جست‌وجوی استاد و پژوهشگر

Vinod Namboodiriمشاهده پروفایل

استاد

• Assistive Technologies
• Applied Computer Vision
• Smart Health
• +۵ مورد دیگر

Prof. Vinod Namboodiri is the Forlenza Chair in Health Innovation and Technology at Lehigh University's Department of Computer Science & Engineering and College of Health. He leads the Accessibility and Assistive Technologies (ACCESS) Lab, focusing on computing technologies to address health disparities affecting people with disabilities. His NSF-funded research develops navigation solutions for individuals with disabilities, with emphasis on smart communities and built environment accessibility. He holds a Ph.D. from UMass Amherst and previously served as Full Professor/Associate Director at Wichita State University and Adjunct Senior Scientist at Envision Research Institute. His research spans assistive technologies, applied computer vision, and smart health systems. Notable work includes MABLESim (indoor accessibility simulation), NaVIP (visually impaired navigation), and economic analyses of accessibility investments. His publications explore both technical innovations and policy implications of assistive technologies. Prof. Namboodiri has received multiple awards for research, teaching, and innovation. His work bridges computer science with disability studies, emphasizing real-world impact through interdisciplinary collaboration. Current projects address indoor navigation systems, cost-benefit analysis of accessibility infrastructure, and human-agent interaction platforms for disability empowerment.

Omprakash Gnawaliمشاهده پروفایل

دانشیار

• Internet of Things
• Smart Devices
• Wireless Sensor Networks
• +۳ مورد دیگر

Omprakash Gnawali is an Associate Professor in the Department of Computer Science at the University of Houston, with expertise in Internet of Things, wireless sensor networks, and artificial intelligence. His research focuses on advanced networking protocols, mobility analysis, and safety monitoring systems. Postdoctoral work at Stanford University PhD in Computer Science from University of Southern California Masters and Bachelors from Massachusetts Institute of Technology His research interests include Ultra-Wideband (UWB) localization, network protocol design, edge computing for monitoring systems, and mobile sensor networks. He leads the Networked Systems Laboratory , where he develops frameworks like the Collection Tree Protocol and CodeDrip for efficient data dissemination. Recent publications highlight trends in UWB-based safety monitoring, routing optimization in dual-radio networks, and deception detection in cybersecurity. He has secured NSF Student Travel Grants for ACM SenSys conferences in 2016 and 2017. Scientific Awards NSF Student Travel Grant (2017) NSF Student Travel Grant (2016) He actively mentors students in research projects and teaches courses such as Research Methods in Computer Science and Computer Networks . His service roles include Technical Program Committee memberships and chairing the TinyOS Network Protocol Working Group.

• Control Theory
• Advanced Control Systems
• Model Predictive Control
• +۷ مورد دیگر

Liuping Wang is a Professor in the School of Electrical and Computer Engineering at RMIT University, Australia, since 2007. He serves as Head of Discipline for Electrical Energy and Control Systems since 2005 and teaches Advanced Control Systems (EEET 2100) and Real Time Estimation and Control (EEET 2221). Current academic rank: Professor Location: City Campus, Australia Industry collaborators: ANCA, Australian Power Academy, Advanced Manufacturing CRC His research interests span: Control Theory with applications to UAVs and industrial processes Development of Model Predictive Control systems System Identification using neural networks Robust Control for constrained systems Control of AC motors and power electronics Applications in biomedical research and food process monitoring The 15 most recent publications (2015-2025) demonstrate expertise in: UAV control systems with segmented surfaces Battery condition monitoring for electric vehicles Mult-agent robotics with coordination algorithms Smart grid security and electricity dispatch GPS-denied localization for mobile robots Disturbance observer control with input constraints As a supervisor, he oversees Masters Research and PhD projects but no specific student names are listed. His email is liuping.wang@rmit.edu.au for collaboration or supervision inquiries.

• Biomedical Signal Processing
• Electroencephalography (EEG)
• Mental Workload Assessment
• +۱۲ مورد دیگر

Tarmo Lipping is a Professor in the Department of Computer Science and Engineering at the Faculty of Information Technology and Electrical Engineering, University of Oulu. His work bridges computing sciences with biomedical engineering, environmental modelling, and data-driven societal applications. Doctor of Science (Technology), Information Technology – Awarded 14 Feb 2001 Master of Science (Technology), Information Technology – Awarded 10 Sept 1993 His research focuses on electroencephalography (EEG) , mental workload assessment , depth of anesthesia monitoring , and machine learning applications in healthcare and human-computer interaction. He also contributes to environmental informatics , particularly in land uplift modelling and radionuclide transport , aligning with UN Sustainable Development Goals. Recent publications highlight trends in transformer networks for EEG analysis , wearable HCI systems , data-driven food safety , and participatory municipal governance . His work integrates deep learning, signal processing, and real-world deployment. Scientific awards include: CIMO opettajavaihto (2017) Lipping has supervised numerous master’s students and served as an examiner in diverse topics including data vault modelling , telecom revenue estimation , and EEG hyperscanning . He has evaluated funding applications, acted as a journal reviewer (65 times), and contributed to editorial work. His activities reflect strong engagement in academic service and interdisciplinary research mentorship. He has contributed datasets on Fennoscandian land uplift , lake isolation , and archaeological shorelines to PANGAEA, supporting open science in geosciences and environmental history.

Gideon Hartmanمشاهده پروفایل

دانشیار

• Paleoenvironmental Reconstruction
• Stable Isotope Analysis
• Archaeology
• +۶ مورد دیگر

Gideon Hartman is an Associate Professor in the Anthropology Department at the University of Connecticut, where he conducts interdisciplinary research at the intersection of paleoenvironmental reconstruction, plant and animal eco-physiology, anthropology, and archaeology. His work primarily employs stable isotope methods to reconstruct past environments, human mobility patterns, paleodiets, and ancient economic systems. Dr. Hartman received his Ph.D. from Harvard University in 2008. His educational foundation in anthropology and archaeological science has enabled his innovative approach to stable isotope analysis. Rather than treating isotopic values as static markers, he investigates the mechanisms causing variability in stable isotope ratios as they move along foodwebs from soil and atmosphere to plants and then to animals and humans. Hartman's research program uniquely begins in the contemporary world to establish principles that can be reliably applied to archaeological settings. His work spans diverse geographical regions including the Eastern Mediterranean, Levant, Jordan Valley, and Armenian Highlands, with temporal coverage from the Middle Pleistocene to the Early Bronze Age. He has made significant contributions to understanding how environmental factors like water availability, temperature, and soil conditions affect isotopic signatures in modern ecosystems, creating robust models for archaeological interpretation. His publication record demonstrates consistent productivity in high-impact journals, with research trends showing increasing sophistication in multi-isotope approaches applied to complex archaeological questions about pastoralism, trade networks, human migration, and human-environment interactions. His work increasingly integrates zooarchaeological, archaeobotanical, and geochemical evidence to build comprehensive pictures of past societies. As director of the Stable Isotope Preparation Lab at UConn, Hartman leads a research team that processes and analyzes samples from archaeological sites worldwide. His laboratory serves as a hub for interdisciplinary collaboration between archaeologists, anthropologists, geoscientists, and biologists seeking to apply isotopic methods to their research questions. His work has been instrumental in refining methodologies for interpreting strontium, carbon, nitrogen, and oxygen isotope data in archaeological contexts, particularly regarding animal and human mobility patterns in the Eastern Mediterranean region.

• Indoor Positioning
• Mobile Computing
• Context-aware Computing
• +۷ مورد دیگر

Adriano Jorge Cardoso Moreira is an Associate Professor with Habilitation at the Department of Information Systems, School of Engineering, Universidade do Minho, Portugal. He is also a Senior Researcher at the Algoritmi Research Centre and Scientific Coordinator of the Urban and Mobile Computing department at Centro de Computação Gráfica. His research focuses on indoor positioning , mobile and context-aware computing , urban computing , and simulation of wireless networks . Research Interests : Indoor Positioning, Mobile Computing, Urban Mobility, Sensor Networks, Wi-Fi and UWB Localization, Smart Cities. Leadership : Coordinated the Computer Communications and Pervasive Media Group (2008-2016), Scientific Committee member (Director of MAP-tele PhD program in multiple terms), and leads the Master in Telecommunications and Informatics since 2021. Publications : Over 100 papers, including IEEE Transactions and Sensors journal articles, with an h-index of 23 and 2136 citations. Awards : First and second prizes in EvAAL-ETRI Indoor Localization Competitions (2015, 2016, 2017).

Chen Wangمشاهده پروفایل

استادیار

• Robotics
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Dr. Chen Wang is an Assistant Professor in the Department of Computer Science and Engineering at the University at Buffalo. He holds a PhD from Nanyang Technological University and a B.Eng from the Beijing Institute of Technology. His research focuses on robotic perception, vision, and learning, emphasizing algorithm development for autonomous systems. He is affiliated with the Spatial AI and Robotics Lab (SAIR Lab) and serves as an Associate Editor for The International Journal of Robotics Research (IJRR) and IEEE Robotics and Automation Letters (RA-L) . His work spans neuro-symbolic AI, SLAM systems, and reinforcement learning for robotics. Dr. Wang's research interests include creating efficient algorithms with theoretical guarantees, open-source distribution, and real-world validation. He has contributed to areas like visual navigation, few-shot detection, and robot autonomy frameworks. His educational background in electrical engineering and robotics underscores his expertise in bridging theory and practical applications. Notable contributions include the iWalker framework for humanoid robots, AirSLAM for visual SLAM, and SuperPC for 3D point cloud processing. His editorial roles and conference service (e.g., CVPR Area Chair) reflect his leadership in the field. The SAIR Lab under his direction advances spatial AI, robotics, and autonomous systems through interdisciplinary collaboration.

Craig Hancockمشاهده پروفایل

استاد پژوهشی

• Geospatial Engineering
• Structural Health Monitoring
• Global Navigation Satellite Systems (GNSS)
• +۳ مورد دیگر

Dr. Craig Hancock is a Research Professor in Geospatial Engineering with 15 years of research experience in Surveying and Geodesy. His expertise spans GNSS error mitigation, structural monitoring, and geospatial techniques for digital construction. He has supervised 10 PhD students and published over 80 academic papers. Education: BSc and PhD in Surveying/Geomatics Key Projects: Principal Investigator for projects on GNSS error mitigation, structural health monitoring, and marine economy technology. His research focuses on three core areas: GNSS error categorization and mitigation (particularly ionospheric effects), structural and environmental change monitoring, and geospatial data acquisition for BIM and digital construction. Recent work includes improving 3D modeling accuracy, UAV-based GNSS spoofing detection, and BIM-enabled facility management in healthcare infrastructure. His articles explore topics like sensor optimization, structural dynamics, and geospatial data fusion. Grants include £150k for bridge deformation studies and £9k for ionospheric error analysis. He actively contributes to teaching and enterprise initiatives, integrating geospatial technologies with industry needs.

• Wireless Sensing
• Radar Technology
• Machine Learning
• +۷ مورد دیگر

Kevin Chetty is a Professor of Wireless Sensing at University College London (UCL), leading the Urban Wireless Sensing Lab within the Department of Security and Crime Science. His work bridges radar technology, machine learning, and healthcare applications, with a focus on passive sensing systems. Education: PhD in Medical Ultrasound Physics (Imperial College London, 2004-2007), MRes in Image and X-Ray Physics (King's College London, 2003), BSc in Physics (King's College London, 1999) Research spans radar micro-Doppler signature analysis for human behavior classification, software-defined radar development, and integrated communication-sensing systems, with applications in security, healthcare, and smart environments. Recent work emphasizes privacy-preserving technologies and edge processing for real-time operations. Scientific awards include the 2022 IET Radar Systems Best Paper Runner-Up, 2022 IEEE Radar Conference 2nd Place, and 2015 National Instruments Engineering Impact Award. He has received funding from government and industry sectors in telecommunications, IoT, security, and healthcare. Teaching roles: Programme Convener for MSc Crime Science and IEP Minor in Crime and Security Engineering; Module Convener for Security Technologies and Crime Mapping & Spatial Analysis Consultancy: Huawei Technologies (2020-2022), Metropolitan Police Service (2019)

Wout Josephمشاهده پروفایل

استاد

• electromagnetic field exposure assessment
• in-body electromagnetic field modelling
• electromagnetic medical applications
• +۱۲ مورد دیگر

Wout Joseph is a Professor in the domain of Experimental Characterization of wireless communication systems at Ghent University (Belgium), where he has been working since October 2009. He is also an IMEC Principal Investigator since 2017. His research is conducted within the wireless, acoustics, environment & expert systems (WAVES) research unit at the Department of Information Technology (INTEC). Dr. Joseph was born in Ostend, Belgium on October 21, 1977. He received his M.Sc. degree in electrical engineering from Ghent University in July 2000. From September 2000 to March 2005 he was a research assistant at the Department of Information Technology (INTEC), where his scientific work focused on electromagnetic exposure assessment around base stations for mobile communications related to health effects. This work led to his Ph.D. degree in March 2005. Professor Joseph's research expertise spans multiple domains within wireless communications and bioelectromagnetics. His primary research interests include electromagnetic field exposure assessment, in-body electromagnetic field modeling, electromagnetic medical applications, propagation for wireless communication systems, IoT, antennas and calibration. He also specializes in wireless performance analysis, industry 4.0 applications, wireless localization, and Quality of Experience metrics. His work is particularly notable for its focus on dosimetric studies in the radiofrequency range, where his research is ranked first in number of peer-reviewed studies. His research has practical applications in wireless network planning, occupational safety, and public health policy related to electromagnetic fields. His extensive publication record (over 886 publications with an h-index of 45 in ISI Web of Science and 66 in Google Scholar) demonstrates a clear trajectory from fundamental electromagnetic field measurements to applied research in industrial wireless networks and bioelectromagnetic applications. Recent work shows a strong emphasis on 5G exposure assessment across multiple European countries, millimeter-wave channel modeling, and the application of machine learning techniques to exposure assessment and wireless localization. EBEA council board member (2015-2018) EBEA board member at large (2019) Bioelectromagnetics Society board member (2022) Bioelectromagnetics Society board member (2024) 24 research awards Professor Joseph leads significant research efforts in electromagnetic field exposure assessment, with particular emphasis on developing measurement methodologies and computational models for real-world exposure scenarios. His work bridges theoretical electromagnetic modeling with practical applications in wireless communications and bioelectromagnetics. His research group within the WAVES unit is highly active in both theoretical and experimental aspects of wireless communications and bioelectromagnetics, with current projects focusing on 5G exposure assessment across Europe, millimeter-wave channel modeling for data centers and industrial environments, and the development of novel exposure assessment methodologies using advanced signal processing and machine learning techniques.

Otman Basirمشاهده پروفایل

استاد

• Intelligent Embedded Systems
• Sensory Systems Design
• Human-Computer Interaction (HCI)
• +۵ مورد دیگر

Otman Basir is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He serves as Associate Director of the Waterloo Institute for Health Informatics Research and Associate Director of the Pattern Recognition and Machine Intelligence Laboratory. Additionally, he is Director of Urban Informatics Corporation and founder/president/CEO of Intelligent Mechatronic Systems (IMS), a leader in telematics and infotainment technologies. Education: PhD in Systems Design Engineering (University of Waterloo, 1993), MSc in Electrical Engineering (Queen's University, 1989), BSc in Computer Engineering (Al-Fateh University, Libya, 1984). Research focuses on intelligent embedded systems, sensory systems design, biologically inspired systems, and human-computer interfaces. He has authored over 400 publications and holds 121 patents. Recent work includes blockchain applications, vehicular communication systems, and cybersecurity frameworks for IoT. His research emphasizes real-world applications in transportation and healthcare. Key awards include the Ontario Premier Research Excellence Award and Canada Foundation Innovation Award. Teaching includes courses like ECE 124 (Digital Circuits) and ECE 659 (Intelligent Sensors). IMS innovations drive connected car technologies, emphasizing driver safety and sustainability. Patents: 121 issued/pending Grants: Multiple awards supporting health informatics and intelligent systems research Labs: Pattern Recognition Lab, Waterloo Health Informatics Research

Dimitrios Koutsonikolasمشاهده پروفایل

دانشیار

• Wireless Networking
• Mobile Computing
• Millimeter Wave Networking
• +۵ مورد دیگر

Dr. Dimitrios Koutsonikolas is an Associate Professor in the Electrical and Computer Engineering Department at Northeastern University, leading the WiNS Lab. Previously, he held a tenured position at the University at Buffalo. His research focuses on experimental wireless networking and mobile computing, particularly millimeter-wave systems, 5G/6G networks, energy-efficient protocols, and high-bandwidth applications like VR/AR. He has published over 80 papers in top venues (e.g., MobiCom, INFOCOM), received NSF CAREER and IEEE awards, and led major grants including an NSF-funded $3M project for an open 5G/6G testbed. His lab explores cutting-edge technologies like O-RAN, beam management, and edge computing for latency-critical applications. Education: PhD in Electrical and Computer Engineering from Purdue University (2010). Research Interests: Experimental validation of wireless protocols, mmWave networking, latency-optimized edge computing, and cross-layer design. Current projects include TARGET (5G/6G latency solutions) and the X5G testbed for open spectrum utilization. Recent Trends in Articles: Focus on 5G deployment maturity, mmWave beam management, and 6G-ready technologies like autonomous space networks. Work bridges theoretical contributions with practical implementations, leveraging testbeds for real-world validation. Awards: Notable honors include IEEE Region 1 Innovation (2019), NSF CAREER (2016), and multiple best paper awards at MobiCom, WCNC, and Globecom. Recognized for both research and teaching excellence. Grants & Labs: Principal investigator on NSF grants ($3M+), leading collaborations with IMDEA Networks and industry partners. WiNS Lab develops open-source tools for 5G testing and explores sub-THz channels. Advises over 15 students, many advancing to top tech firms (e.g., Apple, HP Labs).

• Computer Vision
• 3D Computer Vision
• Machine Learning
• +۸ مورد دیگر

Federico Tombari is a Director of Research at Google Zurich and a Lecturer (Privatdozent) at the Chair of Computer Aided Medical Procedures (CAMP) at TUM. He leads applied research in Computer Vision and Machine Learning, focusing on 3D vision, robotics, augmented reality, autonomous driving, and healthcare applications. His work emphasizes unsupervised learning, large multimodal models, neural radiance fields, and scene graphs. Education & Professional Background: As PD Dr. Ing. Habil., he holds a habilitation in engineering and has been active in academic and industrial research for over a decade. His roles include Area Chair for top conferences like CVPR and ECCV, and Associate Editorships for journals like IJRR. Research Interests: Federico’s research spans 3D scene understanding, object recognition, SLAM, and novel view synthesis. He explores applications in surgical robotics, autonomous systems, and medical imaging. Recent trends in his work include generative models for scene generation and semantic scene graphs for holistic modeling. Grants & Industry Collaborations: He has led projects with Toyota, BMW, Audi, Zeiss, and others, focusing on 3D perception, autonomous driving, and medical vision. His work bridges academia and industry, emphasizing practical applications. Labs & Teams: He contributes to labs like DHM (Deutsches Herzzentrum München), NARVIS Lab, and RobUSt (Robotics and Ultrasound), advancing interdisciplinary research in healthcare and robotics.

Ramsey Faragherمشاهده پروفایل

پژوهشگر

• Infrastructure-free Indoor Positioning
• Simultaneous Localisation and Mapping (SLAM)
• Smartphone Sensing
• +۹ مورد دیگر

Dr. Ramsey Faragher is a Senior Research Associate at the Computer Laboratory , University of Cambridge, and a Bye-Fellow at Queens' College. His work focuses on infrastructure-free indoor positioning systems, sensor fusion, and improvements to smartphone sensing capabilities. Academic Affiliation : University of Cambridge (Computer Laboratory) Professional Roles : Bye-Fellow at Queens' College, Senior Research Associate His research spans multiple disciplines within computer science and engineering, emphasizing innovative navigation solutions and signal processing techniques. Key areas include GNSS robustness, wireless security, and machine learning applications for positioning systems. Recent publications highlight advancements in supercorrelation for automotive GNSS, sensor data calibration, and motion-compensated signal processing. Articles frequently address challenges such as spoofing mitigation, urban navigation, and infrastructure-free localization. Scientific Recognition Fellow of the Royal Institute of Navigation Chartered Physicist (CPhys)

Mihran Tuceryanمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Pattern Recognition
• +۳ مورد دیگر

Professor Mihran Tuceryan is a Professor of Computer Science at Purdue University Indianapolis, affiliated with the Department of Computer Science within the College of Science. He holds a PhD from the University of Illinois at Urbana-Champaign (1986) and a BS from MIT (1978). His expertise spans Computer Vision, Image Processing, Pattern Recognition, and Augmented Reality. Recent research focuses on crime prediction via video analysis, forensic imaging, and distributed tracking systems. He is a Senior Member of IEEE and ACM. Key research interests include augmented reality integration for industrial training, real-time illumination modeling, and monocular SLAM algorithms. His work addresses challenges in photorealistic AR, dynamic object labeling, and medical imaging applications such as hepatic fibrosis detection. He has contributed to projects like the e-DOTS indoor tracking system and forensic 3D impression acquisition. His publications span over three decades, emphasizing real-world applications in security, healthcare, and robotics. Education: Bachelor of Science in Computer Science and Engineering, MIT, 1978 PhD in Computer Science, University of Illinois at Urbana-Champaign, 1986 Awards: Senior Member, IEEE Senior Member, ACM Labs/Teams: Focus on AR, SLAM, and medical imaging applications Collaborative frameworks for distributed visual SLAM