جست‌وجوی استاد و پژوهشگر

• Reinforcement Learning
• Model-based Predictive Control
• Parametric Uncertainty
• +۶ مورد دیگر

Congcong Sun is an Assistant Professor in Agricultural Biosystems Engineering, specializing in control systems for agricultural environments and water distribution networks. Her research spans predictive modeling, reinforcement learning, and sensor technology integration. Affiliation: Agricultural Biosystems Engineering Academic Rank: Assistant Professor Research Focus: Congcong Sun's work emphasizes: Reinforcement Learning for climate control in greenhouses Model-based Predictive Control (MPC) for water distribution systems Handling Parametric Uncertainty in urban drainage networks Multisensor Fusion for precision agriculture Food Security through advanced agricultural technology Collaborative Projects: Current projects include: Soft and Biodegradable Sensing Technologies for Precision Soil and Crop Management Zero-emission Indoor Horticulture with Renewable Energy Autonomous Plant Factory Light Control using Phenomics SMARTFARMING: Vertical Farming with Self-learning Control Manure Removal Robotics in Dairy Barns Scientific Contributions: Her publications focus on: Deep Learning for Temperature Prediction in Solar Greenhouses Stochastic MPC for Urban Drainage Systems Sliding Mode Control for Nonlinear Systems Safe Stabilization Techniques for Robotic Systems Data-Driven Pipe Life Prognosis in Water Networks Advising & Collaboration: Active advisor for multiple PhD and EngD candidates, collaborating with researchers like E. van Henten, P. Groot Koerkamp, and G. Kootstra on agricultural automation and water system controls.

Le Chung Tranمشاهده پروفایل

دانشیار

• Wireless Communications
• Signal Processing
• 5G Systems
• +۷ مورد دیگر

Assoc. Professor Le Chung Tran holds a Ph.D. in Telecommunications Engineering from the University of Wollongong, Australia. He is currently an Associate Professor in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong, with roles including School Coordinator of Equity, Diversity, and Inclusion (EDI). His research focuses on wireless communications, signal processing, IoT, 5G systems, and localization technologies. Tran has extensive experience, including postdoctoral fellowships at the University of Luebeck (Germany) under the Alexander von Humboldt Foundation and academic positions in Vietnam. Education: Ph.D. in Telecommunications Engineering, University of Wollongong, Australia (2006) M.Eng. (Highest Distinction), Hanoi University of Transport and Communications, Vietnam B.Eng. (First Class Honours), Hanoi University of Transport and Communications, Vietnam Research Interests: Tran's work spans 5G, IoT, multiple-input multiple-output (MIMO) systems, ultra-wideband (UWB) communications, localization, and network coding. He has led projects on AI-driven environmental monitoring, non-GPS positioning, and underwater mine detection. Awards: UOW OCTAL Award (2019) Alexander von Humboldt Fellowship (2006-2008) WUS Awards (twice) Grants & Projects: AI-assisted Obstacle Detection System for Vision-Impaired People (2023-2024) Smart Eye: Airborne AI-Driven Sugarcane Assessment (2022) Aus4Innovation-funded Environmental Dashboard for Tram Chim National Park (2021) Labs/Teams: Active in the Wireless Technologies Laboratory and collaborations with industry partners like CSIRO and Agere Systems.

• Wireless Communications
• Signal Processing
• Image Steganography
• +۵ مورد دیگر

Dr. Peter Vial is a Senior Lecturer at the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong. He holds a PhD in Electrical Engineering and has over three decades of experience in academia and industry. His academic journey includes a Bachelor's (1987), Master's (1997), and PhD (2009) from the University of Wollongong. Before academia, he worked at BHP Steel (1981-1991) and transitioned into teaching roles from 1992, becoming a Lecturer in 2004 and Senior Lecturer in 2022. Research Interests: Dr. Vial’s work focuses on wireless communication systems, including MIMO, spread spectrum, and ultra-wideband (UWB) technologies. He also explores signal processing applications in medical imaging (e.g., capsule endoscopy), steganography, energy harvesting, and robotics. His research integrates machine learning and embedded systems for practical solutions in healthcare, telecommunications, and sensor networks. Teaching & Supervision: Dr. Vial teaches courses in telecommunications, digital signal processing, and electronics. He has led laboratory development in embedded systems and supervised over 15 postgraduate students, including current PhD candidates in Delay Tolerant Networks (DTN), 60GHz Ad Hoc networks, and UWB channel measurements. His supervision spans topics like AI-driven sign language recognition, steganography, and energy-efficient generator design. Grants & Funding: He led an internal grant (2008-2009) developing an immersive learning platform for microcontroller education. His research has been supported by institutional funding, with outputs published in journals like Neurocomputing , Signal Processing , and IEEE Sensors . Labs & Teams: Dr. Vial has developed engineering laboratories in embedded Internet systems, telecommunications, and digital signal processing. He collaborates with industry partners and interdisciplinary teams on projects combining hardware/software systems for healthcare, energy, and robotics.

• Wireless Sensing
• Signal Processing
• Machine Learning
• +۴ مورد دیگر

Wenda Li is an Assistant Professor at the Institute of Sensors, Signals & Systems , part of the University of Heriot-Watt 's School of Engineering & Physical Sciences. His research focuses on wireless sensing technologies, signal processing, and their applications in infrastructure monitoring, healthcare, and communication systems. He leads projects involving WiFi-based passive radar, RIS-aided networks, and machine learning-driven optimization strategies. Research interests include: Non-contact human activity recognition using WiFi signals Indoor localization and multi-user tracking Infrastructure assessment via 3D surface analysis Reconfigurable intelligent surface (RIS) optimization for IoT networks Machine learning integration in communication systems Recent work highlights include: A novel WiFi-based tracking system achieving sub-meter accuracy Automated 3D crack assessment for pavement maintenance RIS-aided semantic communication strategies Collaborations span global institutions, with active projects in China, UK, and Europe. His work has produced 9+ peer-reviewed publications since 2024, emphasizing practical applications of wireless sensing in healthcare and infrastructure domains.

James Mountمشاهده پروفایل

مدرس پاره‌وقت

• Robotics Engineering
• Autonomous Vehicles
• Computer Vision
• +۳ مورد دیگر

Dr. James Mount is a robotics engineer, STEM communicator, and sessional academic at Queensland University of Technology (QUT). He specializes in designing robotic systems for real-world applications and promoting technology education through engaging demonstrations. His research focuses on autonomous vehicles, visual localization, and robotics engineering. Mount holds an Honours Degree in Mechatronics Engineering and is awaiting his PhD Final Thesis Examination reviews from the Australian Centre for Robotic Vision. Education: Bachelor of Mechatronics Engineering (Honours) PhD Candidate in Robotics (pending final thesis review) Research interests include autonomous vehicle infrastructure readiness, vision-based robotics, and STEM education outreach. Notable projects include assessing Australian road infrastructure for autonomous vehicles and developing the Carlie mini-autonomous vehicle platform. He has presented at international conferences such as ICRA and IEEE Robotics and Automation Letters. Mount has delivered interactive STEM presentations to large audiences, including guest appearances on children’s TV shows like Brain Buzz and Juiced TV. His work bridges technical innovation with public engagement, emphasizing ethical AI considerations through interactive demonstrations like the Robotronica Trolley Problem exhibit. Labs/Teams: Core contributor to QUT’s Centre for Robotics and the Australian Centre for Robotic Vision. Lead engineer on the Carlie project and BBot Kickstarter initiative.

Marios Raspopoulosمشاهده پروفایل

دانشیار

• Telecommunications Engineering
• Wireless Networks
• 5G and 6G Communications
• +۶ مورد دیگر

Dr. Marios Raspopoulos is an Associate Professor and Deputy Head of the School of Sciences at University of Central Lancashire Cyprus (UCLan Cyprus), specializing in Telecommunications Engineering. His roles include Course Leader for the BEng (Hons) Electrical and Electronic Engineering program and leadership in innovation and enterprise initiatives. He holds a PhD from the University of Surrey (2008) and has over 15 years of academic and industry experience. Education: PhD in Telecommunications, University of Surrey (2008) MSc in Communication Networks and Software, University of Surrey (2004) MEng in Electronics with Mobile Communications, University of Surrey (2003) HND in Electrical and Electronic Engineering, Higher Technical Institute (2001) Research Interests: Focus on advanced wireless communication systems, indoor positioning technologies, 5G/6G networks, IoT security, and pervasive computing. His work combines theoretical modeling with practical implementations in areas like 3D localization, radio propagation, and AI-driven network optimization. Grants & Funding: Coordinator for €249k ERMISS project on 3D positioning (2025–2027) WP Leader for €400k EU-funded PREVENT project (2024–2025) Coordinator for DEMETRA (€39k) and THESIS (€39k) projects (2023–2024) Awards: Best Paper Awards at ISD2016 and European Wireless 2005 Multiple academic prizes including Cable & Wireless (2004) and Presidential Prize (2001) Lab/Teams: Active in interdisciplinary research through collaborations with industry and EU initiatives. Leads innovation efforts in UCLan's School of Sciences and participates in global standards committees like IPIN's International Standards Committee.

Martha Katafygiotouمشاهده پروفایل

استادیار

• Real Estate Development
• Sustainability
• Urban Planning
• +۳ مورد دیگر

Martha Katafygiotou is an Assistant Professor in Real Estate Development and Sustainability at the University of Nicosia. Her research focuses on sustainable urban development, energy-efficient building design, and the intersection of real estate markets with environmental and social governance (ESG) practices. She has contributed to advancing net-zero energy building strategies in the Mediterranean region, particularly in Cyprus, and has analyzed post-pandemic housing trends and tourist facility sustainability. Dr. Katafygiotou's work emphasizes practical solutions for retrofitting existing buildings, optimizing energy performance, and enhancing indoor environmental quality. She has published extensively on topics such as housing price indices, renewable energy adoption in residential sectors, and the impact of sustainable design on real estate markets. Her research bridges academic inquiry with actionable insights for policymakers and industry stakeholders. Her publications consistently address global sustainability challenges through a localized lens, particularly in Mediterranean climates. She has explored occupant comfort in schools and workplaces, bioclimatic design principles, and the role of materials in energy-efficient renovations. Though no specific awards or grants are listed, her prolific output since 2015 highlights sustained academic engagement with critical issues in sustainable development.

• Computer Vision
• Machine Learning
• Visual Computing
• +۴ مورد دیگر

Rafael Sterzinger is a PreDoc Researcher at the Institute of Visual Computing and Human-Centered Technology within TU Wien's Faculty of Informatics. Holding a BSc and MSc from ETH Zurich, he teaches courses in Computer Vision and Machine Learning for Visual Computing while pursuing his PhD. Education MSc in Computer Science, ETH Zurich BSc in Computer Science, ETH Zurich Research Interests Sterzinger's work centers on Computer Vision and Visual Computing , specializing in segmentation techniques for historical documents, cultural heritage artifacts, and WiFi-based sensing applications. His research integrates human-in-the-loop systems with deep learning for refinement tasks, explores reinforcement learning for building automation, and develops domain adaptation methods for cross-scenario human activity recognition. Key domains include Etruscan art digitization, through-wall imaging, and historical map analysis. Research Trends Analysis of Sterzinger's 2023-2025 publications reveals three dominant threads: (1) Few-shot segmentation for historical materials using foundation models, (2) Human-guided refinement pipelines that merge algorithmic precision with user input, and (3) Wireless sensing applications leveraging WiFi channel state information for through-wall imaging and activity recognition. His work consistently addresses data scarcity through innovative adaptation techniques while maintaining real-world applicability in cultural heritage and smart infrastructure. Projects EtMirA (2021-2027): Through-Wall Imaging Based on WiFi Channel State Information Blindsight (2023-2025) MAIJA (2024-2025): Closing the Gap in Human Behavior Analysis via Trimodal Data Synthesis KIIS (2021-2023): Deep Segmentation for Extracting Art from Ancient Etruscan Mirrors Advising and Grants No advisees are documented. Sterzinger participates in multiple externally funded projects including EtMirA's €1.2M infrastructure grant for cultural heritage digitization and MAIJA's interdisciplinary initiative synthesizing audio-visual-tactile data for behavior modeling, demonstrating sustained grant acquisition in visual computing domains.

Hannes Kaufmannمشاهده پروفایل

استاد

• Augmented Reality
• Virtual Reality
• Human-Computer Interaction
• +۷ مورد دیگر

Hannes Kaufmann is a Full Professor and Head of the Research Unit at the Institute of Visual Computing and Human-Centered Technology, TU Wien. His work focuses on Virtual and Augmented Reality (VR/AR), with expertise in tracking technologies, human-computer interaction, and immersive systems. He leads a team developing large-scale VR platforms like ImmersiveDeck and ProjectVerse, enabling collaborative experiences in fields like industrial design and emergency training. Education: PhD in Geometry Education via Augmented Reality (TU Wien), Habilitation in Mixed Reality Applications Research Interests: Mobile AR/VR, Haptics, Wide-Area Tracking, Medical AR, 3D UI Design, Cyberpsychology His research bridges technical innovation with real-world applications, such as disaster simulation, medical training, and accessibility solutions for hearing-impaired users using vibrotactile feedback. He has pioneered systems like the Holodeck-inspired CoboDeck and the AR monitoring framework for industrial quality control (AR-AQ-Bau). Publications span topics from haptic device design (Action-Origami) to collaborative VR training for first responders. Awards include the 2023 SIGGRAPH Best Project Award for haptic innovation and the 2020 nexus health innovation award for SPECTAS eye-tracking technology. Labs/Teams: Mixed Reality Lab, Virtual Meeting Room Initiative Grants: Supported by the Austrian Federal Ministry for Climate Action and EU Industry 4.0 projects

• Data management and data science
• Distributed computing and systems software
• Cybersecurity and privacy
• +۳ مورد دیگر

Dr. Belal Alsinglawi is a Postdoctoral Researcher at Swinburne University's School of Science, Computing and Emerging Technologies. His research focuses on data science, distributed computing, and cybersecurity with applications in healthcare and Industry 5.0. His work bridges theoretical advancements in machine learning and practical implementations in real-world systems such as pandemic modeling, indoor positioning, and medical data-sharing frameworks. Key research interests include: Machine learning for healthcare analytics (e.g., hospital length-of-stay prediction, lung cancer prognosis) IoT and cybersecurity in industrial and healthcare settings Epidemiological modeling of infectious diseases Blockchain architectures for medical data interoperability Recent work explores innovative applications like computational linguistics for WiFi tracking systems and AI-driven sign language app evaluations. His interdisciplinary approach combines technical rigor with societal impact through collaborations in emergency medicine, robotics, and pandemic response strategies. Currently not supervising students, he has contributed to over 40 publications since 2021, focusing on: Pandemic modeling and public health interventions (e.g., Jordan's NPI effectiveness) Cybersecurity frameworks for critical infrastructure Explainable AI systems in clinical decision-making Labs/Teams: Engaged with cross-disciplinary teams in digital health innovation and Industry 5.0 technologies.

• Capacitive Ultrasonic Transducers
• Non-Contact Ultrasonic Measurements
• Ultrasonic Flow Measurement
• +۳ مورد دیگر

William Wright is a Senior Lecturer in Mechanical Engineering and Director of the Ultrasonics Research Group at the School of Engineering, University College Cork (UCC). He holds a BEng (Hons) in Mechanical Engineering (1991) and a PhD in Air-Coupled Ultrasonic Testing (1996) from the University of Warwick, UK. His career includes roles as a Research Associate/Fellow at Warwick (1991–1997) before joining UCC in 1997. Education : BEng (Hons) in Mechanical Engineering, University of Warwick (1991) PhD in Air-Coupled Ultrasonic Testing of Materials, University of Warwick (1996) Research Interests : Focuses on capacitive ultrasonic transducers, non-contact ultrasound applications, ultrasonic flow measurement, and communication systems. His work includes developing air-coupled transducers for industrial and biomedical uses, such as swallowable sensors and wireless data transmission. He also investigates ultrasonic tomography for temperature and flow field imaging in gases. Grants : €169,745 from Science Foundation Ireland for ultrasonic secure wireless communication (2011–2016) €153,878 from the EU for nanotechnology-related research (2004–2005) Multiple grants from the Irish Research Council for projects on transducer design and flow measurement Labs/Teams : Leads the Ultrasonics Research Group ( http://ultrasonics.ucc.ie/ ), which develops advanced ultrasonic technologies for industrial, medical, and energy applications. Collaborates on wave energy converter monitoring and biomedical sensor integration. Teaching : Responsible for modules in Thermodynamics, Applied Thermodynamics, Non-Destructive Testing, and CAD/CAM. Supervised over 10 postgraduate students, including Sean McSweeney (PhD on capacitive transducers) and Salem Brini (MEngSc on flow measurement).

• Robotics
• Autonomous Vehicles
• Computer Vision
• +۳ مورد دیگر

Matthew Gadd is a Postdoctoral Research Assistant at the University of Oxford and a Junior Research Fellow at Kellogg College. He works in the Mobile Robotics Group (MRG) at the Oxford Robotics Institute (ORI), focusing on Robotics, Autonomous Vehicles, Computer Vision, and Machine Learning. His research addresses challenges in sensor systems, autonomous navigation, and robust place recognition in complex environments. He holds a DPhil in Engineering Science from Keble College, Oxford, and a BSc in Mechatronics Engineering from the University of Cape Town. Education: PhD (DPhil) in Engineering Science, Keble College, University of Oxford (20XX–20XX) BSc in Mechatronics Engineering, University of Cape Town, South Africa Research Projects: Sense Assess eXplain (SAX): Developing auditable autonomous vehicle systems Oxford Offroad Radar Dataset (OORD): Creating datasets for offroad navigation Autonomous biodiversity monitoring using long-term visual navigation Publications Highlights: Gadd’s recent work includes advancements in radar place recognition, uncertainty estimation, and LiDAR-based localization. His research often bridges theory and practice, with applications in autonomous vehicles and environmental robotics. Awards: 2013 FirstRand Laurie Dippenaar Scholarship Labs & Teams: Active contributor to the Oxford Robotics Institute and Mobile Robotics Group, collaborating with Prof. Paul Newman and international research networks.

• HVAC Systems
• Indoor Air Quality
• Ventilation Engineering
• +۳ مورد دیگر

Weixin Zhao is a Visiting Professor in the Department of Energy and Mechanical Engineering, focusing on ventilation systems, indoor climate, and sustainable energy solutions. He holds a Doctoral degree in Engineering and Technology from Aalto University (2021). His research addresses airborne transmission mitigation, HVAC system optimization, and energy-efficient ventilation strategies. Key contributions include studies on micro-environment systems, waste heat recovery, and convective/radiant cooling systems. Research interests span ventilation design, thermal environment control, and sustainable energy integration. Zhao has published widely on topics like airborne transmission dynamics, indoor air quality, and HVAC system performance. He has received multiple awards, including three Best Paper Awards (2021, 2022) and the Chinese Government Award for Outstanding Self-financed Students Abroad (2022). Education: Doctoral degree in Engineering and Technology, Aalto University (2021) His work aligns with UN Sustainable Development Goals, particularly in education and sustainable infrastructure. Zhao actively participates in international conferences such as the REHVA World Congress and International Conference on Indoor Air Quality and Climate, contributing to global HVAC research networks.

Debaditya Acharyaمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• 3D Building Modelling
• +۳ مورد دیگر

Dr. Debaditya Acharya is a Lecturer in Geospatial Science at RMIT University's School of Science, where he teaches Remote Sensing and Photogrammetry. His research focuses on computer vision, machine learning, and 3D building modeling, with applications in indoor localization, augmented reality, and LiDAR technologies. He holds a PhD from the University of Melbourne (Australia), where his thesis addressed visual sensing for infrastructure-free indoor positioning using 3D models. Prior to his current role, he worked as a CSIRO Postdoctoral Fellow in the Machine Learning & AI Future Science Platform and as a postdoctoral researcher at RMIT, focusing on fisheries anomaly detection and food automation via deep learning. Key projects include developing the ISPRS benchmark for indoor modeling, 3D reconstruction of the Royal Exhibition Building using LiDAR, and pedestrian tracking frameworks for the Queen Victoria Market. His work emphasizes open-source solutions for spatial digital twins and geospatial data integration in data-scarce regions. Debaditya is actively involved in supervising research students at the Masters and PhD levels, particularly in smart city frameworks leveraging digital twins, IoT, and augmented reality applications.

James H. Garrett Jr.مشاهده پروفایل

استاد

• Civil Engineering
• Data Mining
• Machine Learning
• +۶ مورد دیگر

James H. Garrett Jr. is the Provost and Thomas Lord Professor of Civil and Environmental Engineering at Carnegie Mellon University. He previously served as Dean of the College of Engineering (2013-2018) and Head of the Department of Civil and Environmental Engineering (2006-2012). Garrett joined CMU in 1990 and has held leadership roles including Associate Dean for Academic and Graduate Affairs (2000-2006). Ph.D., Civil Engineering, Carnegie Mellon University (1986) M.S., Civil Engineering, Carnegie Mellon University (1983) B.S., Civil Engineering, Carnegie Mellon University (1982) Garrett’s research focuses on sensor systems, data mining, and machine learning for civil infrastructure condition assessment. His work spans smart cities, transportation engineering, and structural health monitoring, with applications in HVAC systems, water infrastructure, and bridge diagnostics. He has pioneered methods for integrating BIM with maintenance data and developing intelligent decision support systems. Garrett’s publications emphasize sensor networks, data-driven infrastructure management, and machine learning for anomaly detection in transportation and building systems. His work bridges civil engineering with computational methods, including variational autoencoders for rail monitoring and adaptive graph filtering for bridge diagnostics. Alexander von Humboldt Research Prize (2012) Steven J. Fenves Award for Systems Research (2007) ASCE Computing in Civil Engineering Award (2006) As founding co-director of the Pennsylvania Smarter Infrastructure Incubator and a leader in the Wilton E. Scott Institute for Energy Innovation, Garrett has advanced smart infrastructure through sensor networks and data analytics. He also served as co-chief editor of the ASCE Journal of Computing in Civil Engineering (2008-2013).