Roberto Berjón Gallinas is a Professor at the School of Computer Science, Deusto University. His research focuses on semantic technologies, internet of things, and data integration, with a strong emphasis on mobile applications and open data. He leads two research groups: ICS (Innovación en Ciencias Sociales) MARATON (Mobile applications, internet of things, data processing, semantic technologies, open data) His recent work includes developing smart tracking frameworks for IoT workflows and digital twins, event-driven architectures for IoT systems, and semantic integration solutions for university research. His projects often bridge technical innovation with practical applications in collaborative e-learning and spatial analytics. Key trends in his publications highlight advancements in IoT frameworks , semantic technologies for data integration, and real-time systems using BLE and open data. These works frequently intersect with collaborative e-learning , university transparency , and adaptive mobile platforms .
Carme Torras Genís is a Research Professor at the Spanish National Research Council (CSIC), affiliated with the Institute of Robotics and Industrial Informatics (IRI) in Barcelona and the Technical University of Catalonia (UPC). Her career spans over three decades, focusing on robotics, neurocomputing, and artificial intelligence with applications in healthcare and deformable object manipulation. M.Sc. in Mathematics (University of Barcelona, 1978) M.Sc. in Computer Science (University of Massachusetts, 11981) Ph.D. in Computer Science (UPC, 1984) Research Interests : Robotic manipulation of deformable objects (especially textiles) Neurocomputing and machine learning for robotic control Human-robot interaction and assistive robotics Computational topology for cloth state representation Ethics in social robotics and AI Medical applications of robotics for neuromuscular disease assessment Scientific Leadership : ERC Advanced Grant recipient (2016) IEEE and EurAI Fellow Coordinator of Horizon Europe project SoftEnable and former ERC project CLOTHILDE Editorial leadership in IEEE Transactions on Robotics and multiple journals Active in ethics committees and AI policy advisory boards Advisory Committee of Ethics in AI (Catalan Government) Vice-President of CSIC Ethics Committee Member of Royal Academy of Engineering (Spain)
Danfeng Zhang is a faculty member at Duke University whose research sits at the intersection of programming languages and security. Active across the premier PL conferences since 2015, Zhang has served on more than two-dozen program committees and currently co-chairs the POPL Student Research Competition. Education & Affiliation: Home page: users.cs.duke.edu/~dz132 Affiliation: Duke University, United States Research Interests: Zhang’s work spans programming-language design, static and dynamic analysis, formal verification, and security. A recurring theme is developing language-based techniques that guarantee strong security and privacy properties—ranging from side-channel resistance and constant-time execution to differential-privacy proofs—while preserving performance and usability. His recent projects combine type systems, program logics, and automated reasoning to build practical verification tools for concurrent, speculative, and approximate software. Publication Trends: Across nine representative papers (2015-2024) Zhang has advanced static detection of cache side channels, automated proofs of differential privacy, and relaxed concurrency models. The trajectory shows deepening integration of security concerns into language infrastructure, with tool-building (CtChecker, SpecSafe, LightDP) that bridge formal guarantees and real-world systems. Service & Leadership: 2024 POPL Student Research Competition Co-Chair 2025 POPL Program Committee member Repeated reviewer/PC member: PLDI, SPLASH/OOPSLA, ISSTA, ECOOP, APLAS, PriSC, PASS Zhang regularly mentors student researchers through SRC sessions and workshop panels, fostering diversity and early-career participation in the programming-languages community.
Agustín Zaballos Diego is an Assistant Professor in the Department of Computer Engineering at University Ramon Llull (URL), Barcelona, Spain, since 1999. He serves as Research Coordinator in the Department of Engineering at La Salle Campus Barcelona and leads the R&D Networking and Security Area since 2002. His academic background includes a PhD in Data Networks and Internet Technologies (2012), an International MBA (2014), and an M.S. in Electronic Engineering (2000). University: University Ramon Llull (URL) Department: Department of Computer Engineering Research Group: GRITS Research Focus: Real-time QoS-aware routing protocols in Smart Grids, Ubiquitous Sensor Networks, and IoT communications. His work bridges telecommunications, computer science, and energy systems through projects like OPERA (FP6), INTEGRIS (FP7), and FINESCE (FP7). Publication Trends: Recent articles highlight advancements in HF communications for Antarctic research, hybrid genetic algorithms for traffic engineering, IPv6 testing, and Industry 4.0-related networking solutions. Keywords span Smart Grids, IoT, Sensor Networks, and QoS optimization. Collaborative Projects: Key initiatives include the Antarctica Project , ATHIKA (ICT in healthcare), ENVISERA (environmental sensor networks), HOTSUP (online teaching innovation), PLANET4 (AI/ML in industry), and XIoT (IoT scalability challenges).
Alan Briones Delgado is a researcher at the La Salle School of Engineering , Universitat Ramon Llull , with a focus on Internet of Things , Cybersecurity , and Transport Protocols . His work spans projects funded by the European Commission and national grants, including EXCEL4HOUSING4.0 , WeB-Nimbus , and NG-SOC , addressing challenges in cloud computing education, ecological monitoring, and security operations. His research integrates Artificial Intelligence and Wireless Sensor Networks for sustainable solutions. Key research areas include Quality of Service in heterogeneous networks, Environmental Conservation via IoT, and Teaching and Learning strategies for Big Data. Projects like EcoSentinel and BTL-COP highlight his commitment to Environmental Monitoring and Community Policing applications. His collaborations extend to institutions in the UK , Albania , and Western Balkans . Contact: alan.briones@salle.url.edu
Miguel Ángel Sotelo Vázquez is a full Professor at the University of Alcalá, leading the INVETT Research Group (Intelligent Vehicles and Traffic Technologies). He holds the Department of Automatic Control and specializes in autonomous systems, particularly in path planning, sensor fusion, and human-vehicle interaction. His research integrates machine learning, robotics, and control theory to address challenges in intelligent transportation systems. He earned his Ph.D. in 2001 with a thesis on autonomous vehicle navigation in partially known environments. His work emphasizes real-world deployment, explainable AI, and safety-critical systems. Recent projects focus on lane change prediction, pedestrian behavior modeling, and cybersecurity for autonomous systems. Key contributions include neuro-symbolic frameworks for decision-making, real-time multi-physics field reconstruction, and cross-cultural studies of pedestrian interactions. He collaborates internationally on urban mobility resilience and hydrogen refueling infrastructure. Research Highlights : Development of knowledge graph-based prediction architectures Experimental validation of human-vehicle interaction in VR environments Creation of the SCOUT trajectory prediction framework
Jorge Garcia Vidal is a Professor in the Department of Computer Architecture at the School of Computer Science, Universitat Politècnica de Catalunya (UPC). He is a key member of the CNDS - Computer Networks and Distributed Systems research group, with a sustained record of research activity from the late 1980s to the present, including publications projected into 2025. His work bridges theoretical network performance analysis and applied IoT systems, particularly in environmental monitoring. His research interests center on Computer Networks , Internet of Things (IoT) , Sensor Networks , and Data Quality in IoT . He has made significant contributions to ATM network performance, medium access control, and traffic modeling. More recently, his focus has shifted to air quality monitoring using low-cost sensor networks, employing techniques in Graph Signal Processing , Machine Learning , and Anomaly Detection to improve data reliability and estimate pollutants like black carbon. The recent article trends show a strong emphasis on developing data-driven frameworks, virtual sensors, and robust models for environmental IoT platforms. His work integrates advanced signal processing and machine learning to address the challenges of heterogeneous, low-cost sensor data in urban settings. His scientific achievements have been recognized with awards including the Premio Extraordinario de Doctorado and the Premio Mejor Tesis Doctoral . He has advised several doctoral students, including Pau Ferrer-Cid, David Fusté Vilella, Steluta Iordache, and Julian David Morillo Pozo. He is actively involved in numerous competitive and non-competitive R&D projects, such as those related to digital twins, IoT platforms for smart cities, and nature-based urban solutions, often funded by state and regional programs. He collaborates extensively within UPC and with external partners. His research is conducted primarily within the CNDS research group at UPC, a collaborative environment focused on computer networks and distributed systems, with connections to broader initiatives in smart cities and environmental monitoring.
Jesus Escudero-Sahuquillo is a Full Professor at the Computing Systems Department (DSI) of the Faculty of Computer Science Engineering at the University of Castilla-La Mancha (UCLM), Spain. His academic journey began at UCLM where he completed his Degree in Computer Science in 2006, followed by a Master of Science in 2008, and a PhD in Advanced Computing Technologies in 2011. His professional experience includes: Full Professor at UCLM (current position) PostDoc at Technical University of Valencia (2015) PhD Senior Engineer at Oracle Norway (2013-2015) 5-year PostDoc position at UCLM funded by UCLM and European Commission (2016) Dr. Escudero-Sahuquillo's research focuses on high-performance computing and Big Data, with particular emphasis on interconnection networks and related optimization strategies. His work spans congestion management, routing algorithms, network topologies, and power saving techniques. He has extensive experience with InfiniBand technology and has contributed significantly to congestion control mechanisms in high-performance interconnects. His publication record demonstrates a strong focus on advancing network performance in high-performance computing environments. Over the past decade, his research has evolved from foundational work on routing algorithms and network topologies to more sophisticated congestion management techniques applicable to modern data centers and exascale computing architectures. His most recent work addresses cutting-edge challenges in packet identification, hybrid congestion control, and adaptive routing for next-generation interconnection networks. Dr. Escudero-Sahuquillo has served as a program committee member and reviewer for numerous prestigious conferences and journals including IEEE Micro, IEEE Transactions on Parallel and Distributed Systems, and Journal of Parallel and Distributed Computing. He was the co-organizer for five editions of the IEEE International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB). His research has been supported through participation in multiple projects funded by the European Commission and the Spanish Government. He has collaborated extensively with researchers across Europe and has been instrumental in advancing the state of the art in high-performance interconnection networks.
Scott Nelson is an Associate Professor of Finance at the University of Chicago Booth School of Business. His research bridges consumer credit markets, regulatory frameworks, and behavioral economics, with a focus on how information asymmetries and algorithmic decision-making shape market outcomes. He has contributed to understanding the impacts of the 2009 CARD Act, eviction protections in housing markets, and fairness in credit scoring systems. PhD in Economics, Massachusetts Institute of Technology BA (summa cum laude) in Economics and Mathematics, Yale College Nelson's work employs diverse data sources, including credit reports, court filings, and tax records, combined with structural models to analyze consumer and firm behavior. Key themes include regulatory efficiency, validity disparities in predictive models, and the welfare implications of policy interventions. His articles reveal trends in algorithmic regulation (2025), eviction dynamics (2025), credit scoring disparities (2024), and public finance impacts on Chinese real estate (2023). These publications highlight interdisciplinary methodologies integrating economics, law, and data science. Scientific awards include the AQR Top Finance Graduate Award (2018) and National Science Foundation Graduate Research Fellowship. He has held postdoctoral roles at the Consumer Financial Protection Bureau/Princeton University and visiting research positions at the Federal Reserve Bank of Boston.
Mahmoud Khalifa Abdelhamid Khalifa is a Researcher at the Institute for Research in Technology (IIT) of Comillas Pontifical University, affiliated with the Higher Technical School of Engineering (ICAI). He holds a B.Sc. (2019, first class honors) and M.Sc. (2023) in Electrical Engineering from Minia University, Egypt. His current role involves predoctoral research in electrical systems, focusing on battery energy storage systems and their impact on low-inertia power systems stability. Education: B.Sc. Electrical Engineering, Minia University (2019), ranked first in class M.Sc. Electrical Engineering, Minia University (2023) Research Interests: Mahmoud’s work centers on modeling, control, and stability analysis of energy storage systems, particularly in the context of renewable energy integration. His expertise includes doubly-fed induction generators (DFIG), grid stability, and advanced control algorithms for wind and solar systems. Publications & Contributions: He has authored/co-authored peer-reviewed journal articles, conference papers, and a book on DFIG control systems. His work emphasizes optimizing dynamic performance in renewable energy systems and enhancing grid reliability through advanced control techniques. Affiliations & Skills: Mahmoud is proficient in MATLAB/Simulink, PLC programming (Siemens SIMATIC STEP 7), and tools like Arduino C, Microsoft Office, and SPSS. His research is supported by institutional affiliations with IIT and Minia University. Labs/Teams: Engaged in IIT’s electrical systems research group, contributing to projects on smart grids and energy storage solutions.
Jose Miguel Espi Huerta is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, University of Valencia. He is an active researcher in power electronics and control systems, contributing significantly to grid-connected converters, renewable energy integration, and digital control techniques. His research interests include: Power Electronics and Inverter Control Predictive and Robust Control Strategies Renewable Energy Systems (Photovoltaic and Wind) Induction Heating Technologies Remote and Web-Based Educational Labs The analysis of his recent publications reveals a strong focus on improving the efficiency and reliability of grid-connected power converters using advanced control methods such as predictive current control and MPPT strategies. His work spans both industrial applications and academic education, particularly in developing remote laboratory platforms for control systems. Scientific awards and honors: No awards listed in the provided text. He has supervised academic theses and is affiliated with the LEII (Laboratory of Industrial Electronics and Instrumentation) research group. While no formal grants are listed, his extensive publication record indicates sustained research activity. He has contributed to the development of educational tools such as air levitation systems accessible via PLC and web interfaces, promoting innovative teaching methods in engineering education. The LEII research group focuses on industrial electronics, instrumentation, and power systems, providing a collaborative environment for applied research in energy conversion and control technologies.
Dr. Julián Proenza Arenas is an Associate Professor at the University of the Balearic Islands (UIB) within the Mathematics and Informatics Department of the Higher Polytechnic School. As Secretary of the Politechnical School, he contributes to the management of all engineering bachelor degrees and serves as Academic Coordinator for the EU EMJMD Programme on Engineering of Data-Intensive Intelligent Software Systems (EDISS) since 2021. Ph.D. in Informatics (2007), University of the Balearic Islands Licenciatura in Physics (1989), University of the Balearic Islands His research focuses on Dependable and Real-Time Systems , particularly fault tolerance in distributed environments, Clock Synchronization , and Fieldbus Networks . Recent work emphasizes Time-Sensitive Networking (TSN) and adaptive mechanisms for industrial automation. He has co-authored over 100 publications and three patents, with multiple best paper awards at IEEE conferences (2004–2023). IEEE Workshop on Factory Communication Systems Best Paper (2004) IEEE ETFA Best Work-in-Progress Paper (2012, 2014, 2016) IEEE ETFA Factory Automation Best Paper (2023) Dr. Proenza supervises 6 completed and 2 ongoing Ph.D. theses and leads national research projects like FT4TSNgrid (2022–2025) and DFT4FTT (2016–2019). He is Principal Investigator of the Sistemas Empotrados Inteligentes y Robótica (SRV-INTER) R&D group and actively collaborates with international institutions including Mälardalen University and Universidade do Porto.
Dr. Marc Ph. Stoecklin is a Principal Research Staff Member and head of the Security Research Department at IBM Research Europe in Zurich, Switzerland. He co-leads IBM's global research strategy on Quantum Safe Cryptography and Migration, focusing on cryptographic artifact identification and migration implementation. Previously, he directed Threat Management research, applying AI and automation to threat detection, investigation, and response. Education: PhD in Computer, Communication and Information Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland His research spans quantum safe cryptography, threat management, AI security, threat detection, identity management, cyber deception, big data analytics, and security visualization. He pioneered AI-powered security operations, contributing to Watson for Cyber Security and QRadar Advisor with Watson, and analyzes AI/quantum computing misuse in cyber attacks. His 2016-2020 publications emphasize advanced threat detection, malware analysis, and AI security, featuring evasive malware deactivation, threat intelligence computing, and neural network watermarking. These works bridge research and product development, directly influencing IBM security offerings. Dr. Stoecklin led IBM's Cognitive Cyber Security Intelligence group (2014-2019) and the Security Research Department since 2019. As tech lead for IBM's COVID-19 task force (2020-2022), he developed IBM Digital Health Pass, deployed in New York's Excelsior Pass with over 1 million passes issued in two months. He heads the Security Research Department at IBM Research Europe in Zurich and has been integral to the Global Security Analysis Lab (GSAL) and Cognitive Cyber Security Intelligence (CCSI) group at IBM T.J. Watson Research Center.
Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).
Summary Raúl Suárez Feijóo is a Researcher at the Universitat Politècnica de Catalunya (UPC) in the Institut d'Organització i Control de Sistemes Industrials (IOC). Born in Asturias, Spain (1959), he holds an Electronic Engineering degree from the National University of San Juan, Argentina (1984), and a Doctorate in Engineering from UPC (1993). His research focuses on robotized assembly, fine motion planning, grasping, and multi-robot systems. He has led the IOC as Deputy Director (2003–2009) and Director (2009–2016). He coordinates doctoral programs in Automation and Robotics at UPC. Suárez has authored numerous publications and received awards including the Best Paper Award at IEEE ISATP (1995) and the Best Reviewer Award at ICRA (2015). Education: Electronic Engineer (1984, Argentina), Doctor Engineer (1993, UPC) Leadership Roles: Director of IOC (2009–2016), Coordinator of Doctoral Programs Research: Over 100 publications in robotics, emphasizing grasping, manipulation, and industrial automation. His work includes contributions to robotic hands, motion planning, and collaborative robotics. Notable projects involve 5G-enabled robotic systems and multi-AGV traffic management. Awards highlight his impact in both international and national robotics communities.
