جستجوی استاد راهنمای دانشگاهی

• 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.

Douglas Allaireمشاهده پروفایل

دانشیار

• Multidisciplinary design optimization
• Bayesian optimization
• Multifidelity methods
• +۴ مورد دیگر

Douglas Allaire is an Associate Professor and Sallie and Don Davis '61 Faculty Fellow in the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University, part of the College of Engineering. He leads the Computational Design Laboratory, focusing on computational methods for complex engineered systems. His research spans multidisciplinary design optimization, Bayesian optimization, machine learning, and materials design. Education: Ph.D., Aerospace Engineering, Massachusetts Institute of Technology (2009) M.S., Aerospace Engineering, Massachusetts Institute of Technology (2006) B.S., Aerospace Engineering, Massachusetts Institute of Technology (2004) Research Interests: Bayesian optimization and uncertainty quantification Materials design using machine learning Autonomous experimentation and data fusion Predictive analytics for engineering systems Recent Trends in Publications: His work emphasizes integrating Bayesian methods with materials discovery, autonomous systems, and high-fidelity modeling. Key themes include optimizing multifidelity systems, inverse microstructure design, and real-time decision frameworks. Awards: ASEM Fellow (2024) AIAA Associate Fellow (2023) ASME Young Engineer Award (2018) Advising & Grants: Advised students like Jaylen James (Ph.D. 2022) and Danial Khatamsaz. Active in securing grants for computational design and materials research. Collaborates with institutions like the American Institute of Aeronautics and Astronautics. Labs & Teams: Directs the Computational Design Laboratory, part of the Engineering Systems Design Group. Engages in interdisciplinary projects with Texas A&M’s Multidisciplinary Engineering program.

ADAM YOUNGمشاهده پروفایل

پژوهشگر

• Coastal Geomorphology
• Marine Geology
• Coastal Erosion
• +۶ مورد دیگر

Adam Young is a Researcher at the Scripps Institution of Oceanography, UC San Diego, affiliated with the INTEGR OCEANOGRAPHY DIV. He holds a B.S. from California State Polytechnic University, SLO, and M.S. and Ph.D. degrees from UC San Diego. His work focuses on coastal processes, including cliff retreat mechanisms, natural hazards, and quantitative geomorphology. He employs advanced techniques like LiDAR, satellite imagery, and machine learning to monitor erosion patterns and assess coastal vulnerabilities. Research interests include coastal cliff stability, wave-cliff interactions, and the integration of remote sensing data for environmental monitoring. His projects often involve sensor networks and large-scale datasets to track erosion hotspots and model future scenarios under climate change. Notable studies include Arctic coastal morphology analysis using machine learning and predictive modeling of shoreline changes in California using deep learning. Key contributions include developing automated workflows for cliff change detection and advancing understanding of gravel berm dynamics and subsurface hydrology. His work bridges field observations with computational methods, informing coastal management strategies and disaster preparedness.

• Cybersecurity
• Internet of Things (IoT)
• Artificial Intelligence (AI)
• +۱۲ مورد دیگر

Jawad Ahmad is a Lecturer in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University . His work is closely associated with the Centre for Cybersecurity, IoT and Cyberphysical Systems and the Centre for Distributed Computing, Networking and Security , where he contributes to cutting-edge research in secure and intelligent systems. His research interests are centered on cybersecurity , artificial intelligence , and Internet of Things (IoT) technologies. He focuses on developing advanced intrusion detection systems, privacy-preserving frameworks using federated learning and homomorphic encryption, and secure data transmission mechanisms leveraging chaos-based and quantum-inspired encryption. His interdisciplinary work extends to healthcare, smart agriculture, and environmental monitoring, demonstrating the broad applicability of his research. The analysis of his recent publications reveals a strong trend toward AI-driven security solutions, particularly using deep learning models like transformers and attention mechanisms for network intrusion detection. He also explores the integration of machine learning with blockchain and distributed ledgers for trusted threat intelligence sharing. His work consistently emphasizes real-world deployment, performance optimization, and resilience against cyber threats in industrial and healthcare settings. Funded Research Projects: Data Sharing in Highly Secure Environments (Innovate UK, £273,181) PhD Studentship on Homomorphic Encryption (6G Health Institute GmbH, £35,082) TrustShare: Privacy-Preserving Threat Intelligence Sharing (Innovate UK, £31,386) Cyber Hunt: Automated Cyberthreat Hunting (Norway Research Council, £37,500) AI Dashboard for COVID-19 Sentiment Analysis (Chief Scientists Office, £135,104) Dr Ahmad actively supervises postgraduate research, currently serving as Director of Studies for Hisham Ali and as second supervisor for other PhD candidates. He is involved in multiple collaborative research teams focusing on cybersecurity, AI, and IoT, often working with Prof Bill Buchanan and other leading researchers in the field. His research is published in high-impact journals such as IEEE Access , Frontiers in Computational Neuroscience , and Sensors , and presented at international conferences.

• Telecommunications
• Wireless Communication Systems
• Radio Localization
• +۵ مورد دیگر

Henk Wymeersch is a Professor at Chalmers University of Technology's Communication Systems department, part of the School of Electrical Engineering. He leads the Radio Localization and Sensing research area and is affiliated with the FORCE Research Center on optical communication. His work focuses on algorithm design and system analysis for 5G/6G systems, emphasizing integrated communication, localization, and sensing. Notable contributions include RIS-aided positioning, bistatic/multistatic sensing, and joint communication-sensing frameworks. Research Interests: His primary areas include Reconfigurable Intelligent Surfaces (RIS), 6G positioning/sensing, integrated ISAC systems, mmWave/V2X positioning, and distributed radar networks. Recent work explores challenges in near-field localization, OFDM-based ISAC under hardware impairments, and privacy-preserving techniques for localization systems. Publications: Over 485 publications (2025) highlight his expertise in mmWave SLAM, RIS applications, and 6G enablers. Recent trends focus on 6G sustainability, distributed ISAC architectures, and leveraging RIS for robust localization in cluttered environments. Affiliations: Active in the Communication Systems Group and FORCE Research Center. Collaborates internationally on Hexa-X 6G projects and standards development.

• Traffic Systems Engineering
• Transportation Modeling
• Intelligent Transportation Systems
• +۳ مورد دیگر

Dr. V.L. Knoop is a Professor in Traffic Systems Engineering at Delft University of Technology's Civil Engineering & Geosciences school. His research focuses on advanced transportation modeling, autonomous vehicle systems, and data-driven mobility solutions. He has contributed over 250 publications and supervised multiple research projects. Notable awards include the Greenshields Prize (2012, 2015, 2016) and D. Grant Mickle Award (2016). Knoop has led editorial roles for Collective Dynamics and co-edited conference proceedings on Traffic and Granular Flow. His work bridges theoretical models with practical applications, addressing challenges in traffic efficiency, safety, and sustainable infrastructure. Recent media engagements highlight his expertise in traffic management solutions and autonomous vehicle technologies. Education: PhD in Civil Engineering (assumed) Research Interests: Development of macroscopic traffic flow models Integration of autonomous systems into existing transport networks Data analytics for traffic prediction and optimization Key Contributions: Large-scale car-following dataset analysis (Lyft Level-5 collaboration) Ramp metering optimization studies using empirical trajectory data Publications on adaptive cruise control and uncertainty-based decision-making in autonomous vehicles Labs/Teams: Traffic Systems Group at TU Delft Collaborations with Rijkswaterstaat (Dutch Ministry of Infrastructure) and Flitsmeister

• Computer Vision
• Machine Learning
• Video Analysis
• +۵ مورد دیگر

Prof. Laura Leal-Taixé is an Associate Professor at the Technical University of Munich (TUM) leading the Dynamic Vision and Learning group. She holds the Rudolf Mößbauer Tenure Track Chair, promoted from a 2017 Tenure Track Assistant Professorship. Her work focuses on advancing computer vision and machine learning, particularly in video analysis, multi-object tracking, and autonomous systems. She received a Sofja Kovalevskaja Award (2017) for her project socialMaps, which integrates dynamic social data into traffic modeling. Education: B.Sc./M.Sc. in Telecommunications Engineering, Technical University of Catalonia (UPC), Barcelona Ph.D. in Information Processing, Leibniz University Hannover (2014) Postdoc at ETH Zurich (2014–2016), and Senior Researcher at TUM’s Computer Vision Group (2016–2019) Research Interests: Multi-object tracking and segmentation in videos Motion analysis and semantic segmentation for autonomous driving Deep learning for video understanding Social dynamics modeling in urban environments Awards & Grants: €1.65M Sofja Kovalevskaja Award (Humboldt Foundation, 2017) DAAD Australia-German Joint Research Scheme (2017) Multiple travel grants from CVPR and Women in Computer Vision Labs & Collaborations: Dynamic Vision and Learning Group at TUM Collaborations with ETH Zurich, Northeastern University, and NVIDIA

• Biometrics
• Behavioral Biometrics
• Mobile Authentication
• +۱۲ مورد دیگر

Ruben Tolosana is a researcher at the Biometrics and Data Pattern Analytics Lab (BiDA Lab) in the School of Engineering at Universidad Autónoma de Madrid. His work centers on biometrics, with emphasis on behavioral and mobile authentication, face recognition, privacy-enhancing technologies, and deep learning applications in human-computer interaction. He actively contributes to major research initiatives such as the FRCSyn-onGoing challenge and the ChildCI framework. PhD in Computer Science or related field (inferred from publication volume and role) Advanced training in machine learning, computer vision, and biometrics His research interests include behavioral biometrics, mobile device security, synthetic data for AI training, privacy in biometric systems, and the application of Transformer models to user authentication. Tolosana's work often involves the development of novel datasets and benchmarking platforms to advance the field. He has co-authored influential surveys on privacy vulnerabilities in mobile sensors and privacy-preserving techniques in biometric recognition. The most recent articles highlight trends in using synthetic data for face recognition, applying Transformers to behavioral biometrics (keystroke, touchscreen, gait), and developing frameworks for child age detection via interaction patterns. His work consistently addresses real-world challenges such as privacy, bias, and system generalization. Publications in journals like Information Fusion , Pattern Recognition , and ACM Computing Surveys reflect the high impact and interdisciplinary nature of his research. Second FRCSyn-onGoing: Winning solutions and post-challenge analysis to improve face recognition with synthetic data (2025) ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection (2024) FRCSyn-onGoing: Benchmarking and comprehensive evaluation of real and synthetic data to improve face recognition systems (2024) SwipeFormer: Transformers for mobile touchscreen biometrics (2024) An Overview of Privacy-Enhancing Technologies in Biometric Recognition (2024) Ruben Tolosana collaborates extensively with researchers in the BiDA Lab, including Rubén Vera-Rodríguez, Aythami Morales, Julian Fierrez, and others. He has contributed to the development of public databases such as mEBAL and ChildCIdb, supporting open science. His work is supported by ongoing research grants (inferred from project scope and publications), and he plays a key role in organizing workshops such as WAMWB to advance the mobile and wearable biometrics community. He is a core member of the Biometrics and Data Pattern Analytics Lab (BiDA Lab), a leading research group in biometric technologies, where he contributes to multiple projects involving mobile authentication, face recognition, and privacy-preserving AI systems.

Philippe Poignetمشاهده پروفایل

استاد

• Surgical Robotics
• Medical Robotics
• Robotic Systems
• +۷ مورد دیگر

Philippe Poignet is a Professor at the University of Montpellier, affiliated with the Institut Universitaire de Technologie (IUT) and conducting research at the LIRMM (Laboratory of Informatics, Robotics, and Microelectronics of Montpellier). He served as Director of LIRMM from July 2015 to October 2023 and co-heads the IRP with Stanford University since 2025. His work focuses on Surgical Robotics, with a particular emphasis on medical device development, control systems, and biomedical applications. Co-founder of startup ACUSURGICAL (retinal surgery robotics) Scientific collaborator with STERLAB (flexible ureteroscopy robotics) Co-organized Summer School on Surgical Robotics (SSSR) for 20 years His research spans medical robotics , control theory , and biomedical imaging , with applications in needle steering, tissue interaction, and surgical precision. Recent publications highlight advances in soft tensegrity design , model predictive control , and multi-modality imaging registration . Scientific recognition includes: Best Paper Award at ARK’22 Prix de l’Innovation de l’I-Site MUSE (2020) Chevalier des Palmes Académiques (2019) He supervises doctoral students in projects related to flexible robotics , bioimpression , and robotic shoulder surgery , with collaborations across Europe and industry partners like CARANX Medical and CEDRAT Technologies.

Hannah Sirianniمشاهده پروفایل

استادیار

• Geomatics
• Remote Sensing
• Coastal Geography
• +۳ مورد دیگر

Dr. Hannah Sirianni is an Assistant Professor of Geographic Information Science & Technology in the Department of Geography, Planning & Environment at East Carolina University. She leads the Coastal Geography & Terrain Analysis Lab, which specializes in advanced mapping, monitoring, and modeling of coastal environments to support sustainable development and resilience decision-making. Her research employs cutting-edge geospatial technologies including airborne/terrestrial laser scanning, RTK-GNSS, sUAS, and geospatial AI techniques. Education: Ph.D. in Geosciences from Florida Atlantic University M.A. in Geography from University of Hawaiʻi at Mānoa B.A. in Geography (Highest Honors) from University of Hawaiʻi at Mānoa Research Focus: Dr. Sirianni's research integrates geomatics, GeoAI, OBIA, SfM photogrammetry, and Monte Carlo simulation to address coastal challenges. Her work focuses on shoreline dynamics, bluff erosion, living shoreline effectiveness, and coastal carbon capture monitoring. Current projects include the Sugarloaf Island Restoration and monitoring olivine sand placement for climate mitigation. Publication Trends: Her recent publications demonstrate strong focus on coastal vulnerability assessment, LiDAR/UAS applications, shoreline classification, storm impact quantification, and machine learning applications in geospatial analysis. Research consistently addresses practical coastal management solutions. Grants & Projects: Co-PI for NOAA Sea Grant/USCRP project: "Co-developing a community and data-driven framework for coastal protection decision-making" Living shoreline restoration research at NC Aquarium at Pine Knoll Shores Coastal Carbon Capture™ monitoring using UAS technology Student Advising: Dr. Sirianni actively mentors graduate and undergraduate researchers in coastal geospatial applications. Current advisees include 3 MS students and 1 PhD candidate, with 12 former students now working in environmental science and GIS positions. Lab Operations: The Coastal Geography & Terrain Analysis Lab conducts extensive fieldwork including sUAS surveys, RTK-GNSS measurements, and bathymetric mapping, supported by collaborative partnerships with NC Coastal Federation and other institutions.

• Prosthetics
• Rehabilitation Robotics
• Biomechanics
• +۳ مورد دیگر

Louis Flynn is a Research Fellow at the Department of Applied Mechanics within the Faculty of Engineering at Vrije Universiteit Brussel (VUB), specializing in rehabilitation robotics and active prosthetic systems. His work bridges mechanical engineering with clinical rehabilitation through the Federated Labs AI and Robotics group, with current leadership roles in the BRGEOZ458 STEM Project and BRGEOZ461 Human-Centered Robotics initiative. His research focuses on prosthetics and biomechanical robotics , with pioneering contributions in knee prosthesis design , energy transfer optimization , and torque control systems . Key areas include stiffness modeling in lower limb interfaces, population-specific assistance algorithms, and the development of adaptive exoskeletons for transfemoral amputees. His fingerprint analysis reveals dominant expertise in Prostheses and Implants (100%), Prosthetics (68%), and Knee Prostheses (59%). Recent publications demonstrate a clear trajectory toward AI-integrated control systems and multi-modal physiological sensing , with emphasis on real-world clinical validation. The 2024-2025 output shows concentrated efforts in muscle oximetry interfaces, Cybathlon-ready active prostheses (notably the X-Leg system), and longitudinal studies of user adaptation to microprocessor-controlled joints. Research funding includes: BRGEOZ458 : STEM Project - Cybathlon & ExoGames (2024), developing educational frameworks through competitive robotics events BRGEOZ461 : Human-Centered Robotics for the Future (2025), advancing personalized assistive technologies for daily mobility As a core contributor to the VUB Cyberlegs consortium, Flynn actively develops the X-Leg active transfemoral prosthesis system and presents findings at premier venues like the International Conference on Rehabilitation Robotics. His work directly impacts both competitive athletic prosthetics and clinical rehabilitation protocols through close collaboration with clinicians and engineers.

Zahabul Islamمشاهده پروفایل

استادیار

• Additive Manufacturing
• Material Characterization
• Advanced Manufacturing Techniques
• +۷ مورد دیگر

Zahabul Islam is an Assistant Professor and Program Coordinator in Mechanical and Manufacturing Engineering at Bowling Green State University, School of Engineering. His research focuses on additive manufacturing (3D printing) and material characterization, particularly for energy and biomedical applications. Ph.D., M.S., and B.S. in Mechanical Engineering from Penn State University His expertise spans Laser Powder Bed Fusion (LPBF), Selective Laser Melting (SLM), Direct Energy Deposition (DED), and Stereolithography. Current research includes process map optimization for polymer/metal additive manufacturing, radiation damage studies, and multiscale modeling of fused filament fabricated composites. Recent publications highlight work on tungsten lattice structures, MoSiB alloys, and Haynes 282 superalloys. He actively collaborates on projects involving supercritical CO2 heat-to-power systems and ultrahigh-temperature refractory metal alloys for aerospace applications.

• Logistics Operations
• Smart Manufacturing
• Industrial Engineering
• +۶ مورد دیگر

Maharshi Dhada is a Research Fellow at Darwin College, University of Cambridge, focusing on logistics operations and smart manufacturing. His work bridges industrial engineering with advanced statistical modeling. University: University of Cambridge College: Darwin College Rank: Research Fellow His research integrates hierarchical statistical models and machine learning for predictive maintenance in engineering fleets, smart logistics , and public health applications like SARS-CoV-2 policy analysis. Recent publications highlight collaborations in radio access networks , road condition prediction , and low-cost monitoring solutions . Key article trends show a focus on Weibull models , multi-agent systems , and federated learning for cross-system knowledge transfer. His work spans applications from truck fleet survival analysis to genomic epidemiology .

• Road Traffic Control
• Traffic Automation
• Transportation Systems
• +۲ مورد دیگر

Dr. Varga István is a Full Professor at the Budapest University of Technology and Economics (BME) in the Faculty of Transportation Engineering and Vehicle Engineering, and a Scientific Advisor at the HUN-REN Institute for Computer Science and Control. He holds a D.Sc. from the Hungarian Academy of Sciences (2020), a Ph.D. (2007), and an M.Sc. in Transportation Engineering (1998). His primary research focuses on road traffic control and traffic automation systems , with expertise in intelligent transportation solutions and vehicle mechatronics. His research integrates control theory with practical applications in urban mobility, including dynamic traffic light systems, autonomous vehicle impacts, and emission modeling. Recent work explores V2X communication, platooning technologies, and microscopic traffic simulation for urban optimization. He has led major projects such as the national innovation project 'Dynamic, adaptive traffic control services based on digital data sources' (2020-2024) and industrial collaborations with Knorr-Bremse, Siemens, and nuclear energy sectors. Awards include the Hungarian Academy of Sciences Young Prize (2007) and multiple recognitions for technological innovation. Educational activities include courses on Road Traffic Control, Mathematical Methods, and Vehicle System Modeling. Laboratory leadership includes the Road Traffic Control Lab with industry partnerships like Bosch and SWARCO.

• Atmospheric Science
• Meteorology
• Remote Sensing
• +۴ مورد دیگر

Jan Cermak is Professor and acting Director of the Institute of Meteorology and Climate Research - Atmospheric Trace Gases and Remote Sensing (IMK-ASF) at Karlsruhe Institute of Technology (KIT). His research focuses on atmospheric science with specialization in fog dynamics, aerosol-cloud interactions, and satellite remote sensing applications. His primary research interests include Atmospheric Science, Meteorology, Remote Sensing, Aerosol-Cloud Interactions, Fog and Low Stratus Dynamics, Satellite Meteorology, and Machine Learning Applications. He employs geostationary satellite data and explainable machine learning to investigate fog life cycles, particularly in the Namib Desert and Po Valley, examining how aerosols influence cloud formation and dissipation processes. His work bridges observational meteorology with computational techniques for environmental monitoring. Recent publications (2023-2025) reveal a concentrated research trajectory on fog life cycle analysis using multi-sensor approaches, with significant emphasis on aerosol impacts in polluted regions and arid environments. Key methodological trends include explainable AI for cloud fraction adjustment analysis and high-resolution satellite-based air quality estimation, demonstrating strong interdisciplinary integration of atmospheric physics and data science. Scientific Awards: No awards were documented in the provided source material. Advising and Grants: Source documentation contains no information regarding student supervision, research grants, or funding sources. His leadership role as acting director of IMK-ASF suggests administrative responsibilities within the institute's research framework. Labs and Teams: Cermak leads the Atmospheric Trace Gases and Remote Sensing (IMK-ASF) group at KIT, conducting field campaigns including NaFoLiCA (Namib Fog Life Cycle Analysis) and FAIRARI (Fog and Aerosol Interaction Research Italy). The team specializes in satellite data analysis combined with ground-based observations to study fog dynamics in extreme environments.