Dr. Anne-Catherine A.A.M. Dieudonné is an Assistant Professor in Geotechnical Field Testing and Monitoring at Delft University of Technology's Faculty of Civil Engineering and Geosciences. She holds a Ph.D. in Structural, Seismic, and Geotechnical Engineering from Politecnico di Milano, where she previously worked as a doctoral researcher and assistant professor until joining TU Delft in 2022. Her research focuses on experimental, numerical, and theoretical analysis of soil-structure interaction problems, including foundations, tunnels, embankments, and slope retaining systems. Key interests include developing simplified models for infrastructure design, improving sustainability and reliability of structures, and understanding time-dependent material responses. Her work spans geotechnical monitoring with fiber optics, constitutive modeling of geomaterials (e.g., cement-bentonite mixtures), and energy geotechnics. Notable contributions include studies on tunnel face stability, pile-supported embankments, and bio-cemented soils. Publications emphasize THM modeling for geothermal systems, fracture mechanics, and nuclear waste repository optimization. She collaborates internationally, contributing to advanced multiphysics approaches in geomechanics.
Prof Juliana Bowles is a Professor at the School of Computer Science, University of St Andrews. Her research focuses on applying formal methods (model checking, constraint solving) to healthcare challenges such as polypharmacy, cancer treatment optimization, and clinical decision support systems. She collaborates with clinicians and engineers to develop tools for medication safety and efficient healthcare processes. Notable projects include EPSRC-funded work on automated conflict resolution in clinical pathways and RAE-funded collaborations with Brazil on healthcare process analysis. Her expertise spans formal verification, concurrency, and health informatics. She leads projects addressing global health challenges through computational techniques, including work on endometriosis care, cancer treatment in the elderly, and secure healthcare data sharing platforms. Supervising PhD students like Ariane Hine and Qurat Ul Ain Shaheen, she integrates interdisciplinary approaches to enhance healthcare outcomes. Key Collaborations: Royal Academy of Engineering (RAE), UNISC Brazil, EPSRC Grants: EPSRC (EP/M014290/1), RAE Newton Research Collaboration (Project NRCP1617/5/62) Publications: Over 90 peer-reviewed articles, focusing on formal methods in healthcare and computational medicine Her work contributes to UN Sustainable Development Goals by improving healthcare access and decision-making through technology. She develops secure systems for medical data sharing and personalized treatment strategies, balancing usability and privacy concerns in healthcare IT.
Robert Lagerström is a Professor at KTH Royal Institute of Technology specializing in Industrial Information Systems. His research focuses on developing automated cyber security frameworks and threat modeling methodologies for large-scale IT environments. Key areas include vulnerability analysis of IoT, automotive systems, and critical infrastructure, with a particular emphasis on probabilistic modeling and simulation languages like vehicleLang and powerLang. He collaborates extensively with industry partners across automotive, banking, energy, and cloud sectors to validate practical security solutions. His work emphasizes model-based security analysis that avoids disrupting live systems, enabling safe testing of cyber defenses. Notable contributions include the securiCAD tool for enterprise cyber security management and the PatrIoT framework for agile threat research in IoT ecosystems. Lagerström's research integrates enterprise architecture modeling with security behavior analysis, addressing challenges in digitalization and agile development environments. He has pioneered methods for quantifying attack resilience through probabilistic threat simulations and has published widely on topics such as LPWAN security, SCADA system vulnerabilities, and ethical considerations in offensive cyber training. His work bridges theoretical cyber security concepts with real-world implementation challenges in both traditional IT and emerging technologies like blockchain and microservices architectures.
Professor Sarah L Dance is a Professor of Data Assimilation and EPSRC Senior Fellow in Digital Technology for Living With Environmental Change at the University of Reading's Department of Mathematics and Statistics, part of the School of Mathematical, Physical and Computational Sciences. She leads the Data Assimilation Research Centre (DARC) and focuses on advancing data assimilation techniques in weather forecasting, hydrology, and environmental monitoring. Her work integrates cutting-edge computational methods with real-world applications, particularly in improving flood prediction and soil moisture estimation through innovative modeling approaches. Her research interests span data assimilation algorithms, remote sensing applications, and numerical modeling of environmental systems. Recent work emphasizes the use of satellite data, radar observations, and deep learning for environmental monitoring and disaster management. She collaborates extensively with international institutions on projects like Hydro-JULES and the Transatlantic Data Science Academy, advancing both theoretical and applied aspects of environmental data science. Professor Dance has contributed to operational systems such as the Met Office's data assimilation frameworks and has pioneered methods to handle observation uncertainty in high-resolution models. Her projects often bridge academia and industry, addressing challenges in flood forecasting, climate modeling, and sensor data integration.
Paolo Ceravolo is an Associate Professor of Computer Science at State University of Milan, affiliated with the SEcure Service-oriented Architectures Research Lab. His research spans process mining, fairness in AI, knowledge representation, and inclusive technologies. At Human Hall, he directs the Inclusive Artificial Intelligence project and HH4AI initiative focused on human rights impact assessment under the EU AI Act. Publications address fairness assurance in data augmentation, gender bias detection in translation systems, and process mining frameworks for fraud reduction. Technical contributions include the CoSMo simulation framework for business processes and ReJOOSp for SPARQL optimization. His work combines theoretical research with practical applications in criminal investigations, healthcare systems, and regulatory compliance. Ceravolo co-founded Inpolitix (political platform development) and contributed to the Smart Bear project for elderly care monitoring.
Christian Johansen is a Professor at the Department of Information Security and Communication Technology, NTNU, leading the Systems Security Group (S2G). He specializes in Security and Theoretical Computer Science, focusing on formal methods for complex systems' reliability, including security, safety, and concurrency. His work involves models like the Timed Distributed pi-calculus and tools such as LightSC for IoT security. Education: Completed doctoral studies at the University of Oslo in 2010. Research interests span formal verification, cyber-physical systems, and human behavior modeling. Over 60 publications in top venues like CONCUR, ATVA, and journals such as JLAMP. Advising and Grants: Supervised numerous PhD/MSc students and led projects funded by EU-FP7, Horizon-2020, NFR-FRINATEK, and others. Involved in organizing conferences and workshops in formal methods and security. Labs/Teams: Heads S2G and contributes to CCIS, Norwegian Cyber Range, and S2G Playground. Develops tools like SAT modulo Discrete Event Simulation for railway systems and models for human behavior in security.
Duane McVay is a Professor and Albert B. Stevens Chair in Petroleum Engineering at Texas A&M University's College of Engineering, where he also serves as Associate Director of the Crisman Institute for Petroleum Research. His educational background includes a Ph.D., M.S., and B.S. in Petroleum Engineering from Texas A&M University. McVay's research focuses on: Risk and uncertainty quantification in energy systems Unconventional resource evaluation methodologies Integrated reservoir characterization techniques Petroleum reservoir simulation advancements Energy investment optimization under uncertainty His publications demonstrate consistent focus on uncertainty management in energy resource assessment, with recent work emphasizing Bayesian statistical methods, production forecasting improvements, and bias reduction techniques in reserves estimation. The research spans shale resources globally and addresses both technical and economic dimensions. Significant scientific honors include: Distinguished Member, Society of Petroleum Engineers (2007) Distinguished Lecturer, Society of Petroleum Engineers (2015-2016) Practice Award, Decision Analysis Society (2006) Member, Petroleum Engineering Academy of Distinguished Graduates (2015) McVay leads research initiatives at the Crisman Institute, collaborating with industry partners to address challenges in petroleum resource evaluation and management.
Miguel Matos is an Assistant Professor at Instituto Superior Técnico (IST) of Universidade de Lisboa and a Researcher at INESC-ID's Distributed Systems Group. His research focuses on Persistent Memory systems, blockchain scalability, distributed systems evaluation, and database performance. He has led major projects such as Angainor (reproducible evaluation tools) and ACT-PM (crash-consistency testing). Research interests include exploring persistent memory's challenges, blockchain Layer-2 limitations, automated bug detection (HawkSet, Mumak), and decentralized network emulation (Kollaps). He has received awards like the Gilles Muller Best Artefact Award at EuroSys 2025 and Best Paper Awards at DAIS 2017 and IPDPS 2012. He coordinates multi-million Euro grants including EU's Qualichain and national FCT projects. Teaching includes courses like 'Highly Dependable Systems' and 'Large-Scale Systems Engineering' at IST. His work bridges academia and industry, collaborating with startups like MIMA Housing and LeanXcale.
Peter Winter is a physicist in the High Energy Physics Division at Argonne National Laboratory, serving as Intensity Frontier Group Leader since 2019 and Co-Spokesperson for the Muon g-2 Collaboration since 2023. He earned a Dr. rer. nat. (2005) and Dipl. Phys. (2001) from the University of Bonn, Germany. Research Interests: Winter focuses on precision measurements in muon physics to test fundamental symmetries and the Standard Model. His work includes the Muon g-2 experiment, investigating anomalous magnetic moments, and developing advanced magnetometry techniques for particle physics applications. Scientific Awards: DOE Office of Science Early Career Research Award (2015) Günther-Leibfried Award (2001) Notable Contributions: Winter has led key advancements in magnetic field calibration for muon experiments, improved understanding of muon decay dynamics, and optimized detector systems for precision measurements.
Raúl Mateos Gil is an Associate Professor at the Universidad de Alcalá, affiliated with the Department of Electronics. He specializes in electronic engineering applied to renewable energy systems through the GEISER research group. His work focuses on hardware/software co-simulation techniques for system-on-chip (SoC) design and verification, as evidenced by his doctoral research. Education: Doctorate in Electronics from Universidad de Alcalá (2006), thesis: Técnicas de cosimulación Hw/Sw para el diseño y verificación de sistemas CsoC advised by Dr. José Luis Lázaro Galilea. His research emphasizes renewable energy systems integration, with particular attention to electronic engineering solutions for energy conversion and embedded system optimization. No recent publications or grants are explicitly listed in the provided text. No scientific awards or academic advising records are mentioned in the current data.
Álvaro Paricio García is an Assistant Professor at the Department of Automation within the School of Telematics Engineering at Universidad de Alcalá. He is affiliated with the NetIS Research Group (Networks and Intelligent Systems). His research focuses on smart city technologies, traffic engineering, optimization algorithms, and environmental engineering, with a particular emphasis on urban mobility, crowd evacuation systems, and emission reduction strategies. Education: He holds a PhD from Universidad de Alcalá, awarded in 2021 for his thesis Estrategias multi-mapa para el enrutamiento dinámico de tráfico urbano , supervised by Dr. Miguel Ángel López Carmona. Research Interests: His work integrates control systems, machine learning, and simulation-based optimization to address challenges in urban traffic management, crowd dynamics, and sustainable transportation. Key themes include: Design of low-emission zones for urban areas Development of adaptive evacuation systems using MPC (Model Predictive Control) Algorithmic innovations in traffic routing and multi-map strategies Article Trends: Recent publications (2021-2025) highlight his focus on: Wind farm layout optimization using metaheuristics Biometric identification via autoencoder-driven systems Dynamic low-emission zones and their policy implications Adaptive crowd evacuation systems like CellEVAC No scientific awards or grants were explicitly mentioned in the provided texts. He has not supervised any listed students. Labs/Teams: Active member of the NetIS Research Group, which develops networks and intelligent systems for urban and industrial applications.
Miljana L. Milić is a Full Professor at the Faculty of Electronics, University of Niš, Serbia, Department of Electronics. She has been an integral part of this institution since earning her degrees and advancing through academic ranks, culminating in her appointment as full professor in 2024. Education: PhD in Electronics, Faculty of Electronics, University of Niš (2009) Master’s in Electronics, Faculty of Electronics, University of Niš (2005) Bachelor’s in Electronics, Faculty of Electronics, University of Niš (2001) Her research interests span a broad spectrum of electronics engineering, with emphasis on VLSI design, analog and digital circuit diagnosis, cryptographic hardware security, timing analysis under aging, and performance optimization in neural prediction systems. She applies simulation, statistical methods, and AI techniques to solve complex problems in electronic systems design and reliability. The analysis of her recent publications reveals a strong focus on hardware-level innovation, including secure cryptographic cells, fault diagnosis in analog circuits, performance modeling under fading and shadowing, and timing degradation in VLSI systems. Her work bridges theoretical analysis with practical implementation in electronic design and communication systems. She leads the Laboratory for Design of Electronic Processes, Circuits and Automatic Control Systems, and is currently involved in one national research project. Her contributions include over 10 journal publications in high-impact venues. Scientific Contributions: Head of Laboratory for Design of Electronic Processes, Circuits and Automatic Control Systems Active participant in national research projects Author/co-author of 10+ journal papers with impact factor She mentors students through research supervision and contributes to academic leadership within her department. Her work continues to influence both academic research and practical applications in electronic systems engineering.
Jinhua Guo is an Associate Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn's College of Engineering and Computer Science. He holds a Ph.D. from the University of Georgia and B.E./M.E. degrees in Computer Science from Dalian University of Technology. His research spans vehicular networking , mobile/cloud computing , cybersecurity , and optimization algorithms . His recent work focuses on data center energy optimization using neural networks, cache robustness in named data networks , and real-time task scheduling on multi-core processors . Earlier contributions include MAC protocols for vehicular networks and context-aware routing in VANETs . Scientific awards and grants include: NSF Grant (co-PI): Enhancing Pervasive/Mobile Computing Security Education (2014-2016) Amazon AWS in Education Grant (PI): 2012-2015 NSF Grant (PI): Mobile Computing Research for Automotive Applications (2005-2010) He has advised 14 graduate students, including: John P. Baugh (Ph.D., 2018) Vishal Singh (Ph.D., 2016) Jun Liu (Ph.D., 2015) Ryan Bankston (Ph.D. in progress)
Niels Erik Olesen is a Postdoc researcher at the Department of Biotechnology and Biomedicine, Technical University of Denmark (DTU), affiliated with the Nano Bio Integrated Systems group. He serves as Contact Person for the DTU project "Active Wearable Sensors for Monitoring of Levodopa in Parkinson’s Disease" (2023-2025) and is a Member of the International Electrotechnical Commission (2022-2026). His ORCID profile (0009-0001-3908-5043) and institutional email nieol@dtu.dk confirm his active DTU affiliation. Research interests center on electrochemical sensors and drug delivery systems. Early work (2012-2018) focused on biopharmaceutics, including thermodynamic modeling of cyclodextrin formulations, bile salt interactions, and drug-polymer solubility prediction using DSC/ITC techniques. Current research pivots to wearable sensor technology, specifically microneedle-based porous gold electrochemical sensors for real-time levodopa monitoring in Parkinson's disease patients, as evidenced by his active project and 2024 conference presentation. His 15 most recent publications (2015-2018) reveal strong methodological innovation in pharmaceutical formulation science. Key themes include DSC-based solubility prediction (7 articles), cyclodextrin-bile salt displacement mechanisms (4 articles), and polymer molecular weight effects on drug miscibility (3 articles). The shift toward electrochemical sensors is documented in his 2023 project but not yet reflected in publications, indicating emerging research direction. No scientific awards or fellowships were mentioned in the provided sources. Olesen leads the DTU research project on Parkinson's disease wearable sensors (100% focus on levodopa monitoring) and presented preliminary work as Guest Lecturer at a conference in November 2024. No student advisement is documented, though his project involves interdisciplinary collaboration. The International Electrotechnical Commission membership (2022-2026) suggests industry-standardization contributions. He operates within DTU's Nano Bio Integrated Systems group, focusing on nanoscale biointegration. His current project team develops microneedle-based electrochemical sensors for continuous levodopa monitoring, aiming to translate lab research into clinical Parkinson's management tools through wearable technology.
Gruia-Catalin Roman is a Professor in the Department of Computer Science at the University of New Mexico, within the College of Engineering. He has maintained a long-standing and impactful career in computer science research and education, with a focus on mobile computing, distributed systems, and the Internet of Things. His work bridges theoretical foundations and real-world applications, particularly in sensor networks and smart environments. Ph.D., Computer and Information Sciences, University of Pennsylvania, 1976 M.S., Computer and Information Sciences, University of Pennsylvania, 1974 B.S., Computer Science and Engineering, University of Pennsylvania, 1973 Roman's research interests center on enabling natural, responsive, and personalized interactions between people and smart environments. He explores middleware, formal methods, and human-centered computing to support IoT, mobile systems, and distributed applications. His work emphasizes paradigm shifts in how users interact with technology, particularly through spatial characteristics, augmented reality, and context-aware automation. The recent articles reflect a strong trajectory toward intelligent, user-aware IoT systems. Themes include conflict prediction, seamless automation, AR-based control, and abstraction layers like the Space Broker. These works demonstrate a shift from device-centric to human-centric computing, leveraging machine learning, middleware, and distributed algorithms to reduce user cognitive load and enhance personalization. SenSys 2022 Test of Time Award for early efforts to introduce sensor networking technology into clinical practice Roman has supervised 19 doctoral students, many of whom have pursued academic careers. He has secured significant research funding, including an NSF grant on context-assisted interactions in IoT with UT Austin. His leadership extends to organizing flagship conferences such as ICSE 2005 and FSE 2010, and serving on editorial boards of top software engineering journals. He is known for his innovative teaching, mentoring, and advocacy for active learning and multidisciplinary collaboration. Roman leads the Mobile Computing Laboratory (MobiLab), where students and researchers prototype and evaluate IoT interaction paradigms. The lab explores smart glasses, QR-based interfaces, and spatial control algorithms. His work often involves collaborations across institutions and disciplines, reflecting his commitment to impactful, real-world computing solutions.
