Find Academic Supervisors

• Wireless Communications
• IoT
• Machine Learning
• +7 more

Professor Yonghui Li is a faculty member at the University of Sydney, holding the position of Professor and Director of the Wireless Engineering Laboratory within the School of Electrical and Information Engineering. His research focuses on cutting-edge areas such as wireless communications, IoT, 5G/6G networks, machine learning, and signal processing. He has authored over 400 publications, including a book on full-duplex communications, and secured over $8 million in competitive research funding. Notably, he was awarded the Australian Research Council (ARC) Future Fellowship (2012) and IEEE Fellow (2015). Education: PhD in Telecommunications (2002) Roles: Editor for IEEE Transactions on Communications, Specialty Chief Editor of Frontiers Signal Processing Journal Key Projects: Multi-gigabit mm-wave cellular networks, machine learning for wireless spectrum management, 5G ultra-reliable low-latency systems His research has led to high-impact outcomes, including ISI high-cited papers and ESI Web of Science recognition. He also pioneered the IoT undergraduate program at the University of Sydney. Awards: IEEE Best Paper Awards (ICC 2014, PIMRC 2017), ARC Fellowships Grants: $500M national 'Smart Grid Smart City' project participation Current projects explore 3D beamforming, non-orthogonal multiple access, and physical-layer security in 5G systems. His work bridges theory and practice, with prototypes developed for mm-wave networks and AI-driven spectrum management.

Alessandro UgoliniView profile

Associate Professor

• Digital Communications
• Satellite Communications
• Wireless Communications
• +8 more

Alessandro Ugolini is an Associate Professor at the Department of Engineering and Architecture, University of Parma , Italy. His academic journey began with a Master’s (2012) and Ph.D. (2016) in Telecommunications Engineering from the University of Parma. Research Focus: Digital communications, satellite systems, underwater optical wireless, synchronization algorithms, and spectral efficiency. Key Labs: SPADiC Lab, University of Parma. Recent Research Trends include non-terrestrial networks, underwater optical communication, and waveform design for satellite links. His work bridges theoretical analysis (e.g., OTFS diversity, PLH code decoding) with practical implementations (e.g., LiDAR-based underwater systems). Scientific Awards: Best Paper Award, IEEE Wireless Communications and Networking Conference (WCNC 2019) Collaborations span institutions like the University of Luxembourg, Chalmers University of Technology, and agencies such as the European Space Agency (ESA-ESTEC). He has contributed to DVB-S2X optimization and interference exploitation in multibeam systems.

Armando VannucciView profile

Researcher

• Telecommunications
• Optical Communications
• Signal Processing
• +7 more

Armando Vannucci is a tenured Researcher in Telecommunications at the University of Parma's Department of Engineering and Architecture, where he has been active since 2002. His academic journey began with honors in Electronic Engineering from University of Rome La Sapienza in 1993, followed by a PhD in Information Technology from University of Parma in 1998. He progressed from Technical Collaborator (1998-1999) to Research Fellow (2000-2002) before securing his current position. His research spans multiple domains with evolving focus: starting with speech signal processing during his undergraduate studies, moving to radio transmissions for nonlinear channels during his PhD (resulting in two patents), shifting to fiber optic transmissions in the new millennium (focusing on PMD, nonlinear WDM propagation, and optical amplifiers), then to nonlinear polarization attraction, and most recently returning to digital receiver design using AI techniques like variational inference. His work has been conducted within various institutional, third-party, and European projects, with him serving as coordinator for some. Vannucci's recent publications (2022-2025) demonstrate continued research productivity, with significant contributions to expectation propagation algorithms for communication systems, satellite communications, and optical transmission systems. His work shows a clear transition from traditional optical communications toward integrating AI techniques into communication theory. Member of IEEE, OSA, and other scientific societies since 1995 Reviewer for major journals including IEEE PTL, T-COM, JLT, and OSA publications Expert evaluator for national (VQR) and international (FRS-FNRS) panels Visited Alcatel Labs (France), Université Laval (Canada), and Hochschule Karlsruhe (Germany) Administratively, Vannucci has served on the Department Council (2005-2010, 2017-2019), as elected member of the Board of Directors (2009-2012) and Academic Senate (2012-2016), and as DIA Director's Delegate for General and International Affairs (2017-2019). His teaching excellence is evidenced by consistent student evaluations above 90% (faculty average 75%).

Ahmed AlkhateebView profile

Associate Professor

• Wireless Communications
• Communication Theory
• Signal Processing
• +5 more

Ahmed Alkhateeb is an Associate Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His work bridges wireless communications, machine learning, and sensing technologies, with a focus on 6G networks and beyond. He leads the Wireless Intelligence Lab and has contributed to datasets like DeepSense 6G and DeepMIMO. Ph.D., Electrical Engineering, University of Texas-Austin (2016) M.S., Electrical Engineering, Cairo University (2012) B.S., Electrical Engineering (with distinction), Cairo University (2008) Research Interests: Machine learning for wireless communication Integration of sensing and communication for 6G Multi-modal sensing (LiDAR, radar, cameras) for channel optimization AI-based wireless sensing and perception Recent publications emphasize digital twin applications, robust beamforming, and real-world testing of reconfigurable intelligent surfaces (RIS), with a focus on sim-to-real transfer and hardware constraints. His work spans vehicular/drone networks, OTFS modulation, and terahertz communication. Scientific Awards: 2012 MCD Fellowship (University of Texas-Austin) 2016 IEEE Signal Processing Society Young Author Best Paper Award NSF CAREER Award (2021) His lab develops tools like DeepSense 6G and ViWi datasets, advancing AI-driven wireless system design. He explores decentralized interference management and cell-free MIMO architectures for next-gen networks.

Giulio ColavolpeView profile

Professor

• Digital Communications
• Signal Processing
• Information Theory
• +5 more

Giulio Colavolpe is a Full Professor of Telecommunications at the Department of Engineering and Architecture, University of Parma, Italy, where he coordinates the SPADiC (Signal Processing for Advanced Digital Communications) research group. He received his Laurea (cum laude) in Telecommunications Engineering from the University of Pisa in 1994 and his PhD in Information Technologies from the University of Parma in 1998. His academic career includes positions as Researcher (1999-2002), Associate Professor (2002-2016), and Full Professor (2016-present) at the University of Parma, with a visiting period at Institut Eurecom in France (2000). Professor Colavolpe's research focuses on digital communications systems, adaptive signal processing, iterative detection techniques for memory channels, channel coding, and information theory. His work has significant applications in satellite communications, optical systems, and wireless networks. He has coordinated numerous research projects funded by the European Space Agency, the Italian Ministry of Education, Universities and Research, and international telecommunications companies. His recent publications demonstrate expertise in OTFS modulation, phase noise channels, time-frequency packing, and non-terrestrial networks. His publication record includes two authoritative books ( Wireless Communications: Algorithmic Techniques and Detection Algorithms for Wireless Communications ), over 80 journal articles, more than 120 conference papers, and 21 industrial patents. His work on phase noise channels, time-frequency packing, and satellite communications has been particularly influential, with several papers evaluated as 'Excellent' in the Italian VQR assessment. Best paper award at SoftCOM'05 Best paper award for Optical Networks and Systems at ICC 2008 Best paper award at ASMS&SPSC 2010 Included in World's Top 2% Scientists by Stanford University Professor Colavolpe has served as an Editor for IEEE Transactions on Wireless Communications, IEEE Wireless Communications Letters, and IEEE Transactions on Communications. He has supervised 12 PhD students and over 100 Master's theses, and currently supervises one PhD student. His SPADiC research group maintains collaborations with leading institutions including USC, University of Michigan, CNIT, and Politecnico di Torino.

• Digital Communications
• Wireless Communications
• Satellite Communications
• +5 more

Amina Piemontese is an Associate Professor at the Department of Engineering and Architecture, University of Parma, Italy. She teaches courses in Communication Engineering across multiple programs including Master's Degree in Communication Engineering, Bachelor's Degree in Computer, Electronics and Telecommunications Engineering, and Management Engineering for academic years spanning from 2020/2021 through 2025/2026. Professor Piemontese's research focuses on advanced communication theory and signal processing with particular expertise in phase noise channels , non-terrestrial networks , and advanced modulation techniques . Her work bridges theoretical communication principles with practical implementations for next-generation wireless systems, especially in satellite communications and 5G/6G networks. She has made significant contributions to expectation propagation algorithms for channel detection and spiral constellation design for nonlinear channels, with numerous publications exploring these topics in depth. Analysis of Professor Piemontese's recent publications reveals a strong and evolving research trajectory focused on non-terrestrial networks and satellite communications for 6G applications. Her work increasingly explores OTFS modulation as a solution for multi-satellite systems and addresses critical challenges in spectrum sharing between terrestrial and satellite networks. A consistent thread throughout her research is the application of statistical signal processing techniques, particularly expectation propagation , to solve complex communication problems in challenging channel conditions where traditional approaches fail. Professor Piemontese serves as a reference teacher for the Master's Degree in Communication Engineering across multiple academic years and teaches specialized courses including Communication Fundamentals, Elements of Digital Communications, and Internet and Multimedia. While specific grant information isn't provided in the available text, her extensive research output suggests involvement in European or national research projects focused on next-generation wireless communications and satellite systems. Her work on unified software-defined radio frameworks for flexible waveform design indicates leadership in developing practical implementations for emerging communication standards.

• 6G Wireless Communication
• Intelligent Reflecting Surfaces (IRS)
• Information Theory
• +3 more

Dott. Mag. Lorenzo Zaniboni is a Doctoral Researcher at the Institute for Communications Engineering under the Chair of Communications Engineering led by Prof. Gerhard Kramer at the Technical University of Munich (TUM). His research focuses on 6G Wireless Communication models, particularly using Intelligent Reflecting Surfaces (IRS) and Information Theory. He holds a B.Sc. and M.Sc. in Communication Engineering from the University of Parma. Education: B.Sc. in Computer Science, Electronic And Communication Engineering, University of Parma (2018) M.Sc. in Communication Engineering, University of Parma (2020) Research Interests: Lorenzo explores cutting-edge topics in wireless communication systems, including IRS-aided communications, integrated sensing and communication (ISAC), and OTFS modulation. His work addresses challenges in multi-user scenarios and non-linear channel performance optimization. Teaching Contributions: Wireless Communication Laboratory (Summer 2022–2023) Wireless Communication (Winter 2022/23–current) Multi User Information Theory (Summer 2024–current) Awards: Research Fellow Scholarship from CNIT (2021) for work on 5G multicarrier modulation formats. Thesis Topics: Supervises and offers thesis opportunities in IRS-aided communications, ISAC, and wireless communication systems.

• Error Control Coding
• Information Theory
• 6G Wireless Networks
• +4 more

Chentao Yue is a Research Fellow at the School of Electrical and Computer Engineering, University of Sydney. He holds a BSc in Information Engineering (Honors) from Southeast University (2017) and a PhD in Electrical Engineering from the University of Sydney (2021). His research focuses on developing foundational theories and AI-driven techniques for 6G wireless networks, specifically targeting ultra-reliable low-latency communication through advanced error control coding. Research Interests: Dr. Yue's work bridges information theory, machine learning, and telecommunications. Key areas include intelligent channel coding/decoding for 6G, sparse vector transmission, NOMA systems, and distributed consensus protocols. His DECRA-funded project aims to create self-configurable coding frameworks adaptable to dynamic 6G environments. Publication Trends: Recent articles emphasize optimizing short block-length codes for 6G URLLC, integrating Bayesian neural networks with modulation techniques, and refining ordered-statistics decoding (OSD) algorithms. Machine learning applications in signal prediction and distributed ledger technologies are emerging themes. Awards: ARC Discovery Early Career Researcher Award (DECRA, 2024) Postgraduate Scholarship in Wireless Engineering Grants: Leads the ARC DECRA project (2024): "Intelligent self-configurable coding and decoding for 6G wireless networks," focusing on real-time adaptive error correction for industrial automation and telemedicine.

Steven BlosteinView profile

Professor

• Wireless Communications
• 5G and Beyond Networks
• MIMO Systems
• +5 more

Steven D. Blostein is a Professor in the Department of Electrical and Computer Engineering at Queen's University, affiliated with Smith School of Engineering. He holds a Ph.D. from the University of Illinois (1988) and has been a faculty member since 1988. His research focuses on wireless communications, including 5G, massive MIMO, and network coding. He has extensive experience in cooperative communications, synchronization, and multi-user beamforming. Education: Ph.D. in Electrical and Computer Engineering (1988), University of Illinois M.Sc. in Electrical and Computer Engineering (1985), University of Illinois B.Sc. in Electrical Engineering (1983), Cornell University Research Interests: Signal processing for wireless systems, 5G networks, MIMO systems, sensor networks, and machine learning applications in communications. His work emphasizes energy efficiency, network protocols, and decentralized detection in sensor networks. Professional Affiliations: Professional Engineer, Professional Engineers Ontario Senior Member, IEEE Advising and Grants: Supervised nearly 50 students (Ph.D., M.Sc., postdocs) and led projects on 4G/5G systems funded by Canadian and international bodies. Administered grants from NSERC and industry partnerships. Labs/Teams: Active in Queen's research groups focused on communications, signal processing, and network science. Collaborates with institutions like the Australian National University and Communications Research Centre.

• Artificial Intelligence
• 6G Communications
• Integrated Sensing and Communication
• +2 more

Qingqing Cheng is a Lecturer at QUT's School of Electrical Engineering and Robotics and recipient of the 2025 ARC DECRA award. Her research focuses on AI applications in next-generation communication systems. Education includes: Doctor of Philosophy, University of Technology Sydney (2020) Research explores integrated sensing-communication systems for 6G networks, V2X systems, and advanced wireless technologies using machine learning approaches. Her DECRA project develops intelligent sensing solutions for vehicular networks. Publications demonstrate advancements in signal detection, channel estimation, and wireless system optimization using deep learning techniques. Honors include Best Paper Award at IEEE Globecom 2023 and editorial roles for IEEE Transactions on Mobile Computing.

Simon CottonView profile

Professor

• Wireless Communication
• Electrical Engineering
• Computer Science
• +3 more

Simon Cotton is a Professor at Queen's University Belfast, affiliated with the School of Electronics, Electrical Engineering and Computer Science and the Wireless Communication Systems Institute. His research focuses on advanced wireless communication systems, including 5G/6G networks, reconfigurable intelligent surfaces (RIS), and millimeter-wave technologies. He has led major projects such as the Future Communications Hub in All-Spectrum Connectivity and contributed to initiatives like the UK Telecoms Innovation Network (UKTIN). His work encompasses channel modeling, antenna design, and machine learning applications in wireless networks. Key awards include the Harold A. Wheeler Prize Paper Award and Philip Leverhulme Prize, reflecting his impactful contributions to the field. He has been actively involved in national committees, such as the Wireless 2030 Report for the UK Government and DCMS 6G Consultation. His research has been widely disseminated through conferences and media, including BBC features on 5G and future wireless technologies. Recent projects span topics like secure wireless systems, energy-efficient MIMO architectures, and AI-driven network optimization. Collaborative work with institutions like the University of Oxford and Strathclyde highlights his role in advancing cross-disciplinary research in next-generation communication networks.

• Antennas and Propagation
• 5G/6G Communications
• Integrated Sensing and Communications (ISAC)
• +6 more

Distinguished Professor Yingjie Jay Guo is a leading academic at the University of Technology Sydney (UTS), holding positions as Professor and Director of multiple research centers including the Global Big Data Technologies Centre and the NSW Connectivity Innovation Network (CIN). His expertise spans antennas and propagation, 5G/6G communications, and integrated sensing and communications (ISAC). He has authored over 700 publications, including 350+ IEEE journal papers and six books, and holds 27 international patents. His research focuses on reconfigurable antennas, hybrid arrays, and environmental sensing using 5G/6G networks. Education: PhD (Antennas and Electromagnetics) from Xi'an Jiaotong University (1984–1987), BEng/MEng (Microwave Engineering) from Xidian University (1977–1984). Leadership Roles: Chair of ISAP International Steering Committee (2020–2021), Guest Editor for IEEE Transactions on Antennas and Propagation, and Member of Standards Australia IoT Committee. Research Contributions: Pioneered hybrid antenna arrays, base station antennas, and the Generalized Joined Coupler (GJC) matrix theory, earning the IEEE Schelkunoff Prize Paper Award (2023). His recent work includes environmental sensing projects with NSW governments to mitigate flood risks, leveraging 5G/6G networks. He has led over 30 best paper awards and is a Fellow of the Australian Academy of Engineering, Royal Society of NSW, and IEEE. Current projects include multibeam antenna systems, in-band full-duplex communications, and AI-driven metasurface design. Key Grants: NSW Smart Flood Sensing Initiative, TPG Telecom collaborations, and ARC Discovery Projects. Students: Supervised numerous PhD/MSc students in antenna design, sensing, and wireless systems. Labs: Director of TPG-UTS Network Sensing Lab and founder of GBDTC and NSW CIN.

• Wireless Communications
• 5G/6G Systems
• Signal Processing
• +5 more

H. Shaiek is a Professor at Conservatoire national des arts et métiers (CNAM Paris), affiliated with the CÉDRI Laboratory within the École d'ingénieurs. His research focuses on wireless communications, particularly 5G/6G systems, signal processing techniques, and power amplifier linearization. He completed his Habilitation à diriger des recherches (HDR) in 2022 with the thesis 'Multi-carrier waveforms for 5G and beyond systems: from power amplifier impairments to energy efficiency enhancement,' demonstrating his senior academic status in the French system. Shaiek's research interests center around wireless communications technologies, with particular expertise in power amplifier linearization, PAPR (Peak-to-Average Power Ratio) reduction techniques, FBMC-OQAM systems, and RIS (Reconfigurable Intelligent Surface) assisted communications. His work bridges theoretical signal processing with practical implementation challenges in next-generation wireless systems. Recent research has increasingly incorporated machine learning approaches for channel equalization and power amplifier post-distortion. Analysis of his publication trends from 2021-2025 reveals a clear evolution toward 6G technologies, with growing emphasis on RIS-assisted communications, cell-free MIMO architectures, and hybrid OTFS-OFDM frameworks. His work consistently addresses the practical implementation challenges of theoretical wireless concepts, particularly concerning power efficiency and hardware constraints in broadcasting and mobile systems. As an HDR holder, Shaiek supervises doctoral research and contributes to major research projects like ANR POSEIDON. His laboratory work within CÉDRI focuses on electronics and signal processing, collaborating with institutions like CEA LETI. He has developed experimental testbeds for post-OFDM waveforms and contributed to standardization efforts in next-generation broadcasting systems (DVB-T2, ATSC 3.0).

Hovannes KulhandjianView profile

Associate Professor

• Wireless Communications
• Applied Machine Learning
• Intelligent Transportation Systems
• +8 more

Hovannes Kulhandjian is an Associate Professor in the Department of Electrical and Computer Engineering at California State University, Fresno (Fresno State), within the Lyles College of Engineering. He teaches undergraduate and graduate courses in electrical and computer engineering and conducts research in wireless communications, applied machine learning, and their applications in transportation and agriculture. His educational background includes: Ph.D. in Electrical Engineering from the State University of New York at Buffalo (2014) M.S. in Electrical Engineering from the State University of New York at Buffalo (2010) B.S. in Electronics Engineering with high honors (magna cum laude) from the American University in Cairo (2008) Dr. Kulhandjian's research spans wireless communications, applied machine learning, and their applications. His work in intelligent transportation systems includes AI-based road inspection and pedestrian detection, while in precision agriculture, he develops drone-based systems for weed detection and tree health monitoring. He also explores underwater acoustic communications, visible light communications, and physical layer security. His recent publications demonstrate a strong trend in applying artificial intelligence to solve real-world problems in transportation and agriculture, often using drones and multi-sensor fusion. In communications, he advances techniques for next-generation wireless systems, including OTFS and NOMA for 6G, and optical wireless for IoT. Scientific awards and honors: IEEE Senior Member Outstanding Reviewer Award from ELSEVIER Ad Hoc Networks Outstanding Reviewer Award from ELSEVIER Computer Networks Claude C. Laval Award for Innovative Technology and Research Dr. Kulhandjian advises Master's students through thesis (ECE 299) and project (ECE 298) courses. His research is supported by multiple grants, including the Department of Defense Research and Education Program, NSF-ADVANCE Research Alliance Seed Grant, CSU-WATER Faculty Research Incentive, and the Fresno State Transportation Institute SB1 Research Grant for six consecutive years. During his doctoral studies, he worked in the Wireless Networks and Embedded Systems (WiNES) Laboratory at SUNY Buffalo. At Fresno State, he leads a research group focused on the development of innovative solutions in wireless communications and AI applications, collaborating with various institutions and industry partners.

• Wireless Positioning
• GNSS Algorithms
• Wearable Computing
• +7 more

Prof. Simona Lohan is a Full Professor at the Electrical Engineering unit of Tampere University, Finland, and a visiting professor at Universitat Autònoma de Barcelona. Her research focuses on wireless positioning, GNSS algorithms, and wearable computing, with an emphasis on privacy-aware localization and interference mitigation. She leads the Signal Processing for Wireless Positioning research group and coordinates the H2020 MSCA European Joint Doctorate A-WEAR (2019-2023). She holds a PhD in Telecommunications from Tampere University of Technology (2003), and has authored/co-authored over 250 peer-reviewed publications. Education background includes an MSc in Electrical Engineering from Polytechnics University of Bucharest (1997), a DEA in Econometrics from École Polytechnique, Paris (1998). Her research spans satellite navigation (Galileo/GPS/GLONASS), UMTS/WCDMA positioning, 5G positioning, IoT localization, and medical applications of positioning systems. She is an associate editor for the RIN Journal of Navigation and IET Journal on Radar, Sonar, and Navigation . Key projects include the H2020 A-WEAR project (wearable health tech), Academy of Finland ULTRA (2020-2022), and SJU GATEMAN (2018-2019). Her work addresses global navigation challenges through LEO-PNT constellations, low-cost positioning solutions for Africa, and fusion of 5G/mmWave radar for airport surveillance. She has pioneered datasets like TUJI1 for indoor localization and developed open-source tools like SyDR for GNSS algorithm benchmarking. Her research themes include: LEO satellite-based positioning systems Anti-spoofing techniques for GNSS RF fingerprinting for device identification Privacy-preserving localization algorithms IoT and industrial internet applications Embedded signal processing systems Her team's innovations bridge communication and navigation domains, with applications in aviation, healthcare, and smart infrastructure. Recent work emphasizes energy-efficient GNSS signal processing and multi-constellation PNT solutions for global accessibility.