Find Academic Supervisors

Biao ChenView profile

Professor

• Information Theory
• Signal Processing
• Statistical Learning Theory
• +2 more

Dr. Biao Chen serves as the John E. and Patricia A. Breyer Professor in Electrical Engineering at Syracuse University within the College of Engineering and Computer Science. His research primarily focuses on foundational theories and applications in wireless communications and sensor networks, with recent work exploring passive RF sensing systems for indoor situational awareness. He holds a Ph.D. in Electrical Engineering from the University of Connecticut. Research interests span information theory, signal processing, and statistical learning foundations, with applications including software radio system design and RF sensing. His work integrates deep learning approaches for presence detection and develops novel methods for spectrum sharing challenges. Recent publications demonstrate trends in RF sensing through deep learning, kernel-based statistical testing, and information-theoretic frameworks. This body of work advances theoretical foundations while addressing practical challenges in wireless communication systems. Honors include IEEE Fellowship (2015) and NSF CAREER Award (2006), recognizing contributions to information theory and distributed detection frameworks. The Communication Laboratory investigates decentralized inference, interference channels, and airborne MIMO communication platforms. Current projects include energy-efficient spectrum access supported by NSF funding.

Sossena WoodView profile

Assistant Professor

• Biomedical Engineering
• Neuroimaging
• Sickle Cell Disease
• +4 more

Dr. Sossena Wood is an Assistant Professor in Biomedical Engineering at Carnegie Mellon University, with courtesy appointments in Electrical and Computer Engineering and the Neuroscience Institute. She holds a B.S. in Electrical Engineering (2011) and a Ph.D. in Bioengineering (2018) from the University of Pittsburgh, followed by a Presidential Postdoctoral Fellowship at CMU under Dr. Jana Kainerstorfer. Her research focuses on multi-modal, noninvasive imaging techniques to study cerebrovascular diseases like sickle cell disease (SCD), emphasizing neural mechanisms and healthcare equity. Key research areas include hemodynamic imaging (MRI, NIRS, EEG), pain and cognitive deficits in SCD, and inclusive neurotechnology to address biases in medical devices. She leads the Wood Neuro Research Group, collaborating with the CMU-Pitt BRIDGE Center and institutions globally. Awards include the American Society of Hematology Abstract Achievement Award (2020) and recognition as a Women of Color Technology Rising Star (2021). Her lab develops cutting-edge tools like anthropomorphic phantoms and MRI coils, and addresses algorithmic bias in devices like pulse oximeters. Educational contributions include teaching "Fundamentals of MRI and Neuroimaging Analysis" and outreach programs to engage underrepresented youth in STEM. Current collaborations focus on SCD mechanisms, pain biomarkers, and imaging equity. Lab equipment includes 3T MRI systems, EEG setups, thermal stimulators, and advanced NIRS devices. She advises multiple graduate and undergraduate students, with recent alumni including Yuxuan Gu (M.S.) and Alexis Duong (B.S./M.S.).

Sean Seok-Chul KwonView profile

Associate Professor

• 6G Wireless Systems
• Machine Learning for Wireless Communications
• Federated Learning Applications
• +3 more

Dr. Sean Seok-Chul Kwon is a Tenured Associate Professor in the Department of Electrical Engineering at California State University, Long Beach's College of Engineering. He founded and directs the Wireless Systems Evolution Laboratory (WiSE Lab) since Fall 2017, leading research in next-generation wireless systems. His research spans 6G wireless design , machine learning applications for communications, polarization diversity , and body area networks . Current projects focus on AI-driven solutions for wireless channel modeling, federated learning in UAV networks, and polarization-reconfigurable systems. His work bridges theoretical innovation with industry applications through collaborations with Intel, DARPA, NSF, and the US Army. Kwon's publication portfolio shows consistent advancement from polarization channel modeling (2010-2015) to cutting-edge AI-integrated wireless systems (2021-2025), with recent emphasis on interpretable transformers, NOMA optimization, and energy-efficient aerial data delivery. His research trajectory demonstrates progression from foundational channel studies to leadership in 6G-enabling technologies. Award highlights include: 5 IEEE Best Paper Awards Intel Invention Disclosure Awards Multiple TPC Service recognitions As an educator, Kwon advises graduate students through the WiSE Lab and teaches core EE courses. His industry experience at Intel (2015-2017) and Pantech (2001-2004) informs practical curriculum development. Current grants involve Department of Navy, NSF, and aerospace partnerships focused on next-generation wireless standards. The WiSE Lab serves as an innovation hub for wireless research, collaborating with federal agencies and industry on polarization-reconfigurable systems, UAV networks, and 6G standardization efforts.

• Radio Frequency Identification (RFID) Systems
• Wireless Sensor Networks
• Communication Systems
• +3 more

Guangjun Wen is a Professor at the School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Department of Electronic Engineering. His research focuses on advanced RFID systems, wireless sensor networks, and communication protocols. Radio Frequency Identification (RFID) Systems Wireless Sensor Networks Medical Data Transmission Signal Processing Electronic Engineering Communication Systems Wen's recent work includes multiple-antenna RFID tag inventory algorithms, interference cancellation techniques, and dual-functional radar-communication systems. He has developed efficient protocols for large-scale RFID systems and explored 5G-enabled medical data transmission. His contributions span from hardware design (e.g., high-precision sensors) to protocol optimization (anti-collision algorithms) and system integration (energy harvesting wireless networks). Collaborative projects involve researchers from institutions across China and international teams.

Wilhelm KleppmannView profile

Professor

• Design of Experiments (DoE)
• Statistical Process Control
• Reliability Engineering
• +3 more

Prof. Wilhelm Kleppmann is a Professor at the Faculty of Electronics & Computer Science at Hochschule Aalen, Germany. His primary research focuses on Design of Experiments (DoE), statistical process control, and reliability engineering. He has authored influential textbooks on optimization methodologies and contributed to Six Sigma integration in industrial processes. His work bridges theoretical statistical methods with practical applications in manufacturing and engineering systems. Key contributions include developing experimental design frameworks for machine learning integration, optimizing cooling circuits in automotive systems, and statistical evaluation of electromagnetic interference. He maintains active engagement with industry through software recommendations for DoE, emphasizing tools like Minitab and JMP. Kleppmann's educational efforts include curriculum development for engineering courses and promoting hands-on learning through simulation tools. His research spans decades with notable publications from 1980s semiconductor reliability studies to modern machine learning-driven process optimization. While no specific awards are listed, his extensive publication record and textbook revisions (e.g., 10th edition of 'Versuchsplanung') highlight sustained scholarly impact.

Gil ZussmanView profile

Professor

• Networking
• Wireless Networks
• Mobile Networks
• +3 more

Gil Zussman is the Kenneth Brayer Professor of Electrical Engineering and Chair of the Department of Electrical Engineering at Columbia University, with affiliations in the Department of Computer Science and the Data Science Institute. He directs the Wireless and Mobile Networking (WiMNet) Lab. His research focuses on networking, particularly wireless and resilient networks. He earned degrees from the Technion and Tel Aviv University, followed by a postdoc at MIT. He has held visiting roles at Tel Aviv University and led projects like the NSF PAWR COSMOS testbed. Zussman has been recognized with IEEE Fellow, NSF and DTRA awards, and multiple best paper awards. Education: B.Sc. (Industrial Engineering & Management) and B.A. (Economics) from Technion (1995); M.Sc. (Operations Research) from Tel Aviv University (1999); Ph.D. (Electrical Engineering) from Technion (2004). Postdoctoral Associate at MIT (2004-2007). Research emphasizes wireless, mobile, and resilient networks, with contributions to full-duplex systems, spectrum access, and urban sensing. His work integrates theory and experimentation, leveraging testbeds like COSMOS. Key awards include IEEE Fellow (2022), NSF CAREER Award (2010), and seven best paper awards. He chairs IEEE INFOCOM technical committees and serves on multiple editorial boards. Advising and grants: PI of the NSF PAWR COSMOS testbed, team leader in the 2009 Vodafone competition, and mentor to over 20 students. Active in service roles, including TPC chair for IEEE INFOCOM and ACM MobiHoc. Labs: Director of WiMNet Lab; oversees the COSMOS testbed for advanced wireless experimentation. Research spans edge computing, smart city infrastructure, and cybersecurity in networks.

Joe FlemingView profile

Associate Professor

• Sensors
• Electronics and Embedded Systems
• Smart Energy Storage
• +5 more

Joe Fleming is an Associate Professor at Coventry University, specializing in sensors, embedded systems, and smart energy storage. He holds an M.Sc. in Electronic Engineering from De Montfort University (2012) and a Ph.D. in Engineering from the University of Warwick (2018). His research focuses on advancing energy storage technologies through embedded electronics and sensors, particularly in improving thermal management and safety validation via in-situ measurements. He has pioneered novel optical and thermistor-based sensors for cylindrical and pouch cells, revealing critical temperature gradients and safety insights during charge/discharge cycles. Education: M.Sc. Electronic Engineering, De Montfort University, Leicester, U.K. (2012) Ph.D. in Engineering, University of Warwick, Coventry, U.K. (2018) Research Interests: Sensors and instrumentation for energy storage Embedded systems and wireless communications Smart battery monitoring systems Electrochemical and thermal characterization of batteries His work emphasizes practical applications, such as developing sensors that integrate seamlessly into energy storage systems without compromising performance. He is affiliated with the Centre for E-Mobility and Clean Growth and collaborates internationally on topics like PEM fuel cells and sulfur-based batteries. His recent studies address challenges in fast charging, safety validation, and sensor durability in extreme conditions.

Vlad MarsicView profile

Assistant Professor

• RF Engineering
• Wireless Networks
• Electromagnetic Simulation
• +4 more

Dr. Vlad Marsic is an Assistant Professor specializing in RF engineering and semiconductor technologies. He is affiliated with the Centre for E-Mobility and Clean Growth, focusing on experimental and theoretical research in magnetic sensors, GaN transistors, and energy harvesting systems. His work contributes to UN Sustainable Development Goals related to clean energy and infrastructure innovation. Education: BEng in Communication Engineering, Faculty of Electronics and Telecommunications, 'Gh. Asachi' University, Romania (2002) MSc in Low Power RF Sensing, School of Applied Sciences, Cranfield University, UK (2012) EngD in RF Communication and Location Services, Warwick Manufacturing Group (WMG), University of Warwick, UK (2019) Research Interests: RF Technologies: Wireless networks, power line communication (PLC), and remote sensing Semiconductor Devices: GaN transistors, Hall-effect sensors, and switching behavior analysis Energy Systems: Li-ion battery diagnostics and energy harvesting Research Trends: His publications (2021–2025) emphasize advancements in GaN-based sensor integration, magnetic field analysis, and battery diagnostics. Recent work addresses challenges in sensor sensitivity, noise mitigation, and energy-efficient communication systems. Awards: Best Paper Award (multiple conferences in RF experimental and modelling domains) Grants and Labs: Involved in collaborative projects with industry partners, focusing on smart infrastructure and clean energy technologies. Active in interdisciplinary teams developing novel sensing and communication solutions. Key Collaborations: Engaged with institutions across the UK and international partners in electromagnetic simulation, semiconductor design, and sustainable energy systems.

Ghulam MurtazaView profile

Researcher

• Quantum Technologies
• Quantum Cryptography
• Photonics
• +3 more

Dr. Ghulam Murtaza is a Postdoctoral Researcher in the Department of Computing and Mathematics at South East Technological University (SETU). His research focuses on quantum technologies, photonics, and telecommunications engineering. He holds a PhD in Quantum Technologies from the University of Naples Federico II (2023), an MSc in Electronics and Communication Engineering from Beijing University of Posts and Telecommunications (2019), and a BSc in Electrical Telecommunication Engineering from Government College University Faisalabad (2015). His key research areas include quantum cryptography, molecular single-photon sources for quantum key distribution, and electromagnetic compatibility in communication systems. Recent work explores room-temperature molecular photon emitters and the impact of coaxial connectors on signal integrity. Publications highlight advancements in quantum communication systems, optical frequency combs, and energy-efficient routing algorithms. His multi-disciplinary approach bridges quantum optics, telecommunications, and machine learning applications in medical imaging.

• Electrical Engineering
• Communication Systems
• Microwave Engineering
• +5 more

Marcel Joss is a Lecturer at the Institute of Electrical Engineering (IET) within the Lucerne School of Engineering and Architecture at Hochschule Luzern, Technik & Architektur. He has held this position since 2003 and previously served as the Head of the Electrical Engineering Department (2005–2010) and project leader for Bologna reform implementation (2003–2005). His expertise spans telecommunications, microwave engineering, and autonomous systems. Education 1983–86: Diploma in Electrical Engineering, HTL Brugg/Windisch 1989–92: Advanced Diploma in System Technology, Neu-Technikum Buchs SG 1995–96: Master of Science in Communication Networks, EPF Lausanne 2000: International Executive Program (INSEAD) Research Interests Dr. Joss focuses on microwave engineering, satellite communication, wireless power transfer, and autonomous systems. His work includes projects like the CHESS CubeSat mission for atmospheric research, microwave-based medical monitoring, and innovative data communication solutions for cableway systems. He actively explores applications in industrial automation, sensor networks, and energy-efficient systems. Key Projects Satellite Tracking with Radio Detection Wireless Power Transmission at Millimeter Waves CHESS CubeSat Atmospheric Dynamics Measurement Multiband Sensor Networks (MBSnet) Professional Contributions Joss has led Swisscom Mobile AG teams in network development and technology integration. He is also a member of the Amateur Radio Club at HSLU, promoting hands-on technical education. His presentations on 5G technology, antenna design, and railway communication highlight his dual focus on academic and industrial innovation.

• Antenna Design
• Wireless Communications
• Telecommunications
• +3 more

João Nuno Matos is affiliated with the Institute of Telecommunications at the University of Aveiro, Portugal. His research focuses on antenna design, RF engineering, and wireless communication systems. He has consistently published in top-tier journals and conferences since 1998, with notable contributions to reconfigurable antennas, 3D printing in antenna manufacturing, and vehicular communication systems. His work bridges theoretical advancements with practical applications in telecommunications, IoT, and satellite technology. Key contributions include innovations in polarization control, antenna miniaturization, and integration of thin-film technologies.

• Wireless Communication
• Machine Learning
• Signal Processing
• +3 more

Michel Kulhandjian is a researcher specializing in Wireless Communication and Machine Learning applications. His work spans NOMA Systems , RF Fingerprinting , and Drone-Assisted Sensing across academic institutions. Key collaborations with Carleton University , Carleton University , and University of Ottawa researchers Active in 5G/6G technologies and IoT Security since 2018 His recent articles focus on: 2024 : Pedestrian detection, drone-based tree health monitoring, and industrial IoT security 2025 : AI-powered agricultural robotics Scientific contributions include: Code design for OTFS-NOMA systems Low-complexity detection algorithms 3D CNN frameworks for signal analysis RF Fingerprinting under impaired channels

Mustafa NamdarView profile

Associate Professor

• Integrated Sensing and Communication (ISAC)
• Reconfigurable Intelligent Surfaces (RIS)
• Cognitive Radio Networks (CRNs)
• +3 more

Assoc. Prof. Dr. Mustafa Namdar holds an academic position at Kütahya Dumlupınar University's Faculty of Engineering, Department of Electrical-Electronics Engineering. His research focuses on advanced communication systems including Integrated Sensing and Communication (ISAC), Reconfigurable Intelligent Surfaces (RIS), and Non-Orthogonal Multiple Access (NOMA). He has led 11 projects funded by institutions like TUBITAK and the Turkish Presidency of Defense Industries (SSB). His work spans 83 publications, including peer-reviewed journal articles and conference proceedings. Notable achievements include the IEEE ELECO 2024 Best Paper Award and multiple TÜBİTAK publication incentives. Education: PhD in Electronics and Communication Engineering from Yıldız Technical University (2006–2014) Research Interests: 6G Communication Technologies AI-driven Network Optimization Unmanned Aerial Vehicle (UAV) Communication Systems Wireless Security and Privacy Grants & Awards: Overseen 23 projects totaling €1.2M Recipient of Elsevier's Recognized Reviewer Status (2015–2021) Labs & Teams: Collaborates with the 6G Platform at Istanbul Medipol University and the Information and Communications Research Group (ICRG) at ITU.

• Wireless Communications
• Signal Processing
• Neural Networks
• +3 more

Ivan Milovanović is a faculty member at Singidunum University, affiliated with the Faculty of Technical Sciences under the Department of Informatics and Computing. He holds a doctoral degree in Advanced Protection Systems from Singidunum University (2009-2015), following a master's in Contemporary Information Technologies (2008-2009) and a bachelor's in Graphic Design (2004-2008). His research focuses on wireless communications, signal processing, neural networks, and telecommunications, with an emphasis on applications such as direction-of-arrival estimation, stochastic source localization, and channel modeling. He has published extensively in journals like the International Journal of RF and Microwave Computer-Aided Engineering and presented at conferences including TELSIKS and ICEST. Education: PhD: Advanced Protection Systems, Singidunum University (2009–2015) Master's: Contemporary Information Technologies, Singidunum University (2008–2009) Bachelor's: Graphic Design, Singidunum University (2004–2008) High School: Stevan Sremac Gymnasium (2000–2004) Research Interests: His work integrates neural networks with electromagnetic systems to address challenges in wireless communications, including signal localization, noise analysis, and adaptive antenna systems. He explores hybrid models for indoor/outdoor path loss calculation and secure wireless sensor networks for critical infrastructure protection. Recent studies focus on stochastic processes in far-field environments and the design of efficient neural network architectures for real-time signal processing. Publications: Key contributions include papers on DoA estimation using hierarchical neural models, analysis of WSN-FSO systems, and performance benchmarks for DBMS engines. His research bridges theoretical advancements with practical applications in telecommunications and data systems. Labs/Teams: Active in Singidunum University's research groups focusing on telecommunications and neural network applications. Collaborates with institutions like the Faculty of Electronic Engineering in Niš and international partners such as TU Dresden and TU Ilmenau.

Eli De PoorterView profile

Professor

• IoT
• Wireless Network Protocols
• Wireless Testbeds
• +4 more

Eli De Poorter is a Professor at the Faculty of Engineering and Architecture , Ghent University , and affiliated with IMEC since 2017. His work bridges experimental wireless research with machine learning techniques, focusing on IoT , UWB localization , and self-learning networks . Received his PhD in 2011 from Ghent University’s Department of Information Technology FWO Postdoctoral Research Grant recipient Co-author of over 100 international publications Active in program committees of multiple conferences His research spans wireless protocol optimization , interference detection , and system configuration dependencies . Notable projects include UWB-based healthcare monitoring , industrial IoT networks , and animal wearables for agriculture . Develops energy-aware tinyML models for battery-less devices Explores Transformer networks and self-supervised learning for wireless systems Investigates multi-modal industrial IoT and Wi-Fi/UWB hybrid synchronization Scientific Awards FWO Postdoctoral Research Grant Labs & Teams Internet Technology and Data Science Lab (IDLab) IMEC research institute