جست‌وجوی استاد و پژوهشگر

Morten Munkgaard Møllerمشاهده پروفایل

دانشیار

• Supply Chain Management
• Purchasing and Category Management
• Interorganizational Relationships
• +۴ مورد دیگر

Morten Munkgaard Møller is an Associate Professor at the Aalborg University Business School, affiliated with The Faculty of Social Sciences and Humanities and the Marketing and Market Processes Research Group. His research focuses on Supply Chain Management, particularly procurement and category management, emphasizing strategic theory and interorganizational relationships in B2B contexts. He explores topics such as supplier-buyer dynamics, sustainable sourcing, and cross-functional collaboration in both private and public sectors. Key projects include the 'Innovationshub for Cirkulær Plast' (2025–2028) and 'Technology absorption through supplier relationships' (2003). His work bridges theoretical frameworks like contingency theory and typological models with practical applications in strategic sourcing and supply chain ecosystems. Møller has published widely on themes including supply chain ecosystems, distributive justice in apparel sourcing, and big data in procurement. He actively engages in media discussions about procurement strategies in crisis scenarios and category management best practices. His research emphasizes alignment between organizational strategy and operational execution, with a focus on achieving equitable and sustainable outcomes in supply chain relationships.

VG Vinod Vydiswaranمشاهده پروفایل

استادیار

• Information Trustworthiness
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

VG Vinod Vydiswaran is an Assistant Professor in the Department of Learning Health Sciences at the University of Michigan Medical School. He holds a PhD from the University of Illinois at Urbana-Champaign and an MTech from the Indian Institute of Technology Bombay. His research focuses on medical and health informatics, particularly analyzing medical information in clinical notes and online portals. Key areas include information trustworthiness, text mining, natural language processing, and machine learning applications in healthcare. Education: PhD, Computer Science, University of Illinois at Urbana-Champaign (2007-2012) MTech, Indian Institute of Technology Bombay (2002-2004) Bachelor of Engineering, Computer Engineering, Vishwakarma Institute of Technology, Pune (1998-2002) Research Interests: His work spans information trustworthiness, medical NLP, health informatics, and machine learning. Current emphasis is on analyzing medical information exchange between clinicians and patients via electronic health records and online platforms. Recent trends in publications include health vocabulary mining from community forums, trust propagation frameworks, and scenario-based news analysis. Awards: Best Paper Award at COMAD 2005 Second Prize in KDD Cup 2003 (Task 2) Outstanding Teaching Assistant Award (2011) CS Graduate Ambassador (2010-2011) Grants & Advising: Active in interdisciplinary collaborations involving health data mining. Taught SI 671 (Data Mining) in 2015. Served on program committees for AAAI, CIKM, AMIA, and others. Labs & Teams: Part of the Foreseer group at the School of Information, focusing on health informatics applications. Collaborates with Medical School faculty and industry partners like Microsoft Research and Palo Alto Research Center.

Andria B. Eismanمشاهده پروفایل

دانشیار

• Implementation Science
• Health Economics
• Substance Use Prevention
• +۱۲ مورد دیگر

Andria B. Eisman is an Associate Professor of Community Health in the College of Education at Wayne State University. Her work bridges implementation science and health economics to enhance the delivery of evidence-based prevention programs in school and community settings, particularly for adolescents facing health disparities. She leads the WSU ASPIRE Lab and is Principal Investigator on multiple NIH-funded research projects. Ph.D., Health Behavior and Health Education, University of Michigan School of Public Health M.P.H., Health Behavior and Health Education, University of Michigan School of Public Health M.S., Occupational Therapy, University of Indianapolis B.A., Biological Basis of Behavior, University of Pennsylvania Dr. Eisman’s research focuses on improving the implementation of evidence-based practices through hybrid implementation-effectiveness approaches, mixed methods, and economic evaluation. Her work emphasizes substance use prevention, social-emotional learning, mental health, and physical activity in schools, especially in low-resource and trauma-affected communities. She investigates how organizational policies, teacher experience, and stakeholder priorities influence program fidelity and sustainability. Her recent publications highlight trends in implementation science, particularly cost analysis, rapid adaptation during public health crises, and policy alignment to support classroom-based physical activity. These studies often use frameworks like the Exploration, Preparation, Implementation, Sustainment (EPIS) model and Replicating Effective Programs (REP), and employ mixed methods to understand both quantitative outcomes and qualitative implementation barriers. NIH Loan Repayment Program, Health Disparities Research (2016–2020) NIH Loan Repayment Program, Pediatrics, National Institute on Drug Abuse (2020–2022) Dr. Eisman has served as Principal Investigator on major grants from the National Institute on Drug Abuse (NIDA), including an R34 and K01 award, and as Co-Investigator on projects funded by the Institute of Education Sciences and the National Institute of Mental Health. Her advising role includes mentoring graduate students and collaborating with interdisciplinary teams. She teaches courses such as Measurement and Evaluation in Community Health Education and Integrating Evidence-Based Practices in Community Health. She is actively involved in community engagement, including serving on the Michigan Model for Health Steering Committee and collaborating with state agencies, school districts, and community organizations. Her lab, the WSU ASPIRE Lab, focuses on advancing implementation science to improve public health impact and equity.

Anna Mystkowska-Wiertelakمشاهده پروفایل

استاد

• Second Language Acquisition
• Willingness to Communicate
• Learner Engagement
• +۱۲ مورد دیگر

Anna Mystkowska-Wiertelak is a Professor at the University of Wrocław, affiliated with the Faculty of English and the Department of Glottodidactics. Her scholarly work centers on second language acquisition, particularly the psychological and emotional dimensions of language learning. Education: Habilitation in Humanities (Linguistics), Adam Mickiewicz University in Poznań, 2018 PhD in Linguistics, Adam Mickiewicz University in Poznań, 2010 MA in English Philology, Adam Mickiewicz University in Poznań, 1990 Her research focuses on willingness to communicate (WtC) , learner engagement , emotion regulation , motivation , and learning strategies . She investigates how affective and cognitive factors influence language performance, especially in classroom speaking tasks. Her work often employs mixed-methods designs, including idiodynamic and retrodictive qualitative modeling, to capture the dynamic nature of language learning processes. The analysis of her 15 most recent publications reveals a strong trend toward studying the interplay of emotions, engagement, and self-regulation in language classrooms. Her research spans theoretical and empirical domains, with a particular emphasis on advanced learners and third age learners . She frequently collaborates with scholars such as M. Pawlak and J. Bielak, contributing to both monographs and high-impact journal articles. Scientific Contributions: Co-author of key monographs such as Willingness to Communicate in Instructed Second Language Acquisition (2017) and Production-oriented and Comprehension-based Grammar Teaching (2012) Guest editor of special issues, including Contemporary Challenges in Language Education (Anglica Wratislaviensia, 2024) Regular presenter at international conferences such as AAAL, EUROSLA, and Psychology for Language Learning She actively supervises and collaborates with researchers, though specific advisee names are not listed. She has not received specific awards mentioned in the text, but her extensive publication record and editorial roles indicate high scholarly recognition. She is involved in ongoing research projects exploring motivational dynamics, teacher strategies, and learner psychology, contributing significantly to the advancement of applied linguistics and language pedagogy.

Hugh Gorickمشاهده پروفایل

عضو هیئت علمی

• Emergency Department Nursing
• Triage Systems
• Patient Safety
• +۷ مورد دیگر

Hugh Gorick is an Associate Tutor in the School of Health Sciences within the Faculty of Medicine and Health Sciences at the University of East Anglia (UEA). He is currently pursuing a part-time PhD and holds a Postgraduate Certificate in Medical Education from UEA, an MSc in Health Studies from the University of the West of Scotland, and a BSc in Health Studies from City College Norwich. Master in Science, Health Studies – University of the West of Scotland (2021) Post Graduate Certificate in Medical Education – University of East Anglia (2021) Bachelor of Health Science – City College Norwich (2018) Hugh's research is centered on triage in emergency admission areas, with a focus on how nurses assess patient acuity, the impact of these decisions, and how the triage process can be enhanced for better safety and effectiveness. His work spans emergency department nursing, public health, and clinical education, emphasizing patient safety and healthcare delivery optimization. His recent publications demonstrate a strong trend in evaluating triage systems such as the Manchester Triage System, exploring non-clinical roles like receptionists in emergency departments, and advocating for emotional support mechanisms like Schwartz Rounds in educational settings. These works reflect a multidisciplinary approach combining clinical practice, policy, and educational innovation. Fellow of the Higher Education Academy (2022 – present) Hugh has delivered invited talks on evidence-based practice in triage decision-making and is actively involved in research dissemination. While no formal grants are mentioned, his research output and external collaborations indicate active engagement in academic and clinical networks. He also contributes to teaching and clinical education, bridging practice and academia. His work at the Norfolk & Norwich University Hospitals NHS Foundation Trust as an Assistant Practitioner complements his academic efforts, grounding his research in real-world healthcare settings. Hugh is part of a broader research network involving collaboration across institutions, particularly in emergency medicine and healthcare education. His activities include presenting at events and contributing to peer-reviewed journals, with a focus on improving emergency care systems and supporting healthcare professionals emotionally and educationally.

• Energy Demand
• Demand Side Response
• Time Use and Energy Consumption
• +۱۲ مورد دیگر

Jacopo Torriti is a Professor at the University of Reading, affiliated with the School of the Built Environment and the Department of Construction Management and Engineering. His research lies at the intersection of energy demand, social practices, and policy, with a focus on achieving sustainable and equitable energy transitions. His primary research interests include energy demand, demand side response, time-use behavior, electricity pricing, energy policy, smart meters, peak electricity demand, and energy flexibility. His work integrates empirical analysis of time-use and energy data with modeling and policy evaluation to understand how daily activities shape energy consumption and how interventions can shift demand in time and space. The 15 most recent publications highlight a consistent focus on the relationship between human behavior, time-use patterns, and electricity demand. Key themes include the social and spatial dimensions of energy use, the design and impacts of time-of-use tariffs, demand flexibility, and the role of occupant behavior in building energy performance. His research employs diverse methods, including statistical modeling, neural networks, and critical policy analysis, often drawing on large-scale survey data from the UK and other European countries. While no specific scientific awards are mentioned in the provided text, his extensive publication record in top-tier journals and edited volumes, along with contributions to policy reports, reflects significant scholarly impact. Torriti has supervised or collaborated with several researchers, including Yunusov, Ramirez-Mendiola, Lorincz, Curtis, and Smith, on projects related to demand flexibility, time-use analysis, and demand response. He has been involved in research grants and projects funded by organizations such as the DEMAND Centre and has contributed to policy-oriented work for institutions like Citizens Advice and ResPublica. His work often involves interdisciplinary collaboration across energy, sociology, and policy studies. He is a key contributor to research on energy demand through the Centre for Research into Energy Demand Solutions (CREDS) and the DEMAND Centre, where his work on the social and temporal aspects of energy use has been influential. His research helps inform policy and practice on how to manage peak demand, integrate renewable energy, and design equitable energy tariffs.

Vo Nguyen Le Duyمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Statistical Data Analysis
• Artificial Intelligence
• +۲ مورد دیگر

Vo Nguyen Le Duy is a postdoctoral researcher at RIKEN Center for Advanced Intelligence Project (RIKEN-AIP) in Japan, working under the supervision of Prof. Ichiro Takeuchi. Previously, he held positions as a PhD student at Nagoya Institute of Technology and Junior Research Associate at RIKEN. His educational background includes: B.S. degree from Danang University of Science and Technology, Vietnam (2017) M.S. degree from Nagoya Institute of Technology, Japan (2020) Ph.D. degree from Nagoya Institute of Technology, Japan (2022) Dr. Vo Nguyen Le Duy specializes in developing reliable artificial intelligence systems with rigorous statistical foundations. His research bridges theoretical statistics and practical machine learning applications, focusing on quantifying statistical reliability of AI outputs in high-stakes scenarios. He has made significant contributions to statistical inference methods for neural network-based image segmentation and Wasserstein distance calculations. His work addresses critical gaps in current AI systems where confidence in predictions is often not properly quantified. By developing methods with finite-sample validity guarantees, his research enables safer applications in medical diagnostics and autonomous systems where incorrect outputs could have serious consequences.

• Educational Technology
• Collaborative Learning
• Computer-Supported Learning
• +۳ مورد دیگر

Markus Kuhn is a researcher at the University of Cambridge with a diverse academic career spanning over two decades, evidenced by publications from 2003 to 2023. His work bridges educational technology, computer science, and autonomous systems, demonstrating significant interdisciplinary reach across multiple domains. Dr. Kuhn's research has evolved through distinct phases. Initially focused on educational technology (2003-2007), he published extensively on classroom scenarios, collaborative learning, and media integration. His work then broadened to include physics computation (2008) and process support for inquiry learning (2010). More recently (2016-2023), his research has shifted toward autonomous systems, with publications on self-localization technologies and map generation for autonomous vehicles. This publication trajectory reveals a researcher who has successfully adapted his expertise from educational applications to more technical domains while maintaining connections to his foundational work in learning systems. His research demonstrates consistent innovation in applying computational approaches to solve practical problems across different contexts. Dr. Kuhn has maintained long-term collaborations with researchers including Heinz Ulrich Hoppe, Andreas Harrer, and Andreas Lingnau, indicating strong interdisciplinary networks. His work has been published in diverse venues ranging from IEEE Access and Microelectronics Reliability to Research and Practice in Technology Enhanced Learning and International Conferences on Computer-Supported Collaborative Learning.

Kamesh Munagalaمشاهده پروفایل

دانشیار

• Algorithm design
• Discrete optimization
• Approximation algorithms
• +۸ مورد دیگر

Kamesh Munagala is an Associate Professor of Computer Science at Duke University, where he has been employed since 2004. His research spans theoretical computer science with applications in e-commerce, databases, data analysis, and networks. He serves as an Area Editor for PeerJ Computer Science and has held leadership roles including Director of Graduate Studies for the Duke CS department from 2012 to 2015. Education: PhD in Computer Science from Stanford University (2003) BTech from IIT Bombay (1998) Munagala's research focuses on algorithm design and discrete optimization, particularly in scenarios with uncertain inputs. His work encompasses approximation algorithms, online algorithms, and algorithmic game theory. Recent research has concentrated on two main themes: (1) Persuading optimizers or learners toward certain objectives through information revelation and pricing, and (2) Ensuring fairness to groups based on proportionality and stability in resource allocation and societal decision making contexts. His theoretical work has practical applications in designing data networks, facility location, data center scheduling, ad slot allocation, ride-share scheduling, and civic budgeting. Analysis of Munagala's recent publications reveals a strong trend toward interdisciplinary research at the intersection of computer science, economics, and social choice theory. His work shows increasing sophistication in handling fairness constraints across multiple dimensions, particularly in societal decision-making contexts like school assignment, participatory budgeting, and redistricting. There is also a notable expansion into the emerging area of large language models for combinatorial optimization, reflecting the field's evolution toward AI-assisted algorithmic solutions. His research consistently bridges theoretical foundations with real-world applications requiring nuanced approaches to resource allocation under uncertainty. Scientific Awards: NSF CAREER Award (2008) Alfred P. Sloan Research Fellowship (2009) Best paper award at WWW 2009 conference Munagala has served as Director of Graduate Studies for the Duke CS department from 2012 to 2015 and was a Visiting Research Professor at Twitter in 2012. His research has been supported by prestigious grants including the NSF CAREER award. He actively mentors students, with many of his publications featuring student co-authors across his two main research thrusts. His work addresses fundamental challenges in computing efficient solutions under uncertainty, designing pricing and incentive mechanisms for selfish agents, and developing fairness-preserving algorithms for societal decision making. Munagala leads research projects in two broad categories: proportionality in resource allocation and societal decision making, and asymmetric information and persuasion in learning and optimization. His work on proportionality explores fairness concepts like proportionality or core-stability across various societal contexts, while his research on asymmetric information addresses how parties with incomplete information collaborate or compete to achieve optimization objectives through strategic information revelation.

George Lamontمشاهده پروفایل

دانشیار

• Translation theory
• English language structure
• Rhetoric
• +۴ مورد دیگر

George Lamont is an Associate Professor in the Faculty of Arts at the University of Waterloo, specializing in teaching-focused roles. He holds a PhD and MA from the University of Toronto, and a BA and BEd from the University of British Columbia. His work bridges literature, rhetoric, and communication pedagogy across disciplines. PhD: University of Toronto MA: University of Toronto BA: University of British Columbia BEd: University of British Columbia His research spans three key projects: transforming dissertation work into a book on authorship attribution, analyzing Shakespeare's use of etymological sources for emotional shifts, and developing assessment frameworks for communication skill outcomes. Publications focus on engineering education, information literacy, and pedagogical innovations. Recent publications (2019-2022) reveal expertise in: technical writing pedagogy, information-seeking behavior analysis, problem-based learning frameworks, interdisciplinary communication models, and digital learning adaptation. Collaborative works with Kate Mercer, Kari Weaver, and colleagues demonstrate cross-disciplinary applications. President's Excellence in Teaching (2021) Faculty of Arts Teaching Excellence Award (2020) University of Toronto TATP Teaching Excellence Award Outstanding Teaching Assistant Award (University of Toronto English Department) Ontario Graduate Scholarship University of Toronto Fellowship As Director of the Undergraduate Communication Requirement Group, he oversees communication skill development across programs. His teaching experience spans English literature, language studies, and specialized communication training for business and STEM students. Office location HH 156 (University of Waterloo), extension 46875.

Mathias Pelkaمشاهده پروفایل

استاد

• Intelligent Automation Technology
• Smart Factory
• Industry 4.0
• +۶ مورد دیگر

Mathias Pelka is a Professor at the Department of Electrical Engineering and Computer Science at Technische Hochschule Lübeck. His work focuses on intelligent automation technology, smart factory concepts, and Industry 4.0 applications. Education in Informatik (University of Lübeck), Applied Information Technology (Lübeck University of Applied Sciences), and Electrical Engineering (Milwaukee School of Engineering) His research spans localization algorithms, LiDAR-based object detection, neural networks for robotics, and underwater optical distance estimation. Key technologies include sensor fusion, recursive Bayesian filters, and time-based ranging methods. Recent publications highlight trends in autonomous vehicle sensing, indoor positioning systems, and unified location architecture frameworks. His work integrates machine learning, signal processing, and wireless communication for smart infrastructure solutions. Prior roles include software development and Scrum Master positions at Drägerwerk AG & Co. KGaA (2020-2021), software engineering at Ibeo Automotive Systems GmbH (2018-2020), and research associate positions at TH Lübeck (2013-2018).

• Nuclear and Plasma Physics
• Particle and High Energy Physics
• Astronomical Sciences
• +۷ مورد دیگر

Dr. Shanti Krishnan is a Senior Lecturer in the School of Engineering at Swinburne University of Technology, where she conducts interdisciplinary research at the intersection of physics, engineering, and cybersecurity. Her work spans fundamental physics experiments and practical industrial applications. Her research focuses on nuclear and plasma physics , particle physics , and astronomical sciences , with key contributions to muon tomography for monitoring mining infrastructure, dark matter detection via the SABRE South experiment at the Stawell Underground Physics Laboratory, and instrumentation development for the W. M. Keck Observatory. She also explores cybersecurity in Industry 4.0 , particularly through digital twin technologies and anomaly detection in cyber-physical systems. Her recent publications highlight advancements in muon-based navigation for space exploration, cosmic ray-based cybersecurity systems, and simulation of dark matter detectors. These works demonstrate a strong trend toward applying particle physics principles to real-world engineering and security challenges. Dr. Krishnan has received multiple grants, including external funding from HILT CRC Limited and internal grants from Swinburne University, supporting projects such as impact-driven learning materials for net zero in heavy industries and digital twin applications for blood product manufacturing. Development of Impact driven learning materials for net zero in heavy industries – HILT CRC Limited (2025) Rapid Scenario Testing using digital twin for sustainable and scalable manufacturing of blood products – Swinburne University (2024) A Dynamic In-bed Weight Monitoring System for Aged Care Facilities – Cloud Burst Software Pty Ltd (2023) She is actively supervising PhD students, including a project on using digital twins and machine learning to detect cyber-attacks in Industry 4.0 manufacturing systems. Her work is supported by collaborations with institutions such as Caltech, UC Observatories, ANU, and W. M. Keck Observatory, reflecting a strong international research network. Dr. Krishnan leads and contributes to multidisciplinary research teams focusing on detector development, secure industrial systems, and sustainable manufacturing. Her lab and project teams integrate physics, engineering, and data science to solve complex real-world problems.

Maryam Kamgarpourمشاهده پروفایل

استادیار

• Control Theory
• Game Theory
• Mechanism Design
• +۶ مورد دیگر

Maryam Kamgarpour is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), School of Engineering. She previously held faculty positions at the University of British Columbia and ETH Zürich. Her work bridges stochastic control , multiagent learning , and game theory , focusing on safety-critical systems. Education: PhD in Engineering from UC Berkeley, BSc in Applied Science from University of Waterloo. Research Interests: Control under uncertainty, game theory, mechanism design, mixed-integer optimization, and applications to transportation, robotics, power grids, and healthcare. Her recent publications emphasize safe reinforcement learning , multirobot coordination , and stochastic trajectory planning , with applications to aircraft navigation and energy systems. She has received the European Union ERC Starting Grant, NASA High Potential Individual Award, and IEEE Transactions on Control of Network Systems Outstanding Paper Award. Scientific Awards: ERC Starting Grant (2016-2021) NASA High Potential Individual Award (2010) NASA Excellence in Publication Award IEEE Outstanding Paper Award (2022) PhD Students: Jordan Philip Christopher Maddux Anna Maria Ni Tingting Ren Kai Salizzoni Giulio Schlaginhaufen Andreas Vaishampayan Saurabh Dilip Vallat Gabriel Rémi Former EPFL student: Guo Baiwei

Linda Weiser Friedmanمشاهده پروفایل

استاد

• Corporate Social Responsibility
• Leadership
• Operations Management
• +۹ مورد دیگر

Linda Weiser Friedman is a Professor in the Paul H. Chook Department of Information Systems and Statistics at the Zicklin School of Business, Baruch College (CUNY). She holds a Ph.D. in Operations Research (1983) and an M.S. in Applied Statistics (1980) from Polytechnic Institute of New York, and a B.A. in Statistics/Biology (1976) from Baruch College. Her research spans Corporate Social Responsibility, Leadership, Operations Research, Humor Studies , and Quantitative Modeling , with a focus on ethical leadership, simulation metamodeling, and Jewish humor as a cultural/social justice tool. Academic Degrees B.A., Statistics/Biology (Baruch College, 1976) M.S., Applied Statistics (Polytechnic Institute of New York, 1980) Ph.D., Operations Research (Polytechnic Institute of New York, 1983) Her scholarly work examines technology ethics, simulation analysis , and interdisciplinary education , with recent publications on diversity in academia and Jewish humor. She has received multiple awards, including the Zicklin Hybrid & Online Teaching (HOT) Award and annual Celebration of Faculty Scholarship recognitions (2007-2013). Her teaching includes courses in Business Statistics, Object-Oriented Programming , and Jewish Humor . Scientific Awards : Zicklin Hybrid & Online Teaching (HOT) Award (2013) Tenth Annual Celebration of Faculty Scholarship (2012) Ninth Annual Celebration of Faculty Scholarship (2011) Eighth Annual Celebration of Faculty Scholarship (2010) Zicklin Fellow (1999-2000)

Debra Donnellyمشاهده پروفایل

دانشیار

• History Education
• Historical Consciousness
• Global Education
• +۲ مورد دیگر

Associate Professor Debra Donnelly is a history educator and program convenor at the University of Newcastle's School of Education, Australia. With extensive experience as a secondary school history teacher and administrator, she focuses on historical consciousness development, media's impact on historical understanding, and teacher training innovations through programs like TeachReady and TeachLive. She co-edits the Q1-ranked Historical Encounters journal and leads the HERMES research network. PhD (Pedagogy), Monash University Bachelor/Master of Arts (University of Newcastle) Master of Education (Charles Sturt University) Her research explores: How film and digital media shape historical understanding Cognitive and emotional engagement in museums Simulation technologies for teacher skill development Global education frameworks for critical citizenship Recent publications analyze: DNA testing's influence on family history narratives Mixed-reality micro-teaching effectiveness Postmodern picture books in history pedagogy Comparative national identity education approaches She has secured over $1.2 million in grants, including: $625,060 Technology-enhanced Mathematics Retraining $266,517 Mid-Career Teacher Education Program $15,000 iANZAC Youth Perspectives Project Her work also examines: Historical empathy development through textbooks Visual arts in teacher professional landscapes Challenges in Saudi Arabian gifted education Critical post-national citizenship frameworks