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Rubi DebnathView profile

Researcher

• Time-Sensitive Networking
• Machine Learning
• Optimization
• +3 more

Rubi Debnath is a researcher at the Technische Universität München (TUM) affiliated with the Department of Embedded Systems and Internet of Things . They focus on Time-Sensitive Networking (TSN) , Machine Learning for TSN , and Optimization of TSN Scheduling Algorithms using heuristics, ILP, and DRL. Specializes in TSN Scheduling , Runtime Reconfiguration , and Wireless-TSN Actively teaches IoT Security , Software Architecture for Distributed Embedded Systems , and System Design for IoT since Winter Semester 2018/2019 Supervised over 15 Master's and Bachelor's theses on TSN, ML, and 5G-TSN integration Developed simulation frameworks like CyclicSim and 5GTQ Research Trends : Recent publications address TSN scheduling optimization , ML-assisted traffic classification , and 5G-TSN integration , with a focus on low-latency communication and industrial automation . Scientific Awards : IEEE ComSoc Four Minute PhD Thesis Competition - Third Prize Winner (Round 2), Round 1 Winner Global Fellows Program - Imperial College London, TUM, and NTU Singapore Advising and Grants : Supervised 15+ theses on TSN, ML, and 5G-TSN. Involved in the 6G Research Hub "6G-Life" and nIoVe cybersecurity framework for IoT.

• Optical Communications
• All-optical Networks
• Traffic Engineering
• +8 more

Salvatore Spadaro is a Full Professor in the Optical Communications group at the Universitat Politècnica de Catalunya (UPC), affiliated with the Signal Theory and Communications Department. He holds M.Sc. and Ph.D. degrees in Telecommunications Engineering from UPC, along with a Dr. Ing. in Electrical Engineering from Politecnico di Torino. His research focuses on optical networking advancements, including all-optical networks, traffic engineering, resilience, optical transmission technologies, and software-defined networking (SDN)/network function virtualization (NFV). He is a Senior IEEE Member since 2016. Education: M.Sc. in Telecommunications Engineering, Universitat Politècnica de Catalunya (2000) Ph.D. in Telecommunications Engineering, Universitat Politècnica de Catalunya (2005) Dr. Ing. in Electrical Engineering, Politecnico di Torino (2000) Research Interests: His work emphasizes cutting-edge topics such as multi-granular optical switching, optical network virtualization, deterministic networks for 5G/6G, disaggregated data center architectures, and the integration of machine learning into network control systems. He explores energy-efficient optical transmission techniques, including probabilistic constellation shaping and spatial division multiplexing (SDM), while addressing challenges in latency-sensitive industrial control systems and IoT applications. Publications & Awards: With over 150 publications, his recent work highlights advancements in AI-driven network control for deterministic services, energy savings in flex-grid optical networks, and failure analysis of ML/AI-supported disaggregated data centers. His IEEE Senior Membership reflects recognition of his contributions to telecommunications research. Key Contributions: Spadaro leads projects on network slicing for 5G/6G, autonomous resource management in optical data centers, and cross-domain orchestration of time-sensitive services. His lab develops experimental frameworks for SDN-enabled optical infrastructures and collaborates on international initiatives like the ALLIANCE project for 5G beyond networks.

Dirk PeschView profile

Professor

• Artificial Intelligence
• Data Analytics
• Algorithmics
• +9 more

Professor Dirk Pesch is a faculty member at the School of Computer Science and Information Technology , University College Cork. His research focuses on Internet of Things (IoT) , Cyber-Physical Systems , and Smart Manufacturing , with applications in Smart Communities , Health & Wellbeing , and Industrial Automation . As Director of the SFI Centre for Research Training in Advanced Networks for Sustainable Societies and Co-Principal Investigator of the CONNECT Centre , he leads large-scale research initiatives. He has secured over €80M in research funding and authored 250+ scientific publications. His leadership in the Cork Smart Gateway initiative and founding of the Nimbus Research Centre highlight his industry-focused impact. His recent work explores 5G/6G integration with Time-Sensitive Networking (TSN) , machine learning for loneliness detection , and interoperability solutions for IoT ecosystems . He contributes to international conferences as Technical Programme Co-Chair (IEEE SmartComp 2024) and General Chair (IEEE SmartComp 2025).

• Wireless sensor networks
• Next generation computer networks
• Wireless mesh networks
• +5 more

Professor Cormac Sreenan is a full professor in the School of Computer Science and Information Technology at University College Cork (UCC), where he has been a faculty member since 1999. He served as Head of School from 2019-2021 and previously as Head of Department during 2015-2018 and 2000-2004. Prior to joining UCC, he conducted research at AT&T Labs and Bell Labs in New Jersey, USA. Ph.D. from University of Cambridge Computer Laboratory Member of Christ's College, Cambridge Academic lineage traces to computing pioneer Maurice Wilkes Professor Sreenan leads the Mobile & Internet Systems Lab (MISL), focusing on mobile and multimedia networking. His research spans wireless sensor networks, next generation computer networks, wireless mesh networks, and multimedia networking & systems, with specialist expertise in adaptive video streaming. With over 200 peer-reviewed publications and 9 patents, his work bridges theoretical research with practical applications in industry. His recent publications (2024-2025) demonstrate continued innovation in 5G networks, time-sensitive networking, and machine learning applications for network optimization. These works address critical challenges in industrial IoT, smart factories, and next-generation communication systems. Fellow of the British Computer Society (2005) Fellow of the Irish Academy of Engineering (2022) 9 granted patents Professor Sreenan has advised over 30 PhD and postdoctoral researchers through his lab, with significant industry impact through technology transfer, collaboration with Irish companies, and licensing of research outputs. He has served as an expert witness in telecoms, mobile networks, and IoT, and has extensive experience as an External Examiner for degree programs at leading international institutions. The Mobile & Internet Systems Lab under Professor Sreenan's leadership has developed innovative solutions for emergency response networks, adaptive video streaming, and IoT applications, with funding from Science Foundation Ireland, Enterprise Ireland, Horizon 2020, and other agencies. The lab's research has substantial real-world applications in smart cities, industrial automation, and next-generation communication systems.

Christian HagenlocherView profile

Researcher

• Laser Manufacturing
• Real-Time Networking
• Industrial Automation
• +3 more

Christian Hagenlocher is a researcher and Head of the Process Fundamentals Department at the Institute for Beam Tools (IFSW) within the University of Stuttgart. His work focuses on laser-based manufacturing processes, real-time networking, and industrial automation, particularly in the context of Industry 4.0 and cyber-physical systems. He is associated with projects involving Time-Sensitive Networking (TSN) and flexible production environments.

Pieter J.L. CuijpersView profile

Associate Professor

• Cyber-Physical Systems
• Real-Time Systems
• Formal Methods
• +6 more

Pieter J.L. Cuijpers is an Associate Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), affiliated with the Interconnected Resource-aware Intelligent Systems (IRIS) group and EAISI Mobility. His research focuses on quantitative formal modeling of cyber-physical systems, real-time scheduling, and performance analysis of embedded systems, leveraging tools like max-plus algebra and the Lean proof assistant. He holds an MSc in Electrical Engineering (2000) and a PhD in Computer Science (2004), both from TU/e. Research interests include hybrid systems, energy-aware scheduling, Time-Sensitive Networking (TSN), and formal verification. He teaches courses such as Quantitative Evaluation of Embedded Systems and advocates for innovative educational methods like MOOCs and challenge-based learning (CBL). His work contributes to UN Sustainable Development Goals related to industry, innovation, and infrastructure. Notable recognition includes the Outstanding paper award RTNS 2016 . He coordinates the capstone project CBL Embedded Systems and has mentored 44 students, including master’s thesis advisor for M.P.J. Stevens. His lab, IRIS, explores interconnected systems and resource optimization.

• Industrial Automation
• Real-time Embedded Systems
• Cybersecurity
• +4 more

Philippe Saey is a researcher at KU Leuven specializing in industrial automation, cybersecurity, and embedded systems. His work spans multiple domains including clinical trials technology, robotics education, and astronomical instrumentation. Expertise in industrial communication protocols (PROFIBUS, PROFINET, TSN) Developed open data recording devices for clinical trials Contributed to knowledge-driven control system design for telescopes Research Focus : Real-time systems, network redundancy, and human-centric technology. His 2024 work on TSN synchronization attacks highlights vulnerabilities in Industry 4.0 networks. Earlier projects include low-cost Arduino-based error generators and MATLAB code integration for steel manufacturing. Education & Collaboration : Co-developed project-based robotics curricula with industry partners and contributed to international automation projects like i-MOCCA (Flanders, France, UK). Supervised PhD research on telescope control systems.

• Wireless Communications
• Machine Learning
• Network Optimization
• +3 more

Dr Terry Zhang is a researcher affiliated with the School of Engineering at The University of Sydney. His work spans wireless communications, machine learning, and blockchain technology, focusing on optimizing network efficiency and real-time systems. Research Interests: Ultra-Reliable Low-Latency Communications (URLLC) Deep Reinforcement Learning for Networks Wireless Time-Sensitive Networking (TSN) Blockchain Applications in Information Systems Recent Publications (2021–2024) address topics like unsupervised learning for channel estimation, resource allocation in URLLC, and blockchain-based IoT systems. His work intersects network optimization , AI-driven communication protocols , and emerging information architectures . Grants : Collaborated on the 2025 "Long Range WiFi systems for Underground Mines" project funded by Australia's Economic Accelerator (AEA).

• Algorithmic and complexity
• Periodic Scheduling
• Telecom Networks
• +3 more

GUIRAUD Maël is a Researcher-Lecturer at CESI’s Nanterre Campus, affiliated with the Engineering and Numerical Tools department. He teaches in engineering programs, focusing on algorithmic, programming, operational research, and embedded systems. His research emphasizes periodic scheduling, telecom networks, and Industry 4.0 applications. Education: PhD in Computer Science (DAVID Lab, Université Paris Saclay, 2021), Master AMIS (Université Paris Saclay, 2016), and a Computer Science degree from Université de Versailles Saint-Quentin (2014). Research interests span algorithmic complexity, deterministic scheduling for low-latency networks, and smart infrastructure. Key contributions include work on Cloud RAN scheduling, TSN platforms, and smart building modeling. Recent publications address predictive maintenance in smart buildings and 5G/6G network optimization. His lab focuses on bridging theoretical algorithms with real-world applications in telecommunications and Industry 4.0 systems.

• Internet of Things (IoT)
• Cyber-Physical Systems (CPS)
• Smart Manufacturing
• +4 more

Dirk H J Pesch is a Professor at the School of Computer Science and Information Technology , University College Cork (UCC), and currently serves as Head of School. His research focuses on future networked systems for the Internet of Things (IoT) and Cyber-Physical Systems (CPS), with applications in smart communities, health, and manufacturing. He leads the Science Foundation Ireland-funded ADVANCE CRT and is a co-PI of the CONNECT Centre . Prior to UCC, he was at Cork Institute of Technology (now Munster Tech U), where he founded the Nimbus Research Centre. He holds a PhD from the University of Strathclyde and a Dipl.Ing from RWTH Aachen University. Research Interests include IoT/CPS protocols, system architectures, interoperability challenges, and AI-driven analysis for well-being. He has authored/co-authored over 250 publications and co-edited a book on energy-positive urban systems. His work spans conference organization (e.g., IEEE SmartComp 2025 General Chair) and industry collaborations, with €80M+ in grant funding. Key contributions include developing low-power wireless protocols (e.g., MeshMAC), smart building monitoring systems, and frameworks for IoT in energy-positive neighborhoods. His recent work explores loneliness detection via passive sensing and 6G-V2X technologies for autonomous driving. Grants & Leadership: Directed €16M of his own research grants, managed large-scale EU/Irish projects, and advised on industrial IoT implementations. His Nimbus Centre became a leader in IoT applications under his leadership. Labs/Teams: Founded Nimbus Research Centre; active in Cork Smart Gateway initiative. Supervised numerous students and researchers in interdisciplinary projects.

• Networking
• Communications
• Cybersecurity
• +5 more

Martin Reisslein is a Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His research focuses on advanced networking technologies, cybersecurity, and edge computing, with a specialization in Time-Sensitive Networking (TSN), 5G, and network coding. He collaborates closely with institutions like the National Research Data Infrastructure (NFDI) and has published extensively in top-tier journals and conferences. His work spans theoretical and applied domains, including hardware-software co-design for low-latency systems, cybersecurity for satellite and IoT networks, and AI-driven resource management in transportation networks. Recent projects highlight contributions to TSN testbeds, molecular communication simulations, and unified threat management systems for home networks. Reisslein has co-authored over 270 publications, with notable contributions in IEEE Transactions on Networking, Communications Surveys & Tutorials, and the Journal of Signal Processing Systems. His research emphasizes practical implementations, such as hardware-aligned TSN simulations and flexible measurement frameworks for edge computing.

• Machine Learning
• Internet of Things
• Biomedical Engineering
• +7 more

Md. Mehedi Hasan is a researcher at Daffodil International University's Department of Computer Science and Engineering. With over 17 years of research activity, his work spans multiple domains including Internet of Things (IoT), machine learning, biomedical informatics, and environmental technology. Current affiliations include collaborations with institutions in Bangladesh, Japan, and Malaysia. Research areas: Machine Learning, IoT Security, Medical Imaging, Aquaculture Monitoring Key technologies: Deep Learning, Time Sensitive Networking, Kerberos Authentication Notable contributions: NAND Flash memory analysis, Pediatric health applications, Urbanization impact studies His 2025 publications focus on medical data preservation ( Comput. Biol. Medicine ), pedestrian risk assessment ( Complexity ), and toddler screen time management ( SoftwareX ). Recent work explores the intersection of environmental analysis with deep learning and cryptographic solutions for smart infrastructure. Scientific contributions include: Radiation tolerance analysis of neuromorphic systems (IRPS 2020) Smart meter security protocols (Earth Sci. Informatics 2024) Acoustic breathing phase detection (Proc. ACM IMWUT 2021)

Alexander VerlView profile

Professor

• Industrial Robotics
• Control Engineering
• Mechatronics
• +5 more

Prof. Dr.-Ing. Alexander Verl is a leading academic at the University of Stuttgart , serving as Principal Investigator at the Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) . His work bridges control engineering , industrial robotics , and digital twin technologies to enhance precision in manufacturing systems. Research Interests : Improving positioning accuracy of industrial robots through transmission error modeling and compliance compensation. Developing adaptive preload control mechanisms for cable-driven parallel robots and rack-and-pinion systems. Advancing IT/OT convergence via Time-Sensitive Networking (TSN) and cloud-edge integration. Creating digital twin platforms for real-time simulation and quality monitoring in CNC machining. Exploring deep learning applications for perception of deformable linear objects in automation. Recent Work Trends show expertise in: smart manufacturing , Industry 4.0 , and data-driven control systems . Publications emphasize practical validation through industrial testbeds (e.g., KUKA KR210–2 robotics, CNC machine simulations) and theoretical contributions to elastokinematic models and nonlinear dynamics . Advising & Grants : Collaborates extensively with researchers like Armin Lechler and Michael Neubauer. Projects funded through academic-industry partnerships in automotive production, precision engineering, and Gaia-X-based data ecosystems.

• Network Engineering
• Quality of Service (QoS) Control
• Software-Defined Networking (SDN)
• +3 more

ITO Yoshihiro is a Professor at the Nagoya Institute of Technology , affiliated with the Faculty of Engineering and the Department of Information Engineering, Network Field . He holds a Doctor and Master in Engineering from Nagoya Institute of Technology, completed in 1993 and 1991 respectively. His research focuses on Quality of Service (QoS) control , Software-Defined Networking (SDN) , and Time-Sensitive Networking (TSN) for automotive and industrial Ethernet applications. Doctor (Engineering), Nagoya Institute of Technology Master (Engineering), Nagoya Institute of Technology Bachelor (Engineering), Nagoya Institute of Technology His work evaluates QoS mechanisms like IEEE 802.1TSN , IEEE 802.1AS time synchronization , and SDN-based multi-path TCP optimization . He investigates configurations for gate control lists (GCL) in time-aware shapers and frame preemption (FP) efficiency in automotive networks. Recent studies focus on quantifying congestion-induced synchronization errors and their impact on network reliability. Articles from 2024–2023 highlight trends in automotive Ethernet protocols , TSN standardization , and SDN/P4 integration for dynamic network control. Topics span time synchronization accuracy, traffic shaping techniques, and congestion mitigation strategies across in-vehicle and industrial environments. Best TPC Award (2023) IEICE Communication Society Contribution Award (2019, 2006) IEEE GCCE 2015 Outstanding Paper Award IEICE Young Engineer Award (1999) He has advised students on TSN and SDN research and secured collaborative grants with industry partners like Toyota Central R&D and Panasonic. His committee roles include editorships and leadership positions in IEICE and IPSJ .

• Control Systems
• Industrial Automation
• Networking
• +2 more

An Trieu Tran, MD is an Assistant Professor in the Department of Neurology at the University of California, Irvine (UCI) School of Medicine. Their research focuses on dependable control systems, operational technology integration, and time-sensitive networking. Research interests include: Dependable Model Predictive Control (DepMPC) Operational Technology system architectures Time-Sensitive Networking (TSN) applications Replacement Controller (RC) frameworks In 2020, they co-authored a paper exploring fault-tolerant control systems using multi-controller MPC architectures for enhanced operational reliability. This work was published in an IEEE/IEC 60802-compliant context covering industrial automation, automotive, and power/energy systems.