جستجوی استاد راهنمای دانشگاهی

Filippo Malandraمشاهده پروفایل

استادیار

• Internet of Things
• Wireless Communications
• 5G/4G Cellular Networks
• +۴ مورد دیگر

Filippo Malandra is an Assistant Professor in the Department of Electrical Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on Internet of Things (IoT), wireless communications, 5G/4G cellular networks, network performance analysis, smart grid communications, optimization, and machine learning applications. PhD in Electrical Engineering from École Polytechnique de Montréal Master of Engineering in Telecommunications Engineering from Politecnico di Milano Bachelor of Engineering in Telecommunications Engineering from Politecnico di Milano His research interests include experimental testbed development for 5G-enabled smart grids, analytical modeling of cellular network delays, and machine learning frameworks for optimizing network performance under environmental factors. He has contributed to tools like WTTool for 5G network simulation and PeRF-Mesh for RF-mesh network analysis. Recent work emphasizes 5G testbed experimentation (e.g., ExTODS), weather-based signal prediction, and CBRS spectrum analysis. He has explored synergies between federated learning and O-RAN architectures for elastic network services. Active service roles include TPC Member for IEEE SECON 2019 and reviewer for IEEE journals and conferences like DRCN. Recipient of NSF CRII grant (2021) for CNS research on IoT-aware dynamic spectrum sharing. Collaborates on projects like UBSpot (aerial-ground wireless networks) and smartDESC (distributed energy storage control).

Haemin Parkمشاهده پروفایل

دانشیار

• Technology Entrepreneurship
• Venture Capital
• Corporate Venture Capital
• +۴ مورد دیگر

Haemin Park is an Associate Professor at the Naveen Jindal School of Management, University of Texas at Dallas. His research focuses on how external resource acquisition strategies of technology-based ventures influence their development and performance, with a particular emphasis on corporate venture capital (CVC), knowledge governance, and intellectual property rights. He holds a Ph.D. in Technology Entrepreneurship and Strategic Management from the University of Washington, an MBA from Georgetown University, and a B.A. in Computer Sciences, Economics, and Mathematics from the University of Wisconsin. Education: PhD (UW, 2010), MBA (Georgetown, 2000), BA (UW Madison, 1994) Editorial Roles: Area Editor of Journal of Business Venturing ; Editorial Board Member of Strategic Entrepreneurship Journal Research interests include venture capital dynamics, innovation ecosystems, and strategic management of technology firms. His work explores topics like IPO underpricing, corporate venture capital syndicates, and the impact of gender diversity in decision-making groups. Awards: 2017 Journal of Business Venturing Best Reviewer; Finalist for Academy of Management TIM Division Best Dissertation Award. Professional Experience: Prior to academia, he worked as a corporate venture capitalist, business development manager, and management consultant in wireless telecommunications in the U.S. and Asia.

Nico Palleitمشاهده پروفایل

پژوهشگر

• MIMO Communication Systems
• Channel Estimation
• Signal Processing
• +۳ مورد دیگر

Dr.-Ing. Nico Palleit is affiliated with the University of Rostock's Institute of Communications Engineering, part of the Faculty of Computer Science and Electrical Engineering. His research focuses on MIMO (Multiple-Input Multiple-Output) systems, channel estimation, and prediction techniques to enhance spectral efficiency. He holds a PhD titled Channel Prediction in Multi-Antenna Systems (2011) and has contributed to advancements in MIMO channel analysis, including frequency/time prediction and interference management. Research Interests: Nico's work addresses challenges in modern radio transmission systems, emphasizing the development of robust channel estimation strategies. Key areas include MIMO channel modeling, non-line-of-sight (NLOS) positioning, and optimizing transmitter-side channel state information. His research bridges theoretical frameworks with practical implementations in wireless communication systems. Publications Overview: His 15+ publications (2006–2012) span topics like MIMO channel prediction, antenna array design, and interference channel optimization. Recent work emphasizes frequency/time-domain channel prediction and power allocation strategies for maximizing system capacity. These contributions highlight interdisciplinary approaches combining signal processing with electrical engineering principles. Affiliations & Labs: As part of the Radio Communication Research Group, he collaborates on projects within the Institute's advanced wireless communication initiatives. His work supports next-generation radio systems through innovative solutions for MIMO-FDD and OFDM-based architectures.

Anna Brunströmمشاهده پروفایل

استاد

• Computer Networking
• Internet Architectures
• 5G/6G Mobile Systems
• +۳ مورد دیگر

Anna Brunström is a Full Professor and Head of the Distributed Intelligent Systems and Communications Research Group (DISCO) at Karlstad University's Department of Computer Science. She holds a part-time role as a Researcher at the University of Malaga's Institute of Software Engineering and Technologies (ITIS). Her research focuses on computer networking, Internet architectures, low latency communication, and 5G/6G mobile systems. She leads the nationally funded DRIVE initiative and collaborates on European projects like 6G-PATH. She actively contributes to IETF standardization, notably as a former rmcat WG chair. Her work spans over 200 publications, emphasizing network measurement, latency optimization, and multipath protocols. Education: Ph.D. (1996) and M.Sc. (1993) from College of William & Mary, B.Sc. (1991) from Pepperdine University. Research Interests: Distributed systems, IoT networking (NB-IoT), satellite communication (Starlink), machine learning for positioning, and transport protocols (QUIC, MPTCP). Recent work includes latency-aware scheduling, 5G/6G performance analysis, and edge computing frameworks. Publications highlight trends in: 1) Satellite network throughput modeling, 2) 5G/6G architecture validation, 3) Machine learning applications for positioning and network analysis, 4) Cross-layer optimization of latency-critical services. Collaborations with industry and academia drive applied research in smart grids, healthcare, and automotive communication. Labs/Teams: DISCO group at Karlstad University, leading the DRIVE research profile and 6G-PATH consortium involvement.

• Embedded Systems
• FPGA Technologies
• Edge Computing
• +۴ مورد دیگر

Professor Roger Woods is a prominent academic and researcher affiliated with Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, part of the Faculty of Engineering and Physical Sciences. He holds the rank of Professor and is actively involved in advancing research and innovation in embedded systems, FPGA technologies, and AI-driven solutions for industry challenges. His work emphasizes practical applications through close collaboration with industry partners. His research interests span novel computing architectures (e.g., multi-precision and edge computing), FPGA-based systems for data analytics, and secure IoT communication protocols. Notably, he co-founded and serves as Chief Scientist of Analytics Engines Ltd, a data analytics company. He has led significant initiatives like the Kelvin-2 Tier-4 High Performance Computing centre and contributed to semiconductor reviews through EFutures. Professor Woods has been recognized with prestigious awards, including the IET Northern Ireland Engineering Excellence Award and IEEE Fellowship. He has supervised numerous PhD students focusing on topics like FPGA-based image processing, secure wireless communications, and embedded AI platforms. His publications reflect interdisciplinary strengths in hardware acceleration, physical layer security, and structural health monitoring. Key Collaborations : Projects with industry and institutions on semiconductor design, bridge monitoring, and AI hardware. Grants : Principal Investigator for multiple research grants, including Core Equipment Awards for advanced instrumentation. Labs/Teams : Active in Queen's Advanced MicroEngineering Centre and the EFutures network.

Ifana Mahbubمشاهده پروفایل

دانشیار

• Integrated Circuits and Systems Design
• Wireless Communication
• Wireless Power Transfer
• +۵ مورد دیگر

Ifana Mahbub is an Associate Professor at the Erik Jonsson School of Engineering and Computer Science , University of Texas at Dallas, specializing in Electrical & Computer Engineering . Her research focuses on energy-efficient integrated circuits, wireless power transfer systems for biomedical sensors, and advanced antenna designs for UAV and mm-wave applications. She leads the Integrated Biomedical, RF Circuits and Systems Lab . Education: Ph.D. in Electrical Engineering (2017), University of Tennessee, Knoxville B.S. in Electrical Engineering (2012), Bangladesh University of Engineering and Technology Research interests include: Ultrawideband/mm-wave phased-array antennas Far-field wireless power beaming V2V communication for UAVs Energy harvesting via reverse electrowetting Implantable/wearable sensor systems Recent work highlights advancements in high-efficiency rectennas, beamforming algorithms, and AI-driven metasurface design. Her systems address critical challenges in biomedical telemetry and aerial communication.

George N. Karystinosمشاهده پروفایل

استاد

• Communication Theory and Systems
• Wireless Communications
• Signal Processing
• +۹ مورد دیگر

George N. Karystinos is currently a Professor and Dean of the School of Electrical and Computer Engineering at the Technical University of Crete , Greece. He joined TUC in 2005 and was promoted to full Professor in 2019. His academic journey began with a Ph.D. in Electrical Engineering from SUNY Buffalo (2003) and a Diploma in Computer Engineering and Science from the University of Patras (1997). Specialty: Communication theory, coding theory, adaptive signal processing Key research areas: Wireless communications, signal waveform design, L1-norm principal component analysis Leadership: Dean of School of ECE (2021–present) His work focuses on noncoherent detection for RFID/IoT systems and L1-norm PCA for robust signal processing. Recent publications explore power line communication and low-complexity sequence detection . Scientific Awards: 2003 IEEE Transactions on Neural Networks Outstanding Paper Award 2001 IEEE ICT Best Paper Award 2018 IEEE MOCAST Best Student Paper Award 2015 IEEE ICASSP Best Student Paper Award 2013 IEEE ISWCS Best Paper Award 2011 IEEE RFID-TA Second Best Student Paper Award He is affiliated with the Telecommunications Laboratory at TUC and has supervised award-winning research in wireless systems and signal processing.

Christian Haubeltمشاهده پروفایل

استاد

• Embedded Systems
• Cyber-Physical Systems
• Smart Sensors
• +۹ مورد دیگر

Christian Haubelt is a Professor at the Institute of Computer and Network Engineering, School of Engineering, University of Rostock, Germany. He is actively engaged in research and teaching in the areas of embedded and cyber-physical systems, smart implants, and IoT. His work is supported by multiple national and international projects including ELAINE (SFB 1270), SmILE (EU), 6G-Health (BMBF), and GenerIoT (BMBF). His research interests include: Embedded and Cyber-Physical Systems Smart Sensors and Smart Implants System-Level Design Methodologies SystemC-based Modeling and Verification Design Space Exploration and Multi-Objective Optimization Industrial Internet of Things and 6G for Healthcare His recent publications focus on real-time communication protocols, 5G/6G localization, smart implants, and secure IoT systems. Trends show a strong emphasis on integrating embedded systems with medical and industrial applications, particularly leveraging TSN, MQTT-SN, and OPC UA for reliable and secure communication. His work bridges theoretical modeling with practical implementation in safety-critical domains. Christian Haubelt has supervised multiple researchers including Michael Nast, Benjamin Rother, Nico Kalis, and Nico Graumüller. He leads several funded research projects such as ELAINE, SmILE, 6G-Health, and SUSTAIN, which focus on smart implants, secure IoT, and next-generation medical systems. These projects involve collaboration with DFG, EU, and BMBF. He is involved in the following research labs and teams: Embedded Systems and Cyber-Physical Systems Group Smart Implants Research Team (SmILE, ELAINE) 6G-Health Localization Team Industrial IoT Security (SUSTAIN, CargoAssist)

Liang Dongمشاهده پروفایل

دانشیار

• Signal Processing
• Wireless Communications
• Cyber-Physical Systems
• +۱۲ مورد دیگر

Dr. Liang (Leon) Dong is an Associate Professor in the Department of Electrical and Computer Engineering at Baylor University, where he conducts research and teaches in the areas of signal processing, wireless communications, and artificial intelligence. He leads the Laboratory of Signal Processing, Communications, and Artificial Intelligence, fostering innovation in next-generation communication systems, IoT, and AI-driven applications. PhD, Electrical & Computer Engineering, The University of Texas at Austin (2002) MS, Electrical & Computer Engineering, The University of Texas at Austin (1998) BS, Applied Physics with Minor in Computer Engineering, Shanghai Jiao Tong University (1996) Dr. Dong's research focuses on advancing digital signal processing and wireless communications, with strong emphasis on artificial intelligence applications. His work spans NextG wireless systems , IoT and smart cities , cyber-physical system security , and AI in healthcare and industrial automation . He applies deep learning to domains such as autonomous driving and drug discovery, and investigates energy-efficient, secure, and reliable communication protocols. The recent publications highlight a strong trend toward integrating AI into traditional signal processing and communications. Topics include mRNA vaccine stability prediction , smart city infrastructures , secure cyber-physical systems , and deep learning for biomedical and industrial applications . His work bridges theoretical innovation with real-world impact in defense, transportation, and public health. Dr. Dong has earned recognition as a Senior Member of IEEE and a Member of the American Physical Society. He has also served as Faculty Advisor for Baylor University's InterVarsity chapter. Senior Member, Institute of Electrical and Electronics Engineers (IEEE) Member, American Physical Society (APS) He has successfully advised numerous graduate and undergraduate students, many of whom now hold academic and industry positions at institutions like Stanford, Intel, NASA, L3Harris, and Cummins. His research is generously supported by Baylor's VP for Research, the National Science Foundation, NASA, the Department of Defense (TARDEC), the Michigan Department of Transportation, and industry leaders including Intel, L3Harris, ExxonMobil, and Denso. He actively mentors students through research assistantships and senior design projects. Dr. Dong leads the Laboratory of Signal Processing, Communications, and Artificial Intelligence, which provides a collaborative environment for advancing research in signal processing, communications, and AI. The lab supports graduate and post-doctoral researchers and offers opportunities for undergraduate involvement in AI programming, circuit design, and embedded systems.

Haibo Heمشاهده پروفایل

استاد

• Computational Intelligence
• Neural Networks
• Reinforcement Learning
• +۵ مورد دیگر

Dr. Haibo He is the Robert Haas Endowed Professor in the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island (URI). As an IEEE Fellow and NSF CAREER awardee, his research focuses on computational intelligence, neural networks, and reinforcement learning with applications to smart grids and microgrid systems. Ph.D. in Electrical Engineering, Ohio University, 2006 M.S. in Electrical Engineering, Huazhong University of Science and Technology, 2002 B.S. in Electrical Engineering, Huazhong University of Science and Technology, 1999 His research interests include: Computational Intelligence Adaptive Dynamic Programming Reinforcement Learning Deep Learning for Power Systems Distributed Control in Microgrids Imbalanced Data Learning Recent research trends from publications (2018-2025) show a focus on: Multi-agent reinforcement learning for energy systems Digital twin frameworks for grid security Event-triggered control mechanisms Finite-time convergence algorithms Cyber-attack resilient control systems Evolutionary computation in power networks Awards: IEEE Fellow (2018) NSF CAREER Award (2017) Dr. He leads the Computational Intelligence and Self-Adaptive Systems (CISA) Laboratory at URI, which conducts fundamental research on computational intelligence methods with applications to power systems, data mining, and neural networks.

• Indoor Localization
• Wireless Networks
• Pervasive Computing
• +۱۱ مورد دیگر

Shueng-Han Gary Chan is a faculty member in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), within the College of Engineering. He is actively engaged in research and mentoring, with a strong publication record in mobile computing, indoor localization, and AI for pervasive systems. His research focuses on indoor localization using Wi-Fi, geomagnetic, and inertial signals , sensor fusion , crowd counting with deep learning , domain adaptation , and efficient mobile AI systems . His work bridges theoretical innovation with real-world deployment, as seen in systems for missing person search and indoor navigation. Recent publications (2023–2025) show a consistent trend toward self-supervised and domain-agnostic learning , efficient model design for mobile devices , and robust signal fusion in noisy environments . His team leverages transformer architectures, graph neural networks, and novel optimization techniques to solve real-world challenges in urban and indoor spaces. He has advised numerous graduate students, including Jierun Chen, Zhuoxuan Peng, and Tianlang He, who have contributed as first authors to joint publications. His collaborations span institutions and include work on large-scale system deployments and mobile AI. He leads a research group focused on mobile and pervasive computing , with projects involving IoT-based contact tracing, indoor navigation (e.g., DeepNavi, SiFu), and real-time localization systems. The team emphasizes practical deployment and system robustness.

Telex M. N. Ngatchedمشاهده پروفایل

دانشیار

• 5G and 6G enabling technologies
• Optical wireless communications
• Hybrid optical wireless and radio frequency communications
• +۲ مورد دیگر

Telex M. N. Ngatched is an Associate Professor in the Department of Electrical & Computer Engineering at McMaster University, where he has been since January 2023. Previously, he held positions as a Postdoctoral Fellow at the University of KwaZulu-Natal (2006-2007), Research Associate at the University of Manitoba (2008-2012), and faculty at Memorial University (2012-2022). He is currently accepting graduate students. Education: BSc in Electronics, University of Yaoundé, Cameroon MSc in Electronics, University of Yaoundé, Cameroon MScEng (Cum Laude) in Electronic Engineering, University of Natal, South Africa PhD in Electronic Engineering, University of KwaZulu-Natal, South Africa Research Interests: Dr. Ngatched's work spans next-generation wireless systems, including optical/RF hybrid communications, underwater networks, and AI/ML applications for 5G/6G infrastructure. His research addresses signal processing challenges and optimization methods for reconfigurable intelligent surfaces in smart environments. Awards & Honors: Grenfell Campus Research Award (2020) IEEE WCNC Best Paper Award (2019) Carnegie African Diaspora Fellowship (2016) South African Sugar Miller’s Teaching Award (2007) Professional Engineering licensure (P. Eng.) Professional Activities: He serves as Area Editor for IEEE Open Journal of the Communications Society, Associate Technical Editor for IEEE Communications Magazine, and organizes major IEEE conferences (e.g., VTC, GLOBECOM). Teaches courses on optical wireless communications, signals, and communication systems.

• Cyber-Physical Systems
• Distributed Systems
• Internet of Things (IoT)
• +۷ مورد دیگر

Loïc Guégan is an Associate Professor in the Department of Informatics at UiT The Arctic University of Norway, affiliated with the Faculty of Science and Technology. His work is centered on energy-efficient cyber-physical systems and distributed computing, particularly in extreme and constrained environments such as the Arctic. His research focuses on cyber-physical systems (CPS) , distributed data dissemination , IoT and edge computing , and energy-efficient protocols . He actively contributes to the development of the Distributed Arctic Observatory (DAO) project and has designed tools like the ESDS simulator for evaluating distributed systems in challenging conditions. His technical work includes power monitoring using single-board computers and the design of the LoRaLitE protocol for low-energy wireless communication. The recent publications highlight a consistent trend in data dissemination strategies , simulation frameworks , and energy optimization for IoT and edge systems deployed in remote, resource-limited settings. These studies often leverage real-world Arctic deployments and epidemic-style algorithms to ensure robustness and scalability. Loïc is a member of the Cyber Physical Systems (CPS) research group and contributes to projects including The IoT-to-Extreme-Edge Infrastructure and Sustainable Distributed Systems for Sustainable Research and Education . He teaches courses such as Parallel Programming and Operating Systems . His research is supported through institutional and project-based funding, though specific grants are not detailed in the text.

Elif Akمشاهده پروفایل

پژوهشگر

• Digital Twin
• Smart City
• Waste-to-energy
• +۳ مورد دیگر

Elif Ak is a Researcher at Istanbul Technical University's Department of Computer Engineering, College of Engineering. Her work focuses on cutting-edge network technologies and digital twin systems. Current research in 6G communication frameworks Active in AI-enabled network management Digital twin methodology specialist Her research interests span Digital Twin , 6G Networks , and Machine Learning applications in telecommunications. Recent publications highlight advancements in backbone network security , UWB localization , and semantic communication systems. Key publication trends show 7 Scopus citations with 33 Mendeley readers, featuring collaborations with international experts in IEEE Transactions and Communications Magazine . Research outputs (21 total) demonstrate consistent annual contributions since 2019.

Wei Songمشاهده پروفایل

استاد

• Mobile Social Networks
• Internet of Things
• Vehicular Networks
• +۱۰ مورد دیگر

Dr. Wei Song is a Professor and the Coordinator of Software Engineering at the Faculty of Computer Science, University of New Brunswick (UNB) in Fredericton, New Brunswick, Canada. She has been with UNB since 2009, after completing her postdoctoral studies at UC Berkeley, and has established herself as a leading researcher in mobile networking and wireless communications. Her office is located in room ID419 and she can be reached at wsong@unb.ca. Education Ph.D. in Electrical and Computer Engineering, University of Waterloo (2003-2007) Postdoctoral Fellow, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley (2008-2009) Research Focus Dr. Song's research spans multiple cutting-edge areas in mobile and wireless networking, with a strong emphasis on integrating artificial intelligence and machine learning techniques. Her work addresses fundamental problems in mobile social networks, Internet of Things, vehicular networks, and mobile cloud computing. She explores how cooperative intelligence and distributed AI can enhance network performance while addressing practical constraints such as energy efficiency and user incentives. Her recent work particularly focuses on intelligent edge computing, mobile crowdsensing with deep reinforcement learning, and social-aware data dissemination through device-to-device communications. She investigates how to turn decentralized mobile "crowds" into coherent working groups and how social connections can be leveraged to improve data dissemination efficiency. Publication Trends Dr. Song's recent publications (2016-2023) demonstrate a clear evolution from traditional wireless networking to AI-driven approaches. While her earlier work focused on fundamental problems in device-to-device communications and resource allocation, her recent publications increasingly incorporate deep reinforcement learning, graph neural networks, and other AI techniques to solve complex optimization problems in mobile crowdsensing and edge computing. This shift reflects broader trends in the field toward intelligent, adaptive networking solutions. Scientific Recognition Best Paper Award from IEEE ICC (2018) UNB Merit Award (2014) Best Student Paper Award from IEEE CCNC (2013) Top 10% Award from IEEE MMSP (2009) NSERC postdoctoral fellowship (2008) Best Paper Award from IEEE WCNC (2007) Professional Service and Mentoring Dr. Song serves as Senior Member of IEEE and has held significant leadership roles, including Chair of the Joint Computer and Communications Chapter of IEEE New Brunswick Section (2014-2020). She has chaired symposia at major conferences including IEEE VTC Fall 2023, 2017, and 2016. As a supervisor, she mentors graduate students in areas including intelligent edge computing and deep learning for networking, and is currently recruiting students for Winter 2024 and Fall 2025.