Hasti Seifi is an Affiliated Associate Professor at the Department of Computer Science (DIKU), University of Copenhagen, specializing in Human-Centred Computing. Her research focuses on haptics, augmented reality, and human-robot interaction. Institution: University of Copenhagen Department: Department of Computer Science Section: Human-Centred Computing Research interests include: Designing innovative haptic feedback systems Exploring tactile experiences in augmented reality Developing human-robot interaction frameworks Creating generative models for haptic design Investigating social touch technologies Advancing mid-air and ultrasound haptic interfaces Recent publications demonstrate a strong focus on: Generative haptic modeling for AR/XR systems Human-robot interaction dynamics Text input in extended reality environments Visual-haptic multisensory integration Ultrasound mid-air haptic design tools Social touch technologies
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.
Grethe Winther is a Professor and Head of Section in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), specializing in Materials and Surface Engineering. Her research is centered on the analysis and modeling of microstructure and mechanical properties of metals, with a strong emphasis on dislocation structures, deformation textures, and recrystallization processes. Her research interests include: Dislocation structures and boundary analysis in deformed metals Crystal plasticity modeling using synchrotron data (3DXRD) Orientation relationships in recrystallization Prediction of mechanical properties in industrial metal forming Multiscale modeling of plastic deformation and surface roughening The recent articles (2025) highlight a consistent focus on advanced characterization techniques like dark-field X-ray microscopy and discrete dislocation dynamics simulations. These works explore the formation of geometrically necessary boundaries, dislocation cell evolution, and multiscale surface deformation, reflecting a strong integration of experimental and computational methods in materials science. Key themes include plastic deformation mechanisms, microstructure evolution, and predictive modeling in metallic systems. Grethe Winther actively supervises multiple PhD projects, including those on dislocation dynamics, X-ray microscopy, and ductile failure simulations. She collaborates extensively with researchers such as H.F. Poulsen and C.V. Nielsen. Her work is supported by ongoing research projects at DTU, focusing on fundamental and applied aspects of metal deformation and microstructure. She is affiliated with the Materials and Surface Engineering section at DTU, where she leads research efforts combining advanced experimental techniques with theoretical modeling to understand and predict metal behavior under deformation.
Alfred Taudes is a Full Professor at the Department of Information Systems and Operations, Institute for Production Management, Vienna University of Economics and Business (WU Vienna). He holds a doctoral degree and a Habilitation from WU Vienna in Business Administration and Management Information Systems, and a Magister degree from Vienna University. He has held assistant professorships at WU and visiting professorships at Augsburg, Münster, Essen, and Tsukuba University, Japan. He joined WU permanently in 1993 and served as head of the Department of Information Systems and Operations from 2010 to 2016. His research spans Operations and Supply Chain Management , Marketing Engineering , Knowledge Management , and the impact of Big Data and Blockchain on production systems. Using Complexity Science and Cryptoeconomics , he investigates digital production, integrated value chains, and market designs. He teaches undergraduate and graduate courses including Operations Strategy, Data Science, and IT seminars in WU’s International Supply Chain Master program, and has also taught at Japanese universities. His recent publications focus on blockchain privacy (e.g., CoinJoin analysis), CBDCs, MiCAR regulation, decentralized federated learning, and digital custody, reflecting a strong trend toward cryptoeconomics and blockchain-based systems in operations and finance. These works appear in top journals and conferences in information systems, security, and operations research. Cooperation Officer of the Year 2013/14 Distinguished Paper Award WI 2009 VHB Best Paper Award Nomination VHB Best Paper Award Dr. Wolfgang Houska - Recognition Award Alfred Taudes has coordinated major research projects such as the WWTF-project “Integrated Demand and Supply Chain Management” and the Special Research Area Adaptive Models in Economics and Management Science. He currently leads the research group on Cryptoeconomics at WU and chairs the scientific board of the Austrian Internet Offensive . His leadership extends to project management in initiatives like the Austrian Blockchain Center and research on decentralized finance and digital assets. He is actively involved in academic service, including organizing conferences like DEXA 2022, serving on editorial boards, and advising on research policy. His lab and research group focus on blockchain applications, digital transformation in operations, and the societal implications of big data.
Erik Bjørnager Dam is a Professor in the Machine Learning section at the Department of Computer Science, University of Copenhagen (UCPH). His research spans theoretical foundations of machine learning to practical applications in medical data analysis, sustainability, and materials science. His key research interests include: Small-scale and resource-efficient deep learning Medical image analysis and segmentation Sustainable and environmentally conscious AI development Graph neural networks for materials science Resource-constrained AI systems Professor Dam's recent publications demonstrate a strong focus on making AI more accessible and sustainable while maintaining high performance standards. His work on 'Performance Per Resource Unit' metrics addresses critical challenges in deploying AI in resource-limited environments, particularly in healthcare applications. His research bridges theoretical machine learning with practical implementations across multiple domains. His notable professional activities include: Co-founding Cerebriu A/S (since 2018) Co-founding Biomediq A/S (since 2008) Delivering lectures on AI's role in green transition (April 24, 2023) Media contributions on deep learning applications in plant research (September 13, 2018) With 74 documented research outputs, Professor Dam maintains an active research profile with significant contributions in 2023-2025 across medical imaging, sustainable AI, and materials science applications.
Professor Hans Gellersen is a faculty member at the Department of Computer Science, Aarhus University. His research focuses on human-computer interaction, virtual/augmented reality, eye tracking, and multimodal interaction. He leads projects exploring gaze-based interfaces, natural input techniques, and XR applications. Key interests include improving interaction efficiency in 3D environments and addressing accessibility challenges in extended reality systems. Recent work emphasizes dynamic eye dominance analysis for foveated rendering, multimodal input cascades (hand-head-eye), and gaze-assisted 3D object manipulation. He investigates user performance in VR/AR systems, calibration methods for eye tracking, and collaborative mixed reality tools. Notable contributions include frameworks for spatial interfaces, gesture fusion, and accessibility adaptations for users with movement disorders. His publications span top venues like CHI, IEEE VR, and ACM Transactions on Computer-Human Interaction. Research themes include gaze-hand coordination, implicit calibration systems, and reconfigurable collaboration spaces. Current projects explore seamless interaction techniques that combine gaze with physical movements and environmental cues.
Teresa Hirzle is a Tenure Track Assistant Professor at the Department of Computer Science , University of Copenhagen , specializing in Human-Centred Computing . Her research focuses on Human-Computer Interaction (HCI) , Virtual Reality (VR) , Extended Reality (XR) , and Gaze-Based Interaction . Research Interests: Designing interaction techniques for immersive environments Eye movement analysis for educational applications Addressing digital eye strain in interactive systems Evaluating user experience in VR/AR Recent Research Trends: Her recent publications examine AI representation in VR co-creation, VR sickness in locomotion, eye strain in gaze-driven systems, and hybrid applications of comics/AR. She also explores pedagogical implications of eye tracking in remote learning. Contact: Email: tehi@di.ku.dk Office: Sigurdsgade 41, 2200 København N.
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.
Giulio Cimini is Associate Professor of Theoretical Physics in the Department of Physics at the University of Rome Tor Vergata and a Research Associate at the 'Enrico Fermi' Research Center. He is a statistical physicist with a strong interdisciplinary focus on complex networks and their applications in socio-economic systems. His research interests include: Statistical Physics of Complex Networks Reconstruction and Validation of Economic Networks Social Network Interactions and Financial Markets Systemic Risk and Financial Contagion Scientific Success, Fitness, and Complexity Adaptive Social Recommendation Codon Usage Bias and Protein Interaction Networks His recent publications reveal a strong trend in applying statistical physics to real-world networks, particularly in finance and social systems. Key themes include the modeling of systemic risk in supply chains and financial networks, the dynamics of collective action on platforms like Reddit (e.g., the GameStop short squeeze), and the development of network reconstruction methods using maximum entropy and optimal transport frameworks. His work often combines empirical analysis with theoretical modeling. Scientific awards and recognitions include: Associate Editor, Frontiers in Physics – Interdisciplinary Physics Board Member, Network Science Society Member, Council of the Complex Systems Society Steering Committee, CCS/Italy He has advised or collaborated with numerous researchers, particularly in projects related to economic networks and complex systems. His work has been supported by Italian national grants such as PRIN and PNRR. He leads or co-leads research projects including RENet and C2T. His research is conducted within interdisciplinary teams involving physicists, economists, and computer scientists, often in collaboration with institutions like ISC-CNR, IMT Lucca, and the Network Science community.
Charles Marcus is a Professor at the University of Copenhagen's Niels Bohr Institute, holding the Villum Kann Rasmussen Chair in Quantum Sciences. He directs the Center for Quantum Devices and Microsoft Station Q – Copenhagen, while affiliating with the Niels Bohr International Academy. Education : Stanford University (B.S. 1984), Harvard University (Ph.D. 1990), IBM Postdoctoral Fellow (1990-92) Employment : Faculty at Stanford (1992-2000), Harvard (2000-2011), and UCPH (2012-present) His research focuses on experimental condensed matter physics, particularly quantum coherent electronics in semiconductors/superconductors. Key areas include spin qubits for quantum computing, Majorana modes in nanowires, quantum Hall systems, and superconductor-semiconductor hybrids. Recent work explores topological quantum information schemes and novel magnetic resonance imaging approaches. Scientific publications span quantum devices, Josephson junctions, and topological materials. Awards include the H.C. Ørsted Gold Medal, AAAS Newcomb-Cleveland Prize, and fellowships from AAAS and APS. He serves on advisory boards for quantum technology centers globally. Significant Awards : H.C. Ørsted Gold Medal (2020) Industry Prize, Danish Academy of Natural Sciences (2019) Member, National Academy of Sciences (2018) Award for Research Excellence in Nanotechnology (2014) Professional Roles : Director, Center for Quantum Devices (2012-2019) Lab Director, Microsoft Quantum (2016-2021) Scientific Director, Harvard Center for Nanoscale Systems (2004-2009)
Romualdo Pastor-Satorras is an Associate Professor of Applied Physics at the Universitat Politècnica de Catalunya (UPC) since 2006. He earned his PhD in Condensed Matter Physics from the Universitat de Barcelona in 1995, followed by postdoctoral research at MIT (1996–1998) and The Abdus Salam International Centre for Theoretical Physics (1998–2000). His extensive international collaborations include visiting positions at Yale University, University of Notre Dame, Kavli Institute for Theoretical Physics, Helsinky University of Technology, Indiana University, and the ISI Foundation. Research Focus His interdisciplinary work spans statistical physics, network theory, and dynamical systems. Primary research areas include: Modeling epidemic spreading in complex networks Random walks and diffusion processes in temporal networks Social and biological applications of network science Glassy dynamics and energy landscapes His research combines mathematical rigor with data-driven approaches to address problems in public health, social dynamics, and complex system behavior. Publications Overview With over 100 peer-reviewed publications, Pastor-Satorras's work demonstrates consistent focus on network dynamics and epidemic modeling. Recent articles explore COVID-19 herd immunity thresholds (2020), echo chambers in political networks (2019), and non-Poissonian temporal networks (2019). His foundational 2015 review on epidemic processes in networks is highly influential. Publications frequently involve interdisciplinary collaborations across physics, data science, and computational biology. Awards and Distinctions Fellow of Universitat Politècnica de Catalunya ICREA Academia Prize (awarded twice by the Government of Catalonia) Research Infrastructure He maintains active collaborations through visiting positions at leading global institutions. His work involves theoretical modeling and computational analysis, though specific laboratory details are unspecified in the provided text.
Filippo Menczer is a Professor of Informatics and Computer Science and Director of the Center for Complex Networks and Systems Research at Indiana University School of Informatics and Computing. He maintains courtesy appointments in Cognitive Science and Physics, and is affiliated with the Center for Data and Search Informatics and the Biocomplexity Institute. Additionally, he holds a Fellowship at the ISI Foundation in Torino, Italy. His research spans computational analysis of digital ecosystems with emphasis on: Web Science: structural and behavioral analysis of internet-scale systems Social Media Dynamics: information diffusion, meme competition, and attention economy modeling Complex Networks: traffic pattern analysis, popularity dynamics, and social link prediction Publications from 2009-2012 reveal consistent focus on social network analytics and information diffusion mechanisms. Key trends include modeling attention-limited meme competition, bursty popularity patterns in social media, and social link prediction through metadata analysis. His work integrates network science, computational social science, and data mining to decode online behavior. His scientific recognition includes: Fellow of ISI Foundation (2013) He leads the NaN research group within the Center for Complex Networks and Systems Research, focusing on interdisciplinary approaches to complex information networks and social media analytics.
Anne Elisabeth Haxthausen is an Associate Professor at the Software Systems Engineering section within DTU Compute , Technical University of Denmark . Her work focuses on formal methods, railway control systems, and safety-critical software engineering. Founder and leader of the DTU Railway Verification Group Member of European Technical Working Group on Formal Methods in Railway Control Editorial board member for Springer Formal Aspects of Computing Journal Active in the Overture Language Board Her research emphasizes formal verification of railway interlocking systems, particularly through compositional approaches and automated tools. She has contributed to projects like RobustRailS, Overture, and RAISE, focusing on model-based development and verification. She serves as a tutor for bachelor students and contributes to the advisory committee for DTU's Computer Science and Engineering MSc program. Her recent publications explore challenges in verifying autonomous and AI-driven railway technologies.
Sithik Aliyar is a Postdoctoral Researcher at the Department of Wind and Energy Systems, Flows Wind Turbine Design Division, at the Technical University of Denmark (DTU). He specializes in computational fluid dynamics (CFD) and offshore wind turbine dynamics, focusing on wave interactions with floating structures. Institution: Technical University of Denmark (DTU) Department: Flows Wind Turbine Design Division, Wind and Energy Systems Research Focus: Floating wind turbines, extreme sea states, harmonic separation, and numerical algorithms His work combines advanced CFD simulations with experimental validation to analyze floating wind turbine stability under directional waves. Recent contributions include the FloatStepper algorithm for robust wave response modeling and studies on SPAR platform upending risks. Publications highlight collaborations with experts like H. Bredmose and J. Roenby, with research outputs spanning Renewable Energy , Royal Society Open Science , and international conferences on ocean engineering. Key metrics include open-access citations, computational fluid dynamics, and floating wind turbine dynamics.
Ole Winther is a Professor at the Department of Biology, University of Copenhagen, specializing in Computational and RNA Biology. He also holds a joint appointment as Professor at DTU Compute, Technical University of Denmark. His research bridges machine learning, bioinformatics, and natural language processing with applications in biological sequence analysis, transcriptomics, and health informatics. Education: 1998: PhD in Physics, University of Copenhagen 1994: Master of Science in Physics, University of Copenhagen Winther's research focuses on developing advanced machine learning methodologies for biological applications. He has pioneered protein language models for sequence analysis (DeepLoc, SignalP, DeepTMHMM), interpretable deep learning for RNA subcellular localization, and benchmarking frameworks for DNA language models. His work spans latent variable models, variational inference, diffusion models, and novel architectures for deep generative modeling, with increasing emphasis on practical healthcare applications including rare disease diagnosis through findzebra.com and medical question answering with large language models. Scientific Recognition: ELLIS Fellow (2021) Head of ELLIS Copenhagen Unit H-index of 61 (Google Scholar, May 2023) 19,700+ citations (Google Scholar, May 2023) Winther has supervised 25+ PhD students to completion with 7 currently in progress, along with over 100 master's projects. He frequently serves as PhD opponent and committee chairman across European institutions. His research is supported by substantial funding including multiple Novo Nordisk Foundation grants totaling over 60 million DKK for the Center for Basic Machine Learning Research in Life Science and CAZAI projects, plus significant funding from the Danish Independent Research Fund. He leads an active research group developing cutting-edge machine learning approaches for bioinformatics and NLP challenges. Winther co-founded two spin-out companies: findzebra.com (2014, 2018), a search engine for rare diseases, and raffle.ai, an NLP startup for enterprise search. He initiated DTU's popular BSc in AI and Data program and teaches the highly enrolled MSc course in Deep Learning (450+ students) and PhD course in Bayesian Data Analysis.
