جست‌وجوی استاد و پژوهشگر

Griffiths G. Atunguluمشاهده پروفایل

دانشیار

• Grain Processing
• Post-Harvest Systems Engineering
• Food Safety
• +۷ مورد دیگر

Griffiths G. Atungulu is an Associate Professor in the Department of Food Science at the University of Arkansas, where he also serves as the Director of the University of Arkansas Rice Processing Program. His work bridges grain processing, post-harvest systems engineering, and food safety, with a strong emphasis on innovative technologies like infrared and microwave drying. He is actively involved in research, teaching, and outreach, contributing significantly to advancements in rice quality, safety, and processing efficiency. Doctor of Philosophy, Agricultural Engineering, Iwate University, Japan Masters of Science, Agricultural Engineering, Iwate University, Japan Bachelor of Science, Agricultural Engineering, Jomo Kenyatta University of Agriculture and Technology, Kenya Dr. Atungulu’s research focuses on engineering solutions for grain and rice processing, particularly in drying, storage, aeration, and mycotoxin mitigation. His interests include infrared heating , microwave drying , automated quality monitoring , and post-harvest system optimization . He applies lab and field experiments, mathematical modeling, and simulation tools to improve food safety and processing efficiency across the food, feed, and pet food industries. His teaching includes Advanced Food Engineering, Cereal Science, and Alternatives to Conventional Food Processing. The most recent publications highlight a strong trend in microwave and infrared drying technologies , moisture and quality monitoring , and mycotoxin control in grains . His work spans from fundamental studies on rice microstructure and protein functionality to applied engineering of drying systems and storage technologies. The interdisciplinary nature of his research integrates food physics, agricultural engineering, and food safety. Associate Editor, Transactions of ASABE Associate Editor, Applied Engineering in Agriculture Associate Editor, Cereal Chemistry Journal, AACCI Dr. Atungulu has advised numerous graduate students, particularly in drying and storage technologies, and has secured significant research funding to support his program. His grants often focus on improving the efficiency and safety of grain processing systems. He leads a multidisciplinary research team working on both fundamental and applied aspects of food engineering. His outreach includes extension publications and collaborations with industry stakeholders to implement new technologies on farms and in processing facilities. He directs the University of Arkansas Rice Processing Program, overseeing a research, teaching, and outreach initiative focused on advancing rice processing technologies. His team conducts experiments in controlled environments and in the field, utilizing advanced instrumentation and modeling software to develop scalable solutions for the agricultural sector.

Jean-Yves Le Boudecمشاهده پروفایل

استاد

• Network Calculus
• Time-Sensitive Networking
• Deterministic Networking
• +۷ مورد دیگر

Jean-Yves Le Boudec is a Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences and the Institute of Electrical Engineering. He has been a key figure in advancing the theory and application of network calculus and deterministic networking, contributing significantly to standards such as IEEE Time-Sensitive Networking (TSN) and IETF DetNet. His research focuses on network calculus , time-sensitive and deterministic networking , traffic regulation , worst-case delay analysis , and cyber-physical systems , with cross-cutting applications in smart grids , real-time communication , and network security . He has co-authored foundational texts on network calculus and developed theoretical frameworks for traffic regulators, service curves, and delay bounds in complex networked systems. The recent publications highlight a strong trend in analyzing and improving performance guarantees in deterministic networks, including scheduling mechanisms like Deficit Round-Robin and Cyclic Queuing and Forwarding, traffic shaping via interleaved regulators, and security against time-synchronization attacks in power systems. The work spans theoretical modeling using stochastic and min-plus/max-plus algebra, practical algorithm design, and application to critical infrastructure. IEEE Fellow Le Boudec has advised numerous researchers and PhD students, including Ehsan Mohammadpour, Ludovic Thomas, and Seyed Mohammadhossein Tabatabaee. His collaborative projects often involve grants related to European and Swiss research initiatives in networking and smart grid technologies. He leads a research group focused on networked systems at EPFL, contributing to both theoretical advances and real-world implementations in industrial and energy-critical networks. His lab work centers on modeling and verification of time-sensitive network behaviors, integrating formal methods with practical experimentation. The team investigates regulators, shapers, and synchronization mechanisms, aiming to ensure robustness, predictability, and security in next-generation communication infrastructures. Future work continues to explore the interplay between communication, control, and energy systems in highly reliable environments.

Anestis Terzisمشاهده پروفایل

استاد

• Digital System Design
• FPGA Technology
• Camera Monitor Systems
• +۶ مورد دیگر

Professor Anestis Terzis serves as a Professor of Digital Systems Design and Head of the Institute for Communication Technology (IKT) at Technische Hochschule Ulm within the Faculty of Electrical Engineering and Information Technology. He coordinates the International Electrical Engineering Program and is responsible for the Vehicle Systems specialization. His office is located in Room W2405 at Albert-Einstein-Allee 53-55, 89081 Ulm, Germany. Professor Terzis specializes in digital system design with focus on FPGA, VHDL, and high-level design methodologies. His research spans Camera Monitor Systems (CMS) for automotive mirror replacement, advanced camera-based driver assistance systems, vehicle electronics, digitalization in laboratory didactics, and autonomous driving technologies. He has pioneered work in digital mirror systems compliant with ISO 16505 standards and has contributed significantly to image processing for automotive applications. His publication record demonstrates consistent contributions to automotive imaging technology, with recent work focusing on image compression impacts on detection quality, CMS image quality parameters, and programmable processing for autonomous vehicles. Professor Terzis has edited the comprehensive Handbook of Camera Monitor Systems published by Springer, establishing himself as a leading authority in this specialized field. As Head of the Institute for Communication Technology, he leads research initiatives connecting digital systems design with automotive applications. He also serves as Coordinator for the Study with In-depth Practice program and is a member of the Institute for Vehicle System Technology (IFS), demonstrating his commitment to both theoretical advancement and practical implementation in automotive electronics.

Elvino Silveira Sousaمشاهده پروفایل

استاد

• Wireless Communication
• Telecommunications
• Network Architecture
• +۵ مورد دیگر

Elvino Silveira Sousa is a Professor at the University of Toronto's Department of Electrical and Computer Engineering, holding the Jeffrey Skoll Chair in Computer Networks and Innovation. His career spans over 30 years in wireless communication research. Education: PhD in Electrical Engineering (University of Southern California, 1985) Key Affiliations: Wireless Lab (Founder/Director), IEEE Fellow Research Interests focus on advanced wireless systems including: Autonomous infrastructure wireless networks Cognitive radio and spectrum management 5G/Next-generation cellular architecture Smart antenna and software radio systems Scientific Contributions include: Over 150 peer-reviewed publications Foundational work in transmitter diversity (IEEE Fellow citation) Chair roles at PIMRC 95, Globecom '99, PIMRC 2011, WPMC2010 Awards & Recognition: IEEE Fellow (2000) Queen Elizabeth II Golden Jubilee Medal (2002) IEEE TCPC Recognition Award (2002) New Pioneers Science Award (2003)

P. P. Vaidyanathanمشاهده پروفایل

استاد

• Digital Signal Processing
• Sparse Sensor Arrays
• Network Signal Processing
• +۸ مورد دیگر

P. P. Vaidyanathan is the Kiyo and Eiko Tomiyasu Professor of Electrical Engineering at the California Institute of Technology , where he has served since 1983. His career spans over four decades with appointments as Assistant Professor (1983-88), Associate Professor (1988-93), Professor (1993-2018), and Tomiyasu Professor (2018-present). He has also held administrative roles as Executive Officer (2002-05). B.Sc., University of Calcutta (1974) B.Tech. (1977) and M.Tech. (1979) in Radiophysics & Electronics Ph.D., University of California, Santa Barbara (1982) Dr. Vaidyanathan's research focuses on Digital Signal Processing with emphasis on sparse sampling, network signal processing, number-theoretic signal processing, and applications in communications, radar, genomics, and multirate systems. His work on sparse arrays, coarray theory, and Ramanujan subspace signals has transformed direction-of-arrival estimation and genomic signal analysis. Key trends in his 2023-2024 publications include: Optimization of sparse arrays for mutual coupling reduction Advancements in mmWave MIMO channel estimation Mathematical foundations of beamspace methods Applications of number theory in signal processing Scientific recognition includes: IEEE Jack S. Kilby Signal Processing Medal IEEE Gustav Robert Kirchhoff Award EURASIP Athanasios Papoulis Award Membership in U.S. National Academy of Engineering and Indian National Academy of Engineering His academic legacy extends through 30+ PhD graduates including Tsuhan Chen (1993), Truong Nguyen (1989), and recent advisees Pranav Kulkarni (2025) and Po-Chih Chen (2024). His textbooks like Multirate Systems and Filter Banks and Signals, Systems, and Signal Processing (2024) remain foundational references in the field.

Lie-Liang Yangمشاهده پروفایل

استاد

• Wireless Communications
• Wireless Networks
• Signal Processing for Wireless Communications
• +۲ مورد دیگر

Lie-Liang Yang is a Professor of Wireless Communications at the University of Southampton's School of Electronics and Computer Science. With a career spanning over two decades at the institution, he has held roles from Postdoctoral Fellow to his current professorship. His research focuses on wireless communications, networks, signal processing, and emerging areas like molecular and nano communications. BEng (Shanghai Tiedao University, 1988) MEng (Beijing Jiaotong University, 1991) PhD (Beijing Jiaotong University, 1997) Postgraduate Certificate in Education (University of Southampton, 2005) His work spans advanced modulation techniques (e.g., OTFS, index modulation), reconfigurable intelligent surfaces, terahertz communication, and integrated sensing-communication systems. Recent publications emphasize next-generation wireless technologies, including 5G/6G, mmWave systems, and orbital angular momentum applications. Active projects include Beyond The Generations and Pervasive Wireless Intelligence , sponsored by EPSRC and Huawei. He has also contributed to editorial roles in IEEE Transactions on Vehicular Technology , IEEE Access , and special issues for IEEE Journal on Selected Areas in Communications and others. Scientific accolades: Fellow of the IEEE (USA) Fellow of the IET (UK) IEEE Vehicular Technology Society Distinguished Lecturer He supervises multiple PhD students in the School of Electronics and Computer Science, including Yi Zhao , Hugo Zakaria Jose Hawkins , and Zhou Lu . His research group integrates wireless communications with interdisciplinary applications in nanotechnology and machine-type communications.

Ramy H. Goharyمشاهده پروفایل

استادیار

• Machine-to-machine communications
• Internet-of-Things (IoT)
• MIMO wireless communication systems
• +۹ مورد دیگر

Ramy H. Gohary is an Assistant Professor in the Department of Systems and Computer Engineering at Carleton University. His research focuses on advanced wireless communication systems, including machine-to-machine communications, Internet-of-Things (IoT), MIMO systems, convex optimization, differential geometry applications in signal processing, and information-theoretic aspects of multiuser systems. Principal Investigator for Ericsson-Carleton Strategic Partnership projects on 5G+ wireless networks Research emphasizes fairness, cross-layer design, cooperative communications, and jamming-resistant detection techniques His recent work explores direction-of-arrival estimation, non-coherent communication in jamming environments, and distributed MIMO architectures. Publications highlight applications of differential geometry, optimization techniques, and sparse signal recovery in modern wireless systems. He actively contributes to advancements in channel modeling, beamforming, and energy-efficient network design.

Hao Yeمشاهده پروفایل

استادیار

• Machine Learning
• Wireless Communications
• AI Applications
• +۴ مورد دیگر

Hao Ye is an Assistant Professor in Electrical and Computer Engineering at the University of California, Santa Cruz (UCSC). Previously, he worked as a Machine Learning Researcher at Qualcomm AI Research before transitioning to academia. His research focuses on integrating machine learning methodology into communication networks, particularly for applications involving edge devices such as autonomous vehicles. PhD in Electrical and Computer Engineering, Georgia Institute of Technology His research interests center on wireless communications, AI-driven network optimization, and signal processing for vehicular networks. He explores deep learning applications in channel estimation, resource allocation, and end-to-end communication systems, emphasizing adaptability in unreliable environments. Key trends in his publications include: Advancing Massive MIMO systems with data-driven approaches Developing graph neural networks for wireless resource management Integrating reinforcement learning into vehicular network spectrum sharing Proposing pilot-free end-to-end communication frameworks using deep learning Investigating federated learning in decentralized wireless architectures Applying meta-learning to networked AI systems Scientific contributions include being invited as an Editor for IEEE Transactions on Wireless Communications in 2024. He actively mentors PhD students and collaborates with researchers like Le Liang, Geoffrey Ye Li, and Shi Jin. Recent team announcements include welcoming Jing Qiao in September 2024, reflecting ongoing growth in his research group focused on machine learning and wireless systems.

• Internet of Things (IoT)
• Structural Health Monitoring (SHM)
• Microwave Imaging
• +۵ مورد دیگر

Igor Bisio is a Full Professor at the Department of Naval, Electrical, Electronics, and Telecommunications Engineering (DITEN) at Università di Genova. His research focuses on IoT-driven structural health monitoring, microwave imaging for biomedical applications, and wireless surveillance systems. Teaches courses on telecommunications, IoT, and machine learning Pioneers low-cost IoT solutions for SHM and post-stroke rehabilitation Develops microwave tomography techniques for pediatric stroke diagnostics Advances privacy-preserving Wi-Fi-based crowd monitoring Recent research trends include edge AI integration, compressive sensing for vibration analysis, and multi-class object tracking in aerial scenes. He also explores UAV-based monitoring systems, WiFi fingerprinting for localization, and Banach space inversion models for electromagnetic imaging. His work spans interdisciplinary domains combining electrical engineering, biomedical applications, and wireless network security.

Xiaoyan Hongمشاهده پروفایل

دانشیار

• Distributed Systems
• Internet of Things (IoT)
• Wireless Communications
• +۴ مورد دیگر

Dr. Xiaoyan Hong is an Associate Professor in the Department of Computer Science at The University of Alabama's College of Engineering. Her research focuses on mobile/wireless networks, vehicular networks, and delay-tolerant systems. Ph.D., Computer Science, University of California-Los Angeles (2003) M.S., Computer Science, Zhejiang University (2000) Research spans Internet of Things (IoT) , Connected Vehicles , and Underwater Wireless Networks . Key projects include NSF-funded underwater robot communication infrastructure and smart traffic light systems. Recent work explores Named Data Networking (NDN) in vehicular environments, Task Synchronization for autonomous vehicles, and V2I Communication for traffic optimization. NSF Research Experience for Undergraduates (REU) grant recipient $1.5M NSF grant for underwater robotics networking Her research integrates with multiple engineering centers, including the Center for Advanced Vehicle Technologies and Center for Transportation Operations .

Stephan Preihsمشاهده پروفایل

پژوهشگر

• Acoustics
• Digital Signal Processing
• Audio Coding
• +۶ مورد دیگر

Stephan Preihs is a postdoctoral researcher and group leader at the Institute of Communications Technology of the Leibniz University Hannover , with a focus on acoustics, digital signal processing, and immersive audio systems. He received his Dipl.-Ing. in electrical engineering (communications engineering) from the same university in 2010 and his Dr.-Ing. in 2016. Education: Dipl.-Ing., Electrical Engineering (Communications Engineering), Leibniz University Hannover (2010) Dr.-Ing., Leibniz University Hannover (2016) Research Interests: Acoustics for immersive audio reproduction Digital signal processing and audio coding Signal detection/classification Psychoacoustic models Audio transmission for PMSE Recent Article Trends: Deep learning in sound source localization Wind turbine noise analysis via immersive audio Advancements in headphone technology Immersion prediction in spatial audio Low-latency communication protocols Scientific Awards: Best Paper Award at IEEE International Workshop on Networked Immersive Audio (2024) AES Show 2024 Best Technical Paper Award AES Spring 2021 Student Paper Award AES Poster Award 2019 AES Convention Student Paper Award 2019 Teaching: Lecturer for '3D Audio - Fundamentals of Spatial Reproduction Systems' Lecturer for 'Applications of Digital Audio Signal Processing' Coordinator of student laboratories in 'Audio Communication and Acoustics' and 'Transmission Technology'

Xiaojun Caoمشاهده پروفایل

استاد

• Optical Networks
• Wireless Networks
• Network Security
• +۳ مورد دیگر

Dr. Xiaojun Cao is a faculty member at the Andrew Young School of Policy Studies, Georgia State University, specializing in optical and wireless network architectures, protocols, and security. His research addresses challenges in bandwidth scalability, network survivability, and future Internet design through innovations in multi-granular switching, traffic grooming, and cross-layer interactions. B.S., Engineering Physics, Tsinghua University, 1996 M.S., Electrical Engineering, Chinese Academy of Sciences, 1999 Ph.D., Computer Science and Engineering, State University of New York at Buffalo, 2004 His work spans three core areas: Optical Network Optimization : Developing waveband switching frameworks for backbone networks, focusing on multi-layer architectures and performance evaluation. Network Survivability : Designing proactive and reactive strategies for protection and restoration in optical and wireless systems. Edge Network Security : Advancing secure service function chain deployment in multi-vendor and zero-trust environments. Recent research trends highlight his leadership in Network Functions Virtualization (NFV) , Edge Computing , and AI-Driven Networking , with publications on blockchain-based federated learning, prompt chain deployment, and asymmetric protection mechanisms. His work bridges theoretical rigor with practical applications in 5G/6G, UAV networks, and smart infrastructure. Dr. Cao leads a research group exploring optical-wireless convergence and has contributed to foundational studies in network virtualization and traffic management.

Konstantinos Kantelisمشاهده پروفایل

استادیار

• Biological Nanonetworks
• Electromagnetic Nanogrids
• Hybrid Nanonetworks
• +۵ مورد دیگر

Konstantinos Kantelis is an Assistant Professor at the Department of Informatics, Aristotle University of Thessaloniki, specializing in Biological Nanonetworks. He holds a PhD in Nanonetworks and has extensive professional experience as a Software Engineer/Manager at Piraeus Bank (2007-2023), preceded by system administration roles at Marfin-Egnatia Bank (2007-2014). Education: PhD in Nanonetworks (2018), Department of Informatics, Aristotle University of Thessaloniki MSc in Nanotechnology and Nanosciences (2012), Department of Physics, Aristotle University of Thessaloniki MSc in Computer Systems Technology (2006), Department of Informatics and Telecommunications, National University of Athens BSc in Mathematics (2003), Department of Mathematics, Aristotle University of Thessaloniki His research focuses on Biological Nanonetworks, Electromagnetic Nanogrids, and energy-efficient wireless communication protocols for IoT systems. He has contributed to projects like Maestro, IntelTriage, and AYGEIAS, developing protocols for LoRaWAN networks and WDM backbone resilience. Recent publications address spatial scheduling in LoRaWAN, earthquake-tolerant routing, and reinforcement learning-assisted protocols. His work bridges nanoscale communication theory with practical IoT implementations, emphasizing energy efficiency and reliability. As an educator, he teaches graduate courses in Communication Networks, Advanced Topics in Biological Nanonetworks, and Applied Mathematics, alongside postgraduate courses in Networks and Internet (2019-2021).

• Internet of Things
• Smart Cities
• Wireless Networks
• +۴ مورد دیگر

Dr. Yuguang 'Michael' Fang is a globally recognized academic in Electrical and Computer Engineering, currently serving as Chair Professor of Internet of Things at the Department of Computer Science, City University of Hong Kong, since August 2022. Previously, he held positions at the University of Florida, where he advanced from Assistant Professor (2000) to Professor (2005) and Distinguished Professor (2019), and earlier at New Jersey Institute of Technology as an Assistant Professor (1998-2000). Education MS in Mathematics, Qufu Normal University, China (1987) PhD in Systems, Control, and Industrial Engineering, Case Western Reserve University (1994) PhD in Electrical and Computer Systems, Boston University (1997) His research focuses on Internet of Things (IoT) , Smart Cities , and Wireless Networks , with applications in Cyber-Physical Systems , Vehicular Networking , and Communication Systems . His work explores transforming urban environments through interconnected devices and leveraging vehicles as dynamic nodes in resource networks. Dr. Fang has received prestigious awards including the NSF CAREER Award (2001), ONR Young Investigator Award (2002), and multiple IEEE Technical Achievement Awards. He has held significant editorial roles, serving as Editor-in-Chief of IEEE Transactions on Vehicular Technology (2013-2017) and IEEE Wireless Communications (2009-2012), and currently contributes to Proceedings of the IEEE and ACM Computing Surveys . He has also held visiting professorships, including Changjiang Scholar Chair Professor (2008-2011) at Tsinghua University and National Taiwan University's NSC Visiting Researcher (2007-2008). Dr. Fang is an ACM Fellow, IEEE Fellow, and AAAS Fellow, underscoring his sustained contributions to academia.

Ayush Bhartiمشاهده پروفایل

پژوهشگر ارشد

• Probabilistic Machine Learning
• Bayesian Statistics
• Simulation-based Inference
• +۳ مورد دیگر

Ayush Bharti is an Academy Research Fellow (Research Fellow) in the Department of Computer Science at Aalto University, Finland. His primary affiliations include the Probabilistic Machine Learning research group and the Academy Professorship led by Samuel Kaski . His research centers on probabilistic machine learning with dual focus areas: advancing simulation-based inference methodologies and applying statistical techniques to stochastic radio channel modeling. Key interests include Bayesian statistics, robustness under model misspecification, handling missing data, and developing efficient approximate Bayesian computation frameworks. His work bridges theoretical machine learning with practical wireless communication challenges. Analysis of his 15 most recent publications (2021-2025) reveals a consistent trajectory in simulation-based inference innovation, featuring neural processes, diffusion models, and multilevel architectures. Approximately 60% of his work targets general statistical challenges (e.g., robustness, cost-awareness), while 40% addresses radio channel modeling applications. Notable trends include integration of domain expertise in inference loops and development of context-aware optimization techniques. No information is available regarding student supervision or research grants. Bharti operates within Aalto University's Probabilistic Machine Learning ecosystem, contributing to the Academy Professorship project under Samuel Kaski. This collaborative environment focuses on developing scalable inference algorithms for complex real-world systems, with particular emphasis on uncertainty quantification in simulation-driven scientific discovery.