Find Academic Supervisors

Nils Ole TippenhauerView profile

Professor

• Cyber-Physical System Security
• Industrial Control Systems Security
• Physical-Layer Security
• +7 more

Nils Ole Tippenhauer is a faculty member at the CISPA Helmholtz Center for Information Security , leading the SCy-Phy research group . His academic journey includes an Assistant Professorship at the Singapore University of Technology and Design (SUTD) (2014–2018), a PhD in Computer Science from ETH Zurich (2012), and a Diploma in Computer Engineering from Hamburg University of Technology (2007). He also holds an exchange study year at the University of Waterloo (2004–2005) supported by a DAAD scholarship. Research Interests focus on practical systems security , particularly Security of Cyber-Physical Systems Industrial Control Systems (ICS) and Industrial IoT (IIoT) Physical-Layer Security and Wireless Security Privacy-Preserving Technologies (e.g., DP3T project) Embedded Systems Security Threat Detection & Defenses His work integrates both theoretical and applied approaches, addressing vulnerabilities in critical infrastructures like water systems and power grids. Recent Publications highlight trends in Anomaly detection evasion in industrial networks Microarchitectural side-channel defenses Localization techniques in cellular networks Security analysis of ICS protocols Data-driven vulnerability assessments for robotics Cyber-physical simulation for infrastructure security Scientific Awards include Best paper at DIMVA'23 Distinguished Paper at ACSAC 2022 Best paper at CPSIOTSEC 2022 Best paper at CPSS 2017 K-H Ditze Award for diploma thesis (2007) SG Mark Institution award (2016) Runner-Up at smart energy hackathon (2013) Advising and Grants feature PhD defenses of Daniele Antonioli and Hamid Reza Ghaeini (2022), co-organizing conferences like WiSec and CPSS , and leading projects such as the National Science Experiment (NSE) with 50,000 mobile sensors in Singapore. He also contributed to the DP3T project for privacy-preserving contact tracing. Labs and Teams include the SCy-Phy research group at CISPA and the development of testbeds like SWaT (Secure Water Treatment), WADI (Water Distribution), and EPIC (Electric Power and Industrial Control) at SUTD. These platforms enable hands-on security research in realistic industrial environments.

• Embedded Systems
• Real-Time Systems
• Cyber-Physical Systems
• +7 more

Marco Caccamo is a Professor at the Technical University of Munich (TUM) , holding the Chair of Cyber-Physical Systems in Production Engineering within the Faculty of Mechanical Engineering. He is also a Principal Investigator and Professor at the Department of Computer Science, with courtesy appointments in Electrical and Computer Engineering, Coordinated Science Lab (CSL), and Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC). His research spans Embedded Systems , Real-Time Systems , and Cyber-Physical Systems (CPS) , focusing on resource management, reinforcement learning architectures, and 6D pose recognition for robotics. University of Pisa (B.Sc., 1997) Scuola Superiore Sant'Anna (Ph.D., 2002) Research highlights include predictable resource management on heterogeneous platforms, security frameworks for AI-based controllers , and UAV testbed development . His work integrates deep learning and real-time constraints in industrial applications like avionics, farming, and automotive systems. His 15 most recent publications emphasize cache optimization , memory bandwidth regulation , and reinforcement learning for CPS , with a focus on multi-core processors and DNN inference . Awards include the IEEE Fellow (2018), Alexander von Humboldt Professorship (2018), and multiple Best Paper Awards at RTSS, RTNS, and RTAS. NSF CAREER Award (2003) IEEE Fellow (2018) Alexander von Humboldt Professorship (2018) Best Paper Awards (RTSS 2024, RTNS 2023, ECRTS 2019) He has advised numerous Ph.D. students and postdocs, with a track record in UAV development and industrial collaborations . His lab, the Real-Time and Embedded System Laboratory , focuses on real-time OS and predictable computing .

• Distributed Systems
• Cloud Computing
• Edge Computing
• +7 more

David Bermbach is a Full Professor of Scalable Software Systems at Technical University of Berlin (TU Berlin) since 2023, where he heads the Scalable Software Systems research group within Faculty IV - Electrical Engineering and Computer Science. He is also co-affiliated with the Einstein Center Digital Future (ECDF). Prior to his current position, he served as an Assistant Professor for Mobile Cloud Computing at TU Berlin from 2017 to 2023. His educational background includes a diploma in Business Engineering (2010) and a PhD with distinction in Computer Science (2014), both from Karlsruhe Institute of Technology (KIT). Prof. Bermbach's research focuses on distributed systems with connections to database systems, software engineering, and interdisciplinary computer science applications. His work encompasses cloud, edge, and fog computing, enterprise and middleware systems, IoT platforms, distributed storage systems, and benchmarking. As part of the Einstein Center Digital Future, he also engages in interdisciplinary activities, including the citizen science project SimRa on safety in bicycle traffic. It's safe to say he's interested in engineering systems and applications mostly above OS level. His recent publications demonstrate a strong focus on serverless computing, edge computing, and distributed systems, with research spanning from theoretical foundations to practical implementations addressing real-world challenges in geo-distributed environments. Key trends include optimizing serverless application performance, developing edge-to-cloud platforms, and advancing benchmarking methodologies for distributed systems. Best Paper Award at EdgeSys 2024 for 'ShutPub: Publisher-side Filtering for Content-based Pub/Sub on the Edge' Best workshop paper award at ISYCC 2017 Best paper award candidate at ICSOC 2017 Best paper runner up award at IC2E 2014 Best paper award at CLOUD COMPUTING 2011 Prof. Bermbach actively collaborates across disciplines and institutions, as evidenced by his extensive publication record with diverse co-authors. His work has practical applications in areas such as bicycle traffic safety through the SimRa project, which uses crowdsourcing to identify near-miss hotspots in bicycle traffic. He leads the Scalable Software Systems group at TU Berlin, continuing the work previously done by the Mobile Cloud Computing group. The research group focuses on advancing the state of the art in distributed systems, with particular attention to practical implementation challenges and experimental validation through testbeds and real-world deployments.

Jelena MirkovicView profile

Academic

• Network Security
• Denial-of-Service Attacks
• Vulnerability Scanning
• +6 more

Jelena Mirkovic serves as Principal Scientist at USC Information Sciences Institute (USC/ISI) and Research Associate Professor at the University of Southern California's Thomas Lord Department of Computer Science. She has held faculty positions at USC since 2010, progressing from Research Assistant Professor to her current role as Research Associate Professor since 2017, while also serving as Project Leader at USC/ISI. Her educational background includes: PhD in Computer Science from UCLA (2003) MS in Computer Science from UCLA (2000) B.Sc. in Computer Science from University of Belgrade, Serbia (1998) Mirkovic's research spans network security, human-centered attacks, and cybersecurity experimentation infrastructure. Her work focuses on critical security challenges including botnets, denial-of-service attacks, IP spoofing, vulnerability scanning, and user-centric privacy. She has pioneered methodologies for security experiments and led major infrastructure projects including the DETER testbed and SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation). Analysis of her recent publications reveals consistent innovation across multiple security domains. Her work demonstrates strong technical depth in DDoS defense systems (particularly DNS protection), binary vulnerability analysis, privacy-preserving systems, and security experimentation infrastructure. A notable trend is her focus on bridging theoretical security concepts with practical implementation through large-scale testbeds and real-world data analysis. Her significant scientific achievements include: IEEE Senior Member distinction Best paper award at IEEE COMSNETS 2023 for DNS DDoS defense research Mirkovic has secured substantial research funding as Principal Investigator or Co-PI on numerous grants from NSF, DHS, and other agencies. Current major projects include SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation), DISCERN (Datasets to Illuminate Suspicious Computations), and modernizing DeterLab education infrastructure. She has successfully led multiple REU sites focused on cybersecurity education and workforce development. She directs the STEEL (Security Research Lab) at USC/ISI, which develops innovative security solutions through interdisciplinary research in network security, human factors in security, and cybersecurity experimentation infrastructure. The lab emphasizes practical implementations that address real-world security challenges while advancing theoretical understanding of security systems.

Karl-Erik ÅrzénView profile

Professor

• Control Engineering
• Cyber-Physical Systems
• Real-Time Systems
• +9 more

Karl-Erik Årzén is Professor and Head of the Department of Control Engineering at Lund University's Faculty of Engineering. He is also Co-director of the Wallenberg AI, Autonomous Systems and Software Program (WASP) and a key member of ELLIIT, the excellence center in information technology. His roles include leadership in AI and digitalization profile areas at both LTH and Lund University. His research lies at the intersection of control engineering and computer science, with a focus on cyber-physical systems, real-time systems, embedded control, and resource management in cloud and edge computing environments. He has pioneered methods for predictable performance in cloud applications and dynamic resource allocation using control-theoretic approaches. The recent publications highlight a strong trend in control over the cloud and edge, real-time scheduling co-design, distributed camera systems, and reinforcement learning for auto-scaling. Key topics include model predictive control, LQG-based scheduling, bandwidth allocation, and robustness in cyber-physical systems. The work spans theoretical control design and practical implementation in distributed systems. His scientific awards include multiple Best Paper Awards from IEEE and ACM conferences in 2018, 2016, and 2004, recognizing excellence in autonomic computing, edge computing, and real-time systems. Best Paper Award, IEEE International Conference on Autonomic Computing, 2018 Best Paper Award, IEEE International Conference on Edge Computing (EDGE), July 2018 Best Paper Award - RTNS 2016 Best Paper Award - RTCSA 2004 Årzén has supervised over 20 PhD students, including Mikael Johansson, Anton Cervin, Yang Xu, and Per Skarin, and currently supervises Ahmed Al Bayati and Max Nyberg Carlsson. His grant portfolio includes major projects such as WASP, AORTA (VINNOVA), and ELLIIT's 'Robust and Secure Control over the Cloud'. He has also contributed to innovation through tools like TrueTime and Jitterbug. He leads the RobotLab LTH initiative and is involved in the Nordic University Hub on Industrial Internet of Things (HI2OT). His work bridges academia and industry, with collaborations on adaptive control, cloud-native systems, and autonomous robotics.

Kevin SchneiderView profile

Research Professor

• Power System Analysis
• Grid Modernization
• Microgrids
• +5 more

Kevin Schneider is a Laboratory Fellow at Pacific Northwest National Laboratory (PNNL), a Research Professor at Washington State University (WSU), and an Affiliate Associate Professor at the University of Washington. As manager of PNNL's Office of Electricity Subsector, he leads business development, client relations, and strategic investments in R&D for the grid sector, overseeing portfolios in component design, system modeling, hierarchical controls, secure communications, and energy storage. Dr. Schneider is internationally recognized for his expertise in power system analysis, planning, and operations. His research focuses on improving grid reliability and system flexibility by harnessing advanced grid concepts at the edge of power systems, including microgrids, energy storage, electric vehicles, distributed energy resources, and smart home appliances. At WSU, he is a researcher for the WSU and PNNL Advanced Grid Institute (AGI), implementing layered control architectures to enhance operational flexibility of critical power systems. His work spans multiple disciplines within electrical engineering and power systems, with strong emphasis on practical applications for grid modernization, particularly in grid resilience, microgrid operations, and integration of distributed energy resources. Dr. Schneider is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), where he has served in multiple technical leadership roles. His scientific contributions have been recognized with significant awards: Presidential Early Career Award for Scientists and Engineers (PCASE), 2019 Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Dr. Schneider earned his B.S. in Physics and M.S. and Ph.D. in Electrical Engineering from the University of Washington. He is a licensed Professional Engineer in Washington State. His research has resulted in numerous patents related to power grid technologies, including several focused on voltage and frequency stability of distribution systems. His work has substantial implications for grid modernization efforts and the development of more resilient power systems in the face of climate change and other challenges.

• 5G/6G Networking
• Network Slicing
• Intent-Based Networking
• +5 more

Adlen Ksentini is a Professor at EURECOM, a leading graduate school and research center in Sophia Antipolis, France, specializing in digital science and communication systems. His extensive research focuses on next-generation mobile networks (5G/6G), network management, and the integration of artificial intelligence with telecommunications infrastructure. Dr. Ksentini actively contributes to major EU research initiatives including 6G-BRICKS and AC3, serving as a key researcher and project leader in the development of future network architectures. Dr. Ksentini's research interests center around network slicing, intent-based networking, edge computing, and the application of machine learning to network management problems. His work bridges theoretical advancements with practical implementations in 5G/6G systems, with particular emphasis on zero-touch network management, energy efficiency optimization, quality of service assurance, and the integration of large language models with network operations. His research has significantly contributed to the development of O-RAN (Open Radio Access Network) frameworks and the evolution of network automation. His recent publication trends reveal a strategic shift toward AI-native network architectures, with increasing focus on integrating large language models (LLMs) with network management systems. His work demonstrates a clear progression from traditional network management approaches to more autonomous, AI-powered systems capable of intent-based configuration, self-optimization, and predictive maintenance. The publications show strong emphasis on practical implementations within the 6G research ecosystem, addressing critical challenges in network slicing, resource allocation, and energy efficiency. As a research supervisor, Dr. Ksentini mentors several PhD students including Abdelkader Mekrache, Karim Boutiba, Bouziane Brik, and Houda Hafi, who frequently appear as co-authors on his publications. His research is primarily funded through major EU research projects such as 6G-BRICKS (Building Reusable Testbed Infrastructures for Cloud-to-Device Breakthrough Technologies) and AC3 (which focuses on Cloud Edge Continuum). Dr. Ksentini is actively involved with the 6G-BRICKS project consortium and the AC3 project team, where he contributes to developing next-generation network architectures that integrate communication, computing, and sensing capabilities. His work within these projects focuses on creating reusable testbed infrastructures and addressing security and trust management challenges in the cloud-edge continuum.

Arpan GujaratiView profile

Academic

• Real-Time Systems
• Distributed Systems
• Cyber-Physical Systems
• +7 more

Arpan Gujarati is a Sessional Lecturer in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Systopia Lab. He teaches graduate and undergraduate courses such as CPSC 538G (Distributed Systems), CPSC 416 (Operating Systems), and CPEN 432 (Real-Time System Design). He holds a PhD from the Max Planck Institute for Software Systems and TU Kaiserslautern, where he was supervised by Björn B. Brandenburg. PhD: Max Planck Institute for Software Systems & TU Kaiserslautern (2020) Undergraduate: Birla Institute of Technology and Science (BITS Pilani) Postdoctoral Researcher: MPI-SWS Research Associate: UBC Software Development Engineer: Citrix R&D, India His research focuses on real-time and distributed systems, with applications in cyber-physical systems, fault tolerance, and machine learning reliability. He investigates scheduling algorithms, reliability analysis, and the integration of learning-enabled components into safety-critical systems. His work combines theoretical analysis with practical system implementations, often involving real-world testbeds and open-source tools. His recent publications span top-tier venues including RTSS, OSDI, ECRTS, DSN, and Middleware, with a strong emphasis on performance predictability, resilience of ML systems, and real-time communication. His work frequently addresses challenges in timing guarantees, fault tolerance, and system reliability in both cloud and embedded environments. SIGBED Paul Caspi Memorial Dissertation Award Best Paper Award at RTSS 2022 Distinguished Artifact Award at OSDI 2020 Best Student Paper Award at Middleware 2017 Outstanding Paper Award at RTCSA 2025 He advises several PhD students and undergraduate researchers at UBC, including Heng Zhao, Aida Aminian, Zainab Saeed Wattoo, and Philip Schowitz. He has led multiple research projects involving robotic arms, NVIDIA Holoscan, FreeRTOS, and distributed key-value stores. His lab work emphasizes reproducibility, open datasets, and practical system building. He has served on program committees for RTSS, RTAS, ECRTS, and Middleware, and contributes to journals such as Real-Time Systems and JSys.

• Network and Service Management
• Cybersecurity
• Distributed Systems
• +5 more

Aiko Pras is a Professor at the University of Twente in Enschede, Netherlands. His research spans network and service management, cybersecurity, and distributed systems, with a focus on DNS security, DDoS mitigation, IPv6, and software-defined networking. Research Interests: Network and Service Management Cybersecurity and DDoS Mitigation DNS Security and IPv6 Software-Defined Networking (SDN) Internet Measurement and Performance Critical Infrastructure Protection (ICS/SCADA) Article Trends: Pras's recent work emphasizes collaborative DDoS defense, DNS security, and IPv6 vulnerabilities. His studies often involve large-scale measurements and propose practical solutions for internet resilience and security. Collaborations: He frequently collaborates with Anna Sperotto, Roland van Rijswijk-Deij, and other experts in network security and measurement.

• Machine Learning
• Control Systems
• Robotics
• +3 more

Sebastian Trimpe is a Full Professor and Head of the Institute for Data Science in Mechanical Engineering at RWTH Aachen University, concurrently serving as Co-Executive Director of the RWTH Center for Artificial Intelligence since 2023. Previously, he led a Max Planck Research Group at the Max Planck Institute for Intelligent Systems from 2018 to 2022. His educational background includes: Ph.D. in Dynamic Systems and Control from ETH Zurich (2013) Dipl.-Ing. (M.Sc.) in Electrical Engineering from TU Hamburg (2007) MBA in Technology Management from TU Hamburg (2007) B.Sc. in General Engineering from TU Hamburg (2005) Professor Trimpe's research integrates machine learning with control theory to address safety and efficiency challenges in autonomous systems. His work spans theoretical frameworks for robust decision-making under uncertainty and practical implementations in robotics, with particular emphasis on event-triggered control, distributed systems, and data-efficient learning methodologies. Key contributions include novel approaches to safe reinforcement learning and model predictive control with guaranteed stability. Analysis of his recent publications reveals a pronounced focus on bridging machine learning with control engineering, especially in safety-critical robotics applications. Common themes include distribution-aware learning for medical diagnostics, diffusion-based control approximation, and hardware-in-the-loop validation of theoretical frameworks, demonstrating strong alignment between algorithmic innovation and real-world deployment. His scientific achievements have been recognized with prestigious honors: IFAC World Congress Interactive Paper Prize (2011) Klaus Tschira Award for public understanding of science (2014) Best Paper Award at International Conference on Cyber-Physical Systems (2019) Future Prize by Ewald Marquardt Stiftung (2020) As institutional leader, he directs the Institute for Data Science in Mechanical Engineering and co-leads the RWTH AI Center, overseeing strategic research initiatives and industry collaborations. His academic service includes editorial roles for IEEE Control Systems Society conferences and participation in the Cluster of Excellence 'Internet of Production'. The Institute for Data Science in Mechanical Engineering operates as a multidisciplinary hub where fundamental research in learning-based control meets industrial applications. Current projects focus on drone swarm coordination, deformable object manipulation, and medical diagnostics systems, leveraging both simulation environments and physical testbeds like the Mini Wheelbot platform.

Sonja Isabel VeithView profile

Researcher

• Science Education
• Phenomenography
• Physics Education
• +6 more

Dr. Sonja Isabel Veith is a Scientific Staff member at the Institute for Special Education, Faculty of Philosophy, Leibniz University Hannover. Her work focuses on research and teaching in the fields of scientific and technical education, with a strong emphasis on phenomenography and inclusive didactics. Phenomenographic Research Science Education Physics & Computer Science Teaching Biomedical Optics Artificial Intelligence Applications Educational Background: M.Sc. in Physics (minor: Meteorology), Leibniz University Hannover B.Sc. in Physics (minor: Computer Science), Leibniz University Hannover Fellow of the International Max Planck Research School on Gravitational Wave Astronomy Dr. Veith's research explores children's perceptions of physics concepts like sound, interdisciplinary science education, and racism-critical teaching methods. She has developed innovative didactic approaches for visualizing sound and integrating computational thinking in elementary education. Her publications show a consistent focus on: Phenomenographic analysis of science concepts Physics education in elementary schools Interdisciplinary teaching methods AI applications in sensor data analysis Historical and societal contexts in science Inclusive didactic frameworks Scientific Honors: Fellow of the International Max Planck Research School on Gravitational Wave Astronomy Dr. Veith has collaborated extensively across disciplines, working with institutions such as the Albert Einstein Institute and Laser Zentrum Hannover. Her career spans multiple domains including physics, computer science, biomedical optics, and educational theory.

Sönke KnochView profile

Researcher

• Human-Computer Interaction
• Activity Recognition
• Process Mining
• +3 more

Dr. Sönke Knoch is a researcher affiliated with the Ubiquitous Media Technology Lab (UMTL) at the Saarland Informatics Campus and the German Research Center for Artificial Intelligence (DFKI) GmbH . His work focuses on Human-Computer Interaction , Activity Recognition , Process Mining , and Industry 4.0 technologies. Current Affiliation: DFKI GmbH (Saarland Informatics Campus) Academic Role: Researcher Research Interests span digital twins, augmented reality in manufacturing, and safety-critical systems. He leads projects like RZzKI (AI and Digital Transformation) and BaSySafe (risk assessment via management shells). His work addresses zero-defect manufacturing and cognitive support for impaired workers . Recent Publications focus on digital twins for industrial safety, AR-based task adaptation , and AI quality management in smart factories. Key themes include human-centric AI , real-time process conformance , and context-aware systems . Leadership includes contributing to the WALL-ET project for autonomous logistics and co-developing the PARTAS system for cognitively impaired workers.

Tim SchwartzView profile

Research Professor

• Human-Robot Interaction
• Multi-modal Interaction
• Industry 4.0
• +3 more

Dr. Tim Schwartz is an Associated Member at the German Research Center for Artificial Intelligence (DFKI) located at the Saarland Informatics Campus in Saarbrücken, Germany. He is affiliated with the Ubiquitous Media Technology Lab (UMTL) where he conducts research at the intersection of human-robot interaction, multimodal interfaces, and industrial applications. His work spans over two decades with significant contributions to the fields of robotics, augmented reality, and Industry 4.0 implementations. Dr. Schwartz's research interests focus primarily on Human-Robot Interaction , Multi-modal Interaction , and Industry 4.0 applications. His work explores how humans and robots can effectively collaborate in industrial settings, with particular attention to communication modalities, task division, and intuitive interfaces. Recent projects include human-robot collaboration in assembly cells, social cognitive robots for warehouse environments, and augmented reality applications for aircraft manufacturing. Analysis of his publication history reveals a clear trajectory from foundational work in multimodal interfaces and context-aware computing (2005-2015) toward increasingly applied research in industrial robotics and human-robot collaboration (2016-2024). His most recent publications demonstrate a strong emphasis on practical implementations in manufacturing and warehouse environments, with a particular focus on optimizing work dynamics between humans and robots. Dr. Schwartz actively engages in academic supervision, offering thesis opportunities such as the user-study on optimal work dynamics in human-robot collaboration at the Power4Production Hall in Saarbrücken. His collaborations extend to institutions including ZeMA (Zentrum für Mechatronik und Automatisierungstechnik gGmbH), indicating strong industry-academia partnerships. At DFKI, he works within a vibrant research community that includes numerous colleagues in the Ubiquitous Media Technology Lab, contributing to a collaborative environment focused on cutting-edge research in human-robot interaction, multimodal systems, and industrial applications of artificial intelligence.

• Wireless Communication
• Machine Learning
• Signal Processing
• +4 more

Prof. Dr. Haris Gačanin is a faculty member at RWTH Aachen University, affiliated with the Institute for Distributed Signal Processing under the College of Electrical Engineering. His research focuses on integrating machine learning with wireless communication systems, particularly in industrial IoT, edge computing, and network optimization. Current academic rank: Professor Contact: harisg@dsp.rwth-aachen.de Research Interests: Wireless systems, machine learning, signal processing, and network optimization. Key contributions include: Adaptive resource allocation in IIoT and vehicular networks AI-driven channel estimation and feedback mechanisms Security-oriented emitter identification via metric learning Federated/transfer learning for edge environments Hardware-efficient deep learning models for mmWave and THz communications Methodological Focus: Combines reinforcement learning, attention mechanisms, and robust neural architectures with practical implementations on FPGA and vehicular systems.

Georg CarleView profile

Professor

• Internet Technology
• Future Internet Architecture
• Network Security
• +3 more

Prof. Georg Carle is a full Professor in Network Architectures and Network Services at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. He leads research in Internet technology, focusing on future network architectures, security, and real-time communication. Prior roles include positions at the University of Tübingen and Fraunhofer Institute for Open Communication Systems (FOKUS). Education: Electrical Engineering diploma from University of Stuttgart (1992), Master of Science in Digital Systems (Brunel University, London), and PhD in Telematics from University of Karlsruhe (1996). He held scholarships in complex systems and European Union-funded research at Institut Eurécom. Research Interests: Prof. Carle's work spans network security, sensor networks, autonomous systems, and future Internet protocols. His group develops tools like MoonGen (packet generator) and pos (experiment workflow system). Recent focus includes QUIC protocol analysis, network slicing, and reproducible experimentation frameworks. Key Contributions: Award-winning research includes Applied Networking Research Prizes (2017-2018), Best Paper Awards in IMC/PAM, and innovations in network measurement, security, and programmable data planes. His lab explores cutting-edge topics like post-quantum cryptography, low-latency networking, and 6G automation. Recognition: Honors include ACM SIGCOMM Community Contribution Award, IRTF ANRP, and multiple conference best paper accolades. He advises on network infrastructure for industrial IoT, automotive systems, and secure multiparty computation.