Turhan Hilmi Demiray is the Head of the Research Center for Energy Networks (FEN) at ETH Zürich, Switzerland , where he leads industrial and academic research projects in energy systems. His academic background includes a Ph.D. in Electrical and Computer Engineering from ETH Zürich (2008) and an M.Sc. in Telecommunications from TU Vienna (2003). He has held academic and industry roles at ABB Vienna AG, NEPLAN AG, and ETH Zürich’s Power Systems Laboratory.
Professor Paul Black is a distinguished academic at King's College London, affiliated with the School of Education, Communication & Society and the Centre for Research in Education in Science, Technology, Engineering & Mathematics (CRESTEM). His career has centered on advancing educational assessment and pedagogy, particularly in STEM disciplines. He is renowned for pioneering formative assessment strategies that integrate learning and evaluation to enhance student outcomes. Research Interests: Black's work explores how teacher-led assessments can drive classroom innovation, emphasizing the synergy between formative and summative methods. His contributions address global educational challenges, including standardization debates and the equitable implementation of assessment frameworks. Key Article Trends: His publications from 2013–2020 highlight themes like ethical assessment practices, the historical impact of formative assessment, and bridging theory-practice gaps in STEM education. Recent works underscore the adaptability of assessment strategies in diverse cultural and linguistic contexts. Professional Impact: The 2023 book 'Educational Assessment: The Influence of Paul Black on Research, Pedagogy and Practice' documents his legacy, noting his influence on scholars worldwide. His ideas have informed policy responses to crises like pandemic-related exam cancellations. Advising & Grants: While specific grants or advisees are not detailed here, his work reflects collaborative research with educators and policy experts. The CRESTEM centre serves as a hub for advancing his vision of holistic educational reform.
Roman Obermaisser is a Professor at the Vienna University of Technology (TU Wien), affiliated with the Cyber-Physical Systems department. His research focuses on real-time systems, system architectures, communication protocols, safety-critical systems, distributed algorithms, and fault-tolerance. He holds a PhD in Computer Science from TU Wien, awarded in 2003 for his work on integrated architectures for control paradigms. His academic contributions span over two decades, with publications in top-tier conferences and journals. Key research themes include time-triggered architectures (TTA), fault containment in embedded systems, and integration of heterogeneous communication protocols like CAN and Ethernet. He has supervised numerous graduate students, contributing to advancements in system-on-chip (SoC) design, transient-resilient architectures, and diagnostic frameworks for real-time systems. Obermaisser’s work emphasizes practical applications in automotive and industrial systems, addressing challenges such as scalability, reliability, and composability. His involvement in projects like GENESYS and DECOS highlights his role in developing cross-domain reference architectures for embedded systems. Recent efforts include evaluating ontology-based reconfiguration and COTS-based Ethernet solutions for safety-critical networks. His articles reflect a focus on real-time communication protocols, fault-tolerant design, and system integration, with applications ranging from automotive networks to smart transducers. Advising over 20 students underscores his commitment to nurturing the next generation of embedded systems researchers.
Professor Michael Keidar holds the A. James Clark Professorship at the George Washington University (GW) , School of Engineering and Applied Science, within the Mechanical and Aerospace Engineering department. He leads the Micropropulsion and Nanotechnology Lab , pioneering research in plasma medicine, micropropulsion systems, and plasma nanoscience. His lab collaborates with industry partners like Vector (licensed plasma thruster technology) and US Patent Innovations, LLC (a $5.3M grant for cold plasma cancer therapy). Key research areas include: Cold plasma applications in biomedical treatment Microthrusters for nanosatellites Synthesis of graphene and carbon nanotubes Multi-scale plasma simulations Scientific accolades include the 2017 Ronald C. Davidson Award and AIAA Engineer of the Year (2016-2017), alongside leadership in interdisciplinary projects with GW’s Global Food Institute .
Babak Moaveni is a Professor in the Department of Civil and Environmental Engineering at Tufts University, serving as the Associate Chair since September 2024. He also holds a joint appointment as a Professor in Electrical and Computer Engineering. His research focuses on structural health monitoring, Bayesian inference, earthquake engineering, and offshore wind energy systems. Moaveni earned his Ph.D. in Structural Engineering from the University of California San Diego (2007), following an M.S. (2001) and B.S. (1999) from Sharif University of Technology in Tehran, Iran. His research interests span probabilistic system identification, signal processing, uncertainty quantification, and verification/validation of computational models. Notable grants include leadership in the PIRE project on offshore wind energy digital twins and the Coastal Virginia Offshore Wind Pilot Project. He has supervised multiple Ph.D. and M.S. students, with current advisees including Mehdi Akhlaghi and Nasim Partovi-Mehr. Moaveni has received the Best Presentation Award at the 2022 EDGE Symposium and serves on editorial boards for journals like Structural Health Monitoring and Frontiers in Built Environment . His lab, the Structural Health Monitoring Lab, specializes in infrastructure management and offshore wind energy systems. Key professional activities include membership in the American Society of Civil Engineers (ASCE) and roles on Tufts' Tenure and Promotion Committee. His teaching includes courses on structural health monitoring, numerical methods, and structural reliability.
Patrick Wu is a Professor in the Department of Computer Science at American University, with additional affiliations as Faculty Fellow at the Center for Data Science and Faculty Affiliate at the Center for Security, Innovation, and New Technology. He holds a PhD in Political Science and Scientific Computing from the University of Michigan, an MA in Statistics from Michigan, and a BA in Political Science and Statistics from the University of Chicago. His research develops AI/ML and natural language processing approaches for computational social science, focusing on: Political elite and non-elite ideology measurement Affective polarization on social media platforms Detection of hateful/abusive speech and memes Application of large language models to political science research Recent work explores innovative methods for political attitude measurement using LLMs, in-context learning techniques for social media analysis, and frameworks for multimodal representation learning. His publications demonstrate consistent innovation in applying NLP and machine learning to political discourse analysis, with emerging focus on generative AI's impact on political science education and methodology. Wu teaches courses including Object-Oriented Programming and topics in Natural Language Processing/Text as Data.
John Dalsgaard Sørensen is a Professor and Head of Research Group at the Department of the Built Environment, Aalborg University, within the Faculty of Engineering and Science. He leads the Risk, Resilience, Safety, and Sustainability of Systems Research Group and is affiliated with the Danish Centre for Risk and Safety Management. His research focuses on structural safety, wind turbine reliability, probabilistic design, and risk assessment of infrastructure systems. He has supervised 13 PhD students and contributed to over 600 publications. Key research areas include wind turbine structural integrity, fatigue analysis of offshore and onshore structures, probabilistic design standards (e.g., Eurocodes), and risk-based decision-making for infrastructure. He leads projects like Windscanner (remote sensing for wind measurements) and MANTIS (cyber-physical maintenance systems). Collaborations span academia and industry, addressing challenges in energy systems, civil infrastructure, and safety engineering. His work emphasizes practical applications of advanced modeling techniques, such as Bayesian networks and stochastic simulations, to enhance reliability and reduce operational costs. He is actively involved in standardization efforts for structural design and serves on boards like Energi- og MiljøData Fonden. Recent activities include presenting at international conferences and advising on media debates related to structural safety.
Kari Lappalainen is an Assistant Professor in the Department of Electrical Engineering at Tampere University, affiliated with the Faculty of Information Technology and Communication Sciences. His research focuses on photovoltaic power systems, energy storage technologies, and renewable energy integration. He leads studies on photovoltaic module aging, parameter identification, and energy storage system optimization for power smoothing and ramp rate control. Key research interests include: Photovoltaic module diagnostics and performance analysis Energy storage system design for hybrid renewable plants Impact of environmental factors (e.g., temperature, cloud cover) on PV efficiency Advanced modeling techniques for photovoltaic systems Recent work emphasizes real-time monitoring of PV degradation via current-voltage curve analysis and optimization of energy storage configurations to mitigate power fluctuations. Over 50 peer-reviewed publications demonstrate sustained contributions to renewable energy systems research. Notably absent are awards or formal advisee listings, though collaboration with institutions like EU PVSEC and frequent conference participation indicate active academic engagement.
Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.
Mai Ha Vu is an Assistant Professor at the University of Toronto Mississauga , split between the Department of Language Studies and the Department of Mathematics, Computer Science, and Statistics . Her work bridges theoretical linguistics, computational methods, and biological data modeling. Ph.D. in Linguistics, University of Delaware (2020) M.A. in Linguistics, University of Delaware (2014) B.A. in Psychology and Linguistics, Grinnell College (2013) Research focuses on applying formal language theory to understand human language patterns and train biologically reliable language models . Recent work includes antibody language modeling (Nature Computational Sciences 2022) and syntax-prosody mapping via logical transductions (SIGMORPHON 2022). Key research trends in publications: interdisciplinary applications of computational linguistics to immunology, psycholinguistic modeling of neural language models, and formal syntactic analysis of negation and wh-questions across languages.
Kyprianos Papadimitriou is a Researcher at the Microprocessor and Hardware Laboratory within the School of Electrical and Computer Engineering at the Technical University of Crete . He holds a PhD in Electronic and Computer Engineering (2012) and has been involved in teaching laboratory courses such as Logic Design , Computer Architecture , and VLSI/ASIC Circuit Design . Research Areas : His work spans Reconfigurable Systems , Hardware Design , Computer Architecture , RFID Systems , and Real-Time Systems . He has developed innovative approaches in FPGA-based dynamic reconfiguration, MPSoC security, and 3D stereo vision for surveillance. Key Trends : Runtime reconfiguration for FPGAs Security frameworks for NoC-based MPSoCs Low-cost embedded vision systems Optimization of reconfiguration overhead Hardware task scheduling methodologies Genetic algorithm implementations on FPGAs Scientific Contributions : 1 USA patent (2005) Co-author of VLSI-SoC 2013 paper nominated for 1st Prize Active member of scientific committees (FPL, ReConFig) Peer reviewer for IEEE, Elsevier, and Springer journals Session chair at IEEE CNS and HPCC conferences Grants & Projects : Participated in competitive European and national programs, serving as scientific manager, coordinator, and technical coordinator. Developed spin-off company (2003-2005) to commercialize master's thesis research. Laboratory & Teaching : Affiliated with the Microprocessor and Hardware Laboratory , focusing on practical training in digital systems, processor-based systems, and VLSI design.
Andreas Grothey is a Senior Lecturer in the School of Mathematics at The University of Edinburgh, a position he has held since 2011. He completed his MSc in Numerical Algebra and Mathematical Computing at the University of Dundee (1995) and his PhD in Optimization at the University of Edinburgh (2001), supervised by Ken McKinnon. His research focuses on stochastic programming, interior point methods, decomposition approaches, high-performance computing, and energy systems optimization. He has contributed to energy planning, power grid reliability, and emergency response strategies for power networks. Grothey has advised seven PhD students, including work on unit commitment, top-percentile traffic routing, and power flow optimization. His projects include the OOPS solver, CESI energy integration center, and the Structured Modelling Language (SML). Recent work addresses pandemic policy optimization and exascale computational challenges. Education: MSc in Numerical Algebra and Mathematical Computing (University of Dundee, 1995) PhD in Optimization (University of Edinburgh, 2001) Research Interests: Stochastic Programming Interior Point Methods Decomposition Methods High-Performance Computing Energy Systems Optimization Advising & Projects: PhD Supervision (7 students, 2007–2022) OOPS Parallel Solver Development CESI Energy Systems Integration SML Structured Modelling Language Labs/Teams: Member of the Edinburgh Research Group on Optimization, leading projects in power grid stability and energy planning.
Dr. Terje Haukaas is a Professor of Structural & Earthquake Engineering at the University of British Columbia (UBC), Department of Civil Engineering, Faculty of Applied Science. He holds a PhD and Master's from UC Berkeley (2003, 1999) and a bachelor's from the Norwegian University of Science and Technology (1996). His research focuses on probabilistic modeling, structural reliability, and earthquake engineering, with contributions to software development (e.g., FERUM, OpenSees). He teaches courses like Structural Analysis, Nonlinear Analysis, and Reliability & Safety. Education: PhD in Civil Engineering, UC Berkeley, 2003 Master's in Civil Engineering, UC Berkeley, 1999 Bachelor's in Civil Engineering, NTNU, Trondheim, 1996 Engineering Degree (Stavanger University College, 1994) and Technician Degree (Stavanger Technical College, 1992) Research Interests: Probabilistic mechanics and reliability analysis Seismic vulnerability and risk assessment Software tools for finite element analysis (FERUM, OpenSees) Timber engineering and structural optimization Awards & Recognition: UBC Killam Teaching Prize (2016) President of CERRA (2015–2019) Keynote/Semi-plenary speaker at major conferences (ICASP12, COMPDYN 2017) Student Appreciation Awards (Top Professor rankings) Grants & Labs: Recipient of grants supporting seismic risk research Developed computational frameworks for structural analysis
Glaucio H. Paulino holds the Margareta Engman Augustine Professorship in Civil and Environmental Engineering at Princeton University, where he also serves as a Professor at the Princeton Institute for the Science and Technology of Materials (PRISM). His work bridges computational mechanics, topology optimization, and materials science. Paulino leads a research group focused on advancing structural design methodologies, fracture mechanics, and functionally graded materials. His team has pioneered polygonal finite elements and multiresolution topology optimization techniques, addressing challenges in mesh bias and computational efficiency. He has published over 240 peer-reviewed articles and mentored 19 PhD and 11 MS students. Notable contributions include the PPR cohesive model for fracture analysis and adaptive mesh refinement for dynamic simulations. Paulino's research extends to practical applications such as high-rise building design and sustainable construction materials. Awards include election to the European Academy of Sciences and Arts and ASME’s Melville Medal. Current projects involve functionally graded cement-based materials, extrusion processing, and digital image correlation for material characterization. His lab collaborates with industry partners like Skidmore, Owings & Merrill LLP to translate topology optimization into real-world engineering solutions. Paulino’s interdisciplinary approach integrates computational modeling with experimental validation, fostering innovations in civil infrastructure resilience.
Jordi Guitart Fernández is a Professor at the Department of Computer Architecture, Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading national supercomputing facility. He leads the CROMAI research group, focusing on Computing Resources Orchestration and Management for AI. His work bridges high-performance computing, cloud systems, and artificial intelligence. Research Interests: Cloud Computing and Edge Computing Green and Energy-Efficient Computing Containerization and Virtualization for HPC Resource Orchestration and Management Autonomic and Self-Adaptive Systems Machine Learning Workflow Management AI-Driven System Optimization His recent publications reveal a strong focus on intelligent management of computing resources across cloud, edge, and HPC environments using machine learning and agent-based frameworks. He investigates performance, efficiency, and reliability in containerized AI and HPC workloads, particularly within Kubernetes and distributed infrastructures. His work increasingly integrates human-in-the-loop and trustworthiness aspects into AI systems. Scientific Awards: CLOUD Conference 2025 Best Paper Award VISIGRAPP 2025 Best Student Paper Award Premi Extraordinari de Doctorat 2025 - Àmbit d'Enginyeria de les TIC Test of Time Award Honorable Mention (e-Energy) Reconeixement als Mèrits Docents d'Especial Qualitat Top reviewers for Polytechnic University of Catalonia (Computer Science) - September 2017 Advising and Grants: He has advised doctoral students, including Peini Liu. He leads and participates in numerous competitive R+D+i projects, such as CROMAI and DALEST, funded by national and European programs like HORIZON 2020 and the Spanish State Research Plans. His work is supported by grants focused on knowledge generation and industrial leadership in computing technologies. Labs and Teams: He is the leader of the CROMAI - Computing Resources Orchestration and Management for AI research group at UPC. He also collaborates closely with the Barcelona Supercomputing Center (BSC-CNS), contributing to large-scale computing initiatives and strategic research agendas in Europe.
