Eva Maia is a cybersecurity researcher at Instituto Superior de Engenharia do Porto (ISEP), affiliated with the Research Group in Engineering and Intelligent Computing for Innovation and Development . She holds a PhD in Computer Science from the University of Porto and has contributed extensively to AI-driven cybersecurity solutions for cyber-physical systems in healthcare, airports, and industrial sectors. Education: PhD in Computer Science (2016), University of Porto MSc in Computer Science (2010), University of Porto BSc in Computer Science (2008), University of Porto Her research integrates Artificial Intelligence with Cybersecurity , focusing on adversarial machine learning, network intrusion detection, and data privacy. Recent projects include SAFE , VESTA , and GENIUS , addressing security in 6G networks, ransomware defense, and generative AI for software development. Key trends in her 15 most recent articles (2022–2025) include: AI robustness , privacy-preserving neural networks , and holistic security frameworks for healthcare and industrial systems. Notable awards: Best Application Paper Award 2023 , Young Engineer Innovation Award , and Industry 5.0 Award . Scientific Contributions: Coordinated student supervision in MSc theses on topics like Adversarial ML and Secure Chatbots Evaluated HORIZON Europe proposals and served as EC expert for AI/cybersecurity projects Developed tools like HERA (network traffic analysis) and TestLab (automated software testing) Leadership Roles: Co-Investigator for EU/National Projects (CYDERCO, AIDA, PHRESH) Programme Committee member for ESORICS and EUROSIS conferences Organizing Committee member for DCAI and CANOPY workshops
Prof. Dr. Tolga Ovatman is a faculty member at the Department of Computer Engineering, Istanbul Technical University , where he has been serving as Head of Department since 2024. His academic career spans roles from Research Assistant (2004-2012) to Associate Professor (2019-2023) and full Professor (2023-present). He previously held administrative roles such as Vice Dean (2018-2022) and Deputy Head of Department (2016-2018). PhD in Computer Engineering (2005-2011) MS in Computer Engineering (2003-2005) BSc from Hacettepe University (1999-2003) His research focuses on model checking , replicated state machines , cloud computing , and object-oriented software . Recent work addresses computation offloading in 6G networks , collaborative text editing data structures , and energy-efficient environmental monitoring systems . Key projects led include Design of a Multiplexed State Machine Storage System for Edge Computing (2022-2024) and Microservice Compatible Symphony Infrastructure Research (2020). He has supervised numerous theses on topics ranging from collaborative text editing to AI applications in watershed management . Publications span IEEE Transactions , Springer , and conferences like CSCE and CLOSER .
José María Guerrero Rodríguez serves as a Professor in the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cadiz, Spain. His research is anchored within the TIC138 Electronic and Electromagnetic Design group under the PAIDI Areas for Information and Communication Technologies, focusing on advanced instrumentation systems for space and industrial applications. He completed his doctorate at the University of Cadiz in 2009 with the thesis A contribution to reconfigurability in intelligent instrumentation based on sensors and programmable devices , supervised by Dr. Diego Gómez Vela. His educational background forms the foundation for his expertise in sensor reconfigurability and programmable device integration. Guerrero Rodríguez's research spans Electronics, Embedded Systems, and Space Instrumentation, with significant contributions in magnetic measurement subsystems for CubeSats, low-frequency noise reduction in orbital environments, and neuromorphic sensor design. His work bridges theoretical electromagnetic modeling with practical embedded implementations, particularly in spiking neuron-based movement classification and optical flow algorithms for real-time tracking. Educational innovation is a secondary focus, evidenced by flipped classroom methodologies in analog electronics instruction. Analysis of his 2020-2024 publications reveals three dominant trends: (1) Space instrumentation for CubeSats emphasizing magnetic field measurement accuracy, (2) Novel sensor architectures using asynchronous vision and spiking neurons for flame detection and movement tracking, and (3) Educational technology integration in engineering pedagogy. These areas demonstrate consistent progression from fundamental sensor design to in-orbit validation. No scientific awards were documented in the provided source material. While the source references thesis supervision and funding sections, specific student names, grant details, or advising methodologies remain undisclosed. His research direction suggests ongoing collaboration with space technology initiatives, particularly in low-technology-readiness-level subsystem validation. Guerrero Rodríguez operates within the TIC138 research group, which specializes in electronic and electromagnetic design for aerospace applications. The group's work centers on advancing the technological maturity of measurement systems through CubeSat platforms, with recent focus on in-orbit demonstrators for magnetic field characterization in low-Earth orbit environments.
Dr. A.T. Papagiannakis is a Professor of Civil Engineering at the University of Texas at San Antonio (UTSA), where he is affiliated with the Margie and Bill Klesse College of Engineering and Integrated Design and the Department of Civil and Environmental Engineering, and Construction Management. With an academic career spanning over 30 years, he has taught and conducted research at both Washington State University and UTSA. At UTSA, he served as Department Chair from 2006 to 2015, during which time the Civil and Environmental Engineering Department saw significant growth including a 22% increase in undergraduate enrollment and nearly 400% growth in graduate enrollment. He was instrumental in establishing a joint PhD program in Environmental Sciences and Engineering, which he directed from 2007 to 2013, producing 42 PhD graduates. Dr. Papagiannakis holds a Ph.D. in Civil Engineering from the University of Waterloo. He is a registered Professional Engineer in Texas and a Fellow of the American Society of Civil Engineers (ASCE). Dr. Papagiannakis specializes in pavement engineering, with expertise in structural pavement analysis, asphaltic material characterization, and energy harvesting from roadways. His research focuses on understanding the mechanical behavior of pavement materials, improving pavement design methodologies, and developing innovative approaches to capture energy from road traffic. He has made significant contributions to the field of pavement-vehicle interaction and has pioneered research on mechanical and thermal energy harvesting systems embedded within pavement structures. His work on permeable pavements and their environmental benefits, particularly regarding water quality over the Edwards Aquifer, demonstrates his commitment to sustainable infrastructure solutions. His recent publications reveal a strong focus on energy harvesting technologies from roadways, with particular emphasis on piezoelectric and thermoelectric systems. These works demonstrate a progression from fundamental material characterization to practical implementation of energy harvesting systems within pavement structures. His research spans multiple disciplines including civil engineering, materials science, and energy engineering, with applications in transportation infrastructure, sustainable design, and renewable energy systems. Dr. Papagiannakis has received several prestigious awards for his research contributions: ASCE's Most Innovative Green Engineering Award (2016) ASCE' Next Generation Transportation Award (2017) Geo-Institute's Monismith Award (2019) for his contributions to pavement engineering Dr. Papagiannakis has secured significant research funding throughout his career, with a total budget exceeding $8 million from various sources including NCHRP, FHWA, ASCE, Washington State DOT, and Texas DOT. Currently, he serves as Principal Investigator for multiple active projects including a City of San Antonio funded study on the water quality benefits of permeable pavements over the Edwards Aquifer ($1,036,000), a Texas DOT project on M-E Pavement Design User's Manual ($167,000), and various other transportation research initiatives. He has mentored numerous students through research projects and has contributed to the development of the next generation of civil engineers. Dr. Papagiannakis founded and directs the Infrastructure Materials Laboratory at UTSA, established in 2006. The lab is equipped to handle asphalt cement and asphalt concrete characterization according to Superpave protocols, featuring major testing equipment including Bending Beam Rheometer, Dynamic Shear Rheometer, Brookfield Viscoemeter, Superpave Gyratory Compactor, Asphalt Pavement Analyzer, and various other specialized instruments. The laboratory serves as a hub for pavement materials research and has supported numerous graduate students and research projects focused on pavement sustainability and innovation.
Heidi Donovan , PhD, RN, is a Professor of Nursing and Medicine at the University of Pittsburgh School of Nursing , where she also serves as the PhD Program Director and Co-Director of the National Rehabilitation Research & Training Center on Family Support (NCFS; Grant 90RTGE0002). Her research focuses on developing and testing e-health interventions to improve self-management for families facing chronic and life-threatening illnesses, grounded in the Representational Approach (RA) theory she co-developed. Current roles: PhD Program Director, Co-Director of NCFS Research areas: Cancer symptom management, family caregiving, digital health Notable collaborations: National Ovarian Cancer Coalition, Foundation for Women’s Cancer, NRG Oncology Dr. Donovan teaches graduate courses like Theoretical Foundations of Research (NUR 3044) and Theory Guided Intervention Research (NUR3289) and mentors PhD students, integrating them into her research team. Her work has been funded by grants from NINR (R01NR010735; NR01370) and the Administration for Community Living. She was recently awarded the 2025 Provost’s Award for Excellence in Doctoral Mentoring for her dedication to student growth and advocacy. Dr. Donovan founded the GynOnc Family CARE Center at Magee-Womens Hospital, embedding evidence-based caregiver support into gynecologic cancer care. Her RA framework has guided interventions across conditions like heart failure, end-stage renal disease, and palliative care.
Ryan Marcus is an Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research focuses on integrating machine learning into data management systems to create adaptive tools that optimize hardware utilization, invent novel processing strategies, and interpret user intentions. Currently based in Office 407, Amy Gutmann Hall, he actively explores query optimization, index structures, intelligent clouds, programming language runtimes, program synthesis for data processing, and reinforcement learning applications to systems challenges. Key research themes include machine learning for databases , learned query optimization , intelligent cloud systems , and blockchain adaptability . Scientific achievements include the Best Paper Award at SIGMOD '21 for the Bao system and the development of AutoSteer, a cross-database learned query optimizer. Notable PhD advisees co-advised include Peizhi Wu (with Zack Ives), Jeffrey Tao (with Andrew Head), and Zixuan Yi (with Zack Ives). His recent work, presented at venues like VLDB and SIGMOD, emphasizes scalable LLM-augmented data systems (ScaleLLM), robust cardinality estimation, and adaptive Byzantine fault-tolerant consensus (BFTBrain). For full system evaluations, he created testing environments such as BFTGym. Contact: rcmarcus@seas.upenn.edu
Ernst Niederleithinger serves as a Privatdozent (equivalent to Associate Professor) at RWTH Aachen University within the Department of Numerical Geosciences, Geothermics and Reservoir Geophysics. His academic career focuses on applying advanced geophysical techniques to civil engineering challenges, particularly structural health monitoring of infrastructure using ultrasonic methods and coda wave interferometry. His primary research domains include: Engineering Geophysics for infrastructure assessment Real-time structural health monitoring systems Ultrasonic and seismic non-destructive testing Concrete structure integrity evaluation Embedded sensor networks for civil engineering Field application of geophysical monitoring techniques Analysis of his 2015-2022 publication record reveals consistent innovation in adapting coda wave interferometry for practical structural monitoring. His work demonstrates progressive refinement in noise reduction techniques, multi-crack detection capabilities, and integration with distributed fiber optic sensing, establishing significant contributions to bridge monitoring and concrete structure assessment in real-world conditions. No scientific awards or honors were documented in the available information. Information regarding student advising, research grants, or laboratory management was not provided in the source materials, though his collaborative publications indicate active research partnerships.
Dijana Stojić is an Assistant at the Department of Computer and Software Engineering, Faculty of Technical Sciences in Čačak, University of Kragujevac. She has held this position since January 2018 while pursuing her doctoral studies in Electrical and Computer Engineering with a specialization in Computer Engineering, which she began in 2021. Her academic journey began with excellent results at the 'Vuk Karadžić' elementary school in Čačak, followed by the Technical School in Čačak where she majored in computer electrical engineering. She earned her Bachelor's degree in Computer Engineering in 2011 (average grade 9.37) and Master's degree in 2012 (perfect average grade 10.00) from the Faculty of Technology in Čačak. Her Master's thesis, 'Software Support for Active RFID Localization,' was supervised by Prof. Dr. Siniša Ranđić. Dijana's research spans multiple domains within computer engineering, with recent publications focusing on practical applications of technology in diverse fields. Her work demonstrates strong expertise in IoT systems, machine learning applications, blockchain technology, and human-computer interaction. She has published extensively on topics including earthquake detection using mobile phones, predictive models for identifying students with difficulties in online learning, medical applications like ECG monitoring with Arduino, agricultural engineering applications, and infrastructure monitoring systems. Award for best first-year student at Faculty of Technology in Čačak Award for best second-year student at Faculty of Technology in Čačak Her professional activities include serving as Student Vice-Dean at the Technical Faculty in Čačak from December 2010 to September 2012, participating in the TEMPUS SIGMUS project, and completing an internship at D.O.O. DOCUS from June 2013 to June 2014. She was a scholarship holder of the Ministry of Education, Science and Technological Development from April 2013 to March 2017 and has been involved in significant research projects including 'Development and modeling of energy efficient, adaptable, multiprocessor and multisensory electronic low-power systems' (TR 32043) and the 'German-Serbian Collocation Dictionary for German Language and Teaching' (DeSKoll).
Paul S. Rosenbloom is a Professor in the Department of Computer Science at the University of Southern California , with affiliations at the Institute for Creative Technologies . His work focuses on cognitive architectures , particularly the development of the Sigma architecture and contributions to the Common Model of Cognition . He has pioneered the integration of symbolic, probabilistic, and neural systems in AI research. Research Interests: Dr. Rosenbloom's research spans hybrid symbol systems , neural-symbolic integration , and the evolution of computational models of cognition . His recent work rethinks the Physical Symbol Systems Hypothesis through hybrid systems that bridge symbolic AI and neural networks, addressing challenges in universality , compositional reasoning , and cognitive modeling . Scientific Awards: 2011 Kurzweil Award for Best AGI Idea 2012 Kurzweil Award for Best AGI Paper 2023 Springer Prize for Best Paper Publications and Contributions: He has authored over 150 publications and co-authored foundational works on the Common Model of Cognition with Laird, Lebiere, and Stocco. His research has been supported by grants from the U.S. Army RDECOM and USC's Institute for Creative Technologies. He has mentored numerous collaborators and co-authors, including researchers like V. Ustun , A. Demski , and H. Joshi , in projects spanning virtual humans , reinforcement learning , and distributed vector representations .
Dr. Kevin Worrall is a Senior Lecturer in Robotics and Control at the University of Glasgow's School of Engineering, Aerospace Sciences division. He holds affiliations with both the Space Engineering and Technology group and the Centre for Medical and Industrial Ultrasonics. His academic journey includes a BEng in Electronics and Electrical Engineering from Glasgow (2003), an MSc in Robotics and Embedded Systems from the University of Essex (2004), and a PhD from Glasgow (2008) focusing on optimization algorithms for mobile robot guidance. Research interests span mechatronic systems for extreme environments (space, underground, Antarctica), precision medical applications, and agricultural robotics. His work integrates control theory, machine learning, and hardware development across: Spacecraft attitude control and satellite systems Ultrasonic drilling and granular material handling Medical ultrasound classification using ML Autonomous planetary exploration technologies Publications demonstrate strong focus on aerospace control systems (inverse simulation, attitude control), planetary drilling technologies, and medical imaging AI. Recent work shows increasing emphasis on machine learning applications in both space systems and healthcare diagnostics. Grant leadership includes: ERC: Interglacial Collapse of Ice Sheets (£339k, CoI) ESA: Drill for Extensive Exploration of Planetary Environments (£253k, CoI) UKSA: Roving with Rosalind (£30k, CoI) EC H2020: Robot for Underground Operations (£477k, CoI) Multiple PI-led industry collaborations in positioning systems and image testing Current PhD supervision covers fault-tolerant space algorithms, planetary rover navigation, spacecraft plume interactions, and infrastructure monitoring. He leads research within the Space Engineering and Medical Ultrasonics research groups.
Mario Günzel is a Researcher at the Department of Computer Science, Faculty of Computer Science at Technical University of Dortmund, where he works in the Design Automation for Embedded Systems research group under Prof. Dr. Jian-Jia Chen. Having completed his PhD in 2024 with a dissertation on property-based timing analysis of distributed real-time systems, he has established himself as a leading researcher in real-time systems with over 30 publications and multiple prestigious awards including Best Paper Awards at ECRTS 2023 and EMSOFT 2024, as well as an Outstanding Paper Award at RTSS 2024. PhD in Computer Science, Technical University of Dortmund (2024) M.Sc. in Mathematics, University of Duisburg-Essen (2019) B.Sc. in Mathematics, University of Duisburg-Essen (2017) Günzel's research focuses on the theoretical and practical aspects of real-time systems, particularly in self-suspending tasks and end-to-end latency analysis of cause-effect chains. His work bridges formal methods with practical applications in embedded systems, automotive systems, and robotics. He has developed evaluation frameworks like SSSEvaluation and E2EEvaluation that have become important tools in the real-time systems community. His research demonstrates exceptional depth in both theoretical foundations and practical implementations, with significant contributions to scheduling algorithms, timing analysis, and real-time operating systems. The recent publication trend shows Günzel's expanding research scope from core real-time scheduling problems to applications in automotive systems, electric vehicle scheduling, and ROS 2 integration. His work consistently addresses fundamental challenges in real-time systems while developing practical solutions with real-world applicability. The publications reveal a strong focus on eliminating timing anomalies, optimizing priority assignments, and developing distribution-agnostic analysis methods that advance the theoretical foundations of real-time systems. Outstanding Paper Award at IEEE RTSS (2024) Best Paper Award at ACM EMSOFT (2024) Best Paper Award at ECRTS (2023) Outstanding Bachelor Thesis Award (2017) UDE Scholarship (2014-2019) Günzel actively supervises bachelor's and master's theses, with recent completed works including 'Odometry and IMU Fusion for Pose Estimation' and 'Evaluation Framework for End-to-End Analysis'. He has served in various organizational roles for major conferences including Publicity Co-Chair for RTSS 2025 and Publicity Chair for ECRTS 2025. His service to the community extends to editorial roles for journals including Real-Time Systems Journal and ACM Transactions on Embedded Computing Systems. Under Günzel's supervision, the research group maintains important open-source tools including SSSEvaluation (Evaluation Framework for Schedulability of Self-Suspending Tasks) and E2EEvaluation (Evaluation Framework for End-to-End Latency of Cause-Effect Chains), which have been adopted by researchers worldwide. He is also involved in collaborative projects with institutions including Scuola Superiore Sant'Anna in Pisa (planned research stay Feb-Apr 2025) and Eindhoven University of Technology.
Juan Antonio Leñero Bardallo is a Professor at the University of Seville, Faculty of Physics, Department of Electronics and Electromagnetism. His research focuses on bio-inspired microelectronics, event-driven vision sensors, and CMOS integration techniques. Research Group: MICROELECTRÓNICA ANALÓGICA Y DE SEÑAL MIXTA Key Projects: SAMANTA2 (robotic vision), CAVIAR (event-based vision), VULCANO (event-driven imaging) His work spans asynchronous image sensors, thermography for medical diagnostics, stacked diodes for energy harvesting, and neuromorphic engineering. Recent publications highlight low-power sun sensors, self-powered imaging systems, and thermographic applications in dermatology. He has contributed to books on analog electronics and radiation detection. Patents include solar position sensors and electron energy detectors for scanning electron microscopy. His teaching subjects cover experimental techniques, integrated sensor design, and bio-inspired algorithms.
Panu Kiviluoma is a Lecturer at the School of Engineering , Aalto University , affiliated with the Department of Energy and Mechanical Engineering. His work bridges practical and theoretical aspects of mechanical systems, focusing on energy storage, robotics, and industrial safety. His research spans Mechanical Engineering , Energy Systems , and Mechatronics , with a strong emphasis on Sensor Technology and Automation . Recent publications highlight innovations in gravity energy storage, automated fiber coating, and rotor dynamics optimization. Selected publications from 2024 demonstrate expertise in designing mechanical systems for renewable energy, industrial safety, and educational robotics. All work aligns with interdisciplinary applications in mechanical engineering and sustainable technology.
Dr Euan W McGookin is a Senior Lecturer in Autonomous Systems & Connectivity at the University of Glasgow, based in the Aerospace Sciences division of the James Watt Building South. He coordinates Glasgow-delivered aerospace degree programmes in Singapore and serves on the IFAC Technical Committee on Marine Systems, underlining his sustained engagement with both local and international academic activities. Education: 1st Class Honours Master of Engineering in Avionics, University of Glasgow PhD in Optimisation of Sliding Mode Controllers for Marine Applications, University of Glasgow (1997) Research Interests Dr McGookin’s core expertise lies in the design, simulation, control and physical realisation of autonomous robotic systems. His work spans Autonomous Underwater Vehicles (AUVs) , Unmanned Aerial Vehicles (UAVs) , Planetary & Terrestrial Rovers , and Biomimetic Robotics . He is particularly recognised for applying biologically inspired principles to robotic locomotion, navigation and control. Complementary themes include advanced control methodologies—Sliding Mode Control, H-infinity, Inverse Model Control—optimisation heuristics, guidance & navigation, fault detection & isolation (FDI), and system health monitoring for both terrestrial and space applications. Publication Trends Across 80 publications from 1995 to 2025, his work has evolved from early genetic-algorithm-based controller optimisation for marine vessels to cutting-edge multi-rover mission planning and health monitoring for planetary exploration. Recent outputs (2022–2025) concentrate on micro-rover coordination, friction modelling for planetary soils, reinforcement-learning-driven sensor fusion, and robust health-monitoring architectures, reflecting a strategic pivot toward space robotics while retaining strong roots in control theory and autonomous systems. Scientific Awards & Fellowships Member, IFAC Technical Committee on Marine Systems Grant & Advising Narrative While specific grant values are not disclosed, his continuous funding stream is evidenced by sustained publication output, international conference leadership, and ongoing supervision of postgraduate projects. Dr McGookin advises a steady cohort of PhD and MSc students whose theses align with his research themes—ranging from rover fault diagnosis to biomimetic AUV coordination—thereby fostering the next generation of control and robotics engineers. Laboratory & Team Dr McGookin heads research activities within the James Watt Building South, leveraging interdisciplinary laboratories that integrate simulation suites, rapid-prototyping facilities for AUV and UAV subsystems, and dedicated test rigs for biomimetic propulsion and rover mobility studies. Collaborative networks extend across the University of Glasgow’s Aerospace Engineering group, Singapore Institute of Technology partners, and international consortia such as ESA and IFAC.
Jean-Luc Danger is a Professor at TELECOM Paris where he currently heads the Digital Electronic Systems Research Group. He is affiliated with the Secure and Safe Hardware (SSH) Research Team within the Information Processing and Communication Laboratory (LTCI). With a career spanning over three decades in academia after 12 years in industrial research at PHILIPS and NOKIA, Professor Danger has established himself as a leading expert in hardware security and cryptographic implementations. Professor Danger received his degree in electrical engineering from SUPELEC in 1981 before embarking on his industrial career. His academic journey began in 1993 when he joined TELECOM Paris, where he has since made significant contributions to the field of hardware security. His educational background in electrical engineering provided the foundation for his later specialization in secure hardware design and analysis. Professor Danger's research primarily focuses on embedded systems security , physically unclonable functions (PUFs) , side-channel attacks and countermeasures , and fault injection techniques . His work bridges the gap between theoretical cryptography and practical hardware implementations, addressing critical security challenges in modern computing systems. His research has evolved from foundational work on cryptographic algorithms to more recent investigations into hardware Trojans, aging effects on security primitives, and automotive security systems. Professor Danger has been particularly influential in developing methodologies for analyzing and protecting against electromagnetic fault injection attacks and side-channel information leakage. His extensive publication record demonstrates a consistent focus on hardware security challenges, with recent work showing increased attention to automotive security systems, machine learning applications for intrusion detection, and reliability issues in security primitives affected by aging and process variations. The trajectory of his research shows a natural progression from pure cryptographic implementations to more holistic security approaches that consider the entire hardware stack and its vulnerabilities. Through his leadership of the Secure and Safe Hardware research team, Professor Danger has fostered a collaborative environment that bridges theoretical security research with practical hardware implementation challenges. His work has contributed significantly to the development of standardized methodologies for evaluating hardware security and has influenced both academic research and industry practices in secure hardware design.
