Find Academic Supervisors

• Slavic Linguistics
• Russian Language and Culture
• Argumentation Theory
• +7 more

Holger Kuße is a Professor of Slavistics at the Faculty of Languages, Literature and Cultural Studies at Technische Universität Dresden. He has established himself as a prominent scholar in Slavic linguistics, cultural linguistics, and Russian studies with an extensive publication record spanning several decades. Kuße has served as co-editor of multiple academic series including Specimina philologiae Slavicae since 1997, sub-series Slavische Sprachwissenschaft und Interdisziplinarität (1995-2000), Zeitschrift für Slawistik since 2009, and the book series Kulturen der Gerechtigkeit since 2013. Professor Kuße's research interests span Slavic linguistics, Russian language and culture, argumentation theory, cultural linguistics, semantics, philosophy of language, and interdisciplinary Slavic studies. His work demonstrates a particular focus on discourse analysis, religious discourse, and surprisingly, Karl May studies. His research often explores the intersection of language, culture, and philosophy, with significant contributions to understanding argumentative structures in Russian political and religious discourse. Kuße has organized numerous academic conferences including the Bohemicum Dresdense series, focusing on Czech language, culture, and history. Analysis of Kuße's recent publications reveals a consistent focus on linguistic argumentation, cultural linguistics, and Russian studies. His work demonstrates evolution from early studies on conjunctions and coordination in sermons and political speeches toward broader investigations of cultural linguistics, argumentation theory, and axiological approaches to language. Recent publications show increasing interest in contemporary issues including protest communication, language in conflict situations (particularly regarding Ukraine), and the application of linguistic theories to current geopolitical contexts. Professor Kuße has been actively involved in academic leadership through organizing conferences, editing major publications, and co-editing influential academic series. His work has established important connections between Slavic studies, cultural linguistics, and philosophical approaches to language. He has contributed significantly to the academic community through the Bohemicum Dresdense conference series, which has become an important platform for Czech-German academic exchange. While specific laboratory or research team information isn't explicitly detailed in the available materials, Kuße has consistently collaborated with scholars across disciplines and national boundaries. His work with the 'Kulturen der Gerechtigkeit' project (2009-2012) and numerous international collaborations indicate his role in fostering interdisciplinary and international research networks focused on Slavic linguistics and cultural studies.

• Geophysics
• Seismology
• Gravitational Wave Detection
• +3 more

Dr. Luigi Ferraioli is a Researcher at ETH Zurich's Institute of Geophysics, under the Professorship for Seismology and Geodynamics. His work focuses on advanced instrumentation for space-based gravitational wave detection, precision measurement systems, and cosmic ray studies. Key contributions include the LISA Pathfinder mission analysis, seismic sensor design, and data-driven approaches to gravitational wave astronomy. Research interests span seismology, geodynamics, and interdisciplinary applications of space technology. He has extensively contributed to LISA Pathfinder mission analysis, exploring noise mitigation, magnetic force characterization, and sensor calibration. His work bridges theoretical astrophysics with practical engineering solutions for space missions. Publications highlight expertise in gravitational wave detection, precision actuator systems, and machine learning applications for astrophysical data analysis. Current projects involve advancing instrumentation for future missions like LISA and asteroid geophysical exploration.

Inkyung SungView profile

Associate Professor

• Artificial Intelligence
• Operations Research
• Optimization Algorithms
• +5 more

Inkyung Sung is an Associate Professor at the Department of Materials and Production, Aalborg University, Denmark. Her research focuses on Artificial Intelligence for Operations Research, particularly in optimization algorithms, UAV operations, and scheduling systems. She leads projects on maritime search and rescue planning, autonomous vehicle path-finding, and cloud computing resource management. Her work integrates AI-driven solutions with real-world applications in emergency services, manufacturing, and logistics. Key research areas include UAV-based service delivery optimization, dynamic environment adaptation for autonomous systems, and scheduling algorithms for robotic and cloud environments. She has collaborated on datasets for generalized assignment problems and developed methodologies for zone partitioning in UAV operations. Sung’s contributions span 33 peer-reviewed publications and three datasets, emphasizing practical applications of operations research in safety-critical and efficiency-driven domains.

Hans HüttelView profile

Associate Professor

• Process Calculi
• Type Systems
• Programming Languages
• +4 more

Hans Hüttel is an Associate Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design. His research focuses on theoretical foundations of computer science with emphasis on programming languages and formal methods. His research interests span process calculi, type systems, concurrency theory, program synthesis, and security protocols. The fingerprint analysis of his work shows strong emphasis on Type Systems (100%), Process Algebra (27%), Cryptographic Protocols (22%), and Branching Time (18%). His recent work demonstrates a growing interest in the intersection of formal methods with emerging technologies like large language models. Hüttel's publication trend shows consistent output with 97 research outputs including 56 articles in proceedings, 17 journal articles, and 9 conference articles in journals. His most recent work (2024-2025) focuses on type systems for programming languages, program synthesis with LLMs, and functional array programming. Scientific Awards: CONCUR Test-of-Time Award (Sept 2020) Hüttel has participated in multiple research projects including TREsPASS (Technology-supported Risk Estimation by Predictive Assessment of Socio-technical Security), BETTY (Behavioural Types for Reliable Large-Scale Software Systems), and educational initiatives like PBL Exchange. He has 35 media appearances where he discusses topics ranging from AI ethics to university education reform. He leads research within the Distributed, Embedded and Intelligent Systems group and has been active in educational development through problem-based learning (PBL) initiatives at Aalborg University.

Daniel Ortiz ArroyoView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +9 more

Daniel Ortiz Arroyo is an Associate Professor at Aalborg University's Faculty of Engineering and Science, affiliated with the Intelligent Energy Systems and Flexible Markets department. His research focuses on AI-driven solutions for energy systems, wastewater treatment optimization, robotics, and deep learning applications in industrial systems. He leads and collaborates on projects such as AITEKS (AI for Tech Support), OPTIMIZE (Deep Reinforcement Learning in Fermentation), and amphibious drone development for infrastructure inspection. Key research areas include reinforcement learning for environmental control systems, synthetic data generation for defect detection, and predictive modeling in wastewater treatment. His work integrates machine learning with physical systems to enhance efficiency and sustainability. Notable contributions include grey-box models for N₂O dynamics and amphibious quad-rotor designs for pipeline inspection. Dr. Arroyo has contributed to over 97 publications, including peer-reviewed journal articles and conference proceedings, focusing on AI applications in energy, environment, and robotics. He actively participates in editorial peer review for journals like Evolutionary Intelligence and CRC Press . His projects involve collaborations with industry partners like Novo Nordisk Foundation and Innovation Fund Denmark, addressing challenges in microbial fermentation, fiber rope inspection, and wind turbine maintenance. He maintains a strong emphasis on data-driven innovation and interdisciplinary research.

Metin SezginView profile

Professor

• Artificial Intelligence
• Computer Vision
• Human-Computer Interaction
• +3 more

Prof. Metin Sezgin is a Professor in the Department of Computer Engineering at Koç University, College of Engineering. He specializes in Artificial Intelligence, Computer Vision, and Human-Computer Interaction, with notable contributions to sketch recognition, multimodal interaction, and educational technologies. His recent work includes advancing AI-driven systems for comic analysis, human-robot engagement, and child-centered machine learning pipelines. Prof. Sezgin has been appointed as Türkiye's representative in the Global Partnership for AI (GPAI), emphasizing his leadership in AI policy and research. He leads projects like the eHRI database for human-robot interaction analysis and develops tools for classroom engagement monitoring. His research integrates computer vision with real-world applications, including tangible programming interfaces for children and affective computing systems. Grants: TÜBİTAK 1001 Grant (2023) Labs: Koç University Parallel and Multicore Computing Lab Key Areas: Sketch Recognition, Multimodal Datasets, Human-Robot Interaction, Educational Technology His publications span domains from AI ethics to technical advancements in vision systems, with a focus on bridging theoretical research and practical societal impact.

Manuel Ocaña MiguelView profile

Professor

• Robotics
• Computer Vision
• Autonomous Systems
• +6 more

Manuel Ocaña Miguel is a Professor at the Department of Electronics, University of Alcalá. He leads the Robesafe research group (Service Robotics and e-Safety) focusing on robotics applications for road safety and autonomous systems. His doctoral thesis addressed WiFi-based localization for semi-autonomous robots, supervised by Dr. Luis Miguel Bergasa Pascual. Key research interests include autonomous driving technologies, computer vision, sensor fusion, and energy-efficient systems. His work spans robotics navigation, traffic management systems, and AI-driven safety solutions. Recent publications emphasize autonomous vehicle decision-making, energy optimization in EV charging, and human-robot interaction in healthcare. Notable contributions include real-time obstacle detection algorithms, gaze-based driver monitoring, and green machine learning implementations on embedded hardware. Prof. Ocaña's research integrates multi-disciplinary approaches: combining vision-based SLAM with GPS data, developing explainable AI for driver attention estimation, and optimizing solar module efficiency through thermal engineering. His projects often bridge theoretical advancements with real-world applications in automotive safety and smart energy systems. Publications highlight trends in fusion of sensor data (LiDAR/camera), transfer learning for autonomous systems, and simulation-based validation (CARLA). While no specific grants or awards are listed, his prolific output reflects sustained innovation in robotics and intelligent systems. The Robesafe lab serves as a hub for collaborative R&D in service robotics and e-safety technologies.

Zhiwei GaoView profile

Associate Professor

• Control Systems
• Renewable Energy
• Industrial Informatics
• +6 more

Dr. Zhiwei Gao is an Associate Professor in the Department of Mathematics, Physics and Electrical Engineering at Northumbria University. He holds prestigious fellowships including IEEE Fellow (2023), Royal Academy of Engineering/Leverhulme Trust Research Fellowship (2024), and Fellowships of AAIA and AIIA. His research focuses on control systems, renewable energy, fault diagnosis, and real-time systems, with applications in wind turbine systems and wave energy conversion. Education: PhD in Engineering (1996). Research Interests: Real-time diagnosis and resilient control for industrial systems Energy management and renewable energy technologies Machine learning applications in anomaly detection and music generation Fault-tolerant control for fuzzy systems and multi-agent coordination Recent articles highlight advancements in distributed observers for LTI systems, deep reinforcement learning for energy management, and hybrid approaches for fault diagnosis. His work contributes to UN Sustainable Development Goals related to sustainable energy and technological innovation. Awards: IEEE Fellow, RAEng/Leverhulme Trust Fellowship, Alexander von Humboldt Awards (2015, 2018, 2022). Editorial Roles: Co-EIC of IEEE Transactions on Industrial Informatics, Senior Editor of IEEE Access, and editorial board member of Renewable Energy (Elsevier). Projects: Leading research on wave energy conversion systems and resilient control strategies. He advises PhD students in health monitoring and resilient control for complex systems, contributing to cutting-edge advancements in industrial informatics.

Eleonora BottaView profile

Assistant Professor

• Space Debris Removal
• Tethered Systems Dynamics
• Spacecraft Dynamics and Control
• +3 more

Eleonora Botta is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University at Buffalo (SUNY), affiliated with the School of Engineering and Applied Sciences. Her research focuses on space debris removal, tethered systems dynamics, spacecraft control, and flexible structure dynamics. She leads the UB Space System Dynamics and Control Lab. Education: PhD in Mechanical Engineering from McGill University (2017), MEng in Space Engineering from Politecnico di Milano (2013), and BEng in Aerospace Engineering from Politecnico di Milano (2010). Research Interests: Dynamics and control of space tethers Active debris removal strategies Collision detection and avoidance systems Spacecraft dynamics and control Publications Trends: Recent work emphasizes robust debris capture methods, tether system optimization, and real-time control algorithms for uncooperative debris. Key themes include inertia estimation, net deployment validation, and solar-electric propulsion trajectory design. Awards: 2024 NFS Young Professional of the Year 2023 SEAS Early Career Teacher of the Year 2015 Amelia Earhart Fellowship Grants & Advising: Active in grant-funded research on space debris mitigation. Supervises graduate students in robotics, control systems, and astrodynamics. Labs/Teams: Directs the UB Space System Dynamics and Control Lab, collaborating with industry and NASA on debris removal technologies.

• Precision Engineering
• Flexure-Based Mechanisms
• Compliant Mechanisms
• +7 more

Dannis M. Brouwer is a Full Professor in Precision Engineering at the University of Twente, Faculty of Engineering Technology. His research is centered on advanced mechanical systems, particularly in robotics and precision mechanisms. Position: Full Professor Institution: University of Twente School: Faculty of Engineering Technology Department: Precision Engineering His research interests span flexure-based mechanisms, compliant robotics, micro robotics, mechanical design optimization, and dynamic balance in precision systems . He actively contributes to the design of high-precision mechanical components with applications in robotics and instrumentation. The recent publications highlight a strong focus on flexure hinges, underactuated grippers, dynamic balancing, and cryogenic actuators , indicating interdisciplinary work bridging mechanical design, materials, and control. The keywords across articles reflect deep engagement in precision engineering and robotics. He has supervised multiple students, as evidenced by co-authored theses and research outputs. Although no formal awards are listed, his h-index of 16 and 1036 citations reflect significant scholarly impact. Supervised students: K. Dwarshuis, J. de Jong, W. E. Kamphof, M. Nijenhuis, P. Piening Brouwer is involved in collaborative research and data sharing, with datasets related to flexure-based linear guides. He participates in technical conferences and tutorials, contributing to the education and dissemination of precision mechanism design principles.

Dianne P. O'LearyView profile

Professor

• Scientific Computing
• Numerical Analysis
• Computational Science
• +6 more

Dianne P. O'Leary is a Professor affiliated with the Department of Computer Science at the University of Maryland. Her work focuses on scientific computing, numerical analysis, and computational science, with a particular emphasis on matrix factorizations, differential equations, and Monte Carlo methods. She authored the textbook *Scientific Computing with Case Studies* (SIAM Press, 2009), which integrates theoretical concepts with practical case studies across physics, engineering, epidemiology, and biology. Her research explores topics such as image deblurring, blind deconvolution, elastoplastic torsion, and iterative methods for solving large linear systems. The book includes nineteen case studies that illustrate algorithm design, mathematical modeling, and software development principles. Notably, the text emphasizes stability, error analysis, and MATLAB implementation grounded in machine arithmetic and memory management. While no explicit scientific awards or student advisees are mentioned in the provided texts, her contributions to computational education and algorithm development are central to her work. Supplementary materials include solution manuals, MATLAB code repositories, and detailed notes on topics like sensitivity analysis, computer memory management, and finite element methods. Her case studies often bridge theory and application, such as modeling epidemics, robot control systems, and structural engineering problems. The book’s structure reflects a commitment to hands-on learning, with units dedicated to dense matrix computations, optimization, Monte Carlo simulations, and sparse matrix techniques for partial differential equations.

Ketao ZhangView profile

Senior Lecturer

• Robotics
• Aerial Robotics
• Soft Robotics
• +11 more

Ketao Zhang is a Senior Lecturer in Robotics at the School of Engineering and Materials Science, Queen Mary University of London, and serves as the Industrial Engagement Lead of the Centre for Intelligent Transport. He is also affiliated with the Centre for Advanced Robotics, where he leads research in aerial robotics, soft robotics, and bio-inspired design. Senior Lecturer in Robotics, Queen Mary University of London Industrial Engagement Lead, Centre for Intelligent Transport Research Affiliation: Centre for Advanced Robotics Research Group: Robotic Systems Dr. Zhang's research focuses on advanced robotic systems, particularly in the domains of aerial robotics, soft robotics, kinematics, and reconfigurable mechanisms. His work integrates origami-inspired design, bio-inspired locomotion, and additive manufacturing to develop innovative robotic solutions. Key interests include screw theory, reconfigurable parallel manipulators, soft actuators and sensors, and morphable soft-bodied robots. His research themes are highly interdisciplinary, bridging mechanical engineering, materials science, and autonomous systems. The recent publications of Dr. Zhang span high-impact journals and conferences, with a clear trend toward aerial additive manufacturing, soft-actuated systems, and reconfigurable UAVs. His work often involves multi-robot coordination, bio-inspired design, and novel actuation mechanisms. Themes such as electroadhesion, variable stiffness, and 3D printing with drones are recurrent, indicating a strong focus on autonomy, adaptability, and real-world deployment. ERC SyG 2023: Multi-sensor Eversion Robot for Intelligent Endoscopic Microsurgery NERC: EMPreSS – Methane Monitoring with UAVs Innovate UK: Human-Augmented Robotics for Precision Viticulture Royal Society: Electroadhesion for Perching UAVs Royal Society: Bio-inspired Quadruped Locomotion EPSRC: Core Equipment for Robotics Research Dr. Zhang has secured substantial research funding from major UK and EU agencies, supporting interdisciplinary projects with applications in healthcare, environmental monitoring, and agriculture. He collaborates extensively with researchers such as Kaspar Althoefer, Lei Su, and Mohamed Thaha. While student advising details are not publicly listed, his active grants and publications suggest mentorship of PhD and postdoctoral researchers. His lab focuses on intelligent transport systems, aerial robotics, and soft robotic platforms, contributing to both fundamental mechanism design and applied autonomous systems.

• Artificial Intelligence
• Software Development
• Large Language Models
• +4 more

Kai-Kristian Kemell is a Research Fellow in the Computing Sciences department, focusing on interdisciplinary research at the intersection of Artificial Intelligence, Software Engineering, and Ethical AI. His work explores practical applications of Large Language Models (LLMs), autonomous agents in software development, and regulatory frameworks like the EU AI Act. Research Interests : His primary areas include AI-driven software development tools, ethical implementation of AI systems, multi-agent systems for code refactoring, and systematic literature reviews on trustworthiness in LLMs. He investigates how LLMs can automate tasks like microservice generation from API definitions and assist early-stage software startups through prompt engineering. Collaborations : Active collaborations include projects with researchers like Prof. Petri Abrahamsson, focusing on topics such as RAG systems, AI ethics governance, and hybrid work practices in software engineering. His work bridges theoretical AI concepts with practical industrial applications. Publications : His 2025 publications emphasize autonomous software development agents, EU AI Act critiques, and ethical alignment strategies for LLM-based systems. Earlier work (2023–2024) addresses AI ethics implementation via user stories, hybrid work impacts, and MLOps challenges. Awards : No specific scientific awards mentioned in the provided texts. Grants & Labs : No explicit details on grants or affiliated labs, but his research frequently involves collaborative projects with industry and academic partners.

Luigi IannelliView profile

Associate Professor

• Control Systems
• Power Electronics
• Smart Grids
• +7 more

Luigi Iannelli is an Associate Professor at the Department of Engineering of the University of Sannio in Benevento, Italy. He leads research activities within GRACE (Group for Research on Automatic Control Engineering) , focusing on control systems, power electronics, and UAV applications in precision agriculture. Research Interests include: Control systems for autonomous vehicles Power converters and complementarity modeling Smart grid optimization Switched and piecewise linear systems Thermal compensation in automotive control Drone-based sensing for precision viticulture Scientific Awards : No specific awards mentioned in the provided data.

Christopher RomanView profile

Professor

• Ocean Engineering
• Oceanography
• Robotics
• +4 more

Christopher Roman is a Professor of Oceanography in the Marine Geology and Geophysics program at the University of Rhode Island's Graduate School of Oceanography (GSO), with a joint appointment in the Department of Ocean Engineering. He has been at URI since 2006, contributing to deep-sea exploration with the Ballard Group and advancing coastal oceanography through autonomous vehicle development. His educational background includes: Ph.D. Ocean Engineering, Massachusetts Institute of Technology / Woods Hole Oceanographic Institution, 2005 M.S. Mechanical Engineering, University of California, San Diego, 1999 B.S. Mechanical Engineering, Virginia Polytechnic Institute and State University, 1997 Roman's research centers on developing sensing systems for acoustic and photographic seafloor mapping, with dual expertise in deep-ocean archaeology and coastal dynamics. His work spans coastal circulation, underwater robotics, and oxygen minimum zone studies, exemplified by innovations like the Wire Flyer profiling vehicle that captures "shower curtain slices" of ocean properties through rapid vertical maneuvers. Recent publications demonstrate a strong trajectory toward autonomous underwater vehicle technology, with emphasis on real-time bathymetric modeling, acoustic-visual sensor fusion, and deep-sea exploration in extreme environments like the Puerto Rico Trench. His research increasingly addresses climate change impacts through high-resolution observations of mesopelagic ecosystems and interocean fluxes. No specific scientific awards are documented, but research is supported by diverse funding sources including the Champlin Foundations, which enabled development of an educational Autonomous Surface Vehicle (ASV) for Narragansett Bay studies. Roman mentors students in engineering-data science integration, assigning projects that link mechanical design challenges to oceanographic questions. His GSO lab assembles custom instrumentation with external machining partners, focusing on deployable systems for field campaigns. Current projects include methane seep investigations in the Gulf of Mexico, Antarctic krill behavior studies, and hadal zone exploration using the Deep Autonomous Profiler, maintaining active fieldwork across global ocean basins.