María del Pilar Jarabo Amores is a Full Professor at the Department of Signal Theory and Communications, University of Alcalá. Her research focuses on passive radar systems, sensor networks, and signal processing for defense and surveillance applications. She leads the AES3 research group (Acoustic and Electromagnetic Smart Sensor networks and Signal processing) and has expertise in radar detection, clutter modeling, and target tracking. Education: PhD in Telecommunications Engineering from the University of Alcalá (2005), supervised by Dr. Francisco López Ferreras. Research Interests: Development of passive radar technologies using DVB-T/S signals, motion compensation algorithms, and AI-driven detection methods. Key application areas include drone surveillance, maritime monitoring, and urban traffic imaging. Her work emphasizes robust detection in cluttered environments and distributed sensor network architectures. Key Contributions: Pioneered motion compensation techniques for passive radar systems, designed smart antennas for improved coverage (e.g., Ku-band microwave video camera), and developed adaptive beamforming methods. Her group's IDEPAR demonstrator showcases passive radar capabilities for terrestrial traffic monitoring. Labs/Teams: Leads the AES3 group, collaborating on EU-funded projects involving SAR imagery analysis and oil spill detection. Active in developing sensor networks for critical infrastructure protection.
Omar AL-Buraiki is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He specializes in Robotics Automation, Machine Intelligence Algorithms, and Autonomous Systems, with over 12 years of research experience across Canadian and international institutions. His work focuses on developing industrially oriented solutions for defense, robotics, and telecommunications sectors. Education: Ph.D., Electrical and Computer Engineering, University of Ottawa M.A.Sc., Systems Engineering, King Fahad University B.Sc., Electronics and Communications Engineering, Hadhramout University Research Interests: His research spans AI/ML Robotic Vision, Autonomous Systems, Automatic Control, Intelligent Automation, and Multi-Robot Coordination. He has pioneered nonlinear control systems, task allocation algorithms, and machine learning-driven robotic vision solutions, notably through his leadership of the SMART Lab during his PhD. Publications & Trends: His 20+ publications emphasize probabilistic task allocation, sensor fusion, and adaptive control in robotics. Recent work (2023–2025) focuses on slip-compensated visual-inertial odometry and heterogeneous robotic systems under actuator delays. Earlier papers (2016–2020) established foundational methods for specialized agent task assignment in swarm robotics. Achievements: Secured a USPTO patent for robotics automation technology Over 20 peer-reviewed articles and 12+ conference presentations Teaching & Advising: Instructor for courses on control systems, robotics, and AI-based vision at both undergraduate and postgraduate levels Developed specialized courses like Autonomous Vehicles Navigation and Control Labs & Teams: Former leader of the SMART Lab (University of Ottawa), currently active in robotics research at the University of Waterloo’s Mechanical and Mechatronics Engineering Department.
Prof. Dr. René Fahr is a Professor in the Department of Management at Paderborn University's Faculty of Business Administration and Economics, specializing in Corporate Governance and Behavioral Economics. He leads the Chair of Corporate Governance and co-directs the Behavioral Economic Engineering & Responsible Management research area at the Heinz Nixdorf Institute. His work focuses on ethical corporate decision-making, sustainable governance, and human-machine interaction, leveraging experimental methods in the BaER-Lab experimental economics laboratory. Research Interests: - Compliance and Ethical Decision-Making - Sustainable Corporate Governance - Behavioral Ethics - Experimental Economics - Human-Machine Collaboration in Industrial Systems Collaborations include industry partners like Weidmüller, PwC, and dSPACE, as well as academic partnerships such as with Queensland University of Technology. He co-founded the annual Business Ethics Forum to bridge academic and theological perspectives on business ethics. Fahr’s research outputs span over 50 publications in journals like Regional Science and Urban Economics and Customer & Service Systems . Teaching includes foundational and advanced courses on Corporate Governance, emphasizing practical applications through real-world case studies and lab experiments. He oversees student research projects and advises on master's theses in behavioral economics and corporate responsibility. Labs/Teams: Lead of the BaER-Lab and the Behavioral Economic Engineering group at the Heinz Nixdorf Institute.
Pekka Parviainen is an Associate Professor in the Department of Informatics at the University of Bergen, within the Faculty of Mathematics and Natural Sciences. His research spans machine learning, probabilistic modeling, and AI theory, with a focus on Bayesian and Markov networks, adversarial robustness, fairness, and energy forecasting. He is affiliated with the Center for Data Science (CEDAS), an active research center at the university. His research interests include: Structure learning in graphical models Probabilistic forecasting using graph neural networks Adversarial robustness and defense mechanisms Fairness in clustering and machine learning Optimization and approximation in learning algorithms Applications in renewable energy and quantum sensing His recent publications (2020–2025) reflect a strong theoretical grounding combined with real-world applications, particularly in energy systems and AI safety. The works trend toward scalable and interpretable models, with increasing focus on fairness and robustness. Key themes include Bayesian network learning, metric learning, and causal graph modeling. Scientific contributions include: Development of novel adversaries (e.g., Voronoi-epsilon) for measuring robustness Scalable algorithms for learning large DAGs and Bayesian networks Integration of continuous optimization with combinatorial heuristics Applications in electricity demand forecasting and gas sensing Parviainen advises PhD students, including Hyeongji Kim (2023 thesis on distance in machine learning), and collaborates extensively with researchers in Norway and internationally. He has received computational support via Sigma2 (NN9884K) and is part of the CEDAS project, which fosters interdisciplinary data science research. While no specific grants are detailed, his involvement in funded projects and high-impact publications indicates active grant engagement. He is associated with the Center for Data Science (CEDAS), where he contributes to advancing data-driven methodologies across domains. The team emphasizes scalable, robust, and fair AI systems, aligning with national and international research priorities in trustworthy machine learning.
Tiedo Tinga is a Full Professor at the Netherlands Defence Academy and a leading expert in Dynamics-Based Maintenance . With over 175 research outputs and an h-index of 30, his work focuses on predictive maintenance, fault diagnostics, and prognostics in mechanical systems. Research Highlights : Bayesian filtering, sensor performance evaluation, composite material diagnostics, and smart maintenance systems. Scientific Recognition : Recipient of the 2015 Maintenance Awareness Award. Recent Contributions : Advanced methods for impact identification in composites, integration of FMEA/FTA in fault diagnosis, and applications of transfer learning for marine propulsion systems. His research combines physics-based models with data-driven approaches to solve practical maintenance challenges in defense and industrial applications. Recent Publications (2025-2023): Application of transfer learning for shaft power predictions, Bayesian filtering frameworks, bond graph diagnostics, and sensor performance comparisons in composite structures. Scientific Awards Maintenance Awareness Award (2015) Professional Activities Invited talks at conferences (2023-2025) on predictive maintenance, smart systems, and data-driven maintenance challenges. Collaborations on motor vibration monitoring datasets and defense technology projects.
Todd M. Bishop, Ph.D., is an Assistant Professor in the Department of Psychiatry at the University of Rochester Medical Center. He also serves as an Affiliated Research Investigator at the VA VISN 2 Center for Integrated Healthcare and Assistant Director of Fellowship Training at the Canandaigua VA Medical Center's Center of Excellence for Suicide Prevention. PhD in Clinical Psychology, Syracuse University (2014) Post-doctoral Fellowship: VA Advanced Fellowship in Mental Illness Research and Treatment (2014-2016) His research examines how sleep disturbances like insomnia and sleep apnea contribute to suicidal behavior, particularly through exacerbation of co-occurring disorders (e.g., PTSD, depression, substance abuse) and care transitions. He emphasizes primary care settings for intervention scalability, focusing on brief therapies and existing treatment utilization. Key research themes from his publications include: CBT for insomnia in comorbid conditions Pain-insomnia-suicide pathways Opioid misuse and suicide risk Mechanistic models of sleep-suicide links Administrative data for suicide prediction Moral injury in veterans Scientific awards highlight his contributions to sleep research and veterans' mental health, including the VA Sleep Practitioner Jr Investigator Award (2017) and multiple Sleep Research Society recognitions. His military service (Army Achievement Medal, Defense of Liberty Medal) informs his focus on veteran populations. Bishop collaborates with institutions like the Sleep Medicine Division of the Canandaigua VA Medical Center and works on multicenter trials such as the Veterans Coordinated Community Care Study. His work bridges clinical practice, research, and training programs for suicide prevention.
Thanh H. Nguyen is an active Assistant Professor in the Department of Computer Science within the College of Arts and Sciences at the University of Oregon. She teaches courses including Introduction to Artificial Intelligence (CS 471/571) and Multi-Agent Systems (CS 410/510), with office hours held in Deschutes Hall. Her educational background includes a Ph.D. from the University of Southern California (2016), a postdoctoral position at the University of Michigan (2016-2018), and a B.Sc. from Hanoi University of Science and Technology. Her research bridges theoretical AI with practical applications addressing real-world societal challenges. Dr. Nguyen's work focuses on Artificial Intelligence applications for societal benefit, particularly in Public Safety and Security (urban crime prevention, counterterrorism), Cybersecurity (protection from stealthy botnets), Sustainability (wildlife and fish protection), and Public Health (diabetes prevention). Her research integrates techniques from Multi-Agent Systems, Game Theory, Machine Learning, and Optimization with insights from Psychology and Conservation Biology. Her recent publications demonstrate strong trends in security games, adversarial learning, and health applications, with significant focus on strategic deception, robust decision-making under uncertainty, and real-world deployment of AI systems. The work shows increasing interdisciplinary collaboration and practical implementation of theoretical models. Deployed Application Award (IAAI 2016) for PAWS wildlife protection system Runner-up Best Innovative Application Paper Award (AAMAS 2016) WiSE Merit Fellowship from University of Southern California (2015) Runner-Up Best Paper Award at Recourse-21 Workshop (ICML 2021) Army Research Office Grant (~$343K) for Adversarial Reasoning (2020-2023) Dr. Nguyen actively advises PhD students including Sarah Kinsey and Michael Dushkoff (co-advised with Prof. Allen D. Malony), along with numerous master's and undergraduate students. Her research has received significant grant funding, including an Army Research Office grant for developing methods to tackle sequential and coordinated attacks in security domains with real-time information. Her work on the PAWS (Protection Assistant for Wildlife Security) system has been deployed by NGOs like Panthera and the Wildlife Conversation Society in conservation areas in Malaysia and Uganda. She leads the AI Lab at the University of Oregon, which focuses on multiple research projects including AI for Public Health, Deception in Security Games, Security in Data-based Decision Making, Information Leakage and Exploration, and Game Theory for Cybersecurity. The lab maintains strong industry and NGO partnerships for real-world application of research findings.
Harry Millwater is the Samuel G. Dawson Endowed Professor and Associate Chair for Research in the Mechanical Engineering Department at the University of Texas at San Antonio's Margie and Bill Klesse College of Engineering and Integrated Design. With over three decades of academic and research experience, he has established himself as a leading expert in structural mechanics and computational methods. Dr. Millwater's primary research focuses on fracture mechanics, probabilistic structural analysis, sensitivity analysis, and computational mechanics. His work bridges theoretical developments with practical applications in structural reliability, fatigue analysis, and digital twin technologies. He has pioneered methods using hypercomplex variables for sensitivity analysis, which have significantly advanced the field of computational mechanics and structural engineering. His extensive publication record shows a clear evolution from foundational work in probabilistic structural analysis to cutting-edge research in hypercomplex automatic differentiation applied to structural mechanics. Recent publications demonstrate a strong focus on developing arbitrary-order sensitivity analysis methods using hypercomplex mathematics, with applications spanning structural dynamics, fracture mechanics, additive manufacturing, and uncertainty quantification. His scientific recognition includes multiple U.S. Air Force Research Lab Summer Faculty Fellowships awarded in consecutive years (2005-2007). These prestigious awards reflect the practical impact of his research on aerospace engineering applications. Dr. Millwater's research has been supported by significant funding from defense and aerospace sectors, particularly the Air Force Office of Scientific Research. His work on probabilistic methods for risk assessment of airframe digital twin structures represents a major contribution to modern structural integrity assessment. He has also contributed to educational initiatives focused on improving STEM education at Hispanic-serving institutions. His laboratory work centers on computational mechanics, with emphasis on developing and implementing advanced numerical methods for structural analysis. The ZFEM (Complex Variable Finite Element Method) framework appears to be a cornerstone of his research program, enabling high-precision sensitivity calculations that have broad applications across engineering disciplines.
Murat Üçüncü is an Associate Professor in the Department of Electrical and Electronics Engineering at Başkent University . He holds a PhD (1989), MSc (1985), and BSc (1983) from Boğaziçi University, and an additional BSc from Kara Harp Okulu (1980). His academic career spans over 35 years, with a focus on RF systems, control theory, and defense technologies. PhD, Boğaziçi University (1989) MSc, Boğaziçi University (1985) BSc, Boğaziçi University (1983) BSc, Kara Harp Okulu (1980) His research interests include RF power amplifier design, MEMS-IMU systems, underwater communication, and graph signal processing for automotive RADAR. Recent work emphasizes adaptive Kalman filtering, avionics network simulations, and autonomous systems for UAVs. Key article trends show expertise in RF circuit optimization , Kalman filter adaptation , and graph-based classification algorithms . No scientific awards are mentioned in the provided data. Advised 21+ students in areas spanning control systems, avionics, and defense technologies Led projects on shaped charges, underwater communication systems, and avionics networks
Diana Saplacan Lindblom is a Researcher at the University of Oslo's Department of Informatics, Faculty of Mathematics and Natural Sciences. She is a member of the Robotics and Intelligent Systems Research Group (ROBIN) and actively contributes to the Vulnerability in Robot Society (VIROS) research project (2021-present) and the Ethical Risk Assessment of Artificial Intelligence in Practice (ENACT) project (2023-present). Dr. Saplacan received her Ph.D. from the University of Oslo in 2020 with a thesis titled "Situated abilities: Understanding Everyday Use of ICTs" from the Design of Information Systems (DESIGN) Research Group. During Spring 2023, she was a visiting researcher at the Human-Robot Interaction Lab, Department of Social Informatics, Kyoto University, Japan, and a guest researcher at Tohoku University's Frontier Research Institute for Interdisciplinary Sciences. Her research focuses on user studies in Human-Robot Interaction (HRI) and Human-Robot cooperation, with particular emphasis on digitalization of home- and healthcare services, robots as welfare technologies, and ethics regarded through Universal Design principles. She investigates privacy, safety, and security aspects related to robots in healthcare settings, bridging legal and technical considerations. Her work often employs qualitative methods including story dialogue techniques to understand user perspectives and professional reactions to emerging technologies. Analysis of her recent publications reveals a strong interdisciplinary approach connecting computer science, social sciences, and healthcare. Her work spans technical aspects of robotics, ethical considerations in AI implementation, and practical user studies across diverse populations including elderly care recipients and healthcare professionals. She frequently examines how Universal Design principles can be applied to social and assistive robots to ensure accessibility and inclusion. Dr. Saplacan has received notable recognition including an Honorable Mention at HRI (2024) and being named among "Women changing the field of AI in Norway" (2021, 2022). She has also earned Best Paper Awards at ACHI-IARIA (2018, 2020) and a Best Paper Finalist Award at ARSO (2021). HRI Honorable Mention (2024) Women changing the field of AI in Norway (2021, 2022) Best Paper Finalist Award - ARSO (2021) Best Paper Award, ACHI - IARIA (2020) Best Paper Award, ACHI - IARIA (2018) Dr. Saplacan has served as co-supervisor for Ph.D. candidates Adel Baselizadeh (completed 2024) and Marieke van Otterdijk (defense scheduled for December 2024). Her research is supported through collaborations with multiple academic partners including SINTEF, HIOF, and NTNU, as well as industry partners such as DNB, Posten, NAV, Medsensio, and Hypatia Learning. She actively contributes to standardization efforts as a member of Standards Norway Committee on AI & Ethics (WG3) and the IEEE Artificial Intelligence Standards Committee. She is a key contributor to the ROBIN research group's work on healthcare robotics and leads efforts in the UD-Robots project, which examines how universal design principles can be applied to robotics. Her work with the Norwegian Council for Digital Ethics and participation in international workshops demonstrates her commitment to shaping ethical frameworks for emerging technologies.
Andrii Shalaginov is a Professor in Cyber Security at Kristiania University of Applied Sciences, School of Economics, Innovation and Technology. He leads the Smart Security Lab with a research focus on applying artificial intelligence for cybersecurity, detection of computer viruses, network attacks and protection of Internet of Things devices. Dr. Shalaginov holds a PhD in Information Security from the Norwegian University of Science and Technology (NTNU), where he worked with digital forensics at the Center for Cyber and Information Security (CCIS). His research spans multiple critical areas of modern cybersecurity with a particular emphasis on Internet of Things security , machine learning applications for threat detection, and digital forensics . He has developed expertise in intelligent malware detection systems, network security for smart environments, and forensic analysis of IoT devices. His work bridges theoretical computer science with practical security implementations for real-world systems. Analysis of his recent publication trends (2022-2025) reveals a strong focus on AI-enabled security solutions for IoT ecosystems, vulnerability detection frameworks, and resource-efficient security mechanisms for constrained devices. His research increasingly addresses the intersection of machine learning and practical security implementations, with growing attention to energy efficiency in security protocols and international data space security frameworks. Dr. Shalaginov has received professional recognition through: Nomination as Norwegian representative in EU COST Action CA17124 "DigForAsp" Nomination as Norwegian representative in EU COST Action CA22104 "BEiNG-WISE" Membership in the "Impact of Technology" Expert Group at the European Union Intellectual Property Office Observatory As head of the Smart Security Lab, Dr. Shalaginov oversees research projects focused on developing practical security solutions for emerging technologies. His GitHub activity demonstrates active development of open-source tools for malware analysis across multiple platforms (Linux, Windows, IoT) and implementation of machine learning approaches for security applications. His research group appears to focus on bridging the gap between theoretical security models and practical implementations for real-world systems.
Dr. Erik Kline is a Computer Scientist and Research Lead at the Information Sciences Institute (ISI) of the University of Southern California (USC), leading critical research in network and cyber-security through projects including SABRES (DARPA OPS-5G), APROPOS (DARPA SearchLight), and DREAMS (NSF). His educational background includes: B.S. in Computer Science from Georgia Institute of Technology M.S. in Computer Science from University of California, Los Angeles Ph.D. in Computer Science from University of California, Los Angeles Dr. Kline's research centers on network security with emphases on anomaly detection, line-rate traffic analysis, DDoS defense mechanisms, anonymity systems, and security-aware routing protocols. His innovative work in large-scale network modeling enables scientifically rigorous experimentation and validation of complex network systems, directly addressing evolving cybersecurity threats through both theoretical frameworks and practical implementations. His publication record demonstrates consistent advancement in network security testbeds, traffic analysis, and defensive architectures. Key themes include machine learning applications for encrypted traffic classification, novel approaches to DDoS mitigation through traffic deflecting and authentication, and foundational work on security-aware routing systems. These contributions collectively strengthen network infrastructure resilience against sophisticated attacks while maintaining operational efficiency. No scientific awards were mentioned in the provided text. Dr. Kline directs substantial research funding as Principal Investigator on multiple high-impact projects including SABRES (DARPA OPS-5G), APROPOS (DARPA SearchLight), and EXCEED (DARPA XD3), alongside leadership in DREAMS (NSF) and EdgeLab (DARPA EdgeCT). His grant portfolio consistently bridges theoretical innovation with real-world deployment, evidenced by successful technology transitions to commercial applications. Based at USC/ISI's Network and Cyber-security Division, Dr. Kline actively develops and enhances DETERLab for cybersecurity experimentation. His team creates advanced network emulators capable of processing millions of packets per second while implementing realistic network impairments, supporting complex experiments in edge computing, 5G security, and cyber-physical systems through multi-institutional collaborations.
Dr Saeed Sharif is an Associate Professor in the Computer Science department at the School of Architecture, Computing and Engineering , University of East London . He leads the Intelligent Technologies Research Group and serves as Course Leader for MSc Computer Science programs. With a PhD in artificial intelligence from Brunel University London , his work bridges Artificial Intelligence , Medical Technology , and Smart Infrastructure . His research interests span Medical Image Analysis , Intelligent Diagnosis Systems , Big Data Analysis , and IoT Security . Collaborations with NHS Trusts and global institutions focus on improving healthcare systems through machine learning and biomedical signal processing. 2018-2022: £268,000 KTP project with Innovate UK Multiple Research Internship Schemes at UEL (2017-2021) European Research Centre collaboration (2015) As a technical committee member for conferences like IEEE CIT and a journal Guest Editor , he drives academic discourse. He has supervised numerous PhD students and served on examination panels, while maintaining 53+ publications in venues including IEEE Access , Applied Soft Computing , and Computer Methods and Programs in Biomedicine .
Ahmed Serhrouchni is a Professor at Télécom Paris, affiliated with the Computer Science and Networks (Infres) department. He leads the Specialized Masters® in Design, Network Architecture and Cybersecurity and Cybersecurity and Cyberdefense. His research focuses on cybersecurity, cryptography, blockchain, and IoT security. Research interests include: Secure blockchain applications in healthcare and vehicular networks Lightweight cryptographic protocols for IoT and C-ITS Machine learning for security threats detection (e.g., DNS flooding, Sybil attacks) Anti-jamming mechanisms in vehicular communication PUF schemes resistant to ML attacks Recent publications highlight advancements in blockchain scalability, TLS protocol security, and vehicular network defenses. His work emphasizes practical implementations for 5G, IoV, and secure authentication in distributed systems. He is associated with the Cybersecurity and Cryptography (C²) team and the Information Processing and Communication Laboratory (LTCI).
Manuel Egele is an Associate Professor at Boston University’s Department of Electrical and Computer Engineering and co-leads the Secure Systems Lab , a member of the International Secure Systems Lab. His work bridges software, systems, and embedded/mobile security with a focus on privacy. His recent research trends include IoT kernel module analysis ( FirmSolo ), PHP web application debloating ( Minimalist ), and fuzzing innovations ( MORPHUZZ , ThreadLock ). He explores microarchitectural vulnerabilities, denial-of-service detection, and hardware-assisted security mechanisms, often publishing in top venues like USENIX Security , NDSS , and ACM CCS . Egele actively contributes to academic service as an area chair, poster chair, and committee member for conferences such as IEEE Oakland, USENIX Security, and NDSS. He teaches courses like EC440: Operating Systems , EC521: Cyber-Security , and EC700: Vulnerability and Malware Defense , emphasizing practical security education.
