جست‌وجوی استاد و پژوهشگر

Fei Douمشاهده پروفایل

استادیار

• Machine Learning
• Federated Learning
• Wireless Sensor Networks
• +۳ مورد دیگر

Fei Dou is an Assistant Professor in the School of Computing at the University of Georgia, which operates under the Franklin College of Arts and Sciences. He joined UGA in August 2023 and serves as Graduate Program Faculty. His office is located in the Boyd Research and Education Center. He holds a Ph.D. and M.S. in Computer Science and Engineering from the University of Connecticut, both completed in 2023. Dr. Dou's research spans several key areas of computer science with particular focus on: Machine learning systems : Federated learning, reinforcement learning, and self-supervised techniques Wireless sensing : Healthcare monitoring using WiFi signals and contactless sensing Networked systems : Underwater sensor networks and secure communication protocols Applied AI : Education technology, precision agriculture, and indoor positioning His recent publications (2021-2025) demonstrate strong emphasis on federated learning adaptations for resource-constrained environments, healthcare applications using novel sensing methodologies, and security solutions for underwater networks. A consistent theme involves developing efficient machine learning techniques that operate in challenging real-world conditions while preserving privacy and security.

Ilankaikone Senthooranمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Operations Research
• Constraint Programming
• +۳ مورد دیگر

Ilankaikone Senthooran is a Senior Research Fellow in the Department of Data Science & AI at Monash University. Their work focuses on applying artificial intelligence and operations research to real-world challenges, including healthcare optimization, transportation systems, energy networks, and robotics. Research interests include constraint programming, human-centered AI, feasibility restoration algorithms, and optimization under complex constraints. They have led projects on community-centric sports scheduling, AI in policy problems, and hydrogen supply networks. Notable contributions include nurse rostering with fatigue modeling, pavement upgrade scheduling, and hydrogen supply-demand network analysis. Collaborations span disciplines like robotics (swarm systems, MAV localization), infrastructure planning, and public policy. Their work aligns with UN Sustainable Development Goals related to sustainable cities and systems, and responsible innovation. Recent projects include: Community Centric Sport Fixtures (2023-2025) Fitting AI Technology to Complex Policy Problems (2022) Human-Centred Feasibility Restoration (2021-2023) Publications emphasize practical applications of AI and optimization techniques across diverse sectors.

Jinsung Leeمشاهده پروفایل

پژوهشگر

• Cellular/WiFi Systems
• 5G Standard
• Indoor Localization
• +۷ مورد دیگر

Jinsung Lee is a Postdoctoral Research Associate at the University of Colorado and a Senior Staff Engineer at Qualcomm. His research focuses on wireless network design, cellular/Wi-Fi systems, 5G architecture, transport protocols, and deep learning applications in mobile computing. He has contributed to projects like Optimal CSMA (oCSMA) and PERCEIVE, which leverage deep learning for cellular uplink prediction. Key publications include studies on 5G edge computing, energy-efficient transportation mode recognition via sound analysis, and secure LTE network protocols. His work has received Best Paper Awards at ACM MobiSys'19 and IEEE SECON'13. Lee’s research addresses challenges in network performance, security, and resource optimization across cellular, Wi-Fi, and multi-path TCP environments. Roles: Postdoc (University of Colorado), Senior Staff Engineer (Qualcomm) Key Projects: oCSMA Implementation, PERCEIVE, CASTLE over the Air Areas: 5G, Transport Protocols, Deep Learning, Wireless Security

Yudi Daiمشاهده پروفایل

پژوهشگر ارشد

• 3D Computer Vision
• Scene Mapping
• 4D Human Motion Capturing
• +۴ مورد دیگر

Yudi Dai is a Postdoctoral Research Fellow at the ETH AI Center, collaborating with Professors Siyu Tang and Christian Holz. He holds a PhD from Xiamen University (2024), where he also completed his B.E. (2016) and M.Sc. (2019). His research focuses on 3D Computer Vision, emphasizing scene mapping, 4D human motion capturing, and human-scene interaction reconstruction. He aims to develop robust methods for understanding human behavior in complex environments. Education: Ph.D. in Computer Science, Xiamen University, 2024 M.Sc. in Computer Science, Xiamen University, 2017-2019 B.E. in Computer Science, Xiamen University, 2016 His research interests include multimodal datasets (e.g., ClimbingCap, SLOPER4D), sensor fusion (IMUs+LiDAR), and human-centric scene capture. Notable contributions include HSC4D for large-scale indoor-outdoor scene reconstruction and HiSC4D for human-scene interaction modeling. His work bridges computer vision, robotics, and sensor technology for applications in AR/VR, autonomous systems, and urban modeling. Publications span CVPR, TPAMI, and IEEE journals, emphasizing scene-aware human motion analysis and dataset development. Collaborations involve institutions like ShanghaiTech University and the Xiamen University Sensing and Computing Lab. His datasets are widely cited for their focus on real-world, challenging environments. Current work explores dynamic scene reconstruction, wearable sensor systems, and human-environment interaction modeling. His lab at the ETH AI Center focuses on advancing AI-driven perception in unstructured environments.

• Tissue Engineering
• Biofabrication
• Computer Vision
• +۳ مورد دیگر

Dr. Hao Liu is a Researcher in the Department of Tissue Technology and Biofabrication at ETH Zurich's Institute for Biomechanics. His work intersects tissue engineering, biofabrication, and advanced computational techniques such as computer vision and 3D reconstruction. He focuses on interdisciplinary applications, including robotics and neural radiance fields (NeRF) for biomedical and robotic systems. Institution: ETH Zurich Role: Researcher (Staff of Professorship for Tissue Engineering and Biofabrication) Research interests span tissue engineering, biofabrication, and computational methods like 3D reconstruction, visual localization, and neural networks. His recent work emphasizes robust 3D scene understanding, camera pose estimation, and deep learning for multi-view stereo. Publications highlight advancements in relative pose estimation, neural radiance fields, and line-based geometric analysis, contributing to both robotics and biomedical engineering fields. He has no listed scientific awards, but his research demonstrates significant innovation in computational imaging and biofabrication. No advising or grant details are provided in the available texts. His affiliation with the Institute for Biomechanics suggests involvement in labs focused on biomechanical systems and biofabrication technologies.

Stefan Mangoldمشاهده پروفایل

مدرس

• Wireless Communication
• Visible Light Communication
• Internet of Things (IoT)
• +۳ مورد دیگر

Dr. Stefan Mangold is a Lecturer in the Department of Computer Science at ETH Zürich, where he has taught courses on Wireless Networking and Mobile Computing since 2007. He is also the founder and General Manager of Lovefield Wireless, focusing on wireless communication protocols and systems for applications like visible light communication (VLC), IoT, and delay-tolerant networks. His academic and industry work spans themes such as wireless LAN optimization, VLC integration with IoT, and networking solutions for under-served regions. Stefan holds a Ph.D. in Electrical Engineering/Telecommunications from RWTH Aachen University. His research emphasizes practical, scalable solutions for wireless systems, including projects at Disney Research, Swisscom, and Philips. Key areas include VLC protocols, IoT connectivity, and ethical challenges in networked systems. His publications cover innovations like EnLighting (VLC using light bulbs), delay-tolerant networks for remote areas, and gesture-based device association. While no specific awards are listed, his work bridges academia and industry, reflecting contributions to both theoretical and applied wireless systems. Labs and teams: Lovefield Wireless, a hub for research and development in VLC and IoT networking.

• Internet of Things (IoT)
• Sensors and Sensor Networks
• Energy Harvesting
• +۳ مورد دیگر

Philipp Mayer is a Lecturer at ETH Zürich's Department of Information Technology and Electrical Engineering. His work focuses on IoT, energy-efficient sensors, and embedded systems. He has contributed to advancements in underwater communication, energy harvesting, and wearable sensor technologies. His research includes innovations in low-power sensor networks, RF energy transmission, and AI-driven embedded systems. Notable projects include the design of self-sustaining sensors and high-precision localization systems using UWB and LoRa technologies.

• Wireless Networks
• Internet of Things (IoT)
• Energy Harvesting
• +۴ مورد دیگر

Jeroen Famaey is a Professor at Ghent University's Department of Information Technology, Faculty of Engineering and Architecture. His research focuses on wireless communication systems, IoT, energy-efficient networking, and millimeter-wave technologies. He leads projects in 5G/6G enablers, battery-less devices, and extended reality (XR) networking. Key contributions include energy-aware scheduling algorithms for industrial IoT, mmWave-based VR systems, and standardization efforts in nanoscale localization. His work spans over 200 publications across journals like IEEE Internet of Things Journal and conferences such as GLOBECOM. He collaborates extensively with industry partners, advancing practical applications of wireless technologies in smart cities and industrial automation. Current research emphasizes zero-energy devices and terahertz communication for future networks.

• Integrated Circuits
• Wireless Communication
• Signal Processing
• +۵ مورد دیگر

Tae Wook Kim is an academic researcher specializing in integrated circuits , wireless communication , and signal processing with a focus on CMOS technology and IR-UWB systems . His work bridges electrical engineering and biomedical applications , including brain-computer interfaces and mobile robotics. Key research areas : Integrated Circuits, Wireless Communication, Signal Processing, CMOS Technology, Biomedical Engineering Research Trends Recent publications highlight advancements in: Low-power UWB transceivers for brain-computer interfaces High-speed analog circuits with linearity improvements AI-driven radar systems for gesture recognition Time-domain signal processing for precision localization Notable Contributions Kim has co-authored foundational papers on: CMOS track-and-hold circuits (IEEE Access 2024) Volterra series analysis for distortion reduction (IEEE Access 2024) Passive IR-UWB localization for UAVs (IEEE Access 2023) Time-domain AI radar systems (IEEE J. Solid State Circuits 2020)

• Telecommunications
• Wireless Communication Systems
• Machine Learning
• +۵ مورد دیگر

Jianzhong Zhang is a researcher affiliated with Samsung Research America (Plano, TX, USA) , City University of Hong Kong (Department of Mathematics) , and Nankai University (College of Computer and Control Engineering) . His work focuses on 6G networks , machine learning applications in telecommunications , and advanced wireless technologies like THz/mmWave communication and beamforming . Recent publications highlight his contributions to Large Language Models (LLMs) for wireless network optimization , physics-inspired deep learning frameworks for channel state feedback, and ultra-wideband channel measurements for THz/FR3 bands. He also explores AI-driven CSI prediction , network slicing , and in-context learning for power control. His research integrates signal processing , channel modeling , and deep reinforcement learning to address challenges in next-generation wireless systems . Collaborative work includes joint phase-time arrays for frequency-dependent beamforming and end-to-end THz platform demonstrations .

Peng Chengمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Internet of Things (IoT)
• Wireless Communications
• +۵ مورد دیگر

Dr. Peng Cheng is a Senior Lecturer and PhD advisor in the Department of Computer Science and Information Technology at La Trobe University, Australia. He is also an Honorary Senior Lecturer at the University of Sydney. His research focuses on AI-driven IoT, wireless communications, and edge computing. He leads the Cisco-LTU Research Centre for AI and IoT and has secured over $1.3M in ARC grants. Notable contributions include pioneering 'wireless AI' research and developing graph-based deep reinforcement learning algorithms for dynamic resource allocation in 6G networks. His work bridges IoT with AI, addressing challenges in edge computing, network optimization, and sensing technologies. Current projects involve WiFi sensing for healthcare, satellite communications, and energy-efficient 5G/6G systems. Education: PhD in Communication and Information Systems from Shanghai Jiao Tong University. Prior roles include Postdoctoral Research Scientist at CSIRO (2014–2017) and ARC DECRA Fellow at the University of Sydney (2017–2020). Awards: ARC DECRA Fellowship (2020–2022) Teaching: Machine Learning, Data Communications, and Satellite Communications Labs: Cisco-LTU AIoT Centre, US-Cisco Collaboration Network

Vishnu Dutt Sharmaمشاهده پروفایل

پژوهشگر

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

Vishnu Dutt Sharma is a Robotics and Visual Computing Researcher at Nokia Bell Labs . His work focuses on robot perception, planning, and deep learning applications in autonomous systems. He holds a PhD in Robotics from the University of Maryland, College Park , advised by Dr. Pratap Tokekar, and earned his MTech and BTech in Electronics and Electrical Communication Engineering from IIT Kharagpur in 2017, with a minor in Computer Science. His research interests span reinforcement learning, computer vision, and interpretable AI, particularly in robotics and natural language processing. Before his PhD, he worked at American Express India on credit risk management using machine learning. He has interned at Nokia Bell Labs, Comcast, and FlytBase Labs. He received the Kulkarni Foundation Summer Research Fellowship in 2020 for his work at UMD. Key contributions include advancements in robot navigation, next-best-view planning, and generative communication in embodied agents. His interdisciplinary work bridges robotics, computer vision, and NLP, with applications in healthcare, autonomous systems, and security.

• 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.