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Louis-Daniel PapeView profile

Assistant Professor

• Industrial Organization
• Labor Economics
• Digital Economics
• +3 more

Louis-Daniel Pape serves as an Assistant Professor at Télécom Paris within the CREST research center, specializing in Economics. His academic profile positions him as a permanent research member focused on empirical analysis at the intersection of digital platforms, labor markets, and competition policy. Affiliated with both Télécom Paris and CREST (Center for Research in Economics and Statistics), he contributes to France's leading economics research ecosystem. Pape's research centers on industrial organization and labor economics, with particular emphasis on digital economics and competition policy. His methodological approach combines reduced-form and structural modeling techniques applied to administrative datasets, web-scraped information, and firm-provided data. Current investigations examine platform self-preferencing practices, labor market concentration effects, and innovative econometric methodologies for handling zero values in regression analysis. His work demonstrates consistent engagement with real-world policy questions, particularly regarding digital market regulation and antitrust enforcement. Analysis of Pape's publication trajectory reveals a strong focus on digital economy regulation and labor market dynamics. His recent work on the Digital Markets Act's impact on Google Maps represents cutting-edge research in digital competition policy, employing difference-in-differences methodologies to assess regulatory interventions. Parallel investigations into labor market concentration, non-compete clauses, and wage collusion demonstrate methodological versatility across different market contexts. The recurring theme across his publications is the application of rigorous empirical methods to evaluate policy interventions in concentrated markets. Pape maintains active teaching responsibilities across multiple institutions. At Télécom Paris, he delivers courses in Applied Econometrics and Data Collection/Visualization for Master's students, while also teaching Big Data at École Polytechnique. His pedagogical approach integrates machine learning methods with traditional econometric techniques, reflecting the evolving nature of empirical economic research. Course materials demonstrate particular emphasis on instrumental variables, difference-in-differences designs, and structural modeling approaches. Pape's research infrastructure includes collaborations with major institutions including the French Ministry of Public Finances (DGFIP) on VAT fraud analysis for digital platforms. His methodological contributions, particularly the iterated Ordinary Least Squares (iOLS) framework for handling zero values in regression models, have gained recognition in the econometrics community with substantial downloads on SSRN. His software implementations for iOLS/i2SLS and Instrumented Differences-in-Differences (IVDID) methods are publicly available on GitHub, facilitating broader adoption of these techniques.

Jim HarkinView profile

Professor

• Embedded Systems
• Neural Networks
• Hardware Systems
• +5 more

Professor Jim Harkin serves as Head of the School of Computing, Engineering and Intelligent Systems at Ulster University's Magee Campus in Derry~Londonderry. He is a prominent member of the Computational Neuroscience and Neuromorphic Engineering team within the Intelligent Systems Research Centre (ISRC), where he leads cutting-edge research bridging biological neural processes with hardware implementations. Harkin's research focuses on developing intelligent embedded systems capable of self-repair under error conditions, drawing inspiration from neural network models. His work explores how computer models of neural networks can be mapped to hardware to build highly efficient and reliable embedded computers. Key innovations include Networks-on-Chip strategies and hardware implementation of self-repairing Spiking Neural Networks. His research spans multiple domains including fault tolerance, neuromorphic computing, and AI hardware acceleration, with applications in healthcare, structural monitoring, and energy systems. Analysis of his recent publications reveals a strong trend toward practical applications of neuromorphic computing, particularly in healthcare monitoring systems, structural health assessment, and energy-efficient computing. His work shows increasing integration of spiking neural networks with real-world hardware implementations, demonstrating a clear trajectory from theoretical models to deployable systems with commercial applications. Harkin has received numerous scientific accolades including the Life and Health Startup Company of the Year 2019 from InventNI Ulster Distinguished Learning Support Fellowship Multiple awards for innovative routing strategies in neural network hardware implementations Professor Harkin has secured significant research funding exceeding £3.5 million from diverse sources including EPSRC, MRC, Innovate UK, HSC R&D, InvestNI, and DEL. His grant portfolio demonstrates strong industry and healthcare sector engagement, particularly through his co-founded startup Respiratory Analytics which focuses on medical analytics. He has supervised numerous research students and has been instrumental in Ulster University's Computer Science submissions to major research assessment exercises including RAE 2008, REF2014, and REF2021. As Head of School and leader within the Intelligent Systems Research Centre, Harkin oversees multiple research teams focusing on computational neuroscience, neuromorphic engineering, and intelligent embedded systems. His lab has developed specialized FPGA-based platforms for simulating and implementing self-repairing neural networks, including the AstroByte multi-FPGA architecture for accelerated simulations of fault-tolerant spiking astrocyte-neuron networks.

• Structural Mechanics
• Finite Element Analysis
• Computational Mechanics
• +7 more

Ali Saleh is an Adjunct Associate Professor at the School of Civil and Environmental Engineering , University of Technology Sydney. With a PhD from RWTH Aachen University, he specializes in structural mechanics, finite element analysis, and cold-formed steel systems. Dr.-Ing, RWTH Aachen University (1982) Dipl.-Ing, RWTH Aachen University (1978) His research focuses on: Composite flooring systems integrating cold-formed steel and timber Seismic performance of industrial racking structures Slender high-rise building stability Advanced global-local finite element analysis Cable-stayed bridge failure modes Key trends in his 15 most recent publications include composite systems optimization (2018-2022), connection behavior in steel structures (2013-2019), and educational innovations (2008-2011). His work has been cited over 150 times, with high-impact studies on vibration behavior and shear connector performance. As a supervisor, he has guided PhD student Ahmad Firouzianhaji (2012-2015) He has held leadership roles including Deputy Head of School (2015-2017) and contributed to 14 funded industry collaborations with Dexion (Australia) Pty Ltd since 2003. His work bridges academic research with practical applications in structural engineering.

Yatsko Oksana MyroslavivnaView profile

Associate Professor

• Computer-oriented methodological systems for teaching
• Data mining and business analytics
• Game theory applications in economics
• +4 more

Yatsko Oksana Myroslavivna is an Associate Professor at the Department of Computer Science, Chernivtsi National University named after Yuriy Fedkovych. She holds a Candidate of Pedagogical Sciences degree (specialty 13.00.02 - theory and methods of teaching informatics) and has been certified as an Associate Professor since 2022. Her research focuses on computer-oriented methodological systems for teaching computer disciplines, with specializations in data mining for business applications, game theory implementation in economic decision-making, web technologies development, and algorithm design. She actively contributes to educational literature with multiple textbooks on Discrete Mathematics, Operations Research, Web Technologies, and Systems Modeling. Her professional engagements include membership in the Bukovina Information Technology Cluster, Chernivtsi Mathematical Society, and participation in international conferences like SPIE Optical Engineering and Correlation Optics. She has completed advanced certifications in machine learning, data visualization, and online education technologies from Prometheus, SoftServe, and other institutions. Her publications demonstrate expertise in strategic business analysis, cross-platform decision support systems, and educational software development. The 15 most recent works (2023-2024) cover data structures, game theory applications, web development tools, and polarization-based biomedical diagnostics. She serves as an expert for Ukraine's Ministry of Education and National Agency for Quality Assurance in Higher Education.

Matteo SpadaView profile

Researcher

• Risk Assessment
• Resilience Assessment
• Multi-Criteria Decision Analysis
• +4 more

Dr. Matteo Spada is a Senior Researcher in Risk and Resilience at the Zurich University of Applied Sciences (ZHAW) School of Engineering, where he focuses on Technology Assessment. His research spans multiple institutions including the Paul Scherrer Institute, Swiss Seismological Service, and Istituto Nazionale di Geofisica e Vulcanologia in Italy. His educational background includes a Ph.D. in Earth Sciences from ETH Zurich (2006-2011) and an MSc in Physics from the University of Bologna (1999-2005). Dr. Spada's research focuses on risk and resilience assessment of critical infrastructure systems, with particular expertise in energy systems, natural hazards, and multi-criteria decision analysis. His work integrates quantitative methods with practical applications to inform policy and decision-making processes related to infrastructure safety and security. He has developed innovative approaches for probabilistic risk assessment, uncertainty quantification, and decision support systems that have been applied across multiple sectors including energy, water resources, and transportation. His recent work has particularly emphasized the energy transition, analyzing comparative accident risks across different energy technologies and developing frameworks for assessing resilience of electricity supply systems. Through his research, he has contributed to understanding the societal implications of energy infrastructure failures and developing methodologies for more robust risk assessment. Dr. Spada is an active member of several professional networks including the European Safety and Reliability Association (ESRA), the Institute for Operations Research and the Management Sciences (INFORMS), and the Special Activity Group - Sustainable Concrete Structures of the International Federation for Structural Concrete. He leads several research projects including 'Innovative Spatio-Temporal multi-criteria decision analysis Interface to support informed decision-Making for real-world applications' and contributes to initiatives focused on urban energy transition, resilient supply chains, and building decarbonization. His work often involves interdisciplinary collaboration with engineers, economists, and policy experts to address complex infrastructure challenges. Dr. Spada maintains an active research laboratory focused on risk and resilience assessment, where his team develops and applies advanced analytical methods to real-world infrastructure challenges. The lab utilizes a combination of statistical modeling, simulation techniques, and decision analysis tools to support evidence-based policy making.

Bekir Tevfik AkgünView profile

Professor

• Artificial Intelligence
• Information Security
• Internet of Things
• +4 more

Prof. Bekir Tevfik Akgün serves as Professor and Dean of the Faculty of Computer and Information Sciences at Yeditepe University, with prior academic appointments at Istanbul Okan University (Department Head, Institute Director), Ohio State University, and Yildiz Technical University (Dean). His expertise spans artificial intelligence, information security, computer graphics, and distributed systems, supported by extensive research funding and supervision of 19 graduate students. Educational background includes: Ph.D. in Control and Computer Engineering, Istanbul Technical University (1991) M.S. in Control and Computer Engineering, Istanbul Technical University (1984) B.S. in Electrical Engineering, Istanbul State Academy of Engineering and Architecture (1981) His research integrates theoretical and applied computer science, with recent focus on AI-driven environmental monitoring (forest fire detection via drone-IoT networks), bioinformatics security, and advanced color models. Early work established foundational contributions in digital art (marbled paper techniques) and real-time operating systems, evolving into contemporary applications in energy management and autonomous systems. Publication trends since 2001 reveal consistent innovation across domains: computer graphics (2004-2024), distributed systems (2001), and emerging AI/IoT applications (2022-2024). The interdisciplinary nature of his work bridges theoretical computer science with practical implementations in security, environmental science, and human-computer interaction. Scientific Awards: No major scientific awards were listed in the provided information. Advising and Grants: Supervised 18 master's theses and 1 doctoral dissertation covering autonomous vehicles, deep learning, and IoT systems. Secured over 1.5 million Turkish Lira in research funding through TÜBİTAK projects including Smart Renewable Energy Management System (2018-2021, 159,636 TL) and Advanced Autonomous Bus System (2018-2021, 915,810.99 TL), with additional projects in battery management and metrobus efficiency. Labs and Teams: Project descriptions indicate leadership in autonomous systems teams and energy management research groups, though specific laboratory affiliations are not detailed in the source text.

• Power Engineering
• Quantum Computing
• Microgrid Stability
• +5 more

Yan Li is an Assistant Professor in Electrical Engineering with extensive research activity spanning 2013–2025 and 76 research outputs. Their work intersects power systems engineering , quantum computing , and computational symmetry with applications in microgrid stability , neuroimage analysis , and human pose dynamics . Active in UN Sustainable Development Goals related to sustainable energy systems Key research areas: Quantum Computing Training , Transient Dynamics Analysis , Software-defined Networking , and Data-driven Modeling Recent publications focus on adaptive control algorithms for microgrids, quantum computing applications in power systems, and geometric machine learning for differential equations on manifolds. Their work combines theoretical innovation with practical implementations in energy and biomedical domains. Grant funding includes: National Science Foundation (CyberTraining: Quantum Computing Training for Power Engineers, 2024–2026) U.S. Navy (Quantum Analysis of Renewable Energy Transients, 2022–; SCADA Network Security via SDN, 2021–) National Science Foundation (Data-driven Modeling for Renewable Systems, 2022–2025)

• Computational Literary Studies
• Stylometry
• Digital Humanities
• +3 more

Dr. Steffen Pielström is a Research Fellow at the Institute of German Philology within the Philosophical Faculty of the University of Würzburg. He is a core member of the Chair of Computational Philology and Modern German Literary History led by Prof. Dr. Fotis Jannidis and currently contributes to the DARIAH-DE project (Cluster 5 - Quantitative Data Analysis), focusing on computational text analysis for literary scholarship. His research spans Computational Literary Studies, Stylometry, and Digital Humanities with emphasis on authorship attribution, topic modeling, and critical tool development. He investigates methodological frameworks for quantitative text analysis while addressing research data management challenges in humanities contexts, particularly through FAIR data principles and infrastructure design. Analysis of his 15 most recent publications reveals three dominant trends: (1) Development of practical tools like the 'stylo' R package for stylometric analysis; (2) Critical examination of methodological assumptions in computational literary studies; (3) Systematic analysis of research data management needs within digital humanities. His work consistently bridges philological expertise with computational innovation, emphasizing interdisciplinary collaboration and infrastructure sustainability. As part of the DARIAH-DE project and the Chair of Computational Philology, Dr. Pielström collaborates on advancing Germany's digital research infrastructure. His work integrates with the university's broader initiatives in computational literary studies, including the DFG Priority Programme, where he contributes to shaping national research agendas through quantitative data analysis frameworks and tool development.

Francesco LeottaView profile

Assistant Professor

• Ubiquitous Computing
• Human-Computer Interaction
• Digital Humanities
• +8 more

Francesco Leotta is a Tenure Track Assistant Professor in the Department of Computer, Control and Management Engineering at Sapienza University of Rome, specializing in ubiquitous computing, human-computer interaction, and digital humanities with applications in smart spaces, smart manufacturing, and cultural heritage. His educational background includes a PhD in Engineering in Computer Science (2014), Master Degree in Computer Science Engineering (2010), and Bachelor Degree in Computer Science Engineering (2006), all with honors from Sapienza University of Rome. He has been qualified to practice as a Computer Science Engineer since 2010. Leotta's research pioneers 'habit mining' for learning human behaviors from unlabeled sensor data, focusing on usability for technicians through readable process models and for end users via accessible interfaces including chatbots and solutions for people with disabilities. His recent work centers on Industry 4.0, developing AI-driven digital twin architectures for industrial automation. Key projects include privately funded Rotalaser Fustella 4.0 and publicly funded initiatives FIRST and ElectroSpindle 4.0. Analysis of his 2024-2025 publications reveals strong interdisciplinary trends bridging business process management with IoT and AI, particularly in smart manufacturing maturity models, digital twin composition, and multimodal human-robot interaction. His work consistently integrates theoretical frameworks with practical industrial applications. Scientific recognition includes: Best Paper Award at IEEE International Conference on Web Services (ICWS 2019) Leotta actively contributes to research groups in Human-Computer Interaction, Data Management, and Semantic Technologies, with current projects focusing on adaptive smart manufacturing systems. His grant portfolio demonstrates successful collaboration between academic research and industrial applications in the manufacturing sector. He maintains active involvement in the computing continuum ecosystem through projects like DataCloud, addressing big data pipelines and dark data utilization in industrial contexts.

Frank MelandsøView profile

Professor

• Ultrasound
• Microwaves
• Optics
• +5 more

Frank Melandsø is a Professor at the Department of Physics and Technology, UiT The Arctic University of Norway. His research focuses on ultrasound, microwaves, and optics, particularly in nondestructive testing and acoustic imaging technologies. Key research interests include: Development of advanced ultrasound and acoustic microscopy techniques Finite element modeling for wave propagation and transducer design Image processing algorithms for noise reduction and defect visualization Applications in materials science, marine biology, and biomedical imaging Recent publications highlight trends in deep learning applications, tilt compensation methods, and 3D imaging of complex materials. His collaborative work spans institutions and disciplines, with extensive contributions to sensors, imaging systems, and computational analysis. Professor Melandsø is actively involved in the Ultrasound, Microwaves and Optics research group and the VirtualStain project, based at Teknologibygget Tromsø 2.053.

• Computational Fluid Dynamics
• Nuclear Engineering
• Thermal Hydraulics
• +9 more

Elia Merzari is a Professor in the Ken and Mary Alice Lindquist Department of Nuclear Engineering at Pennsylvania State University and a member of the Institute for Computational and Data Sciences (ICDS). His research focuses on computational fluid dynamics, turbulence modeling, and thermal hydraulics in nuclear systems. Research Interests Merzari specializes in Computational Fluid Dynamics (CFD) , with a focus on Large Eddy Simulation (LES) , Direct Numerical Simulation (DNS) , and Reynolds-Averaged Navier-Stokes (RANS) models. His work addresses challenges in nuclear reactor thermal hydraulics , including flow stability in rod bundles, turbulence in pebble beds, and multiscale frameworks for advanced reactor design. He actively applies machine learning techniques like physics-informed neural networks to nuclear engineering problems. Recent Research Trends Merzari's recent publications (2025) highlight advancements in temperature monitoring for high-temperature gas reactors , spectral element implementations of RANS models , and transition to turbulence in complex geometries . His work integrates Nek5000/NekRS software with multiscale modeling to enhance reactor safety and deployment efficiency. Grants & Projects Center for Thermal-Fluids Applications in Nuclear Energy (PI, 2024–present): Focuses on industry adoption of multiscale frameworks. Reduced Order Modeling of Heat and Fluid Flow (CoPI, 2023–present): Aims to accelerate reactor deployment via multiscale techniques. High-Resolution Pebble Bed Data at Low Flow Conditions (PI, 2022–present): Investigates flow dynamics in pebble bed reactors. Innovative Monitoring Technology for Micro-HTGR (CoPI, 2022–present): Develops sensors for reactor vessel stress estimation. Low Temperature Cladding Failures in RIA Transients (CoPI, 2021–present): Studies accident-tolerant fuels under reactor transients.

• Software
• Intelligent informatics
• Control and system engineering
• +4 more

Professor Shigeru Fujimura is affiliated with Waseda University as a faculty member of the Faculty of Science and Engineering , specifically in the Graduate School of Information, Production, and Systems . With a PhD in Engineering from Waseda University, his research focuses on intelligent informatics and system engineering , particularly in scheduling, optimization, and human-robot collaboration. His research spans multiple domains including: Deep Reinforcement Learning for combinatorial optimization Energy-efficient manufacturing systems Multi-agent collaboration frameworks Augmented Reality interfaces IoT business modeling Recent publications demonstrate expertise in graph neural networks , particle swarm optimization , and generative adversarial networks applied to industrial problems. He has received multiple awards including the Invention Encouragement Prize (2003) and IEEJ Paper Presentation Award (1994) .

Giulia Wally ScuratiView profile

Research Fellow

• Mechanical Engineering
• Product Design
• Sustainable Behavior
• +4 more

Giulia Wally Scurati is a Postdoctoral Fellow at the Department of Mechanical Engineering, Blekinge Institute of Technology, specializing in using virtual reality (VR) , augmented reality (AR) , and serious games for sustainable behavior change and product development. Her research spans mechanical engineering , human-computer interaction , and environmental psychology . She has a PhD in Mechanical Engineering from Politecnico di Milano, with a thesis on design methods for VR/AR in sustainable behavior. Current projects include AXESS (Assessment in XR Environments for Sustainable Solutions). Key Research Areas: Sustainable behavior, VR/AR applications, product-service systems (PSS), multisensory feedback, gamification, and human-robot interaction. Collaborations: Works with institutions like Politecnico di Milano, Politecnico di Torino, and University of Twente.

• Perovskites
• Machine Learning
• Materials Science
• +11 more

M. Bokdam is an Assistant Professor at the Computational Chemical Physics department within the MESA+ Institute at the University of Twente. His work bridges computational physics and materials science, focusing on advanced simulation techniques and machine learning applied to complex material systems. Research interests include Perovskite materials and their thermal/electronic properties Machine learning force fields for ab initio molecular dynamics Spin dynamics and quantum mechanical modeling Graphene-based heterostructures and interface phenomena Phase transitions and structural distortions in 2D materials Recent publications highlight trends in using AI-driven simulations to study perovskites and graphene interfaces, with keywords spanning computational physics, materials science, and thermodynamics. His work has been recognized through prizes in 2022, including the FAIR DATA Fund and Onderwijsprijs TN (Teaching Award in Natural Sciences). Scientific awards include FAIR DATA Fund 2022 Onderwijsprijs TN 2022 Applied Physics Prize 2022 Key datasets co-authored by Bokdam include force field training databases for CsPbBr3, LaMnO3/SrRuO3, and mixed MAPbI3−xBrx perovskites, emphasizing open science practices.

• Serious Games
• Digital Cultural Heritage
• Extended Reality (XR)
• +7 more

Vedad Hulusic serves as Associate Professor and Deputy Head of the Creative Technology Department within Bournemouth University's Faculty of Science and Technology. He previously held positions as Assistant Professor at University Sarajevo School of Science and Technology and Post-doctoral Researcher at Télécom ParisTech, and acted as REF 2021 Output Champion for Computer Science and Informatics (UoA11). His academic credentials include: PhD in Engineering, University of Warwick, UK BSc in Computer Science, University of Sarajevo, Bosnia and Herzegovina Hulusic's research spans serious games, digital cultural heritage, XR technologies, assistive technology, and cross-modal interaction. His work bridges computer graphics with real-world applications in education, healthcare, and cultural preservation, emphasizing user-centered design and accessibility. Recent projects focus on multi-user XR for cultural heritage and haptic interfaces for children with disabilities. Analysis of his publication record reveals consistent innovation in XR applications for cultural heritage, with growing emphasis on accessibility and user experience. His work demonstrates strong interdisciplinary collaboration with museums, industry partners, and healthcare institutions, while maintaining technical rigor in image quality assessment and perceptual modeling. His scientific recognition includes: Four international best paper awards (CGVC 2023, EG GCH 2021, EG GCH 2018, ACM SCCG 2008) Innovative Value Award (Kingston University London, 2023) Vice Chancellor Scholarship (University of Warwick, 2007) Hulusic actively mentors PhD candidates including Zhenhao Tian, Ethan Southall, Nicholas Lindfield, and Wenjun Liu, focusing on XR and serious games applications. His funded projects include the HEIF-supported 'Feeling the UNfelt (FUN)' assistive technology initiative and current industry collaboration with Noho Ltd on multi-user XR. He has participated in EU frameworks including V-MusT.net and HDRi projects, demonstrating sustained success in securing competitive research funding. As core member of Bournemouth's Centre for Computer Graphics (CCG) and Studio for Games and Animation Technology (SGAT), he drives collaborative research with cultural institutions and industry partners to advance digital heritage preservation and accessible technology design.