جست‌وجوی استاد و پژوهشگر

• Integrated Sensing and Communication
• Wireless Communications
• Signal Processing
• +۶ مورد دیگر

Dr. Fan Jiang serves as an Associate Senior Lecturer at Halmstad University's School of Information Technology, where he leads research at the intersection of wireless communications and localization technologies. His academic profile reflects strong technical expertise in next-generation wireless systems with practical applications in vehicular networks and satellite communications. His research program focuses on integrated sensing and communication (ISAC) frameworks, with particular emphasis on: Massive MIMO and millimeter wave system design Wireless localization/synchronization algorithms Integration of sensing functionalities within communication protocols Applications for vehicular positioning and satellite networks Analysis of his 15 publications from 2022-2024 reveals consistent output in high-impact venues, with growing emphasis on satellite communications and reconfigurable intelligent surfaces. His work demonstrates strong mathematical rigor in channel modeling and algorithm design while addressing practical implementation challenges like synchronization errors and hardware constraints. Dr. Jiang maintains active research collaboration through co-authorship networks and participates in experimental validation efforts, as evidenced by his 2022 field study on 5G mmWave positioning. His technical approach balances theoretical innovation with real-world applicability across multiple wireless domains.

Thomas Waltherمشاهده پروفایل

پژوهشگر ارشد

• Computational Neuroscience
• Spatial Navigation
• Memory and Learning
• +۵ مورد دیگر

Dr. Thomas Walther is a postdoctoral researcher at the Institute of Neuroinformatics (INI), Faculty of Computer Science, Ruhr University Bochum. His work centers on computational neuroscience with a focus on modeling cognitive processes in mammals, particularly spatial navigation, learning, and memory extinction through computational approaches. His educational background includes: Diploma in Electrical Engineering and Information Technology from the University of Dortmund, with thesis research on medical image interpretation, tumor tracking, and robot-assisted radiotherapy Ph.D. in Electrical Engineering and Information Technology from Ruhr University Bochum, dissertation on autonomous visual model learning based on Organic Computing principles Dr. Walther's research spans computational neuroscience, virtual reality systems, robotics, computer vision, computational auditory scene analysis, and Organic Computing. He investigates hippocampal circuit mechanisms underlying spatial cognition and memory processes, employing deep reinforcement learning and computational modeling to bridge neural mechanisms with behavioral outcomes. His work integrates biological plausibility with artificial intelligence techniques to unravel complex cognitive functions. His publication record shows consistent focus on applying reinforcement learning to neuroscience questions, particularly spatial navigation and extinction learning phenomena, while maintaining strong contributions to computer vision (human body modeling) and robotics (RatSLAM optimization). This interdisciplinary trajectory demonstrates evolving integration between machine learning methodologies and neurobiological inquiry. Scientific awards: None mentioned in available information. Dr. Walther has supervised multiple Master's theses including research on deep reinforcement learning algorithms across environments, virtual reality applications, context representation in learning systems, and transfer of learned associations. His advising emphasizes computational approaches to cognitive questions within the INI's collaborative framework. As a core member of the Computational Neuroscience group at INI, he contributes to the institute's mission of understanding natural cognitive systems through experimental psychology, neurophysiology, and AI to develop novel solutions for artificial cognitive systems within interdisciplinary collaborations.

Ashwin Ashokمشاهده پروفایل

استادیار

• Cyber-physical systems
• Internet-of-Things (IoT)
• Mobile and Wearable Computing
• +۵ مورد دیگر

Dr. Ashwin Ashok is an Assistant Professor in the Department of Computer Science at Georgia State University, directing the Mobile Cyber Physical Systems Lab. He holds a Ph.D. from Rutgers University and a postdoctoral background at Carnegie Mellon University with expertise in vehicular networks, visible light communication, and mobile systems. His research focuses on cyber-physical systems, IoT, and wearable technologies, with contributions to computer vision, underwater communication, and environmental sensing. Education: B.Tech., National Institute of Technology-Warangal (2006) M.S., Texas A&M University (2008) Ph.D., Rutgers University (2014) His research interests span visible light communication, vehicular networks, and sensor systems, with a focus on real-world applications like autonomous systems and environmental monitoring. Recent work includes advancements in non-line-of-sight optical communication and digital rehabilitation systems. Publications reflect a strong emphasis on interdisciplinary innovation, combining communication systems with environmental and healthcare applications. Awards include the Best Teaching Assistant and Research Excellence Awards from Rutgers. Key Grants: CAREER: Towards Practical Mobile Visible Light Communication (2022) He leads initiatives like the OpenRadon Lab for soil radon modeling and collaborates on projects such as the Cosmic Climate Cuboid Nanosatellite for space radiation studies.

• Computer Vision
• Robotics
• Remote Sensing
• +۳ مورد دیگر

Boying Li is a Research Fellow in the Department of Data Science & AI at Monash University. Their research focuses on advancing computer vision, robotics, and remote sensing technologies. Key contributions include developing SLAM algorithms using semantic planar text features, self-supervised depth estimation systems, and SAR datasets for ship interpretation. Research interests span neuro-symbolic AI frameworks, autonomous navigation, and sensor data fusion. Their work contributes to the UN Sustainable Development Goals through applications in maritime surveillance and autonomous systems. Collaborations involve structural regularities in indoor environments and satellite imagery analysis. Notable outputs include the OpenSARShip dataset (2017–2018) and recent advancements in Hier-SLAM++ (2025). Awards and grants are not explicitly listed in available texts. No lab affiliations or future works are detailed.

• Biomechatronics
• Robotics
• Wearable Sensors
• +۶ مورد دیگر

Professor Ravi Vaidyanathan holds a Chair in Biomechatronics at Imperial College London, leading the Imperial College Biomechatronics Laboratory. His research focuses on smart systems integration, including wearable sensors, robotics, and health technologies. He is affiliated with multiple centers such as the Artificial Intelligence Network, Care Research and Technology Centre, and the UK Dementia Research Institute. His work bridges engineering and healthcare, with applications in neurorehabilitation, fetal monitoring, and assistive robotics. Dr. Vaidyanathan has secured funding for over 20 research programs globally and has authored over 200 publications. Notable achievements include 6 patents and innovations recognized by awards from IEEE, SAGE Journals, and industry leaders like Google and Sony. Education: No explicit details provided, though his academic role implies advanced degrees in mechanical engineering. Research interests span mechatronic design, sensor fusion, and human-robot interaction. His lab has spun off 4 companies commercializing neurorobotic solutions. Recent work includes AI-driven dementia care tools and fetal movement monitoring systems. Key Awards: Best Paper Awards from IEEE, AIAA, RSJ, and SAGE Journals UK NHS and IET Innovation Awards 2021 Google & Sony Awards for Dementia Research Advising and grants: Over 20 funded projects; formed 4 companies (3 commercial products). Lab collaborations include the Robotics Forum and Robotic Additive Manufacturing Lab. Labs/Teams: Biomechatronics Lab (website: biomechatronicslab.co.uk ), with multidisciplinary teams in robotics, AI, and biomedical engineering.

Sajad Saeedi Gharahbolaghمشاهده پروفایل

استادیار

• Robotics
• Simultaneous Localization and Mapping (SLAM)
• Focal-plane Sensor-processor Arrays (FPSP)
• +۶ مورد دیگر

Sajad Saeedi Gharahbolagh is an Assistant Professor in the Department of Mechanical, Industrial, and Mechatronics Engineering at Toronto Metropolitan University and an Honorary Research Fellow at Imperial College London's Department of Computing. His research spans robotics, SLAM, focal-plane sensor-processor arrays (FPSP), and deep learning for autonomous systems. Education : PhD in Electrical and Computer Engineering (2014) from the University of New Brunswick. Prior Roles : Dyson Research Fellow (2018-2019) at Imperial College London; Postdoctoral Fellow at University of New Brunswick (2014); R&D Engineer at 2G Robotics (2015). His research focuses on Simultaneous Localization and Mapping (SLAM) for single/multi-robot systems Focal-plane Sensor-Processor Arrays (FPSP) for high-speed, low-power vision processing Autonomous aerial/underwater robotics Deep learning integration with traditional robotics algorithms Control systems for heterogeneous robotic platforms His work addresses challenges in computational efficiency, robustness in GPS-denied environments, and real-time multi-sensor data fusion. Recent publications highlight advancements in Distributed NeRF for collaborative mapping MR.CAP multi-robot control/planning BIT-VIO visual-inertial odometry WiFi-based geometric mapping FPSP-optimized CNNs PathBench benchmarking framework Scientific Awards : Dyson Research Fellowship (2018-2019) Best Robotics Paper (CRV 2021) Best Student Presentation (IROS 2023) Research Team : PhD Students: Christopher Kolios, Navid Zarrabi, Messiah Esfahani, Ishaan Mehta, Mahboubeh Asadi, Jack Saunders MASc Students: Georgia Jovanovic, Hussein Ali Jaafar, Austin Vuong, Roni Sherman, Matthew Lisondra, Glenn Shimoda, Ali Babaei, Robel Efrem, Messiah Ataey, Christopher Kolios, Nikolas Kourtzanidis Laboratory Facilities : Robotics and Computer Vision Lab (RCVL) with Vicon motion capture system 14 TurtleBot 3 platforms (Waffle Pi/Burger variants) Germicidal UVC-equipped G-Robots Jetbots with onboard GPU processing OpenMANIPULATOR robotic arms

• Computer Vision
• Robotics
• 3D Reconstruction
• +۳ مورد دیگر

Luis Puig is an academic researcher specializing in computer vision and robotics, focusing on omnidirectional imaging systems, 3D reconstruction, and sensor calibration. His work bridges theoretical advancements with practical applications in navigation assistance for visually impaired individuals, intelligent tutoring systems, and multi-camera system integration. Key contributions include: Pioneering research in omnidirectional vision systems, including calibration techniques and feature extraction. Development of algorithms for 3D tracking, deformable surface modeling, and RGB-D sensor fusion. Advances in visual SLAM (Simultaneous Localization and Mapping) and stereo visual odometry. His interdisciplinary approach also extends to educational technology, designing adaptive learning systems for mathematical problem-solving. Over 23 publications in top venues like IEEE Trans. PAMI, CVIU, and ICRA reflect his expertise in both technical and applied domains.

• Navigation Systems
• Robotics and Control
• Unmanned Vehicles
• +۶ مورد دیگر

John Arvanitakis is an Assistant Lecturer in the Department of Electronic and Electrical Engineering at Coventry University's School of Engineering. He holds a PhD from the University of Patras (2017) and an MEng in Electrical and Computer Engineering (2009), both from the same institution. His research focuses on navigation systems, robotics control, unmanned vehicles, and fault diagnostics in electrical systems, particularly induction motors. He has been recognized with the 'Best Presentation in session' award (2013) at the Annual Conference. His work spans harmonic isolation methods, rotor fault detection, and nonlinear modeling. He is actively supervising PhD candidates and has contributed to over 25 peer-reviewed publications. Education: PhD (2017), MEng (2009), University of Patras Previous Roles: Researcher at University of Patras (2013–2017) Research interests include SLAM algorithms, optimization theory, and motor diagnostics. His publications emphasize practical solutions for electrical fault detection and control system improvements. Collaborations include international conferences like SDEMPED and ICEM. Current projects involve advancing torque-based diagnostics and harmonic analysis for motor reliability.

Ramviyas Nattanmai Parasuramanمشاهده پروفایل

دانشیار

• Robotics
• Artificial Intelligence
• Networked Multi-Robot Systems
• +۷ مورد دیگر

Ramviyas Nattanmai Parasuraman is an Associate Professor in the Department of Computer Science at the University of Georgia's School of Computing. His research focuses on heterogeneous multi-robot systems, wireless ad hoc networks, and applications in search and rescue robotics, precision agriculture, and human-robot interfaces. He leads the HeRoLab (Heterogeneous Robotics Research Lab) and holds affiliations with the Institute for Artificial Intelligence, Center for Cyber Physical Systems, and Phenomics and Plant Robotics Center. Education: Ph.D. (Robotics and Automation) from Universidad Politécnica de Madrid (2014), M.Tech. from IIT Delhi (2010), and B.Engg. from Anna University (2008). Prior to UGA, he worked as a postdoctoral researcher at Purdue University and KTH Royal Institute of Technology, Sweden. His doctoral work involved optimizing wireless communication for teleoperated robots at CERN. Research Highlights : Developed frameworks for knowledge transfer in multi-robot systems (KT-BT and IKT-BT). Pioneered the Analog Twin Framework for human-AI teleoperation. Advanced localization and trust assessment models for autonomous systems. Designed cybersecurity solutions for cyber-physical systems. Grants include a $1M NIFA grant for AI-driven precision poultry farming (2024) and a $1.68M Army grant for cooperative multi-agent systems (2023). He has been recognized with the CURO Faculty Mentoring Award and multiple Student Career Success awards. Labs & Teams : Director of HeRoLab, focusing on heterogeneous robotics and swarm systems. Faculty Investigator at the Small Satellite Research Lab.

Kris Hauserمشاهده پروفایل

استاد

• Robot Motion Planning
• Robot Control
• Autonomous Systems
• +۶ مورد دیگر

Kris Hauser is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), with affiliate appointments in the Departments of Electrical and Computer Engineering and Mechanical Science and Engineering. He holds a PhD in Computer Science from Stanford University and B.A. degrees in Computer Science and Mathematics from UC Berkeley. Prior to UIUC, he served as faculty at Indiana University (2009–2014) and Duke University (2014–2019), where he founded the Intelligent Motion Lab. He has also consulted for Waymo since 2019 and is the Director of the Coordinated Sciences Lab Robotics Group at UIUC. His research focuses on robot planning and control, semi-autonomous systems, and applications in intelligent vehicles, medical robotics, and legged locomotion. Key methodologies include optimization, probabilistic methods, AI, and physics simulation. His work bridges theory with real-world applications, such as robotic surgery, warehouse automation, and autonomous driving. Prof. Hauser has received notable awards including the NSF CAREER Award, Siebel Scholar Fellowship, and multiple Amazon Research Awards. He actively engages in teaching advanced robotics courses at UIUC and has contributed to open-source robotics frameworks like the Klamp't package. His lab emphasizes interdisciplinary collaboration, with projects ranging from UV disinfection robots to telepresence avatars.

Georg von Wichertمشاهده پروفایل

پژوهشگر

• Cognitive Systems
• Computer Vision
• Robotics
• +۳ مورد دیگر

Georg von Wichert is a Rudolf Diesel Industry Fellow at the Technical University of Munich (TUM) since 2009, affiliated with Siemens Corporate Technology. He holds a Diploma (M.Sc.) in electrical and control engineering from Darmstadt University of Technology (1992) and a Ph.D. in electrical engineering (1998). His research focuses on cognitive systems, including computer vision, robotics, and sensor fusion, with applications in autonomous systems and human-robot interaction. Affiliations: Siemens AG (Corporate Technology) & TUM Institute for Advanced Study (Focus Group: Cognitive Technology) Education: Darmstadt University of Technology (Diploma 1992, Ph.D. 1998) His work spans probabilistic modeling for multi-agent systems, semantic scene understanding, and robotic navigation. Notable contributions include table-top scene analysis, semantic indoor mapping, and robotic systems for everyday environments. He has led national and European research projects and contributed to initiatives like the Robotic Bar demonstration of human-robot collaboration. Scientific Awards: Rudolf Diesel Industry Fellowship (2009). Research Highlights: Developed algorithms for 6-DOF pose estimation, robotic exploration in dynamic environments, and context-aware robotic assistants. His publications address challenges in simultaneous segmentation, object recognition, and 3D localization using stereo vision.

Michele Magnoمشاهده پروفایل

مدرس ارشد

• Smart Sensing
• Low-Power Machine Learning
• Wireless Sensor Networks
• +۴ مورد دیگر

Michele Magno is a Senior Lecturer and Privatdozent at ETH Zürich's Department of Information Technology and Electrical Engineering (D-ITET), leading the D-ITET Center for Project-based Learning (pbl.ee.ethz.ch). He holds a PhD in Electronic Engineering from the University of Bologna (2010) and has held visiting roles at institutions like the University of Nice and Mid Sweden University. His research focuses on low-power systems, wearable devices, energy harvesting, and IoT applications. Magno has authored over 350 peer-reviewed papers, with a Google H-index of 49. Notable awards include the 2024 Best Paper Award at ECCV and multiple best poster/demo recognitions at IEEE conferences. His industrial collaborations include projects with STMicroelectronics, Texas Instruments, and Logitech. Teaching contributions include courses on embedded systems, FPGA programming, and machine learning on microcontrollers. Magno's innovations span smart sensors for wind turbines, bio-medical monitoring, and autonomous racing systems, with patents in touch communication and energy-neutral devices. Recent work emphasizes ultra-low-power solutions for AI-integrated wearables, energy-efficient IoT nodes, and real-time embedded vision systems. His labs and teams pioneer technologies like TinyssimoRadar for in-ear gesture recognition and WakeMod for ultra-low-power IoT connectivity.

Patricia A. Vargasمشاهده پروفایل

دانشیار

• Robotics
• Evolutionary Robotics
• Swarm Robotics
• +۷ مورد دیگر

Patricia A. Vargas is an Associate Professor/Reader in Computer Science and Robotics at the School of Mathematical & Computer Sciences, Heriot-Watt University, UK. She is the Founder Director of the Robotics Laboratory and Director of Ethics. Her research focuses on interdisciplinary robotics, including Evolutionary Robotics, Swarm Robotics, Biologically-Inspired Algorithms, Computational Neuroscience, and Neurorobotics. She holds IEEE Senior Member and Fellow of the Higher Education Academy titles. Education: PhD in Robotics, postdoc at the Centre for Computational Neuroscience and Robotics (University of Sussex, UK). She has contributed to over 66 research outputs since 2009, with recent work emphasizing neurorobotics, SLAM systems, and precision robotics. Her research aligns with UN Sustainable Development Goals, particularly in healthcare and industrial innovation. Research interests span from bio-inspired algorithms to human-robot interaction, with notable contributions in Parkinson’s disease modeling and swarm robotics. She co-founded the Edinburgh Centre for Robotics and is an executive member of the IEEE Ro-Man Standing Steering Committee. Awards include the 2017 Spirit of Heriot-Watt Award (Outward Looking). Her work bridges robotics with neuroscience, aiming to advance assistive technologies and ethical robotic systems.

Yvan Petillotمشاهده پروفایل

استاد

• Marine Robotics
• Autonomous Systems
• Sensor Processing
• +۴ مورد دیگر

Yvan Petillot is a Professor of Robotics and Autonomous Systems at Heriot-Watt University, co-academic lead of the National Robotarium, and chair of Robotics at the Scottish Research Partnership in Engineering. His expertise spans marine robotics, autonomous systems, sensor fusion, and subsea domain control. He leads a £3M grant portfolio focused on marine robotics innovations, emphasizing multi-vehicle collaboration and AI-driven autonomy. Petillot co-founded SeeByte Ltd to translate academic research into commercial solutions and pioneered EU robotics competitions fostering talent. His research emphasizes underwater robotics, including navigation, perception, and intervention in hazardous environments. Notable achievements include developing advanced underwater imaging techniques, reinforcement learning platforms (e.g., MarineGym), and frameworks for digital twins in teleoperation. He has received the Royal Society Industry Fellowship (2013) and was part of the 2022 Research Team of the Year award. Key technical contributions include synthetic aperture sonar systems, underwater SLAM (Simultaneous Localization and Mapping), and control strategies for vehicle-manipulator systems. His work addresses challenges in autonomous exploration, environmental monitoring, and safe human-robot collaboration in marine and industrial settings.

• Machine Learning
• Computer Vision
• Deep Learning
• +۴ مورد دیگر

Dr. Maryam Haghighat is a Lecturer at QUT's School of Electrical Engineering & Robotics, specializing in Machine Learning, Computer Vision, and Robotics. She holds a PhD from UNSW's School of Electrical Engineering and Telecommunications, where her thesis earned the 2020 UNSW Award for Outstanding Doctoral Thesis. Her postdoctoral research at the University of Oxford's Big Data Institute (2020–2022) focused on medical image analysis for the PathLAKE project. Currently, she leads AI projects with over $10M in funding, including ARC grants and industry collaborations. Her research spans applications in robotics, healthcare, and remote sensing. Notable contributions include developing machine learning algorithms for histopathology image analysis and robust multi-robot localization systems. Awards include the UNSW Doctoral Thesis Award (2020). She actively supervises PhD students in topics like multimodal fusion and 3D visual understanding. Publications highlight advancements in AI-driven medical imaging, hyperspectral transformers, and illumination-aware video compression. Her work bridges theoretical machine learning with practical applications in healthcare, robotics, and environmental monitoring.