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Brian FloydView profile

Professor

• RF Circuits and Systems
• Millimeter-Wave Communication
• Phased Arrays
• +5 more

Dr. Brian Floyd is the Alton and Mildred Lancaster Professor in the Department of Electrical and Computer Engineering at NC State University. His research focuses on RF and millimeter-wave circuits for wireless communication, radar, and imaging applications. He has extensive industry experience, including roles at IBM Research and leadership in the IEEE RFIC Symposium. His work includes pioneering contributions to 60-GHz transceivers and silicon phased arrays. Education: Ph.D., M.S., and B.S. in Electrical Engineering from the University of Florida. Leadership: IEEE Solid-State Circuits Society AdCom Secretary and IEEE RFIC Symposium Executive Committee. Research Interests : RF and millimeter-wave integrated circuits Phased arrays and beamforming Low-cost radar and imaging systems 6G/5G communication systems Recent publications emphasize phased-array calibration, mmWave platforms, and Gallium Nitride-based transmitters. His awards include the NC State Innovator of the Year (2023) and multiple teaching accolades. He leads advanced wireless research initiatives like AERPAW and 6GNC, focusing on 6G technologies and autonomous spectrum management.

Tan LeView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• +7 more

Tan Le is an Assistant Professor in Electrical and Computer Engineering at Hampton University, Virginia, USA. He previously held a Research Assistant Professor position at Virginia Modeling, Analysis and Simulation Center (VMASC), Old Dominion University. He received his Ph.D. from the University of Quebec (2015), M.Eng. and B.Eng. from Ho Chi Minh City University of Technology (2004 and 2002 respectively). His research focuses on AI/ML applications in cybersecurity, IoT, 5G networks, smart healthcare, and edge computing. Key contributions include secure mobility management in vehicular networks, privacy-preserving data sharing, and AI-driven edge caching frameworks. Education Path: Ph.D. Electrical and Computer Engineering, University of Quebec, 2015 M.Eng., Ho Chi Minh City University of Technology, 2004 B.Eng., Ho Chi Minh City University of Technology, 2002 Research Interests: AI/ML for Cybersecurity and Privacy 5G and Beyond Networks Vehicular Networks and Edge Computing Smart Healthcare Systems Blockchain and Distributed Computing His recent publications emphasize AI-aided resource management (e.g., multi-timescale actor-critic learning), privacy-preserving IoT communication, and mobility-aware edge caching in vehicular networks. Collaborations with ODU focus on 5G and IoT infrastructure for DoD mission-support systems. Lab/Team Affiliations: Research involves VMASC and cross-university partnerships, particularly with Old Dominion University teams advancing cybersecurity and next-generation network solutions.

• Parallel Computing
• Distributed Systems
• High-Performance Computing (HPC)
• +5 more

Torsten Hoefler is a Professor affiliated with ETH Zurich, leading research in parallel computing, distributed systems, and high-performance computing (HPC). His work bridges theoretical foundations and practical implementations, focusing on optimizing algorithms, network topologies, and hardware-software co-design. Research Interests: His primary areas include parallel algorithms, distributed systems, machine learning infrastructure, and network architectures. He emphasizes scalable solutions for large-scale applications, particularly in data-centric computing and serverless environments. Publications: Recent work highlights include innovations in network topologies (e.g., HammingMesh), serverless benchmarking frameworks (SeBS), and optimizations for large language models (LLMs). His publications often address performance bottlenecks and energy efficiency in HPC and cloud systems. Awards & Grants: While no specific awards are listed here, his prolific publication record and leadership in HPC indicates significant recognition in the field. Active in grant-funded projects related to exascale computing and AI infrastructure. Labs & Teams: Leads the Communication Systems Lab at ETH Zurich, collaborating with industry partners like NVIDIA and IBM on hardware-accelerated computing and cloud-native systems.

Deepak ToshView profile

Associate Professor

• Cybersecurity
• Blockchain
• Cybersecurity Information Exchange (CYBEX)
• +12 more

Dr. Deepak Tosh is an Associate Professor at the University of Texas at El Paso in the Department of Computer Science. He specializes in cybersecurity , blockchain , and cyber-physical systems , with a focus on decentralized solutions for critical infrastructure security. Ph.D. in Computer Science and Engineering, University of Nevada, Reno M.S. in Computer Science, University of Hyderabad, India Postdoctoral Researcher, Tennessee State University Former Cybersecurity Researcher, Norfolk State University His research bridges cybersecurity information sharing (CYBEX) , data provenance in cloud/edge environments , and game-theoretic models for cyber-investment and cyber-insurance. Recent work explores federated learning for anomaly detection , blockchain for industrial IoT , and cyber deception frameworks . Key publication trends include: Federated learning applications in industrial cyber-physical systems Game theory and SDN for battlefield communication security Blockchain for provenance in energy systems and medical IoT Graph machine learning for automotive network threats Cyber deception via Monte-Carlo planning Scientific recognitions include: NSF CAREER award for critical infrastructure resiliency NSF grant for cyber security network development At UTEP, Dr. Tosh teaches CS 5352: Computer Security and leads the TRUCYBER Lab , which focuses on decentralized trust frameworks, blockchain security, and cyber situational awareness. The lab has produced notable alumni like Adeel Malik (Ph.D.) and Abel Gomez (Ph.D.) , with projects published in IEEE MILCOM, SecureComm, and CCGrid.

• Computer Networks
• Control Systems
• Optimization
• +3 more

A. Kevin Tang is a Professor of Electrical and Computer Engineering (ECE) at Cornell University, affiliated with the School of ECE. His research focuses on computer networks, control systems, optimization, and information theory. He teaches advanced courses such as ECE 5800 (Control and Optimization of Information Networks) and ECE 6960 (Interplay between Economics and Systems). His work bridges theoretical foundations and practical network applications, including network coding, distributed control, and protocol design. Recent contributions address privacy-preserving data sharing, network routing stability, and optimization techniques for heterogeneous systems. Tang’s publications span top venues like NeurIPS, ICML, NSDI, and IEEE Transactions. His research group explores cutting-edge topics in networked systems, with applications to distributed storage, software-defined networking, and multipath communication protocols. He advises on interdisciplinary projects combining control theory, optimization, and networking. His lab collaborates closely with industry partners to translate theoretical insights into real-world network solutions.

Thomas MoonView profile

Assistant Professor

• Signal Processing
• Wireless Communication Systems
• mmWave Radar
• +5 more

Thomas Moon is a Teaching Assistant Professor in the Department of Electrical & Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC), holding this position since 2019. He previously served as a postdoctoral researcher at UIUC (2017–2019) and a Principle Test Development Engineer at IBM/Globalfoundries (2015–2017). His academic journey includes a Ph.D. in ECE from Georgia Institute of Technology (2015) and a B.S. in EEE from POSTECH, South Korea (2008). Research Interests: Current research focuses on Radar Tracking via Bayesian Estimators , Radar Security , and Wireless Sensing using mmWave and Phase-Arrays . Previous work includes mmWave Phased Array Test Systems , Sub-Nyquist Rate Sampling for Wideband Signals , and High-Speed Signal Testing Methodologies . His work bridges theoretical signal processing with practical hardware implementations, emphasizing cost-effective solutions and real-time applications. Recent Contributions: Recent articles emphasize radar security (e.g., BlueFMCW interference mitigation), mmWave phased array calibration, and embedded DSP education. His 2015 work on sparse signal characterization earned the JETTA-TTTC Best Paper Award. Teaching & Advising: Teaches courses like ECE 398MA (Modern Communication with Python/SDR) and ECE 420 (Embedded DSP Lab). He mentors undergraduate students in senior projects focusing on remote sensing, signal processing, and wireless communication. Labs & Infrastructure: Engages with mmWave radar systems and software-defined radio platforms, leveraging FPGA-based testing modules and Android-based DSP implementations.

Gábor MolnárView profile

Associate Professor

• High-Tech Innovations
• Big Data
• Digital Transformation and Strategy
• +1 more

Gábor Molnár, PhD, is an Associate Professor of Applied Sciences at Wittenborg University and holds adjunct roles as Associate Professor at the University of Colorado Boulder's ATLAS Institute and Fellow at Silicon Flatirons. He also serves as an Evangelist of Video Technology and Science at Divitel and advises e-Conomics, a telecom policy consultancy. Dr. Molnár's expertise spans high-tech innovations, AI-driven digital transformation, and data policy, with over 20 years in the high-tech industry. His research emphasizes bridging human and machine collaboration, AI ethics, and the socio-economic impacts of broadband infrastructure. He holds degrees from Corvinus University of Budapest (BSc Economics), Budapest University of Technology and Economics (MSc Electrical Engineering), and the University of Colorado Boulder (MSc/PhD Telecommunications). Education: BSc Economics (Corvinus), MSc Electrical Engineering (Budapest University of Technology), MSc/PhD Telecommunications (CU Boulder) His research focuses on human-centric AI, digital transformation strategies, and telecom policy. Recent work explores HRM's role in AI adoption, algorithm factories, and broadband accessibility's socio-economic effects. He has contributed to journals like Journal of Industrial Economics and Discover Artificial Intelligence . As a consultant, he advises Fortune 500 firms, SMEs, and governments on digital transformation and high-tech strategies. His articles highlight trends in algorithmic video delivery, 5G network sharing, and spectrum policy, reflecting his dual academic and industry perspectives.

• Computer Networks
• Software Defined Networking (SDN)
• Network Function Virtualization (NFV)
• +5 more

Wouter Tavernier is an Associate Professor at Ghent University and a Postdoctoral researcher at IMEC, affiliated with the Faculty of Engineering and Architecture's Department of Information Technology (EA05). He leads research at the Internet Technology and Data Science Lab, focusing on networking innovations for future communication systems. His research explores: Network architectures for 5G/6G, HPC, and deterministic systems SDN/NFV orchestration for cloud/edge services Optical networking including programmable photonics and routing optimization Network resilience through fault-tolerant protocols and traffic engineering Publications (2020–2025) emphasize: Deterministic networking for real-time systems and industrial IoT Resource optimization in HPC/cloud networks Convergence of optical/wireless technologies in 6G Decentralized edge intelligence via programmable swarm solutions He advises doctoral researchers on projects including: QoS Optimization in 6G Networks (Jakob Miserez) Control Strategies for Network-Cloud Services (Abhinaba Chakraborty) Software-Based Networking for 6G (Mohammadreza Heydarian) and secured grants such as Network optimization for HPC workloads (Special Research Fund). At the Internet Technology and Data Science Lab, he collaborates on EU-US initiatives like the Next Generation Internet program, advancing open internet architectures.

Ryan DoengesView profile

Research Fellow

• Programming Languages
• Formal Verification
• Type Systems
• +4 more

Ryan Doenges is a Distinguished Postdoctoral Fellow at Northeastern University in Boston, working with Amal Ahmed. He holds a PhD from Cornell University under Nate Foster and completed undergraduate studies with Zach Tatlock. His educational background includes: PhD in Computer Science, Cornell University Bachelor's degree, institution unspecified Doenges' research focuses on enhancing programming safety through type systems and verification, specializing in program logics for effects/resources like concurrency and memory. His doctoral work established formal semantics and verification frameworks for the P4 network programming language, ensuring termination and correctness. His publications (2017-2025) show consistent advancement from distributed systems verification to network programming (P4) and foundational program logics, culminating in categorical semantics for separation logic. Key themes include certified equivalence, stateful packet processing, and fibrational weakest preconditions. No scientific awards are documented in available sources. He formally supervised Tia Vu's Master's thesis (Cornell MS, now MIT PhD) and informally mentored eight students including Rudy Peterson (ETH Zürich PhD) and Amanda Xu (UW Madison PhD). No grant details are provided. Doenges collaborates with Amal Ahmed's group at Northeastern and previously worked in Nate Foster's Cornell research team focused on network programming languages.

Jason P. JueView profile

Professor

• Optical Networking
• Network Protocols
• Network Survivability
• +7 more

Jason P. Jue is a Professor of Computer Science at the University of Texas at Dallas and director of the Advanced Networks Research Lab. He holds a Ph.D. in Computer Engineering from UC Davis (1999) following M.S. and B.S. degrees in Electrical Engineering from UCLA (1991) and UC Berkeley (1990). Research Interests: His work focuses on next-generation optical network architectures and protocols, including control and management in optical networks, multi-domain optical network protocols, and survivability methods. He has pioneered research in network slicing, software-defined networking, and AI-driven network optimization. Scientific Contributions: Recipient of the prestigious NSF CAREER Award (2002) Recognized for Ph.D. Education & Research (2005) at UTD's Erik Jonsson School Co-authored 3 IEEE Best Paper Awards (Globecom 2005, ONDM 2010, ICC 2011) Leadership Roles: Currently serves on editorial boards of IEEE Communications Surveys and Tutorials and Springer Photonic Network Communications . Former Associate Editor (2009-2012) for IEEE/OSA Journal of Optical Communications and Networking . Organized key conferences as Technical Program Chair of OptiComm 2000 and Co-Chair of multiple IEEE symposia. Lab & Team: Leads the Advanced Networks Research Lab at UT Dallas, mentoring students and collaborating with researchers like Genya Ishigaki, Riti Gour, and Ashkan Yousefpour. The lab focuses on fog computing, optical network survivability, and AI-driven network resource allocation.

• Network Function Virtualization (NFV)
• Cloud Computing
• Resource Allocation
• +8 more

Danny Raz is a Professor at the Technion - Israel Institute of Technology, specializing in computer science and networking. His work focuses on cloud computing, network function virtualization (NFV), resource allocation, and online algorithms. Institution: Technion - Israel Institute of Technology, Haifa, Israel Research interests include: Network Function Virtualization (NFV) and service chaining Stochastic and dynamic resource allocation Online algorithms in random-order models 5G/edge computing infrastructure Blockchain network analytics Over the past decade, his publications in venues like IEEE/ACM Transactions on Networking and INFOCOM address: Optimal deployment of cloud services TCAM-based classification and flow measurement Game-theoretic approaches to load balancing Cost-aware live migration and fault recovery Wireless network optimization (4G/5G) Collaborations with researchers like Yuval Shavitt, Joseph Naor, and Haim Kaplan highlight his interdisciplinary work bridging theory and practice in networking and cloud systems.

• Connected vehicles
• Intelligent transportation systems
• Vehicular networks
• +3 more

Francesco Raviglione è Ricercatore a tempo determinato (Law 240/10 art.24-a) presso il Department of Electronics and Telecommunications (DET) del Politecnico di Torino. Con expertise in Connected Vehicles , Intelligent Transportation Systems , e Wireless Communication , svolge attività di ricerca e insegnamento. Università: Politecnico di Torino Dipartimento: Electronics and Telecommunications Ruolo: Assistant Professor Interessi di Ricerca: Si concentra su architetture di comunicazione per veicoli autonomi e connessi, con particolare attenzione a 5G-based Collective Perception , Time-Sensitive Networking , e ETSI Standards Compliance . Pubblicazioni Recenti: I suoi ultimi lavori trattano Telemetry Analysis , Dynamic Mapping , e Network Optimization per sistemi veicolari, presentati in conferenze IEEE e MedComNet 2024. Insegnamenti: Collabora in diversi corsi post-laurea tra cui Software-defined Communication Systems , Networking Technologies for Connected Vehicles , e Mobile and Sensor Networks . Patents: Co-inventore di un International Patent per V-Edge , una soluzione per Vehicular Edge Intelligence in bande di spettro non licenziate.

• Nonlinear Dynamics
• Symbolic Dynamics
• Heart Rate Variability
• +4 more

Dr. Teodor Buchner is a faculty member at the Faculty of Physics, Warsaw University of Technology. He received his doctoral degree on April 25, 2002, with a dissertation titled "Symbolic dynamics and local ordering measures of selected dynamical systems" under the supervision of Prof. Dr. hab. Jan Jacek Żebrowski. His research focuses on nonlinear dynamics, symbolic dynamics, heart rate variability analysis, electrocardiography, and biomedical physics. Dr. Buchner has made significant contributions to understanding the complex dynamics of physiological systems, particularly focusing on cardiac signals and their relationship with respiratory patterns. His work bridges physics, mathematics, and medical applications, developing novel analytical methods for physiological time series. Analysis of Dr. Buchner's recent publications reveals a strong interdisciplinary focus on applying advanced mathematical and computational techniques to cardiac electrophysiology. His research spans from fundamental theoretical investigations of signal propagation to practical clinical applications, including studies on the effects of SARS-CoV-2 on heart function and the development of deep learning models for ECG analysis. A notable trend is his persistent questioning of conventional assumptions, such as his groundbreaking work on the finite velocity of ECG signal propagation. Dr. Buchner has contributed to educational initiatives at Warsaw University of Technology, including quantum engineering education programs. His work extends beyond traditional physics research into areas such as cryptography and network security, demonstrating the breadth of his expertise and ability to apply physical principles across diverse domains. His research methodology combines theoretical modeling, experimental investigation, and advanced computational techniques to address complex problems in biomedical physics and beyond.

Arpit GuptaView profile

Associate Professor

• Network Security
• Machine Learning for Networking
• Digital Equity
• +5 more

Arpit Gupta is an Associate Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he co-directs the Systems and Networking Lab (SNL). He also serves as a Faculty Scientist at Lawrence Berkeley National Laboratory and holds the Marjorie & Charles Benton Opportunity Fund Fellowship at the Benton Institute. His research focuses on two main areas: developing production-ready machine learning systems for self-driving networks that ensure secure and performant connectivity with limited infrastructure, and enabling data-driven policymaking to address digital inequity through better broadband measurement and analysis. His work bridges networking, security, and analytics to solve real-world problems at scale. Gupta's research has resulted in several influential systems including Trustee (for ML interpretability in networks), BQT (for broadband plan analysis), PINOT (programmable data collection), netUnicorn (network data collection platform), and netFound (network foundation models). His team develops practical solutions that have been deployed in production environments, including at Tencent. NSF CAREER Award (2025) Google Research Scholar Award (2025) Google ML and Systems Junior Faculty Award (2025) IETF/IRTF Applied Networking Prize (2025, 2023) SIGCOMM Doctoral Dissertation Award (2024) Best Paper Honorable Mention, ACM CCS (2022) As a mentor, he has advised multiple award-winning students including Udit Paul who received the SIGCOMM Doctoral Dissertation Award. His research is supported by substantial funding from NSF (including a $700k CAREER award), DoE, Google, Verizon, Cisco, and state agencies including the California Public Utility Commission.

Jacqueline WalkerView profile

Associate Professor

• Telecommunications
• Signal Processing
• Biomedical Signal Processing
• +5 more

Jacqueline Walker is an Associate Professor in the Department of Electronic and Computer Engineering at the University of Limerick, Ireland. She is affiliated with the Centre for Research Training in Foundations of Data Science and the Centre for Robotics and Intelligent Systems. Education: Bachelor of Engineering (University of Western Australia, 1993) B.A. (University of Western Australia, 1988) Research Interests span telecommunications synchronization, nonlinear signal processing, and higher-order statistics with applications in biomedical, speech, and music domains. Key areas include: Satellite and network timing transfer Software Defined Radio (SDR) systems Musical sound synthesis and transcription Biomedical signal reconstruction (EMG/MEAP) Jitter analysis and metastability Recent Publications highlight trends in SDR for offshore energy networks (2023), direct-sequence spread spectrum (2021), and cross-disciplinary work in music processing (2014–2003) and biomedical signal analysis (2005–2001). Her work integrates spectral modeling, genetic algorithms, and bispectrum techniques. Labs & Teams: Active in the Centre for Research Training in Foundations of Data Science and Centre for Robotics and Intelligent Systems, focusing on data-driven and robotic applications.