جستجوی استاد راهنمای دانشگاهی

• Data Mining & Machine Learning
• Network Science & Complex Systems
• Artificial Intelligence & Society
• +۲ مورد دیگر

Tina Eliassi-Rad is Professor and the Inaugural Joseph E. Aoun Chair at Khoury College of Computer Sciences, Northeastern University in Boston. She serves as Core Faculty at the Network Science Institute and holds External Faculty positions at both the Santa Fe Institute and Vermont Complex Systems Institute. Additionally, she maintains Affiliated Faculty status across six Northeastern University institutes including the NULab for Digital Humanities and Computational Social Science, Global Resilience Institute, Cybersecurity and Privacy Institute, Institute for Experiential AI, and Internet Democracy Initiative. Her research spans: Data Mining & Machine Learning Network Science & Complex Systems Artificial Intelligence & Society She leads two major research initiatives: Trustworthy Network Science , which addresses explainability, transparency, stability, and robustness in network science ML algorithms; and Just Machine Learning , which examines broader complex systems where ML operates to understand and mitigate risks. Her work bridges theoretical foundations with societal applications. Dr. Eliassi-Rad's publication record demonstrates consistent focus on applying network science to critical societal challenges. Her recent research examines pandemic mobility patterns and cybersecurity threats using network-based approaches that combine epidemiological modeling with network analysis techniques. She actively mentors doctoral students through her RADLAB research group, currently advising PhD candidates Wan He (Network Science) and David Liu (Computer Science), along with PhD students Zohair Shafi and Samantha Dies (Computer Science). Her research has secured funding from prestigious organizations including the National Science Foundation, Department of Defense, Defense Advanced Research Projects Agency, Army Research Lab, and others. As leader of RADLAB, she directs research at the intersection of data science, network analysis, and societal impact, with particular emphasis on ensuring that technical advances in AI and network science serve societal needs responsibly and equitably.

Sara Greenمشاهده پروفایل

دانشیار

• Philosophy of Science
• Precision Medicine
• Consumer Medicine
• +۴ مورد دیگر

Sara Green is an Associate Professor at the Department of Science Education, University of Copenhagen, specializing in the Section for History and Philosophy of Science . Her work bridges philosophy, biology, and biomedical ethics, focusing on the epistemic and social implications of datafication in healthcare and the ethical challenges of precision medicine and consumer health technologies. Green holds a PhD in Science Studies from Aarhus University and was a postdoctoral fellow at the University of Pittsburgh’s Center for Philosophy of Science. She leads the PROMISE and COPE projects and contributes to EU-funded initiatives like DataSpace , TRANSCEND , and REDESIGN . Research Themes: Philosophy of precision medicine and data-driven healthcare Ethics of patient-derived organoids and organ-on-chip technologies Epistemic standards in consumer medicine Interdisciplinary integration in systems biology Article Trends: Recent publications explore organoid ethics , datafication in medicine , and philosophical frameworks for emerging health technologies . Key sub-fields include biobanking, cross-border data governance, and temporal dimensions of personalized medicine. Scientific Recognition: DFF Research Project 1 (2020) Semper Ardens Accellerate Grant (2023) Silver Medal, Royal Danish Society of Science and Letters (2024) Werner Callebaut Prize (2015) EU SwafS-Horizon stipend (2020) Teaching & Supervision: She teaches philosophy of science to students in biology, chemistry, and sports science, supervising projects on philosophy of biology and medicine and co-supervising science communication research. Collaborative Networks: Green collaborates across Denmark, the EU, and the U.S., particularly on cross-border health data infrastructure and reduction of animal models through organoid technologies.

Claudia Wagnerمشاهده پروفایل

استاد

• Computational Social Science
• Algorithmic Fairness
• Digital Behavioral Data
• +۷ مورد دیگر

Claudia Wagner is a full professor for Applied Computational Social Sciences at RWTH Aachen University and the Scientific Director of the Computational Social Science department at GESIS—Leibniz Institute for the Social Sciences. She is also an External Faculty member at the Complexity Science Hub Vienna. Her work bridges computer science and the social sciences to study algorithmic systems and their societal impacts. Her research focuses on socio-technical phenomena such as inequality, sexism, and perception bias in algorithmically infused societies. She investigates methodological challenges in using digital behavioral data to study human behavior, attitudes, and group dynamics. Her interests span computational social science, algorithmic fairness, network science, and AI ethics. The analysis of her recent publications reveals a strong emphasis on bias, fairness, and methodological rigor in digital data analysis. Her work spans AI psychometrics, gender inequality in online platforms, and validation frameworks for digital traces. She frequently publishes in top-tier venues such as Nature , Science , and AAAI conferences. DOC-fFORTE fellowship from the Austrian Academy of Sciences Four best paper awards at international conferences (ICWSM, CSCW, WWW, AAAI) Associate Editor, EPJ Data Science Steering Committee Member, International AAAI Conference on Web and Social Media Board Member, International Society for Computational Social Science Claudia Wagner has led and co-led substantial research projects funded by national and international agencies. She mentors a diverse group of PhD students working on topics like algorithmic bias, data quality, and dehumanization. She has organized training events such as the CSS Methods Summer School and delivered keynotes globally on inequality and computational social science. She leads the Computational Social Science department at GESIS and collaborates with interdisciplinary teams at RWTH Aachen and the Complexity Science Hub. Her group develops tools for measuring algorithmic impacts and visualizing disparities in socio-technical systems, such as the 'Planets of Disparity' dashboard.

Francisco Camara Pereiraمشاهده پروفایل

استاد

• Intelligent Transportation Systems
• Machine Learning
• Active Learning
• +۳ مورد دیگر

Francisco Camara Pereira is a Professor and Head of Section at the Department of Technology, Management and Economics at the Technical University of Denmark (DTU). His research focuses on Intelligent Transportation Systems, Machine Learning, and Data-Driven Decision-Making in transportation contexts. He actively contributes to advancing transportation science through interdisciplinary approaches combining simulation, optimization, and AI techniques. His work addresses challenges in public transport analysis, charging infrastructure planning, and multimodal demand prediction. Recent projects include developing graph-based optimization methods for electric vehicle networks and causal discovery frameworks for transportation systems. He supervises multiple PhD students in areas like federated learning for cyclist safety, causal graph neural networks, and socially aware AI models. Key contributions include publications on smart card data analysis for travel surveys, stochastic infrastructure expansion models, and transfer learning for bike-share systems. His research aligns with UN Sustainable Development Goals related to sustainable cities and innovation. Dr. Pereira collaborates internationally on transportation policy and infrastructure projects. His lab focuses on translating theoretical advancements into practical solutions for urban mobility challenges.

Qiongxiu Liمشاهده پروفایل

استادیار

• Cybersecurity
• Distributed Optimization
• Privacy-Preserving Technologies
• +۵ مورد دیگر

Qiongxiu Li is a Tenure-Track Assistant Professor in the Cyber Security group at Aalborg University's Copenhagen campus, part of the Technical Faculty of IT and Design. Her research focuses on cybersecurity, distributed optimization, privacy/security, and federated learning. She has authored/co-authored 38 papers in top-tier venues including IEEE Transactions on Information Forensics and Security, ICLR, and EUSIPCO. Education: PhD in Privacy and Security from Aalborg University (2018-2021). Notable achievements include winning the EUSIPCO 2020 3MT Contest and co-delivering a tutorial on privacy-preserving distributed optimization at EUSIPCO 2024. She actively reviews for conferences like NeurIPS, ICLR, and journals such as TPAMI and TIFS. Research Themes: Privacy-preserving distributed algorithms, federated learning security, differential privacy, and adversarial machine learning. Recent Trends: Focus on securing AI systems (e.g., LLM vulnerabilities, federated clustering privacy), quantization for privacy, and theoretical bounds in decentralized learning. Awards: 2020 EUSIPCO 3MT Winner (outstanding finalist in EURASIP's annual doctoral research competition). Grants/Projects: Co-PI of the AI:SECURITY project (2025-2029) addressing AI security threats like phishing and malicious actors. Labs/Teams: Leads the Cyber Security group at Aalborg's Copenhagen campus, focusing on theoretical and applied research in secure distributed systems.

Tom Brughmansمشاهده پروفایل

دانشیار

• Archaeological Network Research
• Roman Economy
• Computational Archaeology
• +۴ مورد دیگر

Tom Brughmans serves as Associate Professor in Classical Archaeology at Aarhus University's School of Culture and Society, where he pioneers the application of network science and computational modeling to archaeological questions. His work bridges theoretical archaeology with complexity science, focusing on long-term economic dynamics in the Roman Empire through quantitative analysis of material culture distribution. His research centers on developing methodological frameworks for archaeological network analysis, with specific expertise in Roman economic integration, amphorae trade networks, and agent-based simulation of ancient economies. Brughmans advocates for computational reproducibility and open-science practices, creating accessible tools that transform complex archaeological data into analyzable network structures while challenging traditional interpretations of Roman market systems. Brughmans' publication trajectory reveals three dominant trends: advancing theoretical foundations of archaeological network science through handbooks and methodological guides; empirical investigations into Roman economic complexity using big-data approaches to amphorae distributions; and development of public-facing simulation platforms that translate academic research into interactive experiences. His work consistently integrates computational techniques with archaeological evidence to model socio-economic processes across centuries. His scientific recognition includes prestigious competitive fellowships: Leverhulme Early Career Fellowship (2017-2019) for the MERCURY project Marie-Curie Individual Fellowship (2019-2020) for SIMREC Brughmans directs multiple major research initiatives including the Past Social Networks Project (an open repository for ancient network data), NEFLARA (a Marie-Curie project developing landscape archaeology frameworks), and MINERVA (focused on Roman economic functioning). He has secured substantial funding from the Leverhulme Trust, Marie-Curie Actions, and ERASMUS+ for projects advancing computational archaeology, while actively promoting collaborative research through platforms like FORVM that make economic modeling accessible to broader audiences. As a core member of Aarhus University's Centre for Urban Network Evolutions (UrbNet), he contributes to interdisciplinary investigations of ancient urban connectivity. His leadership extends to developing international research networks through the Oxford Handbook of Archaeological Network Research and creating open educational resources that democratize access to network analysis methodologies in archaeology.

Alex Arenasمشاهده پروفایل

استاد

• Complex Systems
• Network Science
• Multilayer Networks
• +۱۲ مورد دیگر

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.

Sebastian Risiمشاهده پروفایل

استاد

• Neuroevolution
• Evolutionary Robotics
• Self-Organizing AI
• +۹ مورد دیگر

Sebastian Risi is a Professor at the IT University of Copenhagen , where he directs the Creative AI Lab and co-directs the Robotics, Evolution and Art Lab (REAL) . His work bridges computational evolution, deep learning, and collective intelligence for applications in robotics, art, and video game design. His research focuses on self-organizing AI systems that grow or assemble through local interactions, inspired by biological development. Key areas include neuroevolution , neural cellular automata , and generative modeling , with applications in adaptive robotics, game content creation, and damage-resilient AI. Recent publications highlight trends in self-assembling neural architectures (NDPs) and 3D functional machine generation (Minecraft experiments). Awards include ERC Consolidator Grant (2022), Best Paper at FDG’21 , and Google Faculty Award (2019). Scientific Awards : ERC Consolidator Grant (GROW-AI), Best Paper FDG’21, Runner-Up IEEE Games’20, GECCO 2017 Competition Winner, Sapere Aude Grant, Amazon/Google Faculty Awards He advises on projects like GROW-AI (EU-funded), AI-TESTER (game testing), and C2SIM (military systems). Media coverage includes Science , Wired , and Popular Science .

• Algorithms
• Algorithmics
• Big Data
• +۷ مورد دیگر

Stephen Alstrup is a Professor in the Algorithms and Complexity section at the Department of Computer Science (DIKU), University of Copenhagen, Faculty of Science. His research bridges theoretical computer science with practical applications in modern computational challenges. His primary research interests include: Algorithm design and analysis Graph algorithms and data structures Big Data processing techniques Streaming algorithms and Internet distribution Theoretical foundations with practical implementations Alstrup's work demonstrates how theoretical algorithm research can lead to real-world applications, as evidenced by his development of Octoshape technology for large-scale Internet streaming. His research spans from fundamental theoretical problems to applications in Big Data, cloud computing, and information retrieval systems. He has published extensively with 93 research outputs including journal articles, conference proceedings, and books. His recent work focuses on graph spanners, semantic hashing, recommendation systems, and universal graph structures, showing continued productivity in theoretical computer science. Alstrup actively engages with industry and media, contributing to discussions about Big Data applications, technology innovation, and how businesses can collaborate with universities to access cutting-edge knowledge and funding opportunities. His work has been featured in 10 media contributions discussing practical applications of algorithms in education, municipal IT projects, and business innovation.

Vito Latoraمشاهده پروفایل

استاد

• Complex Systems
• Network Science
• Applied Mathematics
• +۱۳ مورد دیگر

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.

Carsten Greveمشاهده پروفایل

استاد

• Public management and governance
• Public management reform
• Public-private partnerships
• +۱ مورد دیگر

Carsten Greve serves as Professor of Public Management and Governance and Head of the Department of Organization at Copenhagen Business School (CBS), where he maintains an office in room KIL/14.A-4.75 with contact number +4538153598. His academic leadership extends to directing departmental operations while maintaining an active research profile focused on the intersection of public sector management and private sector collaboration. At CBS, he teaches core courses including Leading Reform and Change for the Master of Public Governance program and Strategic Public Management Across the Public Sector , shaping the next generation of public sector leaders. Greve's research program centers on four interconnected domains: public management and governance systems, public management reform trajectories, public-private partnership frameworks, and market-based governance mechanisms. His work critically examines how privatization processes transform public service delivery, particularly in Nordic contexts where traditional welfare state models confront market-oriented reforms. Through comparative analyses of infrastructure projects and elderly care systems, he investigates the tension between efficiency-driven market mechanisms and democratic accountability requirements in public administration. His scholarship consistently bridges theoretical frameworks with Danish policy implementation challenges, especially in healthcare and transportation sectors. Recent publications reveal evolving research trajectories toward regulatory capitalism frameworks and agile governance models, with the 2025 Research Handbook on Privatisation synthesizing global privatization debates while the 2023 Handbook on Strategic Public Management advances collaborative governance approaches. His article corpus demonstrates increasing focus on temporal dimensions of reform implementation, risk allocation in complex partnerships, and the adaptation of public management practices in digitally transforming administrations. The recurrent Nordic case studies highlight distinctive administrative traditions navigating privatization pressures while maintaining public value commitments. No scientific awards or formal honors are documented in the available materials. Greve's supervisory record includes 10 successfully completed PhD dissertations at CBS, though specific student names and dissertation topics remain unlisted. His research activities generate substantial external engagement through presentations at national institutions including Rigsrevisionen (National Audit Office), Aalborg University, and Danske Professionshøjskoler, alongside international contributions to European Union policy reports. While grant funding details are unspecified, his prolific publication output across edited volumes, book chapters, and peer-reviewed journals indicates sustained research productivity.

Romualdo Pastor-Satorrasمشاهده پروفایل

دانشیار

• Condensed Matter Physics
• Mathematical Physics
• Theoretical Physics
• +۳ مورد دیگر

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.

Kantaro Fujiwaraمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Neural Data Analysis
• Machine Learning
• +۱ مورد دیگر

Kantaro Fujiwara serves as Associate Professor at the Graduate School of Medicine, The University of Tokyo, with concurrent appointments at the International Research Center for Neurointelligence (IRCN) and the Department of Mathematical Informatics, Graduate School of Information Science and Technology. He also manages the Data Science Core infrastructure for IRCN. His academic background includes a Ph.D. in Information Science and Technology from the University of Tokyo (2008), followed by postdoctoral research at the University of Tokyo (JSPS) and University of Cambridge, then assistant professorships at Saitama University and Tokyo University of Science before joining the University of Tokyo faculty. Dr. Fujiwara's research bridges computational neuroscience and neural data analysis through mathematical modeling of neural networks, development of neural data analysis methodologies, and exploration of brain-inspired machine learning. His work extends to biological information processing with specific applications in pancreatic beta cell modeling for diabetes research, establishing connections between theoretical frameworks and experimental neuroscience. His publication record (2017-2023) reveals consistent interdisciplinary contributions applying echo state networks, recurrence analysis, and nonlinear dynamics to neural data classification, physiological signal processing, and disease modeling. These works demonstrate strong integration of computer science, neuroscience, and biomedical engineering methodologies to solve complex neurobiological problems. As Data Science Core Manager at IRCN, he oversees computational infrastructure and software resources that enable advanced neurointelligence research across the University of Tokyo ecosystem, providing critical support for data-intensive neuroscience projects.

Matias Thuen Jørgensenمشاهده پروفایل

دانشیار

• Tourism
• Sustainable Tourism
• Tourism Development
• +۶ مورد دیگر

Matias Thuen Jørgensen is an Associate Professor and head of the Center for Tourism Research at Roskilde University, Denmark, within the Department of Social Sciences and Business. His interdisciplinary research bridges business studies, sociology, and human geography to examine tourism's societal impacts, with empirical focus on Chinese tourism markets and Nordic destinations. He holds a PhD in Tourism Management from The Hong Kong Polytechnic University (2017), awarded through the competitive Hong Kong PhD Fellowship Scheme. His educational foundation combines rigorous academic training with field expertise in tourism phenomena. The PhD research at Hong Kong Polytechnic University established his methodological approach to analyzing tourism distribution systems through Activity Theory and Actor-Network Theory frameworks. Jørgensen's research critically examines tourism's role in sustainable community development, emphasizing how mundane everyday experiences create destination value in Nordic contexts. His work explores social value creation through tourist-resident interactions, regenerative tourism models like CopenPay, and the socio-economic implications of tourism transitions in peri-urban areas. Key themes include the ethical dimensions of tourism development, community mobilization through social entrepreneurship, and the complex interplay between tourism policy and local realities. Analysis of his 15 most recent publications reveals dominant trends in regenerative tourism frameworks, micro-level host-guest interactions, and policy responses to overtourism challenges. His scholarship increasingly focuses on climate-responsive tourism models, ethical pricing mechanisms in aviation, and regulatory approaches to short-term rentals, demonstrating consistent evolution toward solution-oriented sustainability research. Notable recognitions include: Hong Kong PhD Fellowship Scheme (2014) Nomination for Danish National University Teaching Award (2023) Peter Keller Award (2022) Roskilde University Teaching Prize (2022) Teacher of the Year Award, Roskilde University (2022) As principal investigator on seven research projects totaling over 3 million DKK in funding, Jørgensen has secured grants from diverse sources including industry partnerships and public research councils. Current projects include the SeNSE initiative on sustainable nature-based tourism entrepreneurship and the Tourism Business Model Tool development. He actively supervises doctoral research on social value creation in urban tourism encounters while contributing to policy formulation through UNWTO engagements and frequent media commentary. Leading the Center for Tourism Research (CFTR), he fosters cross-disciplinary collaboration between academics, industry stakeholders, and policymakers. His recent activities include organizing the 2025 Academy of Management symposium on tourism transitions and establishing the 'Tourism and Everyday Life in Cities' research network, positioning CFTR at the forefront of contemporary tourism scholarship.

Troels Schultz Larsenمشاهده پروفایل

دانشیار

• Urban Sociology
• Territorial Stigmatization
• Social Inequality
• +۹ مورد دیگر

Troels Schultz Larsen is an Associate Professor in the Department of Social Sciences and Business at Roskilde University, specializing in Social Dynamics and Change. With a PhD and MSc in Public Administration, he has been with Roskilde University since 2005, progressing from PhD fellow to his current position as Associate Professor since 2014. His work focuses on urban sociology, territorial stigmatization, and the dynamics of marginalized urban areas within the Danish welfare state context. Dr. Schultz Larsen's academic journey includes: 2014-Present: Associate Professor, Department of Social Sciences and Business, Roskilde University 2009-2014: Assistant Professor/Post-Doc, Department of Society and Globalization, Roskilde University 2005-2009: PhD Fellow, Department of Society and Globalization, Roskilde University 1998-2005: MSc (Public Administration equivalent), Department of Social Science, Roskilde University Identifying his theoretical position as "Historically-Specific Praxis-Theory," Dr. Schultz Larsen draws inspiration from Bourdieu, Wacquant, Gramsci, and other critical theorists. His research spans urban sociology, territorial stigmatization, welfare state dynamics, and public innovation. He examines how marginalized urban areas are produced and maintained through intersecting social, economic, and political processes, with particular attention to the Danish context and its "ghetto list" policies. His work challenges simplistic interpretations of urban marginality, emphasizing the complex interplay between housing markets, labor markets, education systems, and family structures in reproducing spatial inequalities. Dr. Schultz Larsen's recent publications reveal a deepening focus on territorial stigmatization as both a theoretical concept and practical policy issue. His 2024-2025 work, including the book "Fragmenting Cities: The State, Territorial Stigmatization and Urban Marginality," develops a comprehensive framework for understanding how state policies actively produce spatial inequalities. He critically analyzes Denmark's controversial "ghetto list" policy, demonstrating how such classifications function as mechanisms of dehumanization and social exclusion. His research increasingly adopts comparative perspectives, connecting Danish urban marginality to broader European and global patterns of spatial inequality. Dr. Schultz Larsen's scholarly contributions include: Active participation in major research projects including EU-HORIZON24's RURALITIC Membership in the Royal Danish Academy (2025-2027) Extensive media engagement on urban policy issues With over 15 years of teaching experience at Roskilde University, Dr. Schultz Larsen has supervised numerous student projects across social sciences, politics, and public administration. His supervision spans diverse topics including urban policy, social integration, housing, labor market policies, and public innovation. He has been involved in several significant research grants, most notably as a participant in the CLIPS project (Collaborative Innovation in the Public Sector), a major multi-institutional collaboration examining innovation in public services. His current research includes the EU-HORIZON24 project RURALITIC and the BOSID project on housing stigmatization in Denmark. Dr. Schultz Larsen is actively involved in research networks focused on urban marginality and territorial stigmatization. He collaborates closely with Dr. Katrine Nørgaard Delica on multiple projects and publications, including their forthcoming book "Fragmenting Cities." His work with the North Seeland Police Department on the "TRYK Politi" initiative represents a significant practice-oriented research partnership examining citizen engagement in crime prevention. As a member of the Royal Danish Academy (2025-2027), he contributes to national scholarly discussions on urban policy and social governance.