Marina Papatriantafilou is an Associate Professor in the Department of Computer Science and Engineering at Chalmers University of Technology and University of Gothenburg. Her research focuses on distributed computing, fault-tolerance, parallel algorithms, and concurrency control. She has contributed to methods for fault-tolerant distributed systems, visualization tools for distributed algorithms, and scalable overlay networks. Her academic roles include teaching advanced courses on distributed systems, computer communication, and operating systems. She advises graduate students in areas like distributed algorithms and parallel computing. Key research interests include lock-free synchronization, memory reclamation, and self-stabilizing systems. She has authored over 100 publications in top-tier conferences and journals, with recent work on data streaming frameworks, energy-sharing optimization, and vehicular network processing. Professional involvement includes roles in program committees for conferences like OPODIS, SWAT, and SSS, plus membership in research evaluation boards for Swedish and European funding agencies. She pioneered educational tools like the Lydian environment for distributed algorithm visualization.
Elke Schwarz is a Professor of Political Theory at Queen Mary University of London, School of Politics and International Relations. Prior to this role, she held academic positions at UCL, Anglia Ruskin University, and Leicester University. Her work focuses on the intersection of ethics, technology, and warfare, particularly in the context of military artificial intelligence (AI), autonomous weapon systems, drones, and robots. Elke holds a BBA from Belmont University (USA), an MA in Conflict Studies from King’s College London, and a PhD from the London School of Economics and Political Science (LSE). She is the author of Death Machines: The Ethics of Violent Technologies and has published widely on topics such as algorithmic ethics for lethal autonomous weapons systems and the ethics of military AI. Her research interests include ethics, military AI, autonomous weapon systems, digital technologies, apocalyptic studies, war studies, critical security studies, political theory, philosophy of technology, and posthumanism. She has received notable fellowships, including the 2024 Leverhulme Research Fellowship, the 2022/23 CAPAS Fellowship, and the RSA Fellowship. She also secured a British Academy/Leverhulme Small Grant (2017–2019) for research on military ethical values in autonomous weapons systems. Elke is actively involved in public engagement, serving as Vice-Chair of the International Committee for Robot Arms Control (ICRAC), an Associate of the Imperial War Museum (IWM), and collaborating with organizations like Drone Wars UK, Stop Killer Robots, and the Alan Turing Institute. Her work bridges academia, policy, and civil society to address ethical and security challenges posed by emerging technologies.
Ozgur Ozdemir is an Associate Research Professor in the Department of Electrical and Computer Engineering at North Carolina State University's College of Engineering. He is affiliated with the university's primary faculty and works closely with platforms like AERPAW and AFAR Challenge. His research focuses on advanced wireless systems, including UAV networks, mmWave technology, spectrum analysis, and radar-communication integration. His work spans experimental testbed development, digital twin applications for AI research, and methodologies for improving coverage in rural and urban environments. Ozdemir has contributed to standards like 5G NR and non-standalone 5G systems, emphasizing practical implementation and environmental impact analysis. He leads efforts in signal processing for autonomous systems and has expertise in software-defined radio (SDR) technologies. Research interests include aerial threat detection, RF signal analysis, and robust localization techniques. He explores challenges in NLOS bias correction, antenna radiation patterns, and passive reflector-based coverage enhancement. His work often combines theoretical models with experimental validation using platforms like AERPAW. His articles highlight advancements in drone detection systems, channel modeling for mmWave, and the integration of radar and communication systems. Key trends show a focus on outdoor/indoor spectrum measurements, UAV navigation, and resilient network design. Ozdemir's contributions are characterized by empirical studies and cross-disciplinary approaches to wireless challenges.
Alberto Ferrante is a Lecturer and Researcher at the Faculty of Informatics of the Università della Svizzera italiana (USI), affiliated with the IDSIA (Dalle Molle Institute for Artificial Intelligence) USI/SUPSI. His work bridges cybersecurity, embedded systems, and AI applications, particularly in IoT and pest control. He holds a PhD from Università degli Studi di Milano (2006) and an MSc from Politecnico di Milano (2002). Research Interests: Ferrante focuses on Secure communication protocols and embedded systems security Malware detection and resource-optimized hardware solutions Machine learning applications for IoT, including agricultural pest monitoring and healthcare diagnostics Cyber-physical systems design and security-enhanced embedded systems His publications emphasize practical implementations, such as AI-driven UAVs for pest control and low-power drone systems for environmental monitoring. He actively contributes to tech transfer projects with industry partners and participates in major conferences like ICC and Globecom as a TPC member. He teaches the Master’s course Edge Computing in the IoT and collaborates on hardware-software co-design for security-critical systems. His work often integrates real-world constraints like energy efficiency and computational resource limitations. Key contributions include frameworks for dynamic security adaptation in wireless sensor networks and hardware-accelerated security for embedded systems.
Jarek Nabrzyski is the founding and current director of the Center for Research Computing (CRC) at the University of Notre Dame and a concurrent Professor in the Department of Computer Science and Engineering. He co-directs the Blockchain Research Lab with Ian Taylor and leads the Quantum Computing Lab. His research focuses on distributed ledger technologies, quantum computing, and resource management in distributed, cloud, and exascale systems. He has overseen over 50 national and international research projects developing cyberinfrastructure for science and industry, emphasizing collaboration and team-building in complex projects. Key areas of research include blockchain applications in decentralized systems, quantum algorithm optimization for near-term hardware, and cybersecurity protocols for data integrity. He actively engages in interdisciplinary initiatives like the Center for Social Science Research and has pioneered frameworks for verifiable credentials and reproducible scientific data. His work bridges theoretical advancements with practical industry partnerships. Notable contributions include hybrid cross-chain protocols, quantum Poisson solvers, and frameworks for blockchain trust analytics. His recent publications highlight advancements in AI-driven blockchain stabilization, suspicious transaction detection, and scalable quantum computing solutions. Despite no explicit mentions of awards, his leadership roles and project count underscore significant contributions to computational science and infrastructure. As a mentor, he fosters student engagement in cyberinfrastructure through initiatives like the Cyberinfrastructure Center of Excellence. His labs and collaborations drive innovation in quantum computing, blockchain interoperability, and high-performance computing systems. Current efforts include transparent data tracking for aerospace supply chains and secure scientific data reproducibility.
Professor Pietro Valdastri is a Full Professor and Chair in Robotics & Autonomous Systems at the University of Leeds. He directs the Science and Technologies Of Robotics in Medicine (STORM) Lab, the Institute of Robotics, Autonomous Systems and Sensing (IRASS), and the Robotics at Leeds network. His expertise spans surgical robotics, robotic endoscopy, and magnetic manipulation, with a focus on developing soft magnetic surgical robots (SMSRs) for minimally invasive medical procedures. Valdastri holds a Laurea in Electronic Engineering (University of Pisa, 2001) and a PhD in Biomedical Engineering (Scuola Superiore Sant’Anna, 2006). He previously served as Assistant Professor at Scuola Superiore Sant’Anna (2006–2011) and Vanderbilt University (2011–2016) before joining Leeds in 2016. His research aims to leverage magnetic actuation for surgical navigation, with applications in cancer therapy and endoscopy. Key awards include the NSF CAREER Award (2015), ERC Consolidator Grant (2019), and KUKA Innovation Award (2019). He is a Royal Society Wolfson Research Fellow, IEEE Fellow, and editor for IEEE Robotics and Automation Letters. His work has been featured in major media outlets like the BBC, New Scientist, and WIRED. Valdastri has secured over £25M in grants from NSF, NIH, ERC, EU-H2020, and industry partnerships. He co-founded WinMedical srl (acquired in 2017) and Atlas Endoscopy Limited, advancing robotic colonoscopy platforms. Current research emphasizes autonomous robotic systems, magnetic tentacles for lung therapy, and patient-specific surgical tools.
Simone Ferlin is an Adjunct Senior Lecturer at Karlstad University working with 5G and Internet evolution. She completed her PhD in computer science in 2017 at the Simula Research Lab and Universitetet i Oslo under the supervision of Dr. Ozgu Alay and Prof. Michael Welzl. Her PhD dissertation focused on increasing robustness in multipath transport with MPTCP. Dr. Ferlin's educational background includes a PhD in Computer Science from the Simula Research Lab and Universitetet i Oslo (2017). Her doctoral research centered on enhancing robustness in multipath transport protocols, specifically focusing on MPTCP (Multipath TCP). She also completed undergraduate work that contributed to a book project with Prof. Friedrich Oehme on electronics and circuit technology. Dr. Ferlin's research spans multiple domains at the intersection of networking, systems, and performance engineering. Her primary interests include network and system measurements, performance analysis, security, and congestion control. She investigates how networks like the Internet evolve, examining technology development, adoption patterns, and their impacts on various entities. Additionally, she explores ways to harmonize security and privacy while making them more usable and assessable. Her work particularly focuses on transport layer and multipath transport protocols, examining their performance and security aspects. She also investigates application and transport layer performance, automation, and monitoring. Her research extends to network programming in both Linux kernel and user space, mobile broadband networks from 2G to 5G, and their intersection with the Internet. She is deeply engaged in observability, distributed and system performance monitoring, and automation. Analysis of Dr. Ferlin's recent publications reveals a strong focus on next-generation networking technologies. Her work spans multiple domains including 5G/6G networks, transport protocols (particularly QUIC and MPTCP), network virtualization, container orchestration, and the application of machine learning to networking problems. She has increasingly incorporated large language models into network configuration and automation research. Her publications demonstrate a consistent emphasis on performance measurement, optimization, and security across diverse networking environments from the edge to the cloud. Dr. Ferlin has received notable recognition for her research contributions: Best paper award at IEEE ICIN'21 for 'Learning-based Incast Performance Inference in Software-Defined Data Centers' Applied Networking Research Prize (ANRP)'25 winner for 'NetConfEval: Can LLMs Facilitate Network Configuration?' Dr. Ferlin is actively involved in mentoring the next generation of networking researchers. She has co-supervised numerous Master's and PhD students across multiple institutions including Karlstad University, KTH, TU Berlin, University of Oslo, and universities in Brazil. Her students have worked on diverse topics including NAT64 performance comparison, system tracing visualization, network observability, ML applications to multipath transport, FEC integration with QUIC, high-performance networking for 5G, congestion control, shared bottleneck detection, multipath IoT applications, and container runtime performance. She is also involved in several significant research projects including Vinnova's SEMLA (Securing Enterprises via Machine-Learning-based Automation), Horizon Europe's CODECO (Cognitive Decentralised Edge Cloud Orchestration), and the Knowledge Foundation of Sweden's DRIVE (Data-driven Latency-Sensitive Mobile Services for a Digitized Society). Dr. Ferlin serves as Workshop Chair for ACM SIGCOMM '25, is a member of the ACM/IRTF Applied Networking Research Workshop (ANRW) steering committee, and co-chairs the Internet Congestion Control Research Group (ICCRG) at the IRTF. She previously served as Associate Technical Editor for IEEE Communications Magazine and has been active on numerous program committees for major networking conferences including SIGCOMM, CoNEXT, IMC, and PAM.
Manuel Reis is an Associate Professor with Agregação at the University of Trás-os-Montes e Alto Douro (UTAD), Portugal, in the Electrical Engineering Department. His research focuses on signal/image processing, smart environment systems, and multimedia education technologies. He is affiliated with the Institute of Electronics and Telematics Engineering of Aveiro (IEETA) and collaborates with Brazil's IFPA-Santarém in computing education research. Education: Bachelor's in Electrical Engineering (University of Trás-os-Montes e Alto Douro, 1991) Master's in Electronics and Telecommunications (University of Aveiro, 1996) PhD in Electrical Engineering (University of Aveiro, 2001) Research Interests: Signal & Image Processing Cybersecurity for IoT and Smart Environments Education Technology (e-learning, multimedia tools) 5G and Edge Computing Applications Artificial Intelligence in Agriculture and Healthcare Recent articles highlight his work on cybersecurity in connected vehicles, federated learning for IoT security, and IoT-based systems for drowsiness detection. He has contributed to projects involving smart city infrastructure, sustainable waste management, and low-cost biomedical devices. His educational research explores e-learning frameworks, student engagement metrics, and innovative teaching methodologies in engineering education. Lab/Affiliations: Institute of Electronics and Telematics Engineering of Aveiro (IEETA) Multidisciplinary Research Group IFPA-Santarém-Brazil (Computing in Education)
Prof. Adrian Filipescu is a full professor and PhD supervisor at the Department of Automation and Electrical Engineering, Dunărea de Jos University of Galati. He holds a PhD in Control Systems (1993) and has over 40 years of academic and research experience. His expertise spans numerical calculus, adaptive control, robotics, and Industry 4.0/5.0 applications. He has authored 12 books and over 110 indexed articles with an h-index of 11 (SCOPUS), and his work earned two UEFISCDI awards (2014, 2019). Education: Engineer diploma in Automatic Control (Polytechnic University of Bucharest, 1981) and PhD in Control Systems (Dunărea de Jos University, 1993). His research focuses on mechatronics systems integration, robotic control, digital twins, and industrial automation. Notable contributions include developing a mechatronics line with integrated autonomous robots, wheelchair systems for disabled users, and multidirectional autonomous vehicles. Research Themes: Digital twin frameworks, IoT-cloud robotics control, Industry 4.0/5.0 systems, inverse kinematics modeling, and autonomous robotic navigation. His recent work emphasizes cloud-based remote control, HIL simulation, and SCADA integration. Awards: Recipient of the 2014 and 2019 UEFISCDI 'Award for Research Results' for highly commended papers. He has led 10+ research projects, endowing labs with advanced robotic infrastructure and PLC-controlled systems. Advising & Grants: Supervised 7 completed PhD theses (including 1 international co-supervision). Projects focused on robotic-assisted manufacturing, autonomous systems, and mechatronics line optimization. Current lab facilities include mobile robots, industrial manipulators, and PLC-based control systems. Labs/Teams: Director of a research lab developing Industry 5.0-ready systems, including robotic assistants for elderly/disabled users and flexible assembly/disassembly technologies. Collaborations include NATO internships at Politecnico di Torino (Italy), INPG Grenoble (France), and ISR Coimbra (Portugal).
Haijian Sun is an Assistant Professor at the University of Georgia's School of Electrical & Computer Engineering. His research focuses on advanced wireless communication systems, including 5G/6G networks, federated learning, mobile edge computing, and physical layer security. He explores cutting-edge topics like reconfigurable intelligent surfaces (RIS), hybrid active-passive symbiotic radio systems, and UAV-enabled communication. His work integrates machine learning and optimization techniques to address challenges in channel modeling, energy efficiency, and network security. Recent projects include autonomous agricultural monitoring via drones and energy-harvesting sensors, as well as secure IRS-VLC communication strategies. Publications highlight innovations in dynamic wireless charging for electric vehicles, graph-based phishing detection, and radio radiance field modeling. While no specific awards are listed, his contributions reflect significant engagement with industry-relevant 6G research. Research collaborations involve digital twin networks, IoT systems, and smart grid applications. His team develops practical solutions for real-world communication challenges, emphasizing both theoretical rigor and deployable technologies.
Andrea Araldo is an Associate Professor at Telecom SudParis within the SAMOVAR research lab, specializing in NeSS (Networks, Systems, and Services). His work focuses on optimizing transportation systems, edge computing, and network resource allocation using advanced techniques like reinforcement learning and game theory. He has published extensively on topics including demand-responsive transit, vehicular cloud computing, and multi-tenant edge resource management. His research addresses challenges in urban mobility equity, infrastructure resilience, and energy-efficient network design. Research Interests: Transportation systems optimization Edge computing architectures Reinforcement learning applications Network resource allocation Urban accessibility equity Autonomous mobility systems Recent Trends in Publications: Recent work emphasizes adaptive transport network design during disruptions, equity-driven public transit planning, and vehicular cloud alternatives to traditional edge computing. He explores hybrid optimization methods combining reinforcement learning with classical algorithms for virtual network embedding and resource scheduling. Grants & Collaborations: Engages in multi-institutional projects involving institutions like Université Paris-Saclay and industry partnerships. Active in conferences such as TRB, IEEE ICC, and ACM SIGCOMM. Labs/Teams: Leads projects within SAMOVAR lab focusing on smart transportation and edge computing systems.
Haihua Chen is an Assistant Professor of Data Science in the Department of Information Science at the University of North Texas (UNT), with a co-affiliation in Health Informatics. They lead the Intelligent Data Engineering and Analytics (IDEA) Lab, focusing on interdisciplinary research in artificial intelligence, data science, and informatics. Chen earned a Ph.D. in Information Science (concentrating in Data Science) from UNT in 2022, an M.S. in Information Science from Wuhan University, and dual B.S. degrees in Information Science and English Literature from Central China Normal University. Research interests span applied machine learning, data quality evaluation, NLP, and informatics applications in legal and healthcare domains. Notable work includes developing frameworks for measuring scientific novelty, constructing high-quality legal and biomedical datasets, and leveraging AI for precision medicine and disaster response. Chen has secured over $499K in external grants, including NSF REU and HSI projects, and $20K+ in internal grants. Their work has been published in top journals like Journal of Informetrics , IEEE Transactions on Reliability , and Scientometrics , with a strong focus on innovation measurement and data-centric AI. Teaching includes courses on computational methods, data analysis, and AI in healthcare. Professional leadership roles include chairing ASIS&T SIG-STI and editorial roles for Journal of the Association for Information Science and Technology , Knowledge and Information Systems , and others. Awards include UNT’s Great Grads Award and the Linda Schamber Writing Award.
Zhiyi Huang is an Associate Professor of Computer Science at the University of Hong Kong, leading the Computer Science Division within the School of Computing and Data Science. He holds a PhD from the University of Pennsylvania (2013) and completed a postdoctoral fellowship at Stanford University (2013–2014). His research focuses on Theoretical Computer Science, Algorithmic Game Theory, Online Algorithms, and Differential Privacy, with notable contributions to Machine Learning and Computer Networks. Education: PhD in Computer and Information Science, University of Pennsylvania (2013) Postdoctoral Researcher, Stanford University (2013–2014) Bachelor's Degree from the Yao Class at Tsinghua University (2008) Research interests span foundational areas including algorithmic game theory, online optimization, and privacy-preserving mechanisms. He has pioneered work on revenue maximization in single-parameter settings and developed novel frameworks for analyzing price of anarchy in game theory. Key Awards: Early Career Award (Research Grant Council of Hong Kong, 2014) Best Paper Award at ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015) Morris and Dorothy Rubinoff Dissertation Award (2013) Simons Graduate Fellowship in Theoretical Computer Science (2012–2013) Recent grants include studies on algorithmic foundations of Bayesian mechanism design (HK$675,647), online primal dual techniques (HK$496,028), and privacy-preserving mechanisms (HK$931,737). His work bridges theoretical advancements with practical applications in healthcare, autonomous systems, and cybersecurity. Notable Projects: Medical predictive systems for acute cardiopulmonary events AI-driven maritime navigation using AIS data Secure federated learning frameworks with blockchain
Prof. Dr. Murat Dener is a full Professor in the Department of Information Security Engineering at the Institute of Science and Technology, Gazi University, where he also serves as the Head of Department since 2020. He has been continuously affiliated with Gazi University since 2005, progressing from Research Assistant to full Professor in 2023. He is also a Member of the Gazi University Rectorate Quality Commission and a Researcher at the High Performance Computational Neuroscience Laboratory at the Neuroscience and Neurotechnology Excellence Joint Application and Research Center. His educational background includes a BSc, MSc, and PhD, all from Gazi University, with his doctoral studies partially conducted at Georgia Tech University, USA. He completed English language training at Georgia State University and has participated in multiple EU-funded international projects across Greece, Portugal, Belgium, Germany, and Kazakhstan. His research focuses on cutting-edge areas such as cyber security, artificial intelligence, internet of things, blockchain, big data analytics, and computational neuroscience. His work bridges theoretical research with practical innovation, exemplified by the development of Turkey’s first domestically produced wireless sensor node, "WiSeN", through a company he founded in 2014. The analysis of his recent publications reveals a strong trend toward integrating AI and deep learning into cyber defense, secure IoT systems, blockchain applications, and computational neuroscience. His work emphasizes real-world applicability, security, scalability, and innovation in smart city and critical infrastructure technologies. Academic Achievement Award, Georgia State University (2011) Second Prize, Gazi University Business Idea Competition (2014) Turkish First Prize, Junior Chamber International 'Ten Successful Young People of Turkey' (2014) World Top 20 Finalist, Junior Chamber International (Japan, 2014) First Prize, Young Entrepreneurship Category, Liyakat Association (2015) First Prize, Smart Buildings and Environment, TET R&D Project Market (2018) Prof. Dener actively advises master’s and doctoral students and has led numerous national and international research projects, including EU-funded collaborations. His leadership extends to editorial and peer-review roles in multiple journals. He is deeply involved in academic quality improvement as a member of the Rectorate Quality Commission and leads advanced research in computational neuroscience using high-performance computing platforms. He founded a technology company in 2014 under the Technopreneurship Capital Support Program, producing the first Turkish-made wireless sensor node (WiSeN), which led to several national innovation awards. His lab work centers on the High Performance Computational Neuroscience Laboratory, where he contributes to neurotechnology research, combining AI and neuroscience for brain-computer interface applications.
Thor Inge Fossen is a Professor of Navigation and Marine Craft Control at the Department of Engineering Cybernetics, Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). He is a key scientist at the Norwegian Centre for Embodied AI (NCEI) and internationally recognized for his work in navigation systems, guidance systems, and control of marine vessels, aircraft, and drones. Professor Fossen holds a PhD in Engineering Cybernetics and an MSc in Marine Technology. His academic journey has led him to become a Fellow of AAIA, IEEE, and IFAC, reflecting his significant contributions to the field. His research spans several critical areas in marine and aerospace systems: Marine craft hydrodynamics and motion control Navigation, guidance, and control systems for marine craft, aircraft, and drones Cybersecurity of autonomous vehicles Sea-state estimation and wave analysis Attitude control and estimation Fossen's marine craft model, which is widely used in the industry Professor Fossen's publication record demonstrates a strong focus on adaptive control systems, particularly Line-of-Sight (LOS) guidance laws, with numerous papers on 3D path following for marine and aerial vehicles. His recent work (2023-2025) shows increasing integration of machine learning techniques with traditional control systems, particularly in areas like constrained control allocation using deep neural networks. There's also a growing emphasis on cybersecurity aspects of autonomous vehicle guidance systems. His scientific recognition includes: Fellow of the American Institute of Aeronautics and Astronautics (AAIA) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the International Federation of Automatic Control (IFAC) Professor Fossen has been actively involved in advising graduate students, with numerous PhD and MSc graduates. He has led significant research projects including the Marine Systems Simulator (MSS) and the Python Vehicle Simulator, which are widely used tools in the field. His current appointments include being a Study Program Coordinator for the Master's program in Cybernetics and Robotics at NTNU and a Key Scientist at the Norwegian Centre for Embodied AI. He leads research teams focused on embodied AI applications for marine systems, with particular emphasis on safe and secure autonomous operations in complex maritime environments. His work bridges theoretical control systems with practical marine applications, making significant contributions to both academic research and industry implementation.
