Find Academic Supervisors

• Renewable Energy Systems
• Electronics Engineering
• Sensor Technology
• +4 more

Francisco Javier Meca Meca is an Associate Professor in the Department of Electronics at the Universidad de Alcalá. He holds a Ph.D. from the same institution (2001), with a thesis titled Medida de temperatura sin contacto con alta velocidad de respuesta supervised by Dr. Manuel Ramón Mazo Quintas and Dr. Francisco Javier Rodríguez Sánchez. His research focuses on electronics engineering applied to renewable energy systems, sensor technology, and control systems, particularly in thermal measurement, infrared systems, and robotics localization. He is a member of the GEISER research group, dedicated to electronic engineering for renewable energy applications. Key research interests include developing sensor systems for industrial monitoring, thermal infrared sensing for aerospace applications (e.g., Mars 2020 mission), and FPGA-based control systems for power electronics. His work integrates signal processing techniques with hardware implementation, emphasizing real-time systems and embedded electronics. Notable contributions span thermal drift compensation in transimpedance amplifiers, phase-based positioning for mobile robots, and optimal anchor placement algorithms for wireless networks. Publications highlight advancements in infrared positioning systems, predictive current control for power converters, and stability analysis of active power filters. His research bridges theoretical modeling with practical applications in renewable energy, industrial automation, and space technology. Ongoing work likely explores sensor fusion, energy-efficient control systems, and smart environmental monitoring.

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.

• Robotics
• Autonomous Systems
• Computer Vision
• +3 more

Pedro Alfonso Revenga de Toro is an Associate Professor at the Department of Electronics of the Universidad de Alcalá. His research focuses on robotics, autonomous systems, computer vision, and real-time embedded systems. He holds a Ph.D. from Universidad de Alcalá with a thesis on real-time image processing architectures (2017), supervised by Dr. José Luis Lázaro Galilea and Dr. Alfredo Gardel Vicente. His work integrates advanced AI techniques like deep learning and reinforcement learning into autonomous vehicle systems, emphasizing safety and efficiency. He leads the Robesafe research group, dedicated to service robotics and road safety technologies. Key research areas include autonomous driving decision-making, 3D object detection in dynamic environments, and energy-efficient embedded systems. His contributions span both theoretical advancements (e.g., GAN-based driver attention models) and practical implementations (e.g., ROS-based autonomous vehicles). He has developed educational robotics workshops (Depecabot) to enhance student engagement in electronics and robotics. His publications address challenges in sensor fusion, path planning, and real-time positioning systems for autonomous applications. No scientific awards or grants are explicitly listed, but his extensive publication record reflects sustained contributions to robotics and transportation engineering since the 1990s. His work bridges academic research and real-world applications, particularly in improving road safety and vehicle automation.

• Robotics
• Renewable Energy Systems
• Microgrids
• +4 more

Enrique Santiso Gómez is a Professor in the Department of Electronics at the University of Alcalá, specializing in electronic engineering applications for intelligent transport and renewable energy systems. His work bridges theoretical control strategies with real-world implementations in robotics and energy infrastructure. He earned his PhD from the University of Alcalá in 2003 with the thesis Absolute positioning of a mobile robot from brand recognition , supervised by Dr. Manuel Ramón Mazo Quintas and Dr. Jesús Ureña Ureña. His educational background established the foundation for his current research trajectory in mobile robotics and sensor systems. His research focuses on event-triggered and aperiodic control systems applied to diverse domains. Key areas include Robotics: Trajectory tracking, indoor positioning, and multi-robot coordination Renewable Energy: Blockchain-based microgrid management and photovoltaic integration Transport Systems: Railway safety with virtual balises and vehicle platooning Sensor Innovation: Laser scanning for state estimation and pressure monitoring in industrial processes Analysis of his 15 most recent publications (2022-2013) reveals a consistent evolution toward resource-efficient control architectures . Early work emphasized robot localization and event-based sensing (2013-2017), transitioning to energy-focused applications (2020-2022) where blockchain strategies now optimize community microgrids. The interdisciplinary nature spans electrical engineering, computer science, and transportation engineering with recurring themes of delay tolerance and measurement error reduction. He actively contributes to two major research groups: GEINTRA : Electronic Engineering Applied to Intelligent Spaces and Transport GEISER : Electronic Engineering Applied to Renewable Energy Systems These groups drive his collaborative projects in smart infrastructure and sustainable energy solutions.

• Cartography
• Surveying Techniques
• Geomatics Engineering
• +5 more

Assoc. Prof. Dr. Serdar Bilgi is an academic at Istanbul Technical University (ITU), affiliated with the Civil Engineering Faculty and the Department of Geomatics Engineering . He holds the rank of Associate Professor and has served in leadership roles such as Head of Department and Vice Dean at ITU. His research focuses on Cartography , Surveying Techniques , and interdisciplinary applications of geomatics, including 3D modeling, deformation monitoring, and geospatial analysis. Education : PhD in Geomatics Engineering, ITU (2003–2012) MSc in Geodesy and Photogrammetry Engineering, ITU (1997–2001) BSc in Geodesy and Photogrammetry Engineering, ITU (1997–2001) Research Interests : Prof. Bilgi’s work spans cultural heritage documentation (using UAVs and 3D modeling), deformation monitoring of dams and fault zones via GPS and geodetic methods, and GIS applications in urban planning and disaster management. He has led projects on topics like laser scanning for endoscopic imaging and integrating historical data into modern systems. Publications : His recent work includes studies on visual localization algorithms, dam deformation analysis, and spatial patterns in Istanbul. These reflect his expertise in computational geomatics, sensor fusion, and geophysical modeling. Awards : BİDEB 2214 International Research Scholarship (TUBITAK, 2010) Grants & Projects : He has executed over 15 research projects, including: Deformation Monitoring of Atatürk Dam (2006–2013) – Geodetic risk assessment Integration of 3D UAV Models into GIS (2019–2024) – Heritage site preservation CBS Sel Heyelan Hasar Tahmini (2009–2017) – Flood risk modeling Labs/Teams : Though not explicitly named, his projects involve collaboration with ITU’s geomatics and engineering teams, focusing on fieldwork and computational modeling.

• Measurement Technique
• GIS and Information Technologies in Planning
• Lidar
• +3 more

Ramazan Alper Kuçak is an Assistant Professor at the Department of Geomatics Engineering, Faculty of Civil Engineering at Istanbul Technical University. He holds a PhD in Geomatics Engineering from the same institution and has extensive experience as a Research Assistant at multiple universities, including Nigde University and Republic University. His research focuses on advanced geospatial technologies, including LiDAR, 3D modeling, and GIS applications in urban planning. Education: PhD in Geomatics Engineering (2016), Istanbul Technical University Master's Degree in Surveying Engineering (2013), Yildiz Technical University Bachelor's Degree in Surveying Engineering (2010), Yildiz Technical University Research Interests: His work emphasizes innovative applications of geomatics technologies, such as terrestrial laser scanning for heritage preservation, mobile mapping systems for smart cities, and comparative analysis of localization algorithms. He also explores low-cost sensor integration and open-source software for geospatial data analysis. Publications Trends: His recent articles highlight advancements in LiDAR sensor performance, 3D point cloud processing, and algorithmic improvements for geospatial data. He frequently publishes in domains like cultural heritage documentation, urban infrastructure analysis, and sensor fusion techniques. Professional Contributions: Dr. Kuçak has no documented scientific awards but has actively contributed to academic research through collaborative projects and teaching. His work experience spans research roles at multiple institutions, demonstrating a strong commitment to advancing geomatics engineering. Future Work: Ongoing research includes optimizing LiDAR integration with consumer electronics and enhancing point cloud registration algorithms for real-world applications.

Visa KoivunenView profile

Professor

• Statistical Signal Processing
• Wireless Communications
• Radar Signal Processing
• +4 more

Visa Koivunen is the Aalto Distinguished Professor at Aalto University, Finland, with a global reputation in statistical signal processing and wireless communications. He has held prestigious positions including Academy Professor (2010-2014) and Principal Investigator for the SMARAD Center of Excellence (2002-2013). Education: D.Sc. (EE) from University of Oulu Current roles: Full Professor at Aalto University Visiting appointments: EPFL (2022-2023), Princeton University (2007, 2010-2013) His research spans statistical signal processing , radar systems , machine learning for radio frequencies , and integrated sensing and communications (ISAC) , with a focus on robust algorithms and practical applications. Recent work explores reinforcement learning for ISAC resource allocation and James-Stein estimator-based change detection. Notable awards include IEEE Fellow , EURASIP Fellow , Mannerheim Research Foundation Award , and Knight of the Order of the White Rose of Finland . Patents: 5 co-invented (US Patent Nos. 7787548, 7929937, 7949357, 20090197550, 20100120467) Publications: 490+ scientific papers, 116 peer-reviewed journal papers, h-index 60 Service: IEEE Fourier Award Committee, SPS Awards Board, NATO Radar panels

Simon CottonView profile

Professor

• Wireless Communication
• Electrical Engineering
• Computer Science
• +3 more

Simon Cotton is a Professor at Queen's University Belfast, affiliated with the School of Electronics, Electrical Engineering and Computer Science and the Wireless Communication Systems Institute. His research focuses on advanced wireless communication systems, including 5G/6G networks, reconfigurable intelligent surfaces (RIS), and millimeter-wave technologies. He has led major projects such as the Future Communications Hub in All-Spectrum Connectivity and contributed to initiatives like the UK Telecoms Innovation Network (UKTIN). His work encompasses channel modeling, antenna design, and machine learning applications in wireless networks. Key awards include the Harold A. Wheeler Prize Paper Award and Philip Leverhulme Prize, reflecting his impactful contributions to the field. He has been actively involved in national committees, such as the Wireless 2030 Report for the UK Government and DCMS 6G Consultation. His research has been widely disseminated through conferences and media, including BBC features on 5G and future wireless technologies. Recent projects span topics like secure wireless systems, energy-efficient MIMO architectures, and AI-driven network optimization. Collaborative work with institutions like the University of Oxford and Strathclyde highlights his role in advancing cross-disciplinary research in next-generation communication networks.

Erik LeitingerView profile

Academic

• Ultrawideband Wireless Communication
• Indoor Positioning
• Estimation/Detection Theory
• +3 more

Erik Leitinger is a Senior Researcher at the Graz University of Technology, Austria. He holds a Dipl.-Ing. (M.Sc.) and Ph.D. in electrical engineering from the same institution, awarded in 2012 and 2016 respectively. His work focuses on ultrawideband (UWB) wireless communication, indoor positioning systems, Bayesian inference, and factor graph-based algorithms. He has contributed to multipath-based simultaneous localization and mapping (SLAM), cooperative localization, and MIMO systems. Leitinger’s research integrates theoretical frameworks like belief propagation and variational inference with practical applications in automotive radar, RFID positioning, and 5G/6G systems. His academic contributions span over 50 peer-reviewed articles, with recent work emphasizing non-ideal reflective surfaces, scalable positioning systems, and neural-enhanced SLAM algorithms. He actively collaborates with institutions like the University of Lund (Sweden) and KTH Royal Institute of Technology, contributing to projects such as the EU-funded IPIN competitions. Leitinger teaches courses on adaptive systems, signal processing, and machine learning. His student projects include topics like neural-enhanced SLAM, acoustic source localization using reflections, and real-time multipath-assisted localization with channel sounders. He is affiliated with TUGRAZonline and ORCID, maintaining an open research profile.

• Activity Recognition
• Sensor Networks
• Machine Learning
• +3 more

Roles and Affiliations: Duc V. Le is an Assistant Professor at the Digital Society Institute and Pervasive Systems department. His work focuses on pervasive computing, sensor networks, and machine learning applications in smart environments. Research Interests: Dr. Le's research spans activity recognition, indoor localization, underground communication, and IoT systems. He explores innovative solutions like inertial navigation using Transformers and anchor-free localization techniques. His work integrates machine learning with sensor data to address challenges in smart infrastructure monitoring and human activity analysis. Awards: Best Paper Nominee (2023) - Pervasive Computing Key Contributions: Notable contributions include patents on fluid parameter detection and publications on subsoil communication, Wi-Fi CSI activity recognition, and self-diagnostic water pipelines. His research bridges theoretical advancements with practical applications in smart cities and environmental monitoring.

Julian HuberView profile

Associate Professor

• Energy Informatics
• Smart Grids
• Data Science
• +3 more

Julian Huber is an Associate Professor at MCI Management Center Innsbruck, where he also served as Senior Lecturer from 2021 to 2024. Previously, he held roles such as Senior Expert in Smart Grids & Energy Markets at FZI Forschungszentrum Informatik and led the Information Management and Analytics department there. He earned a Dr. rer. pol. in Information Systems from Karlsruher Institute für Technologie (KIT) and holds M.Sc. and B.Sc. degrees in Engineering from KIT and TU Berlin. His research focuses on integrating technical and behavioral dimensions of energy systems, including smart charging systems, energy markets, and sustainable technologies. Notable projects include optimizing EV charging for carbon efficiency and improving indoor air quality using IoT sensors. He teaches courses on data science, IoT, and energy systems at MCI and other institutions. Huber’s work spans over 30 peer-reviewed publications, with recent emphasis on environmental data analysis, user-centric systems, and smart grid innovation. He actively contributes to conferences like the DACH+ Conference on Energy Informatics and co-leads research initiatives on energy informatics and sustainability.

Silvia ÖttlView profile

Senior Lecturer

• Smart Building Technologies
• Energy Efficiency in Buildings
• Ventilation Systems Design
• +3 more

Silvia Öttl is a Senior Lecturer at MCI Management Center Innsbruck in the Smart Building Technologies department. Previously, she held a PostDoc position at the University of Innsbruck’s Institute for Construction and Material Science and worked at Bartenbach GmbH in R&D, focusing on energy-efficient building technologies. Her academic career includes a PhD in Astrophysics (2014) and prior roles in astrophysical research at the University of Innsbruck’s Institute for Astro- and Particle Physics. Education: PhD in Astrophysics (University of Innsbruck, 2014), MSc/BSc in Physics (University of Innsbruck, 2011), and Matura from Naturwissenschaftliches Bundesrealgymnasium Wörgl (2001). Research interests span smart building systems, energy-efficient ventilation, fire safety in HVAC systems, and sustainable construction. Her astrophysical work focused on planetary nebulae ionization, gamma-ray sources via H.E.S.S. collaboration, and astrochemistry of interstellar molecules. Publications include peer-reviewed studies in astrophysics and building technology, including contributions to the H.E.S.S. collaboration’s gamma-ray observations and recent work on indoor air quality optimization in educational facilities. She has received the MCI Teaching Award (2022). Teaching roles include courses on energy-efficient lighting, building physics, and astrophysics at the University of Innsbruck. She advises Bachelor’s theses on energy communities, renewable energy integration, and indoor environment monitoring. Professional training includes project management for Horizon 2020, didactic qualifications, and mediation in academic environments.

Olaoluwa PopoolaView profile

Lecturer

• Wireless Communications
• Optical Communications
• Medical Robotics
• +4 more

Olaoluwa Popoola is a Lecturer in the field of Autonomous Systems & Connectivity at the University of Glasgow. He holds a PhD from Glasgow Caledonian University and has over 10 years of experience in higher education across Nigeria, the UK, and China. His research focuses on wireless and optical communications, robotic communications, medical robotics, localization systems, and intelligent vehicles. He has won grants including EPSRC IAA and Glasgow GKEF grants and is a member of professional institutions like IEEE and the Institution of Engineering and Technology. Education: Bachelor's in Electronic and Electrical Engineering (Federal University of Technology, Akure, Nigeria) MEng in Communication Engineering (Distinction) PhD in Communication Engineering (Glasgow Caledonian University) Research Interests: Wireless and Optical Communications Medical Robotics and Robotic Teleoperation Localization Technologies (Indoor/Outdoor) 5G/6G Networks and Intelligent Transportation Systems His work integrates AI, contextual beamforming, and sensor fusion to enhance communication and positioning systems in challenging environments. Recent Trends in Publications: Recent articles emphasize advancements in 5G/6G networks, localization algorithms, teleoperation systems, and autonomous vehicle communication. Key topics include adaptive beamforming, UAV-based edge networks, and resilient teleoperation for extreme environments like nuclear sites. Awards and Recognition: Best Poster Award (SICSA PhD Conference) Nominated for THE Technology Innovation of the Year Award (2018) Chartered Engineer (UK Engineering Council) Grants and Advising: EPSRC IAA grants (e.g., 5G VISTA, Roboguide) Supervision of PhD students in areas like AI-driven localization and teleoperation systems Course coordinator for Dynamics and Control Systems Professional Activities: Secretary, Institution of Engineering and Technology (IET) Scotland Senior Member, IEEE

U-Xuan TANView profile

Professor

• Robotics & Automation
• Mechatronics
• Localization & Mapping
• +5 more

Professor U-Xuan TAN is affiliated with the Sensing, Actuation, and Mechanism (SAM) Design Group within the Engineering Product Development (EPD) school at Singapore University of Technology and Design (SUTD). His research focuses on Robotics & Automation, Mechatronics, Localization & Mapping, and Sensing & Control systems. His work spans applications in medical robotics, 3D food printing, industrial IoT, and human-robot interaction. He leads a dynamic research group, evidenced by frequent group photos (e.g., 2017/2019) and ongoing projects involving multi-robot systems. Notable contributions include advancements in UWB-based localization, neural network-driven vibration compensation, and autonomous medical service robots like ARIS 1.0. His team has developed systems for precision tasks such as kidney stone treatment and high-rise glass cleaning. Over 40 publications since 2018 demonstrate expertise in robotics algorithms, sensor fusion, and AI-driven solutions across healthcare, manufacturing, and environmental domains. Current openings include Post-Doctorate Fellowships and Research Assistant roles in robotics. PhD scholarships are available for candidates with project/publication portfolios.

• Acoustics
• Transportation Noise
• Urban Sound Planning
• +5 more

Wolfgang Kropp is a Professor at the Department of Architecture and Civil Engineering, Chalmers University of Technology, specializing in applied acoustics. His research focuses on tyre/road interaction, wheel/rail interaction, urban sound planning, and building acoustics, with particular emphasis on structure-borne sound and time-domain formulations. Key research areas include noise reduction strategies for transportation systems, perceptual evaluation of acoustic alerting systems for electric vehicles, and computational modeling of sound transmission in buildings and railways. His work bridges engineering, environmental science, and human perception to address urban noise challenges. Notable contributions include auralization techniques for noise assessment, numerical models for low-frequency sound transmission, and studies on the cognitive impacts of traffic noise. Kropp collaborates on projects like SONORUS, advancing urban sound planning methodologies.