Find Academic Supervisors

• Cybersecurity
• Machine Learning
• Wireless Sensor Networks
• +5 more

Daniel T. Ramotsoela is an academic researcher at the University of Pretoria's Department of Electrical, Electronic and Computer Engineering, within the College of Engineering, Built Environment and Information Technology. His research focuses on cybersecurity applications for critical infrastructure, particularly water distribution systems and industrial control environments. With over 30 publications spanning from 2015 to 2024, he has established himself as a significant contributor to the fields of intrusion detection, machine learning applications in critical infrastructure protection, and wireless sensor network security. Dr. Ramotsoela's research interests center around applying machine learning techniques to enhance security in critical infrastructure systems. His work particularly emphasizes water distribution networks, where he has published extensively on anomaly detection methods using neural networks and other AI approaches. He also investigates security challenges in 5G networks, industrial environments, and microgrids, with a strong focus on practical implementation challenges. His recent work shows an increasing emphasis on reinforcement learning applications for network resource allocation and admission control in next-generation communication systems. Analysis of his publication trends reveals a consistent focus on applying machine learning to infrastructure security problems, with a clear progression from foundational surveys to more sophisticated technical implementations. His early work (2017-2019) established survey papers on anomaly detection in industrial wireless sensor networks, particularly using water systems as case studies. From 2020 onward, his research became more specialized, addressing specific challenges like behavioral intrusion detection, data imputation in sensor networks, and biometric authentication systems for industrial applications. The most recent publications (2023-2024) demonstrate advanced applications of deep reinforcement learning and multi-agent systems for 5G network optimization and security.

• Machine Learning
• Deep Learning
• Cybersecurity
• +7 more

Amandeep Kaur is a researcher with affiliations across multiple institutions including the University of Cambridge , IIT Delhi , and Central University of Punjab . Her work spans interdisciplinary fields such as machine learning , deep learning , cybersecurity , and biomedical signal processing . Her research focuses on solving complex problems in healthcare, network security, and agricultural technology. Key contributions include optimizing SDN environments for DDoS attack detection, advancing 6G IoMT applications, and developing deep learning models for rice disease detection and COVID-19 classification using X-rays. The 15 most recent articles highlight her expertise in multi-objective optimization , hybrid algorithms , and federated learning for privacy protection. Topics range from smart city management and blockchain security to medical image segmentation and sentiment analysis in multilingual contexts.

• Optical Communications
• Network Engineering
• Software-Defined Networking (SDN)
• +3 more

Saquib Amjad is an academic researcher affiliated with the Chair of Communication Networks at the Technical University of Munich (TUM), led by Prof. Wolfgang Kellerer. His work focuses on optical communications, network engineering, and software-defined networking (SDN), with a particular emphasis on optimizing network architectures for 6G and future telecommunication systems. He is actively involved in research projects such as the ERC Network Flexibility and 6G Future Lab Bavaria, contributing to advancements in elastic optical networks, spectrum efficiency, and network resilience. Amjad’s research addresses challenges in network planning, resource allocation, and vendor-agnostic SDN solutions. His publications highlight innovations in adaptive regenerations for elastic optical networks and minimizing traffic disruptions in next-generation optical transport systems. He collaborates on open-source tools for optical network simulation and has contributed to projects like the BMBF OptiCON initiative, focusing on optimizing optical network capacity and long-term scalability. His work trends emphasize a blend of theoretical and applied research, with a focus on practical implementations in real-world network environments. Key themes include improving network efficiency through dynamic hypervisor placement and enhancing network flexibility to support evolving 6G requirements. Amjad holds an M.Sc. and maintains contacts through his TUM affiliation. He is involved in various academic activities, including conference presentations and contributions to major networking conferences such as ONDM, OFC, and NoF.

• Software Defined Networking
• Programmable Data Planes
• Machine Learning
• +3 more

Cristian Bermudez Serna is a researcher at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich (TUM). He holds an M.Sc. in Electrical Engineering from TUM and a Bachelor's in Telecommunications Engineering from Universidad de Antioquia, Colombia. His research focuses on mechanisms for efficient network reconfigurations in mobility scenarios, with emphasis on Software Defined Networking (SDN), programmable data planes, and machine learning applications in networking. Education: Bachelor's in Telecommunications Engineering, Universidad de Antioquia (2016) M.Sc. in Electrical Engineering, Technical University of Munich (2021) Research Interests: Optical access networks planning and robustness Future railway communication systems Survivable multi-domain network routing Post-quantum cryptography in optical networks Publications span topics like infrastructure cost savings in rural PONs, survivable routing mechanisms, and SDN control plane optimization. His work integrates algorithmic approaches with real-world network challenges in telecommunications and transportation systems.

• 5G/6G Networks
• Cloud-Native Core Networks
• Software-Defined Networking (SDN)
• +3 more

Endri Goshi is a Researcher at the Chair of Communication Networks (Prof. Wolfgang Kellerer) at the Technical University of Munich (TUM). He holds a Master of Science in Communications Engineering (2019, distinction) and a Bachelor’s in Electronics Engineering (2015). His research focuses on Virtualized/Cloud-Native Core Networks, Software-Defined Networks (SDN), and Programmable Networks. He has contributed to projects like the ERC Network Flexibility initiative and the 6G Future Lab Bavaria. His work emphasizes network orchestration, edge computing, and fault-tolerant systems. Education: B.Sc. Electronics Engineering, Polytechnic University of Tirana, Albania (2015) M.Sc. Communications Engineering, TUM (2019, distinction) Research Interests: Cloud-Native Mobile Core Networks Edge Computing & Network Function Virtualization SDN/Programmable Networks Network Orchestration & Resource Management Byzantine Fault-Tolerant Systems Recent Work Trends: His publications (2021–2025) address challenges in 5G/6G core networks, including mMTC traffic modeling, UPF placement optimization, and procedure-based stateless architectures. He also explores reproducible data plane performance modeling and hardware-accelerated fault tolerance. Lab/Affiliations: Active at the FlexComNetsLab and involved in TUM’s 6G testbed initiatives.

• Networked Control Systems
• Wireless Communication
• Transport Layer Protocols
• +3 more

Polina Kutsevol is a Ph.D. candidate at the Chair of Communication Networks (Prof. Wolfgang Kellerer) at the Technical University of Munich (TUM). Her research focuses on transport layer protocols, wireless networked control systems, and SD-RAN architectures. She holds a B.Sc. in Applied Mathematics and Physics from the Moscow Institute of Physics and Technology (2019) and an M.Sc. in Communication Engineering from TUM (2021). Research Interests : Semantic-aware transport protocols, real-time networked control systems, software-defined networking (SDN), and optimization of wireless communication systems. Her work bridges theoretical foundations (e.g., information theory) with practical implementations in 5G/6G networks and multi-hop systems. Key Contributions : Recent studies include optimizing throughput in SD-RAN environments, evaluating packet prioritization in control systems, and developing task-oriented scheduling frameworks. She collaborates with research groups like the FlexComNetsLab and contributes to projects such as the 6G Future Lab Bavaria . Advising & Grants : Advises students on thesis topics related to networked control systems and transport protocols. Engaged in funded projects exploring next-generation network architectures and protocols. Labs/Teams : Active member of the Chair of Communication Networks and FlexComNetsLab , leveraging experimental setups like the 6G Testbed (6G-IP Lab) for protocol testing.

• Cloud-Native Network Functions (CNFs)
• Kubernetes Orchestration
• Telecom Cloud Infrastructure
• +4 more

Razvan-Mihai Ursu is a Researcher at the Chair of Communication Networks (Lehrstuhl für Kommunikationsnetze) at the Technical University of Munich, led by Prof. Wolfgang Kellerer. His research focuses on cloud-native network functions (CNFs), Kubernetes-based orchestration, energy-efficient telecom cloud architectures, and network security in open RAN systems. He holds a Master’s degree in Electrical Engineering and Information Technology from TUM (2023) and has been actively involved in the Chair since June 2023. Key research areas include: Design and optimization of Kubernetes orchestration for telecom core networks Energy-efficient redundancy models for telco applications Simulation frameworks for multi-tier Kubernetes deployments (e.g., using Shadow simulator) Security vulnerabilities in O-RAN nearRT-RIC platforms Autonomous network adaptation via digital twins He supervises master’s theses on topics such as CNF orchestration tools evaluation, energy optimization in Kubernetes clusters, and security testing of FlexRIC platforms. His work aligns with projects like the 6G Future Lab Bavaria and the ERC Network Flexibility initiative. Current projects involve advancing simulations for Kubernetes-based systems and developing mathematical models to optimize telecom cloud redundancy for energy efficiency while maintaining service availability.

• Flow-Aware Networking
• Optical Networks
• Network Resilience
• +5 more

Andrzej Jajszczyk is a prominent researcher in telecommunications and computer networks, with extensive contributions spanning Flow-Aware Networking, optical networks, resilience mechanisms, and Quality of Service (QoS) architectures. His work frequently appears in IEEE publications and conference proceedings, reflecting his active role in advancing network technologies. Research Focus: Jajszczyk's primary interests include congestion control algorithms, network reliability frameworks, and traffic management in Flow-Aware Networks. Recent work explores nanocommunications (FRET-based signaling) and energy-efficient cloud-fog interplay. His research consistently addresses both theoretical models and practical implementations in optical and software-defined networks. Publication Trends: Analysis of his 15 most recent articles reveals strong emphasis on: (1) Optimization of optical routing and spectrum allocation, (2) Nanoscale communication systems for biomedical applications, (3) Congestion mitigation in flow-oriented architectures, and (4) Energy-aware network resource provisioning. The work demonstrates consistent innovation in network resilience and QoS frameworks since the early 2000s. Awards & Recognition: No specific scientific awards or fellowships are documented in the provided text. Academic Leadership: Jajszczyk has edited IEEE Communications Magazine features and co-authored comprehensive books like Guide to Flow-Aware Networking . While student advisees aren't listed, his frequent collaborations (e.g., with Domżał, Wójcik) suggest mentorship roles.

• Automated Deduction
• Program Synthesis
• Logic Programming
• +4 more

Richard J. Waldinger is a distinguished researcher at SRI International in Menlo Park, California, with a career spanning over five decades in the fields of automated deduction, program synthesis, and artificial intelligence. His work has significantly influenced the theoretical foundations of computer programming and automated reasoning. Waldinger's research focuses on deductive question answering, program synthesis, and applying logical methods to artificial intelligence problems. His work bridges theoretical computer science with practical applications in knowledge representation, natural language processing, and semantic web technologies. He has been particularly influential in developing methods for translating natural language queries into formal logical representations that can be processed by automated reasoning systems. His recent publications demonstrate a continued focus on natural language access to structured data, health informatics applications, and semantic web technologies. Waldinger's work has evolved from foundational program synthesis research to contemporary applications in question answering systems and semantic technologies. Herbrand Award (2016) - Recognizing his significant contributions to automated deduction Waldinger has maintained a prolific research career through extensive collaborations with leading researchers in artificial intelligence and automated reasoning. His work with Zohar Manna represents one of the most influential collaborations in the field of program synthesis. He has also worked with researchers on projects involving health information systems, semantic web technologies, and natural language interfaces to databases. His research has been supported by various funding sources including DARPA, as evidenced by his work on DAML (DARPA Agent Markup Language). Waldinger has been associated with SRI International's Artificial Intelligence Center, where he has contributed to numerous projects involving automated reasoning, knowledge representation, and natural language processing. His work has helped establish formal methods for program synthesis and deductive question answering that continue to influence contemporary research in artificial intelligence.

• Computer Science
• Network Virtualization
• Cloud Computing
• +4 more

R. Boutaba is a prominent academic in the field of computer science and networking, with extensive research contributions in cloud computing, network virtualization, and software-defined networking. His work is widely cited and published in top-tier IEEE and Springer journals and conferences. His research interests include network management, virtualization, cloud computing, and the application of machine learning in networking. He has contributed foundational surveys and algorithms in network function virtualization and virtual network embedding, influencing both academic and industrial developments. The recent articles show a strong trend toward intelligent network management, leveraging machine learning and virtualization to optimize network performance, reduce operational costs, and enhance security. His work spans theoretical modeling and practical implementation in SDN and NFV environments. Network Virtualization Cloud Computing Machine Learning for Networking Software-Defined Networking Network Security Resource Allocation R. Boutaba has collaborated with researchers such as Reaz Ahmed, S. R. Chowdhury, and Mosharaf Chowdhury. While specific details of grants and advising are not provided in the text, his high citation count and publication volume suggest significant research leadership and student supervision. He is affiliated with a major research institution, though not explicitly named here, and continues to be active in advancing networking technologies.

Martin SerrorView profile

Researcher

• Industrial Internet of Things (IIoT) Security
• Machine-to-Machine Communication
• Low-Latency Wireless Networks
• +7 more

Martin Serror is a researcher at the Chair of Communication and Distributed Systems at RWTH Aachen University , where he has been active since March 2015. He earned his Ph.D. in Computer Science from RWTH Aachen University in 2021 and his master’s degree in 2014. His research lies at the intersection of industrial IoT security and reliable low-latency communication systems. University: RWTH Aachen University School: Faculty of Mathematics, Computer Science and Natural Sciences Department: Department of Computer Science Academic Rank: Researcher His research interests include industrial IoT security , machine-to-machine communication , cooperative wireless networks , and network intrusion detection . He focuses on developing secure, efficient, and reliable communication protocols for industrial environments, particularly under strict latency and bandwidth constraints. His work often integrates SDN, behavioral modeling, and cryptographic techniques to enhance system resilience. His recent publications demonstrate a strong trend toward practical security solutions for industrial control systems , including authentication protocols (e.g., BP-MAC), intrusion detection frameworks (e.g., INSIDE, METRICS), and secure data handling in power grids. He contributes to high-impact venues such as IEEE LCN, ACM WiSec, and IEEE Transactions on Industrial Informatics. Martin Serror has actively advised numerous bachelor’s and master’s students at RWTH Aachen University, supervising theses on topics ranging from secure industrial communication to SDN-based security and anomaly detection. He has collaborated extensively with researchers like Klaus Wehrle, Martin Henze, and Eric Wagner. While no formal awards are listed in the provided text, his consistent publication record in top-tier venues reflects significant scholarly impact. He is currently involved in the CONSENT and KoI research projects, indicating ongoing active research in industrial cybersecurity. He is affiliated with the Department of Computer Science and contributes to the academic ecosystem through advising, collaborative research, and innovative security methodologies for critical infrastructure.

Lukas PolzinView profile

Researcher

• Microwave Engineering
• Integrated Circuits Design
• High-Frequency Systems
• +3 more

Lukas Polzin is a Researcher at the Department of Electronic Circuit Technology within the Faculty of Electrical Engineering and Information Technology at Ruhr University Bochum. His work focuses on high-frequency integrated circuits, phase-locked loops, and microwave engineering. He contributes to projects involving SiGe:C BiCMOS technology and ultrafast circuit design. Research interests include millimeter-wave circuits, low-phase-noise prescalers, wideband frequency synthesis, and advanced signal processing techniques. His publications address challenges in high-linearity circuits, ultra-wideband frequency generation, and phase noise optimization. Polzin collaborates on projects like the 142-GHz dual-modulus prescaler and ultra-wideband chirp generators, demonstrating expertise in both analog circuit design and system-level integration. His work often intersects with practical applications in telecommunications and high-frequency systems.

• Computer Science
• Disaster Management
• Health Informatics
• +3 more

Mina Abadeer is a Researcher affiliated with the University of Münster, Germany. She is based in Room 710 at Einsteinstraße 62, 48149 Münster. Her work focuses on agent-based modeling, disaster management simulations, and machine learning integration into complex systems. Key projects include contributions to the CrowdSim system for crowd behavior analysis and the PACXX framework for parallel computing. She actively participates in teaching and research activities, including courses on distributed systems and interactive simulations. Her research interests emphasize the practical application of computational models to real-world challenges, such as pandemic response, evacuation planning, and network optimization. She has published widely on topics like QoS-aware routing mechanisms in SDN networks and interactive simulation frameworks for disaster recovery scenarios. Her work bridges theoretical computer science with applied systems engineering, addressing both technical and societal challenges through interdisciplinary approaches.

• Network Security
• Cyber-Physical Systems Security
• BGP Routing Security
• +6 more

Gabi Dreo Rodosek is a distinguished researcher and faculty member at Bundeswehr University Munich , Germany. With a prolific publication record spanning over three decades, she has contributed extensively to the fields of network security, cyber-physical systems, BGP routing security, and software-defined networking (SDN). Research Interests: Network Security & Intrusion Detection BGP Routing Security & RPKI Software-Defined Networking (SDN) Malware Analysis & Adversarial Machine Learning Mobile Ad-hoc Networks (MANETs) Content Delivery Networks & IP Geolocation Her recent work focuses on advanced BGP security mechanisms, including path plausibility algorithms and RPKI deployment strategies. She has also explored adversarial techniques in machine learning, particularly in the context of malware detection and evasion. Her research in SDN-based defenses includes novel frameworks for DDoS mitigation and anomaly detection in 5G networks. Scientific Contributions: Over 159 peer-reviewed publications (1991–2025) Key contributions to BGP security, including RPKI validation and route leak mitigation Pioneering work in adversarial machine learning for cybersecurity Development of SDN-based intrusion detection and threat hunting frameworks Collaborations & Advising: She has mentored and collaborated with numerous researchers, including Nils Rodday, Peter Hillmann, Florian Steuber, and Raphael Labaca Castro. Her work often involves interdisciplinary teams tackling challenges in network security, AI-driven defense mechanisms, and resilient communication systems. Labs & Teams: While specific lab affiliations are not detailed in the provided text, her extensive collaboration network and affiliation with Bundeswehr University Munich suggest involvement in leading cybersecurity and networking research initiatives.

• Network Management
• Software-Defined Networking
• 5G/6G Networks
• +4 more

Cédric Prosper Chemouil is a Professor at Institut Mines-Télécom, Télécom SudParis , affiliated with the Cédric Laboratory . His work focuses on Network Management , Software-Defined Networking , and 5G/6G Networks , with a strong emphasis on Network Slice Robustness and Teletraffic Engineering . He has contributed extensively to IEEE journals and conferences as a guest editor and organizer. Dr. Chemouil's research trends include the integration of Artificial Intelligence and Machine Learning into network management, optimization of UAV Support Systems , and advancements in Secure Systems for future networks. His recent publications highlight 6G Network Slice frameworks, MANO Evolution , and AI for SLA Management . He has served as a guest editor for multiple IEEE journals, including IEEE Transactions on Network and Service Management and IEEE Journal on Selected Areas in Communications , and has organized key conferences such as IEEE NetSoft and NOMS . His collaborations span institutions like University College of London , Università di Bologna , and China Mobile Research Institute .