جست‌وجوی استاد و پژوهشگر

Ketil Maldeمشاهده پروفایل

دانشیار

• Bioinformatics
• Marine Genomics
• Machine Learning
• +۵ مورد دیگر

Ketil Malde is an Associate Professor at the Department of Informatics, University of Bergen. He is affiliated with the Norwegian Marine Data Center and the Institute of Marine Research. His research focuses on applying machine learning and bioinformatics to marine science challenges, including genome sequencing, acoustic data analysis, and fisheries management. Education: PhD in Algorithms for the Analysis of Expressed Sequence Tags (2005, University of Bergen). Research Interests: Bioinformatics, marine genomics, deep learning applications in fisheries science, acoustic signal processing, and automated data analysis for marine ecosystems. Scientific Contributions: Developed tools like DeepOtolith for fish age estimation, contributed to the salmon louse genome project, and pioneered methods for acoustic target classification using deep learning. His work bridges computational methods with ecological and fisheries management needs. Projects: CRIMAC (Center for Research-based Innovation in marine acoustic abundance estimation), COGMAR, and collaborations with Scantrol Deep Vision for eco-friendly fish sampling. Supervised students include Peter Løkhammer Liessem (object tracking for catch estimation) and Knut T. A. Holager (acoustic frequency subset selection). Active in organizing workshops like the Norway-U.S. Machine Learning in Marine Science collaboration.

• Radiation Hardening
• Fault-Tolerant Systems
• Microelectronics
• +۵ مورد دیگر

Mario Garcia Valderas is an Associate Professor at the Department of Electronic Technology, Universidad Carlos III de Madrid. He holds roles as Coordinator of the Electronic Technology program and Deputy Director of Infrastructure and Laboratories. His research focuses on radiation-hardened systems, fault-tolerant architectures, and embedded systems for aerospace and space applications. His work emphasizes reliability in microelectronics and FPGA-based solutions, addressing challenges like single-event effects in space and high-reliability computing. Key areas include RISC-V processors, heterogeneous computing, and hardware-software co-design for planetary exploration instruments. Publications highlight advancements in radiation-hardening techniques, error detection/recovery architectures, and fault-injection methodologies. Over 100 peer-reviewed articles and book chapters evidence his contributions to microelectronics and embedded systems reliability. He leads the Microelectronic Design and Applications (DMA) research group and collaborates with institutions like CNA for combined irradiation testing. His research spans from theoretical design hardening to practical implementations in aerospace-grade electronics.

Stuart Sandinمشاهده پروفایل

استاد

• Coral Reef Ecology
• Fish Ecology
• Conservation Biology
• +۷ مورد دیگر

Stuart Sandin is a Professor in Marine Biology at Scripps Institution of Oceanography, University of California, San Diego. His research focuses on the structure and functioning of marine communities, particularly coral reef ecosystems across the Pacific Ocean. He leads the Sandin Lab, which employs innovative large-area imaging techniques to study reef ecology and collaborates extensively with conservation organizations globally. Education: B.S. from University of California, San Diego Ph.D. from Princeton University Professor Sandin's research spans multiple interconnected domains including coral reef ecology, fish ecology, conservation biology, and mathematical ecology. His work examines fundamental questions about marine community organization, with particular emphasis on how human activities and biophysical forces shape reef ecosystems. The Sandin Lab has made significant contributions to understanding coral demography, spatial ecology, fish assemblage dynamics, and the application of large-area imaging technologies for ecological monitoring. A notable aspect of his research investigates how coral reefs respond to environmental disturbances, including thermal stress events, while exploring mechanisms of resilience and recovery. Analysis of Professor Sandin's recent publications reveals a strong focus on integrating technological innovation with ecological research. His work increasingly combines large-area imaging techniques with traditional ecological methods to address conservation challenges. Key trends include the development of standardized protocols for reef monitoring, exploration of island-ocean connectivity for holistic conservation, and detailed demographic studies of both coral and fish populations. His research bridges fundamental ecological questions with practical applications for marine spatial planning and community-based conservation efforts across the Pacific region. Collaborations and Field Work: Longstanding partnership with Waitt Institute and Blue Prosperity Coalition Collaboration with OneReef for community-driven coral reef management Island-Ocean Connection Challenge with Island Conservation and re:Wild Field research across multiple Pacific nations including Tonga, Maldives, Samoa, Fiji, and Vanuatu Professor Sandin's laboratory actively engages in capacity building through hands-on workshops that train local stakeholders in standardized data collection methods. His team develops data collection plans, establishes protocols, processes data, conducts analyses, and visualizes findings to support conservation efforts. The Sandin Lab has established field sites at Palmyra Atoll and other remote Pacific locations, creating long-term ecological datasets that track reef community changes over time.

Tanya Vladimirovaمشاهده پروفایل

استاد

• Embedded Systems
• Artificial Intelligence
• Space Systems Engineering
• +۵ مورد دیگر

Professor Tanya Vladimirova is a Professor of Electronic and Computer Systems Engineering at the University of Leicester, affiliated with the School of Engineering's Mathematical Sciences department. Her research focuses on custom computing for edge intelligence, embedded systems design, and space-based applications. She pioneered innovations in satellite computing systems, including reconfigurable on-board computers, fault-tolerant designs, and FPGA-accelerated image processing. Her work integrates AI, digital signal processing, and hardware acceleration for applications in autonomous vehicles, spacecraft, and IoT. Key achievements include the first FPGA-based on-board hyperspectral image compression systems, fault-tolerant distributed computing frameworks for satellites, and self-healing distributed intra-satellite systems. Current projects explore machine learning for satellite reliability and autonomous vehicle vision systems. Prior to Leicester, she led a globally recognized group at the Surrey Space Centre, collaborating with Surrey Satellite Technology Limited (SSTL). Her research spans satellite miniaturization, wireless sensor networks for planetary exploration, and radiation-hardened computing. Her publications address challenges in satellite data processing, fault tolerance, and embedded AI. Notable contributions include novel algorithms for landmine detection, radiation mitigation strategies for FPGAs, and adaptive middleware for distributed space systems. Her work bridges theoretical computing with practical aerospace engineering, emphasizing resilience and efficiency in hostile environments.

• Structural Engineering
• Seismic Performance of Concrete Structures
• Anti-Terrorist Design
• +۳ مورد دیگر

Assoc Prof Li Bing is an Associate Professor at the School of Civil and Environmental Engineering, Nanyang Technological University (NTU). He specializes in structural engineering, with research focused on seismic performance of reinforced concrete structures, anti-terrorist design for infrastructure, and blast testing for explosive effects on concrete buildings. Dr. Li holds a B.Eng. in Structural Engineering from Tong Ji University and a Ph.D. from the University of Canterbury, New Zealand. He teaches courses on structural design and assessment, emphasizing reinforced concrete applications. His recent work explores innovative materials and methodologies for enhancing building safety and resilience against extreme events. His research interests span advanced materials characterization, failure mechanisms under dynamic loads, and sustainable construction practices. Notably, he has contributed to studies on glass-ceramic composites, MXene-based materials, and energy-efficient structural solutions. His articles reflect interdisciplinary approaches, combining material science, computational modeling, and engineering applications. Dr. Li’s academic contributions include advancements in electromagnetic wave absorption materials, transparent ceramics for laser applications, and neuromorphic device fabrication. His work bridges fundamental research with practical engineering solutions, addressing contemporary challenges in civil infrastructure resilience and safety.

• Intelligent Sensor Systems
• Autonomous Systems
• Cyber-Physical Systems
• +۱۹ مورد دیگر

Niki Trigoni is a Professor of Computing Science at the University of Oxford, Department of Computer Science, and a Governing Body Fellow at Kellogg College. She leads the Cyber Physical Systems Group and is Director of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (AIMS), a major interdisciplinary program combining robotics, machine learning, sensor systems, and verification/control. Her research focuses on intelligent and autonomous sensor systems, with applications in indoor positioning, healthcare monitoring, environmental sensing, and smart cities. Key interests include data fusion, inference and learning from sensor data, human-robot interaction, communication protocols for sensor networks, and innovative mobile sensing architectures such as participatory and social sensing. Her recent publications (2020–2023) highlight a strong trend in deep learning-based sensor fusion, particularly using mmWave radar, LiDAR, inertial, and visual data. Work spans human sensing (e.g., mmPoint), localization (e.g., PointLoc, RadarLoc), SLAM (e.g., iMag+), and domain adaptation (e.g., illumination-aware thermal detection). The research demonstrates a consistent focus on robustness in GPS-denied environments and real-world deployment. She has secured external funding, including a 3-year NIST grant for indoor positioning systems for emergency responders. She actively supervises a large cohort of PhD students and research associates, many of whom have gone on to notable careers. Her leadership roles in major conferences such as IPSN and Sensys further underscore her impact in the field. Labs and Teams: Cyber Physical Systems Group EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (AIMS)

Cem Direkoğluمشاهده پروفایل

استادیار

• Computer Vision
• Pattern Recognition
• Image and Video Analysis
• +۷ مورد دیگر

Cem Direkoğlu is a faculty member in the Department of Electrical and Electronics Engineering at Middle East Technical University - Northern Cyprus Campus (METU NCC), within the College of Engineering. His research is centered on computer vision and image analysis, with a strong emphasis on feature extraction, human behavior modeling, and video understanding. Research Interests: His primary research areas include computer vision, pattern recognition, image and video analysis, and signal processing. He focuses on human (individual and group) behavior analysis in sports and surveillance contexts, video event detection, object detection and localization, motion analysis and tracking, and feature/shape/skeleton extraction and segmentation. His ongoing projects involve crowd behavior analysis in surveillance videos, team behavior analysis in sports, and player detection and classification. Publication Trends: His recent work (2004–2014) shows a consistent focus on applying physical analogies (e.g., heat flow) and mathematical models to shape and feature extraction. Later publications shift toward higher-level video understanding, particularly in sports and surveillance, using motion trajectories, team activity modeling, and information retrieval methods for event detection. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: There is no information available regarding students supervised or research grants received. However, his involvement in projects like SAVASA (TRECVid) suggests participation in collaborative research initiatives. Labs and Research Teams: While no specific lab is named, his work appears to be conducted within the research ecosystem of the Electrical and Electronics Engineering department at METU NCC, likely involving collaboration with researchers in multimedia and computer vision, as evidenced by co-authorship with researchers from institutions like Dublin City University.

Anders Blomdellمشاهده پروفایل

استاد

• Control Systems
• Real-Time Systems
• Embedded Systems
• +۷ مورد دیگر

Anders Blomdell is a Professor in the Department of Control Engineering at the Faculty of Engineering, Lund University. His work bridges theoretical control systems with practical applications in real-time, embedded, and cloud-based environments. He is actively involved in research projects focusing on autonomous systems, industrial automation, and networked control. His research interests include Control Systems , Real-Time and Embedded Systems , Networked Control , Industrial Automation , Robotics , and Cloud-Controlled Systems . These areas reflect his focus on scalable, adaptive, and secure control solutions for complex, interconnected systems. The recent publications highlight a strong trend toward event-based control , large-scale optimization , autonomous adaptation , and secure cloud integration . His work often combines control theory with computer science, particularly in distributed and real-time settings, showing a consistent effort to address challenges in latency, scalability, and robustness. Scientific Awards: Advising and Grants: While specific students are not listed, Anders Blomdell leads and participates in major research initiatives such as WASP, ELLIIT, and the Nordic University Hub on Industrial Internet of Things (HI2OT). These projects involve significant funding and collaboration with industry and academia, indicating active mentorship and leadership in training next-generation researchers. Labs and Teams: He is associated with RobotLab LTH and contributes to the development of tools like TrueTime and LabComm , which are widely used in real-time and networked control research. His work supports both academic and industrial innovation in automation and intelligent systems.

• Urban Intelligence
• Smart Cities
• Climate Mitigation
• +۷ مورد دیگر

Dirk Ahlers is a Senior Researcher and Research Manager at the Department of Architecture and Planning, Norwegian University of Science and Technology (NTNU), within the Faculty of Architecture and Design. He leads projects such as ClimaGen, +CityxChange, NEB-STAR, and Re-Value, focusing on urban regeneration, climate action, and smart city initiatives. His work bridges disciplines like computer science, geospatial analysis, and urban planning to address climate challenges. He coordinates EU-funded projects and contributes to frameworks like the New European Bauhaus and the EU Cities Mission. Education: PhD in computer science and geospatial analysis. Background includes postdoctoral research at the Data and Information Management group and roles in the Department of Computer Science, focusing on Urban Intelligence, mobility, and emission monitoring. Research Interests: Urban Intelligence, Smart Cities, Climate Mitigation, Sustainability, Geospatial Analysis, and Information Retrieval. Projects emphasize data-driven approaches for urban transitions, carbon neutrality, and stakeholder engagement. Grants & Projects: Key roles in ClimaGen, +CityxChange (completed), NEB-STAR, Re-Value, CrAFt, and others. Contributions to EU Smart City Marketplace and SCC1 Lighthouse Group strategies. Labs & Teams: Involved with NTNU Smart Sustainable Cities group and initiatives like UBIMOB (data-driven mobility), SCIL (Smart City Infrastructure Lab), and FME-ZEN (Zero Emission Neighborhoods).

• Neuromorphic Computing
• Spiking Neural Networks
• Cognitive Robotics
• +۷ مورد دیگر

Sergio Davies is a researcher at Sheffield Hallam University, actively contributing to the fields of neuromorphic computing, spiking neural networks (SNNs), and cognitive robotics. His work focuses on the development and application of biologically inspired neural systems, particularly using the SpiNNaker neuromimetic platform, for real-time learning, robotic guidance, and human-robot interaction. His research interests include neuromorphic computing, spiking neural networks, cognitive and developmental robotics, event-based vision, neural engineering, and real-time learning systems. These areas are consistently reflected in his publications, which explore both theoretical and applied aspects of brain-inspired computation. The recent articles highlight a trend toward real-time, adaptive robotic systems using event-driven sensors and neuromorphic hardware. Key themes include gesture recognition with event cameras, dynamic attention mechanisms for object tracking, supervised learning in SNNs using STDP and homeostasis, and the development of communication protocols for neural hardware. His work bridges the gap between neural modeling and practical robotic applications, emphasizing efficiency, real-time performance, and biological plausibility. Sergio Davies has collaborated extensively with researchers such as Alessandro Di Nuovo, Steve Furber, and Alexander Rast, indicating strong integration within the international neuromorphic and cognitive robotics communities. He is actively publishing, with works in 2025, and maintains a consistent institutional email, confirming his current affiliation. No formal awards or grants are listed in the provided texts. Sergio Davies has contributed to projects involving the iCub humanoid robot and the SpiNNaker platform, working within interdisciplinary teams focused on cognitive neuromorphic systems. His work on data specification protocols and model translation systems suggests involvement in core software and infrastructure development for neuromorphic hardware.

• Aerospace Engineering
• Operations Research
• Aircraft Maintenance
• +۳ مورد دیگر

B.F. Santos is an Assistant Professor of Airline Operations at Delft University of Technology (TU Delft), specializing in aerospace engineering and operations research. His research focuses on strategic airline planning, aircraft maintenance optimization, and the integration of artificial intelligence in aviation systems. He serves as the project leader for the ReMAP initiative, which explores real-time condition-based maintenance for aircraft. Santos has been recognized with numerous awards, including the TRA VISIONS 2022 Senior Researcher Award Airborne and multiple AIAA best paper awards. Expertise: Aircraft Maintenance, Airline Network Optimization, Prognostics Key Projects: ReMAP (€6.8M EU-funded project) Media Engagement: Extensive coverage in Dutch tech and aviation media His work bridges operational efficiency and sustainability, with contributions to predictive maintenance models and reinforcement learning applications in airport operations. Over 60 peer-reviewed publications and 6 datasets highlight his impact in aviation systems.

• Energy-Efficient Computing
• High-Performance Computing
• Compiler Techniques
• +۴ مورد دیگر

Kanishkan Vadivel is a Researcher in the Electronic Systems group at Eindhoven University of Technology (TU/e), specializing in energy-efficient hardware architectures and compiler-based code-generation techniques. He holds a Master’s degree in Embedded Systems from TU/e (2017) and a Bachelor’s from Coimbatore Institute of Technology (India). Prior to academia, he worked in embedded systems at Tata Engineering and Arm Ltd. Research Interests : His work focuses on computation-in-memory architectures using resistive devices, optimal code generation for CGRA (Coarse-Grained Reconfigurable Architecture), and high-performance computing. Key projects include the MNEMOSENE initiative and development of the CIM-SIM simulator for computation-in-memory systems. Awards : HiPEAC collaboration grant (2019) Advising & Grants : His research is supported by grants focused on neuromorphic processors and edge-AI hardware. He collaborates on projects like NEUROKIT2E for embedded deep learning systems. Labs/Teams : Active member of TU/e’s Electronic Systems Center and Efficient Stream Processing Lab, contributing to neuromorphic and energy-efficient computing initiatives.

Hui Wangمشاهده پروفایل

دانشیار

• Stochastic Optimization
• Mathematical Finance
• Game-Theoretic Importance Sampling
• +۴ مورد دیگر

Hui Wang is an Associate Professor of Applied Mathematics at Brown University, specializing in stochastic optimization, mathematical finance, and game-theoretic importance sampling. He holds a PhD from Columbia University (2000) and an MS from Tsinghua University (1996). His research focuses on variance reduction techniques in Monte Carlo simulations, particularly through a game-theoretic lens developed with Paul Dupuis. He has received the Manning Assistant Professorship (2004) and held grants from NSF and DOE. Teaching interests include probability theory, stochastic processes, and financial mathematics courses such as APMA 1720 and APMA 1655. His work intersects with queuing networks, simulation methodologies, and stochastic games. Recent efforts explore robust control in high-dimensional systems and extensions of importance sampling to complex network models. He actively referees for top journals like Annals of Applied Probability and SIAM Journal on Control and Optimization. Key contributions include explicit solutions for path-dependent options and convex duality methods in incomplete markets. Current research priorities involve advancing differential game frameworks for adaptive sampling algorithms and addressing scalability challenges in stochastic network optimization.

Erich Schikutaمشاهده پروفایل

دانشیار

• Cloud Computing
• Information and Database Systems
• Parallel and Distributed Computing
• +۳ مورد دیگر

Erich Schikuta is an associate professor at the University of Vienna's Faculty of Computer Science and heads the Research Group Workflow Systems and Technology. He has held multiple administrative roles, including Vice Dean and Curricular Commission Head. His research focuses on Cloud Computing, Parallel/Distributed Systems, Neural Networks, and Database Systems, with over 200 peer-reviewed publications. Education: Studied Computer Science, Business Informatics, and Mathematics at the University of Technology Vienna and University of Vienna. Holds titles including Dipl.-Ing., Dr., and Berufstitel Universitätsprofessor (2009). Research interests emphasize Utility Computing, Cloud Resource Optimization, and Neural Network Simulation. Notable contributions include ranking 25th globally in Cloud Computing productivity and developing frameworks like N2Sky for neural network-as-a-service. Key awards include the 2011 Best Paper Award and 2010 Best Teacher Award. Active in international collaborations, he serves as a European Commission evaluator (FP5-FP7/H2020) and chairs program committees. Labs/Teams: Leads the Research Group Workflow Systems and Technology. Involved in projects like BIG-Business (Grid Infrastructure) and 'Änderung in kollab.Prozessen' (2011-2016).

Nakul Gargمشاهده پروفایل

استادیار

• Ambient Intelligence
• Wireless Sensing
• Healthcare
• +۴ مورد دیگر

Nakul Garg is an Assistant Professor in the Department of Electrical & Computer Engineering at Rice University. He leads research in ambient intelligence, wireless sensing, and embedded AI, focusing on energy-efficient and scalable solutions for IoT systems, robotics, and healthcare. His work bridges the gap between sensing, computing, and communication in everyday environments. Education includes a PhD in Computer Science from the University of Maryland, College Park, and a B.Tech in Electronics & Communication Engineering from Indraprastha University, Delhi. His research has been recognized with awards such as the Marconi Society Young Scholar Award (2024) and the Best Paper Award at MobiSys 2022. Research interests span spatial sensing, low-power IoT localization, and integrating AI into wearable devices. Key projects include LiTEfoot (cellular-based asset tracking), FreshSense (food quality monitoring), and SPiDR (acoustic navigation for micro-robots). He actively collaborates with industry (e.g., Microsoft Research, NEC) and has advised multiple students in developing innovative systems. Awards and recognitions include the Cyber-Physical Systems Rising Star (2024), NSF I-Corps support, and multiple best paper/demo awards at top conferences. His work has been featured in ACM GetMobile and highlighted by the ACM SIGMOBILE community.