combining classical optimization techniques with machine learning insights. Marco Lübbecke actively participates in academic conferences and serves as a co-author in numerous technical reports and journal publications, contributing to the development of efficient optimization algorithms and their practical implementation.

• Disaster Resilience
• Earthquake Engineering
• Structural Health Monitoring
• +4 more

Alessandro Cardoni is a Fixed-term Assistant Professor at the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Polytechnic University of Turin, Italy. He holds a position under Law 240/10 art.24-a and is actively involved in teaching and research activities related to structural engineering and disaster resilience. His educational background includes a doctoral dissertation titled "Community Resilience and Seismic Performance of Physical Infrastructures" completed in 2021. His academic progression shows a clear trajectory from doctoral research to independent research leadership with increasing supervisory responsibilities. Dr. Cardoni's research focuses on critical infrastructures, disaster resilience, earthquake engineering, and structural health monitoring. His work bridges theoretical approaches with practical applications for improving infrastructure safety. He has developed innovative methodologies for structural identification, seismic vulnerability assessment, and resilience analysis of complex infrastructure systems, often incorporating machine learning techniques, sensor networks, and advanced computational modeling. His publication record shows consistent output with a focus on practical applications of structural engineering principles to real-world problems, including analysis of historical structures, port infrastructure, and critical urban systems. His recent work demonstrates particular attention to infrastructure interdependencies and frameworks for assessing community resilience. RESILFIRE (2025-2028): Dynamic Infrastructures and Resilient Communities: a Systemic Approach to Wildfire Risk Mitigation and Adaptation - Scientific Research Manager FOURIER (2024-2028): Innovative Artificial Intelligence methodologies for monitoring and maintaining large scale complex infrastructures - Research Group Member Dr. Cardoni supervises PhD students including Simone Salvatori (40th cycle, 2025-present) and Amir Reza Elahi (39th cycle, 2023-present) in Civil and Environmental Engineering. He is actively involved in the Disaster Resilience Simulation Laboratory (DISEG) where advanced research on infrastructure resilience is conducted through interdisciplinary collaboration.

• Reinforcement Learning
• Military Simulation Technologies
• Medical Signal Processing
• +3 more

Hüseyin Oktay Altun is an Assistant Professor at Bogazici University, serving as a full-time faculty member. His research focuses on advanced topics such as smart virtual entity design via reinforcement learning, multimedia security with convex optimization, medical/military signal processing, and time series prediction for environmental and financial data. His work bridges theoretical computer science with practical applications in healthcare, defense, environmental science, and energy systems. Notable research interests include the development of autonomous systems for military simulations, AI-driven medical diagnostics (e.g., hip dislocation detection in infants and epilepsy diagnosis), and environmental modeling for pollution prediction. His contributions also extend to cybersecurity, particularly in watermarking and steganography, as well as renewable energy grid management. His publication trends highlight a strong emphasis on reinforcement learning (RL) for multi-agent systems and tactical simulations, alongside deep learning applications in medical imaging, environmental monitoring, and maritime security. His work often integrates interdisciplinary approaches, combining machine learning with domain-specific challenges in defense, healthcare, and energy sectors. While no formal awards or grants are mentioned in the provided text, his extensive list of publications reflects significant contributions to both theoretical and applied computer science. No information on academic advising or lab affiliations is available here, but his research collaborations likely span multiple departments at Bogazici University and international partners.

Harry Bradford BinghamView profile

Professor

• Nonlinear Ocean Waves
• Coastal Engineering
• Ocean Engineering
• +4 more

Harry Bradford Bingham is a Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on nonlinear ocean waves and their interaction with marine structures, contributing to UN Sustainable Development Goals related to sustainable oceans and energy. He specializes in numerical methods, coastal engineering, and wave energy systems. Key research areas include fluid mechanics, potential flow modeling, and the development of high-fidelity numerical models for marine systems. His work spans topics such as wave energy converters, wind propulsion optimization for ships, and hydrodynamic response analysis of offshore structures. Recent publications highlight advancements in machine learning applications for hydrodynamic calculations, comparative studies on floating offshore wind turbines, and cost-benefit analyses for sustainable maritime technologies. He oversees multiple interdisciplinary projects, including PhD supervision in areas like propeller noise reduction, ship hydro-elasticity, and wind propulsion systems. Bingham collaborates globally, contributing to datasets like the DeRisk Database. His research emphasizes practical solutions for maritime sustainability and energy efficiency.

• Autonomous Systems
• Communications Systems
• Defense Information Systems
• +5 more

Professor Weisi Guo is a faculty member at Cranfield University, serving as Head of the Centre for Assured & Connected Autonomy and Head of the Human Machine Intelligence Group. He holds a Professorial rank in Human Machine Intelligence. His academic background includes MEng, MA, and PhD degrees from the University of Cambridge. Research interests focus on autonomous systems, communications systems, defense information systems, safety, resilience, risk management, and systems engineering. He leads projects such as the EPSRC CHEDDAR (£3+8.5m) and TAS-S (£1.2m) grants, emphasizing trustworthy autonomous systems and security. Notable achievements include the IET Innovation Award (2015) and Bell Labs Prize runner-up mentions. Key publications span drone trajectory prediction, underwater sensor networks, and 6G network specifications. He has supervised students like Sorin Negru and collaborates with institutions like BAE Systems and Thales. His work bridges AI, communication systems, and human-centric design to address societal challenges in cyber-physical systems.

Ozgur KabadurmusView profile

Assistant Professor

• Supply Chain Management
• Operations Research
• Sustainability
• +3 more

Ozgur Kabadurmus is an Assistant Professor in the Department of Marketing and Supply Chain Management at the University of Wisconsin-Eau Claire, within the College of Business. His research focuses on sustainable supply chain design, operations optimization, and the application of data-driven methodologies in logistics systems. Dr. Kabadurmus holds a Ph.D. in Industrial and Systems Engineering from Auburn University, along with multiple advanced degrees from Istanbul Technical University. Education: Ph.D., Industrial and Systems Engineering, Auburn University M.S., Industrial and Systems Engineering, Auburn University M.S., Industrial Engineering, Istanbul Technical University B.S., Industrial Engineering, Istanbul Technical University Research Interests: His work spans lean manufacturing systems, green logistics optimization, big data analytics for supply chain decision-making, and circular economy models. He has published extensively in journals like Socio-Economic Planning Sciences, Journal of Combinatorial Optimization, and Annals of Operations Research. Key Research Trends: Recent publications emphasize pandemic-resilient supply chains, disruptive technologies in last-mile delivery, and multi-objective optimization for carbon footprint reduction. His methodologies often integrate machine learning and simulation tools for predictive analytics. Grants & Advising: While specific grants are not listed, his collaborative work with industry partners (e.g., logistics firms) indicates applied research funding. No advisee information is included in the provided text. Labs/Teams: Affiliated with the College of Business research initiatives in supply chain innovation and sustainable operations.

Pål EllingsenView profile

Associate Professor

• Remote Sensing
• Cryptography
• Space Science
• +6 more

Pål Ellingsen is an Associate Professor at the Department of Computing, Mathematics, and Physics at Western Norway University of Applied Sciences. His research spans remote sensing, cryptography, space science, and machine learning, with applications in structural monitoring, marine data management, and aerospace engineering. Contact: Pal.Ellingsen@hib.no | Office E407 Research Interests include: Remote sensing techniques like DInSAR for monitoring storage facilities Cryptographic properties and Boolean function analysis Space science via CubeSats and aurora observation Machine learning applications in port automation His recent publications highlight trends in interferometric SAR for volume tracking , free space optical communication in Arctic environments , and open data practices in marine science . Ellingsen contributes to projects like the Nansen Legacy Project and the Boreal Aurora Camera Constellation (BACC) . His work bridges technical and multidisciplinary fields, emphasizing data-driven solutions and advanced signal processing.

Panagiota TselentiView profile

Lecturer

• Artificial Intelligence
• Data Mining
• Information Retrieval
• +5 more

Panagiota Tselenti is a Lecturer in the Department of Informatics and Computer Engineering at the University of West Attica. She holds a PhD in Computer Science from Kingston University (UK, 2017), specializing in artificial intelligence algorithms, social network analysis, and recommender systems. Her teaching spans undergraduate and postgraduate programs since 1995, covering Robotics, Artificial Intelligence, Information Retrieval, and Natural Language Processing. She actively contributes to the Lab Teaching Staff, integrating academic rigor with practical applications. Her research focuses on artificial intelligence, data mining, and robotics, with notable work on trust-based recommendation systems and fuzzy logic methodologies. Education: PhD in Computer Science (Kingston University, UK, 2017) MSc in Data Communication Automation Engineering (BSc) Research interests include Recommender Systems, Social Network Analysis, Knowledge Management, and Robotics. Her work bridges machine learning techniques with real-world applications in education and energy systems. Recent publications explore trust models, deep learning for electric load forecasting, and policy development in maritime education using fuzzy cognitive maps. Her teaching spans over two decades, emphasizing both theoretical foundations and hands-on experience in informatics disciplines. Professional contributions are documented in her CV and personal website.

Bernhard RabusView profile

Professor

• Synthetic Aperture Radar (SAR)
• Maritime Applications of SAR
• Landslide Monitoring
• +5 more

Bernhard Rabus is a Professor and holder of the Industrial Research Chair in Synthetic Aperture Radar (SAR) at Simon Fraser University's School of Engineering Science. His work focuses on SAR technologies, with emphasis on maritime applications and novel land applications using multi-channel SAR systems. He leads the SARlab and collaborates with institutions like IEEE. Rabus earned his Ph.D. in Geophysics from the University of Alaska Fairbanks and an M.Sc. from the Technical University of Munich. His research integrates advanced interferometric and polarimetric techniques to study glaciers, landslides, and environmental dynamics. Recent projects include landslide deformation analysis, glacier motion tracking, and SAR-based wildlife monitoring. Rabus teaches graduate courses like ENSC895/EASC609 and advises students on SAR applications. His work is funded through industrial and academic partnerships, addressing challenges in geohazard monitoring and remote sensing innovation. Education: Ph.D., Geophysics, University of Alaska Fairbanks (1997); M.Sc., Technical University of Munich (1992) Affiliations: IEEE, SARlab Director Labs/Teams: SARlab, collaborating with NASA, ESA, and industry partners Research Highlights: Rabus pioneers SAR applications for maritime domain awareness, landslide prediction, and glacier dynamics. His team develops novel algorithms for interferometric analysis and airborne SAR systems. Recent studies include Fels Slide displacement tracking and Arctic ice cap stability assessments. Outcomes contribute to disaster risk reduction, climate science, and environmental policy. Awards: Industrial Research Chair in SAR (SFU), recognized for advancing SAR technology in geoscience and engineering. Grants/Projects: Funded by NSERC, NASA, and industry partnerships for SAR sensor development and environmental monitoring initiatives.

Andreas AustengView profile

Professor

• Medical Ultrasound Imaging
• Beamforming
• Ultrasound Wave Propagation
• +4 more

Andreas Austeng is a Professor of Signal Processing and Acoustic Imaging at the Department of Informatics, University of Oslo, leading the Machine Learning section. He is affiliated with the Digital Signal Processing and Image Analysis (DSB) research group. His research focuses on medical ultrasound imaging, beamforming, sonar systems, and applications of AI/deep learning in acoustics. He holds a PhD and has been actively involved in academic leadership roles. Research interests include medical ultrasound imaging, sonar beamforming, wave propagation, and machine learning integration. He has supervised numerous PhD students, with ongoing and completed projects addressing challenges in adaptive beamforming, synthetic aperture sonar, and medical imaging quality enhancement. His work is funded by initiatives like MEDIMA and CIUS, and he collaborates with institutions such as Kongsberg Maritime and GE Vingmed Ultrasound. Publications span advancements in beamforming algorithms, array design, and acoustic imaging techniques. His contributions emphasize improving diagnostic accuracy and system performance in medical and underwater acoustics. Projects like Brainsight and interferometric sonar applications highlight his interdisciplinary impact.

Fabio CozmanView profile

Professor

• Artificial Intelligence
• Machine Learning
• Probabilistic Reasoning
• +7 more

Fabio Cozman is a Full Professor at the School of Engineering, University of São Paulo (USP), and Director of the Center for Artificial Intelligence at USP. He holds a PhD from Carnegie Mellon University (1996) and completed his engineering degree at Poli-USP. His research spans artificial intelligence, machine learning, and probabilistic reasoning, with significant contributions to knowledge representation under uncertainty, credal networks, and physics-informed AI. Current research focuses on AI interpretability , AI and societal impact , and ocean hazard prediction . Key publications cover probabilistic logic programming , credal networks , and Bayesian network extensions . He is a founding member and former president of the Society for Imprecise Probability Theory and Applications (SIPTA) and has served as Associate Editor for multiple AI journals. His work integrates theoretical advancements in probabilistic modeling with practical applications in robotics, computer vision, and environmental systems, particularly focused on the Brazilian maritime territory through projects like the Blue Amazon Brain (BLAB) architecture.

• Logistics and Supply Chain Management
• Transportation Systems
• Machine Learning Applications
• +5 more

Dr. Bill Du is a Senior Lecturer in Logistics and Supply Chain Management at La Trobe Business School, La Trobe University. He holds a PhD in Control Theory and Control Engineering from Nankai University and has held academic positions at institutions including the National University of Singapore and the University of Tasmania. His research focuses on applying machine learning, simulation, and optimization to transport and logistics systems, with particular emphasis on sustainability (e.g., carbon accounting, decarbonization of transport) and emerging technologies like blockchain and AI. Education: B.E. in Software Engineering (Nankai University, 2004) M.Eng. in System Engineering (Nankai University, 2009) PhD in Control Theory (Nankai University, 2012) Research Interests: AI-driven optimization in logistics Freight transport sustainability Agribusiness value chain risk analysis Blockchain in container shipping Articles Trends: His recent work emphasizes real-time carbon accounting frameworks, blockchain adoption barriers, and stochastic optimization models for maritime operations. He frequently explores interdisciplinary applications of machine learning in transport systems. Awards: Recognized for INFORMS President’s Pick (2015), IBM’s CPLEX industry mention, and a Transportation Research Part E Most Cited Article (2011). Advising & Grants: Total research funding exceeds $1M, with industry collaborators like American President Lines and Kongsberg Digital. Supervised PhD projects on agribusiness logistics and blockchain risks in container transport. Labs/Teams: Active in cross-disciplinary teams addressing UN SDGs (Goals 9,12,13), particularly through projects funded by AgriFutures Australia and Singapore Maritime Institute.