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Alex Arenas is a Full Professor in the Department of Computer Engineering and Mathematics at Universitat Rovira i Virgili (URV), Tarragona, Spain. He is also an External Faculty member at the Complexity Science Hub in Vienna and Chief of Complex Systems Science at the Pacific Northwest National Laboratory, USA. His research spans complex systems, network science, computational epidemiology, and multilayer dynamics, with applications in public health, neuroscience, and social systems. Research Interests: His work focuses on the physics of multilayer networked systems, particularly the interplay between structure and function in complex networks. Key areas include synchronization, epidemic modeling, network medicine, the physics of the microbiome, and higher-order interactions in spreading processes. He investigates dynamic transitions using functional multilayer frameworks and develops models for real-world systems like urban mobility and misinformation diffusion. The recent articles highlight a strong trend in computational epidemiology, especially post-COVID modeling of vaccination strategies, rebound dynamics, and wastewater surveillance. There is also significant work on synchronization in oscillator networks, chimera states, and higher-order network effects, reflecting a deep engagement with nonlinear dynamics and theoretical network science. Applications span medicine, urban planning, and social systems. Scientific Awards: Fellow, American Physical Society (2018) Fellow, Network Science Society (2020) ICREA Academia (2011, 2017, 2022) Narcís Monturiol Medal (2022) Web Science Trust Test of Time Award (2024) Complex Systems Society Senior Award (2024) Advising and Grants: Arenas has supervised numerous PhD students and postdoctoral researchers, though specific names are not listed. He has been Principal Investigator on 47 research projects, including EU FP7 projects, a James S. McDonnell Foundation grant, and Horizon Europe's CREXDATA project. He has served as an editor for Physical Review E , Journal of Complex Networks , and Network Neuroscience , and has reviewed for major funding agencies including ERC, MINECO, and international bodies. Labs and Teams: He leads the Alephsys Lab at URV, which develops tools like Radatools for network analysis and community detection. His team focuses on interdisciplinary modeling of real-world complex systems using data-driven and theoretical approaches.

• Complex Systems
• Network Science
• Multilayer Networks
• +12 more

Vito Latora is a Professor of Applied Mathematics and Chair of Complex Systems at the School of Mathematical Sciences, Queen Mary University of London, and also holds the position of Professor of Theoretical Physics at the University of Catania. He leads the Complex Systems and Networks Group, driving cutting-edge research at the intersection of physics, mathematics, and interdisciplinary sciences. His research focuses on complex systems, particularly the structure and dynamics of networks, including multiplex, temporal, and higher-order networks such as simplicial complexes and hypergraphs. He explores applications in social, biological, financial, and cognitive systems, with recent work on creativity, innovation, and success through network analysis. The 15 most recent publications reveal a strong trend in advancing network theory beyond pairwise interactions, with a focus on higher-order structures, memory effects, synchronization, and epidemic spreading. His work combines rigorous mathematical modeling with real-world applications, often published in high-impact journals like Nature Communications , Physical Review Letters , and Science Advances . Dual communities in spatial and biological networks Modeling epidemics with limited detection resources Synchronization via higher-order and directed interactions AI-driven financial risk management Evolutionary games on hypergraphs Interdisciplinary success and funding dynamics Vito Latora has mentored several researchers who appear as co-authors, including Iacopini, Williams, Di Bona, and Lacasa. While specific grants are not listed, his collaborative projects with neuroscientists and anthropologists, along with frequent publications, suggest active funding. He is involved in major scientific events such as NetSci 2023, indicating leadership in the network science community. He leads the Complex Systems and Networks Group at Queen Mary, fostering a collaborative environment for studying complex systems through theoretical, computational, and data-driven approaches.

• Complex Systems
• Network Science
• Applied Mathematics
• +13 more

Peter Behrensdorff Poulsen serves as Solar Photovoltaic Systems Group Leader at the Department of Electrical and Photonics Engineering, Technical University of Denmark (DTU). His work spans photovoltaic research, solar-powered lighting systems, and drone-based inspection technologies within DTU's College of Engineering. His research focuses on Solar Cell Engineering , Photovoltaic Modules , and Drone Applications for renewable energy systems. Key areas include bifacial photovoltaics, electroluminescence imaging diagnostics, building-integrated photovoltaics, and ultra-efficient solar-powered lighting solutions. His work significantly contributes to UN Sustainable Development Goals related to affordable clean energy and sustainable cities. Recent publications reveal strong trends in AI-driven PV diagnostics , bifacial module performance in northern climates, and dark-sky compatible lighting systems . His research bridges fundamental photovoltaic science with practical applications in urban infrastructure and environmental sustainability. Best Poster Award at 44th IEEE Photovoltaic Specialists Conference Best Poster Award at 48th IEEE Photovoltaic Specialists Conference Characterizing the Performance of Daylight Filters for Electroluminescence Imaging Poster Award at 35th European Photovoltaic Solar Energy Conference Poster Prize at Sustain 2017 Poulsen leads multiple research grants including the Ultra-efficient Dark Sky-compatible Solar-powered Outdoor Lighting project (2024-2026) and previously managed the DronEL project (2017-2019) for drone-based PV inspection. His work connects photovoltaic engineering with practical lighting applications through the Lighting Color and Radiation Laboratory. He actively collaborates with industry partners on building-integrated photovoltaics and solar-powered infrastructure solutions, with notable projects including the Plateau Sun Hub public charging stations and Black Si BIPV panel development.

• Solar Cell Engineering
• Photovoltaics
• Drone Engineering
• +5 more

Michael Szell is an Associate Professor at the IT University of Copenhagen (ITU), affiliated with the Data Science Networks, Data, and Society Center for Climate IT. He holds external positions including Affiliate at the Danish Pioneer Centre for AI (since Feb 2023), External Researcher at the Institute for Scientific Interchange Foundation (2019–2024), and External Faculty at the Complexity Science Hub (since 2017). Research Interests : Social networks, human mobility, computational social science, data science, urban sustainability, network science, and infrastructure design. His work focuses on urban systems, bicycle networks, mobility patterns, and data-driven strategies for sustainable urban planning. Awards : Received the Årets Forskningsmiljø 2022 award for contributions to research environments. Projects : Currently leads projects like NADanBI (Danish Road Directorate, 2022–2025) and JUST STREETS (European Commission, 2024–2027), focusing on bicycle infrastructure analysis and spatial justice in urban mobility. Publications : Over 50 peer-reviewed papers, including high-impact work on bicycle network growth, universal visitation laws in human mobility, and urban superblock modeling. His research bridges data science, urban planning, and computational modeling to address sustainability challenges. Contributions : Developed tools like superblockify and BikeDNA , and contributed to datasets on urban mobility and bicycle networks. Engages in media discussions on cycling infrastructure and urban policy.

• Social networks
• Human mobility
• Computational social science
• +7 more

Tiziana Di Matteo is a Professor of Econophysics in the Department of Mathematics at King's College London, part of the Faculty of Natural, Mathematical & Engineering Sciences. She is also External Faculty at the Complexity Science Hub and affiliated with the UCL Centre for Blockchain Technologies, the Complex System Laboratory, the Complex Systems Society, and the Museo Storico della Fisica e Centro Studi e Ricerche “E. Fermi”. Her research focuses on econophysics, complex systems, complex networks, and data science , with applications in financial modeling, systemic risk, and multiscaling analysis. She integrates methods from statistical physics and network science to analyze financial markets and economic interactions. The most recent publications reveal a strong trend in financial network modeling, multiscaling volatility, tensor-based learning for multidimensional data, and early warning systems using scaling properties . Her work bridges econophysics and traditional financial economics, emphasizing empirical validation and interdisciplinary approaches. Scientific Leadership and Editorial Roles: Editor-in-Chief, Journal of Advances in Mathematical Physics Main Editor, Physica A Editor, European Physical Journal B Editor, Artificial Intelligence in Finance Former Editor-in-Chief, Journal of Network Theory in Finance Guest Editor for multiple special issues Tiziana is the co-founder of the Econophysics Network and has served as a consultant for the Financial Services Authority, hedge funds, and financial companies. She has authored over 100 papers and delivered keynote talks globally. She supervises PhD students and leads collaborative research in complex financial systems. She is actively involved in interdisciplinary research collaborations with institutions like the Francis Crick Institute and industrial partners including EDF Research and Unilever.

• Econophysics
• Complex Systems
• Complex Networks
• +7 more

Sune Thorsteinsson serves as Project Manager at the Department of Electrical and Photonics Engineering, Technical University of Denmark (DTU), specializing in Solar Photovoltaic Systems. Based at DTU's Roskilde campus, Thorsteinsson leads research initiatives focused on advancing photovoltaic technologies with practical building applications and energy system integration. Research Expertise Thorsteinsson's research portfolio demonstrates deep expertise in building-integrated photovoltaics (BIPV), with significant contributions spanning structural colored interlayers, thermal behavior analysis of solar façades, and comprehensive performance evaluation methodologies. Their work bridges materials science, electrical engineering, and architectural integration to address real-world challenges in solar energy deployment. Recent research shows a clear trajectory toward optimizing both aesthetic and functional aspects of photovoltaic systems, particularly through colored PV technologies and reliability assessment frameworks. The research emphasizes practical implementation considerations while maintaining rigorous scientific evaluation standards. Awards and Recognition Best Poster Award at 44th IEEE Photovoltaic Specialists Conference (2017) Best Student Paper at IEEE PVSC 2021 on Spectral Albedo in Bifacial Photovoltaic Modeling Poster Award at 35th European Photovoltaic Solar Energy Conference and Exhibition (2018) Multiple Poster Prizes at Sustain conferences (2017-2018) Academic Leadership As Main Supervisor for multiple PhD projects including 'Edge Passivation and Advanced Metallization of Solar Cells' and 'Performance and reliability assessment of coloured building-integrated photovoltaics,' Thorsteinsson plays a pivotal role in developing next-generation photovoltaic technologies. Current projects extend through 2027, demonstrating sustained research leadership in the field. Thorsteinsson also contributes to the International Energy Agency - Photovoltaic Power Systems Programme (2021-2023) and maintains active collaboration networks across European photovoltaic research institutions, focusing particularly on drone-based inspection systems and building-integrated solar solutions.

• Photovoltaics
• Solar Cells
• Building-Integrated Photovoltaics
• +5 more

Yubin Zhang serves as a Senior Researcher at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU), with expertise in advanced materials characterization. His primary affiliation is with DTU Mechanical Engineering (MEK), where he contributes to the 3D Imaging Center (3DIM) project and conducts research on microstructure engineering of metallic materials. His research focuses on Microstructure Engineering, Materials Science, and Tomography, with specialized expertise in aluminum alloys, recrystallization phenomena, nucleation mechanisms, and grain boundary dynamics. He integrates experimental techniques like X-ray microscopy with computational approaches including deep learning for microstructural analysis, enabling precise characterization of deformation and phase transformations in complex materials. Recent publications demonstrate a clear trend toward multimodal 3D/4D imaging techniques combined with machine learning for microstructure quantification. His work bridges fundamental materials science with industrial applications, particularly in additive manufacturing and aluminum processing, where advanced imaging provides critical insights into material behavior during thermo-mechanical treatments. As a dedicated supervisor, Dr. Zhang mentors PhD candidates including Defer, M. C. on additive manufactured AlSiMg alloys, Knipschildt-Okkels, E. F. F. on recrystallization nucleation, and Lindkvist, A. A. on residual stresses in multiphase steels. His research is supported through major grants including the 3DIM project (2016-2029) and Microstructural Engineering of Additive Manufactured AlSiMg (2023-2026), where he serves as Principal Investigator and supervisor respectively. Dr. Zhang operates within DTU's 3D Imaging Center, a state-of-the-art facility utilizing synchrotron radiation and laboratory X-ray sources for non-destructive 3D characterization. His team specializes in diffraction contrast tomography, dark field X-ray microscopy, and machine learning applications for microstructure analysis, with strong collaborations across European research institutions.

• Microstructure Engineering
• Materials Science
• Tomography
• +6 more

Dr. Anand Ramesh Sanadi serves as an Associate Professor in the Department of Geosciences and Natural Resource Management within the Faculty of Science at the University of Copenhagen. Since joining the institution in 2008, he has established himself as a leading researcher in biomass and wood science, specializing in the material science of lignocellulosics and sustainable composite development. His work bridges fundamental research with industrial applications across packaging, construction, and bioenergy sectors. Dr. Sanadi holds a PhD in Engineering Science from Washington State University (1990), where he specialized in polymer composites and fiber-polymer interactions. His academic journey includes an MS in Chemical Engineering from the University of Toronto (1983) and a BS in Textile Technology from the Indian Institute of Technology, New Delhi (1983). Prior to his current position, he gained extensive industry and research experience at the USDA Forest Products Laboratory, Global Resource Technologies, and as a Visiting Associate Professor at Denmark's Royal Agricultural and Veterinary University. His research focuses on the material science of biomass and wood materials, with particular expertise in polymer composites, wood/agrofiber composites, adhesion mechanisms, surface-coating interactions, bioenergy applications, and nanocellulose technology. He pioneered the development of highly filled natural fiber composites (up to 90% fibers) in polyolefins and invented formaldehyde-free binders for biomass composite panels. Current projects include 'Adhesion and reinforcement for Superior Bio-based Coatings,' thermal properties of wood, and enzymatic nanofiber production. Analysis of his 15 most recent publications reveals a strong trajectory toward sustainable materials innovation, particularly in bio-based adhesives, nanocellulose extraction from waste streams, and biomass pelletization mechanics. His work demonstrates consistent advancement in understanding bonding mechanisms in biomass pellets, enzymatic hydrolysis for bioethanol, and reinforcement strategies using agricultural waste. Scientific recognition includes: USDA Award for Excellence in Research for pioneering natural fiber technologies Dr. Sanadi has secured significant competitive funding, including a 2.9 million DKK HTF grant for bio-based coatings and a 205,000 DKK International Network Grant with Brazil for enzymatic nanofiber production. His industrial collaborations span packaging, furniture, construction, and automotive sectors, where he provides expert consulting on natural fiber composites and bonding mechanisms. Within the Biomass and Ecosystem Division, he leads research on thermal properties of wood, lignocellulosic bonding, and the development of sustainable composite materials using agricultural residues.

• Material Science of Biomass
• Wood Science
• Polymer Composites
• +7 more

Aldona Ilona Mzyk is an Assistant Professor in the Department of Health Technology at the Technical University of Denmark (DTU), where she conducts cutting-edge research at the intersection of quantum sensing, biomaterials, and biomedical applications. Her work is closely aligned with the UN Sustainable Development Goals, particularly in advancing healthcare technologies and sustainable materials. Research Interests: Dr. Mzyk’s research spans quantum biosensing using nitrogen-vacancy (NV) centers in nanodiamonds, development of biocompatible implant materials, and cellular mechanics. She investigates how nanodiamonds can be used for intracellular detection of free radicals in cancer cells and how hydrostatic extrusion affects the properties of absorbable zinc alloys for medical implants. Her work also explores surface modifications of bioactive scaffolds to enhance bone integration and examines the role of mechanoregulation and reactive oxygen species in heart regeneration. The recent publications reveal a strong trend toward quantum-enabled biomedical diagnostics and advanced biomaterials engineering . Her work integrates physics, materials science, and biology to develop novel tools for disease monitoring and regenerative medicine. Scientific Awards: 1st Poster Prize (2022) – Recognizing excellence in quantum sensing and arthritis-related research Early Career Research Award (2024) – Honoring contributions to diamond materials and quantum biosensing in Germany Supervision and Research Projects: Dr. Mzyk is actively involved in supervising PhD research. She is a co-supervisor in the active project Diamond based Intracellular NMR and Cell Mechanics (2024–2027), which aims to develop quantum sensing techniques for probing intracellular environments and mechanical properties of living cells. This reflects her leadership in interdisciplinary research and mentorship. Collaborative Networks: She collaborates with researchers across institutions in Denmark and internationally, particularly in the fields of quantum sensing (e.g., with R. Schirhagl and K. Berg-Sørensen) and biomaterials (e.g., with F. Baino and E. Verné). Her network spans Switzerland and Germany, indicating strong European research integration.

• Quantum Sensing
• Nanodiamonds
• Biosensing
• +12 more

Valkyrie Arline Savage is a Tenure Track Assistant Professor in the Human-Centred Computing section of the Department of Computer Science (DIKU) at the University of Copenhagen's Faculty of Science. Her research bridges the gap between physical input devices and digital systems, with a focus on creating interfaces that can be custom-designed, fabricated, or simply picked up to solve specific user problems in particular contexts. Dr. Savage studies physical input devices (like mice, game controllers, or surgical tools) as the ultimate bridge between humans and computers. Her work pushes for deeply custom interfaces that fit specific user needs for particular times, places, and tasks. She is fascinated by the interaction between sensing (which takes physical information and digitizes it) and fabrication (which takes digital information and physicalizes it). Her methodology centers on systems research, where project outputs are functional, novel systems that users can interact with directly, with contributions often coming from the algorithms required to make these prototypes work. Dr. Savage's recent publications demonstrate a strong research trajectory in innovative fabrication techniques that integrate electronics with traditional manufacturing processes. Her work spans 3D printing innovations, laser cutting applications, textile integration, and novel sensing mechanisms. Key themes across her research include democratizing fabrication technologies, combining digital and craft-based methods, and developing responsive input devices that adapt to specific user requirements. Her publications in top-tier venues like CHI, UIST, and TEI showcase her contributions to computational fabrication and human-computer interaction. Dr. Savage actively works with students in her fabrication lab, which is equipped with 3D printers, lasercutters, electronics tools, a CNC mill, and other fabrication equipment. Her advising focuses on interdisciplinary projects that explore the boundaries between technology and craft, including 3D printing combined with crochet, underwater 3D printing applications, and lasercut slot-together circuits. She has published 22 research outputs including journal articles, conference proceedings, a PhD thesis, and a patent, demonstrating consistent productivity in her field. Her research has practical applications across multiple domains including maritime automation, medical interfaces, and general human-computer interaction. The citations and downloads of her work indicate growing impact in her field, with applications spanning from specialized industrial contexts to everyday user interfaces. Dr. Savage's work represents a significant contribution to making fabrication technologies more accessible and integrated for creating custom interactive systems.

• Human-Computer Interaction
• Physical Input Devices
• Sensing Technologies
• +5 more

Tianbo Yu is a Senior Researcher in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), specializing in metallic microstructure analysis and industrial material applications. His work integrates advanced characterization techniques with manufacturing process optimization. Education: Bachelor degree from Tsinghua University PhD degree from Risø DTU Research Focus: Dr. Yu's expertise spans experimental microstructure characterization using electron microscopy and synchrotron X-ray techniques, microstructure evolution during deformation/annealing/additive manufacturing, and microstructure-property relationships in industrial alloys. His fingerprint analysis reveals dominant work in aluminum processing (65%), stainless steel (34%), mechanical strength (60%), and transmission electron microscopy (31%). Publication Trends: Recent 2025 publications demonstrate concentrated investigation into additively manufactured stainless steel microstructures, particle-stimulated nucleation in aluminum alloys, and deformation mechanisms in multilayered systems. These works consistently bridge fundamental microstructural phenomena with industrial manufacturing challenges, particularly in electric vehicle components and 3D printing. Supervision & Projects: Actively supervises five PhD candidates across DTU projects including sustainable aluminum busbars for EVs, LPBF stainless steel microstructure, and particle-stimulated nucleation. His collaborative network spans metallurgy, additive manufacturing, and semiconductor printing with international partners.

• Microstructure of Metallic Materials
• Materials Characterization
• Metal Alloys
• +3 more

Esben Lindgaard is a Professor at the Department of Materials and Production, Faculty of Engineering and Science, Aalborg University. His research focuses on composite materials, fracture mechanics, and fatigue-driven damage in wind turbine structures. Projects: CIRCWIND (Circular material solutions for wind turbines), MulFat (Multiscale fatigue modeling), MADE4WIND (Innovative floating wind components). Research: Specializes in delamination behavior, crack propagation, and computational modeling of composite structures under static and fatigue loading. His recent work explores deep learning for delamination traction fields, cohesive element fatigue modeling, and binder-stabilized fabric forming simulations. Collaborates extensively with industry partners and contributes to open-access datasets and software tools. Awards: AAU Talent Project (2018), honored for wind turbine blade defect research (2020). Expertise: Composite material failure, multiscale modeling, industrial validation, and wind energy structural integrity.

• Composite Materials
• Wind Turbine Engineering
• Fracture Mechanics
• +3 more

Rosario N. Mantegna is a Professor at the University of Palermo and holds visiting positions at Central European University and honorary status at University College London. Since 2017, he has been a member of the External Faculty at the Complexity Science Hub Vienna, reflecting his active engagement in interdisciplinary research on complex systems. His research lies at the intersection of statistical physics and economics, where he is recognized as one of the pioneers of econophysics and economic networks . His work explores financial markets through the lens of complex networks, high-frequency trading, information transfer, and data-driven modeling. He has led and participated in numerous international and national research projects, contributing foundational insights into market structure and dynamics. The recent publications (2017–2023) highlight a strong focus on network analysis in finance , clustering techniques , information theory applications , and fintech evolution . These works span disciplines including physics, finance, computer science, and data analytics, demonstrating a consistent interdisciplinary approach. Key themes include validation of network structures, trader clustering, and systemic risk assessment. His scientific contributions are recognized through editorial roles in major conference proceedings and collaborations with leading researchers in complexity science. While no formal awards are listed, his sustained publication record in high-impact journals and books underscores his influence in the field. Rosario Mantegna advises students and researchers through his leadership in research projects and academic supervision, though specific advisees are not named. He has been involved in significant research grants and collaborative initiatives across Europe, particularly in complexity science and financial network analysis. His work is closely tied to interdisciplinary research groups and networks, including those at the Complexity Science Hub Vienna and Central European University, where he contributes to advancing the science of complex systems.

• Econophysics
• Complex Networks
• Statistical Physics
• +7 more

Prof. Yamir Moreno is a Professor of Physics at the Department of Theoretical Physics, Faculty of Sciences, University of Zaragoza, where he also serves as Director of the Institute for Biocomputation and Physics of Complex Systems (BIFI) and leads the Complex Systems and Networks Lab (COSNET). He holds international affiliations as Research Director at CENTAI Institute (Turin, Italy) and External Professor at the Complexity Science Hub Vienna (Austria), and was previously a Principal Scientist and Area Coordinator at the ISI Foundation. PhD in Physics, University of Zaragoza (Summa Cum Laude, 2000) Ramón y Cajal Fellow (2005-2010) First-class Fellow, ISI Foundation Fellow, American Physical Society (2021) Fellow, Network Science Society (2022) His research focuses on complex systems , network science , epidemic modeling , and social dynamics . He investigates disease dynamics, diffusion processes, nonlinear systems, and higher-order network structures using tools from physics, mathematics, and data science. His work bridges theoretical foundations with real-world applications in public health, urban systems, and social behavior. Recent publications highlight trends in multilayer and higher-order networks , digital twins of cities , epidemic modeling with behavioral feedback , and social contagion in complex systems . His research integrates data-driven modeling, machine learning, and network theory to study urban resilience, information spread, and collective behavior. Complex Systems Society’s Senior Scientific Award (2019) Highly Cited Researcher (Web of Science, 2019) Service Award, Complex Systems Society (2022) Editor-in-Chief, Journal of Complex Networks Editor, PLoS Computational Biology, Chaos, Solitons & Fractals, Proceedings of the Royal Society A Divisional Associate Editor, Physical Review Letters (2014-2020) Prof. Moreno has supervised 23 PhD theses and over 30 master’s theses. He has led multiple EU-funded projects and has served on advisory boards for the EU Future and Emerging Technologies and the WHO Collaborative Center on Complexity Sciences for Health Systems. His collaborative network spans institutions in Europe, Latin America, and North America. He leads the Complex Systems and Networks Lab (COSNET) at BIFI, a multidisciplinary team focused on network theory, computational epidemiology, and social dynamics. The lab develops models for epidemic forecasting, urban resilience, and collective behavior using high-performance computing and data analytics.

• Complex Systems
• Network Science
• Disease Dynamics
• +7 more

Jakob Sauer Jørgensen serves as a Senior Researcher in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), affiliated with the UltraSound and Biomechanics Scientific Computing group within the Center for Fast Ultrasound Imaging. His work spans computational mathematics, medical imaging, and uncertainty quantification. His research focuses on Image Reconstruction , Tomographic Reconstruction , and Uncertainty Quantification with emphasis on regularization techniques, sparsity, and Bayesian approaches. Key methodologies include total variation, inverse problems, and computational frameworks like CUQIpy for Python-based uncertainty quantification in inverse problems. His publication trends show strong emphasis on computational methods for medical imaging (2025), uncertainty quantification frameworks (2024-2025), and applications in nuclear fusion diagnostics (2024). Recent work integrates neural networks with traditional reconstruction methods and develops open-source tools for uncertainty modeling. He actively supervises PhD students across multiple projects including neural network-based X-ray tissue imaging, Mars meteorite analysis, and additive manufacturing modeling. Current projects include: Neural networks-based X-ray tissue imaging for robotic automation (2025-2028) Multi-modality reconstruction for Mars meteorite analysis (2024-2027) Modeling of volumetric additive manufacturing (2023-2026) Uncertainty quantification for tomographic reconstruction (2020-2024)

• Image Reconstruction
• Sparsity
• Regularization
• +4 more