جستجوی استاد راهنمای دانشگاهی

Cailean Gallagher is an Associate Lecturer in Management at the School of Management, University of St Andrews . Their research bridges technology, labor rights, and historical analysis, focusing on algorithmic management in the gig economy and 18th-century Jacobite political economy. Key projects include the Workers' Observatory (2020) and Worker Data Science (funded by Edinburgh Futures Institute). Education : PhD in History, University of St Andrews (2022) Research Interests include gig economy organizing, workplace resistance, and Scottish Jacobitism. They apply interdisciplinary methods (sociology, computer science, legal studies) to study power asymmetry in platform economies and historical labor movements. Recent Publications examine participatory data science for Deliveroo riders, James Steuart’s political economy, and temporal control in Edinburgh’s gig economy. Their work aligns with UN Sustainable Development Goals (SDGs) related to decent work and technological justice. Scientific Awards : Policy Fellowship (AHRC/DCMS R&D Unit on AI) British Academy funding for Scottish Histories of Resistance Activities include organizing the 2025 Genealogies of Corporate Morality conference and media contributions like the 2024 Edinburgh rider survey analysis.

• Labor Studies
• Gig Economy
• Workplace Organization
• +۶ مورد دیگر

Robin Lemmens is a Professor at the Faculty of Medicine, KU Leuven, and leads the Laboratory of Neurobiology (VIB-KU Leuven). He serves as head of Academic Consultants Training in Specialist Medicine and Program Director of the POC Medical Specialist in Training. His affiliations include the LBI - KU Leuven Brain Institute and membership in multiple institutional committees including the Metaforum Steering Committee and Faculty Council of Medicine. Dr. Lemmens' research focuses on stroke neurology with particular expertise in neuroimaging, cerebrovascular diseases, and endovascular therapy. His work spans ischemic stroke management, anticoagulation therapy, intracerebral hemorrhage, and advanced imaging techniques for stroke diagnosis and treatment planning. Current research explores AI applications in stroke imaging, optimal timing of anticoagulation after stroke, and endovascular therapy in extended time windows. Analysis of recent publications reveals a strong emphasis on translational stroke research with significant contributions to clinical trial methodology. Key themes include validation of imaging biomarkers, optimization of thrombolytic and anticoagulant therapies, and development of AI tools for stroke lesion segmentation. His work frequently appears in high-impact journals including Stroke , Neurology , and The Lancet . Dr. Lemmens supervises research projects and students, with recent supervision including Oosterbos, C. on peroneal nerve entrapment research. His grant portfolio includes multiple active projects totaling millions in funding, with recent grants focusing on secondary stroke prevention, comprehensive stroke management systems, and AI for stroke outcome prediction. He leads the Laboratory of Neurobiology at VIB-KU Leuven, which collaborates extensively with international stroke research networks. Current research directions include developing patient-centered stroke care pathways, advanced imaging techniques for early ischemic changes, and personalized stroke diagnostics and treatment protocols.

• Stroke Neurology
• Neuroimaging
• Cerebrovascular Diseases
• +۴ مورد دیگر

Haoyu Wang is a Researcher in the Computer and Information Science department at the University of Pennsylvania . He previously held research positions at Shanghai Jiao Tong University and interned at Google DeepMind , Amazon AWS , ByteDance , AI2 , Tencent AI Lab , and Goldman Sachs . Education : PhD in Computer and Information Science (2021–Present), MS in Computer and Information Science (2019–2021), BS in Computer Science (2015–2019). His research focuses on Event-Centric NLP/NLU , LLM Reasoning and Planning , Knowledge Graph , and Pose Estimation in Computer Vision . His work includes event causality identification, semantic classification in context, and synthetic control for temporal reasoning. He has contributed to multimodal hallucination analysis and safety in reasoning models through projects like RESIN-11 and Devil's Advocate . His publications span venues like EMNLP , EACL , and ACL . His recent articles analyze LLM limitations in NP-hard problems , clinical trial prediction , event causality , and hallucination in vision-language models . He has served as PC Member for conferences including ACL , NAACL , NeurIPS , and EMNLP since 2019.

• Event-Centric NLP/NLU
• LLM Reasoning and Planning
• Knowledge Graph
• +۵ مورد دیگر

Zehang Richard Li is an Assistant Professor in the Department of Statistics at the University of California Santa Cruz. His research focuses on statistical methods for demography, epidemiology, and global health, with expertise in latent variable modeling, space-time models, survey sampling, data integration, and weakly supervised learning. He develops workflows and pipelines for complex statistical analysis and real-world data-driven decision-making. Ph.D. in Statistics from the University of Washington (advisor: Tyler McCormick) Postdoctoral Researcher at Yale School of Public Health (Department of Biostatistics, advisor: Forrest Crawford) His work emphasizes high-dimensional data and uncertainty quantification in prevalence mapping. He leads the development of the SUMMER R package and SAE4Health platform, including ShinyApps for subnational health indicator analysis. Current projects address farmworker health under climate change through a UCOP grant and Bayesian frameworks for integrating verbal autopsy data via NIH funding. Recent publications highlight methodological advances in small area estimation, verbal autopsy analysis, and pandemic modeling. Key article themes include: Bayesian hierarchical modeling and tensor decomposition (2025) Domain adaptation for cross-population cause assignment (2024) Verbal autopsy validation and diagnostic accuracy (2023) Bayesian multilevel poststratification for disease prevalence (2022) Respiratory virus transmission dynamics and immune mechanisms (2021) Grants supporting his research include: National Institutes of Health Melinda and Bill Gates Foundation Vital Strategies Hellman Fellows Program University of California Office of President (UCOP) UCSC Committee on Research He advises Ph.D. students Yu (Zoey) Zhu, Qianyu Dong, Sho Kawano, and Toshiya Yoshida, all of whom have received academic recognition for their work on Bayesian models, small area estimation, and prevalence mapping.

• Statistical Methods
• Demography
• Epidemiology
• +۷ مورد دیگر

Antonio Aloisi is a Professor of Labor Law at IE University in Madrid, where he teaches European and Comparative Labour Law and guides students in digital regulation. He co-leads the Jean Monnet Center 'Lawtomation' and is affiliated with the 'LawAhead' Center on the Legal Profession, while also serving as a fellow at the UNESCO Chair in Ethics and Governance of Artificial Intelligence. His research focuses on the impact of digital transformation on labor markets, particularly in the gig economy and algorithmic decision-making, blending insights from labor law, data protection, and EU policy. Antonio’s work examines the dual transition of green and digital economies, advocating for governance frameworks that balance innovation with labor rights. His scholarship frequently appears in high-impact journals and is cited in policy documents, court rulings, and media, reflecting his influence on debates about platform work and AI surveillance. He has held visiting roles at institutions like NYU School of Law, Fundação Getulio Vargas, and European University Institute, and his collaborations with international bodies such as the European Parliament, ILO, and OECD underscore his global engagement. Articles by Aloisi highlight trends in algorithmic management, EU Platform Work Directive, and the socio-legal implications of AI. His work critiques the 'robocalypse' narrative, emphasizing that automation often intensifies organizational processes rather than displacing workers, while advocating for collective action and regulatory innovation. Scientific awards include the Marie Skłodowska-Curie Fellowship for the 'Boss Ex Machina' project and a research grant by the European Commission. Scientific Awards: Marie Skłodowska-Curie Fellowship (2020-2022) European Commission Research Grant

• Labor Law
• Digital Transformation
• Platform Work
• +۷ مورد دیگر

Dr. John Zerilli is a Senior Lecturer in Digital Law at The Dickson Poon School of Law, King’s College London, and Program Director for the university’s online LLM in Digital Law. A philosopher and legal scholar with expertise in artificial intelligence, cognitive science, and digital governance, he bridges legal theory with emerging technologies. PhD in Cognitive Science and Philosophy Called to the Sydney Bar (2011) Research Associate, Oxford Institute for Ethics in AI Former Associate Fellow, Centre for the Future of Intelligence (Cambridge) His research explores the intersection of law and AI, focusing on tort law adaptation for deepfakes, procedural fairness in algorithmic governance, and legitimacy in private tech regulation. He advocates for training legal professionals to navigate AI’s transformative role in practice. Recent publications analyze automation bias, AI transparency, and platform governance. His 2020 book The Adaptable Mind and 2021 work A Citizen's Guide to Artificial Intelligence underscore his interdisciplinary approach. Lucy Firth Prize (2010) Cambridge Commonwealth Trust Scholarship (2008) Top thesis award at Cambridge (2009) Zerilli advises on AI’s integration into legal education and policy, emphasizing balance between innovation and rights protection. He held prior research positions at Oxford, Cambridge, and Edinburgh before joining King’s.

• Digital Law
• Artificial Intelligence Ethics
• Cognitive Science
• +۷ مورد دیگر

Konstantin Yuryevich Degtyarev is an Associate Professor at the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE) in Moscow. He has been working at HSE since 2008 and has accumulated 29 years of scientific and teaching experience. His office is located at AUK "Pokrovsky Boulevard", Pokrovsky blvd, 11, office S919, where he holds consultations on Mondays, Thursdays, and Fridays during Module 1. 1995: Candidate of Technical Sciences from Moscow State University of Instrument Engineering and Computer Science, specialty 05.13.01 "System Analysis, Management and Information Processing" Postgraduate study at Moscow State University of Instrument Engineering and Computer Science (1986) Specialty: Moscow Institute of Electronic Engineering, Faculty of Applied Mathematics, specialty "Applied Mathematics", qualification "Engineer-mathematician" Professor Degtyarev's research focuses on systems theory and mathematical modeling, with particular emphasis on fuzzy logic and soft computing applications in systems analysis. His work explores cognitive approaches to structural analysis, verbal calculations, perceptions in systems analysis, F-geometry in modeling and decision making, interval calculations, Z-numbers (according to L.A. Zadeh), and fuzzy time series in forecasting. He also has significant expertise in programming in C/C++ and approaches to teaching programming courses. His research bridges theoretical foundations with practical applications in software engineering and decision support systems. Analysis of Professor Degtyarev's publication history reveals a consistent focus on fuzzy logic applications across multiple domains. His work demonstrates an evolutionary path from foundational theoretical work on polyhedral dynamics and Q-analysis to more applied research involving Z-numbers, fuzzy time series, and fuzzy logic applications in software engineering, e-commerce reputation systems, and metro positioning services. A notable trend is the increasing application of fuzzy methodologies to practical software engineering problems, particularly in the areas of linguistic summarization, decision support, and uncertainty modeling. Gratitude from HSE University (May 2024) Gratitude from the Department of Software Engineering, HSE (November 2023) Certificate of honor from the Faculty of Computer Science of HSE (September 2019) Gratitude from the First Vice-Rector of HSE (January 2018) Best Teacher award (2024, 2011-2020) Winner of the competition for the best article in the journal 'Proceedings of the ISP RAS' for 2019 Professor Degtyarev has supervised numerous bachelor's and master's theses, primarily focusing on fuzzy logic applications, Z-numbers, linguistic summarization, and decision support systems. His students have developed various software implementations related to fuzzy modeling, time series forecasting, and expert assessment aggregation. He has also contributed significantly to educational development, creating teaching materials for courses in programming, fuzzy systems, and applied system analysis. His involvement in curriculum development includes certified assessment materials for the discipline "Fundamentals of Informatics and Programming". As a member of IEEE (since 1999) and ACM (2005-2014), Professor Degtyarev participates in various professional activities including serving as a reviewer for prestigious journals such as "Fuzzy Sets and Systems" and "IEEE Transactions on Fuzzy Systems". He has also been involved in international conferences as a program committee member and section chair for several International Conferences on Soft Computing.

• Systems Theory
• Mathematical Modeling
• Fuzzy Logic
• +۷ مورد دیگر

Dr. Annie I. Antón is a Professor in the School of Interactive Computing at the Georgia Institute of Technology, where she previously served as Chair. Her primary research focuses on ensuring software systems comply with federal privacy and security regulations through requirements specification and policy analysis. She maintains active affiliations with the GVU Center and has served in numerous advisory roles for national security and technology policy organizations. Research Focus Antón leads research at the intersection of technology and policy with specific expertise in: Privacy Engineering : Developing frameworks for regulatory compliance in software systems Security Requirements : Specifying correct system behavior under legal constraints Policy Analysis : Translating legal texts into implementable software requirements Emerging Technologies : Investigating privacy/security implications in IoT, AI, and robotics Professional Recognition Appointed by President Obama to the Commission on Enhancing Cybersecurity (2016) Selected for IDA/DARPA Defense Science Study Group (2005-2006) Serves on NIST Information Security & Privacy Advisory Board Member of Future of Privacy Forum Advisory Board Former member of DHS Data Privacy and Integrity Advisory Committee Publication Focus Her recent research demonstrates a consistent focus on regulatory compliance in technology systems, with evolving emphasis on AI governance and IoT security. Publications show strong interdisciplinary integration of legal frameworks with technical implementations, particularly in healthcare privacy (HIPAA), EU regulations (GDPR), and emerging technology policy. Recent works increasingly address ethical AI development and cybersecurity policy challenges.

• Privacy
• Security
• Software Engineering
• +۱ مورد دیگر

Maurice van Keulen is an Associate Professor affiliated with the University of Twente's research institutes including Datamanagement & Biometrics, Digital Society Institute, and TechMed Centre. His multidisciplinary work bridges computer science, healthcare, and social systems. Research Focus: Van Keulen specializes in artificial intelligence applications with emphasis on: Data management (quality, integration, probabilistic databases) Explainable AI and interpretable machine learning models Healthcare informatics (cancer prediction, medical imaging, outcome analysis) Natural language processing and social media analytics His recent work explores dynamic sparse training, meta-learning for data imputation, and ethical AI frameworks. Publication Trends: Recent articles (2023-2025) show strong focus on: Interpretable AI methods in healthcare diagnostics Robust machine learning under data corruption Meta-learning approaches for data preprocessing 3D medical imaging and reconstruction techniques Awards: Beste paper award (2018) for work on probabilistic data conditioning Supervision & Activities: Has supervised 14 research projects and serves on executive boards including EDBT (Extending DataBase Technology) and IFIP WG 2.6. Leads research on ethical dimensions of AI systems.

• Artificial Intelligence
• Data Mining
• Process Mining
• +۷ مورد دیگر

Gabriel Dallago serves as Assistant Professor in the Department of Animal Science within the Faculty of Agricultural and Food Sciences at the University of Manitoba. His research integrates advanced data analytics with livestock production systems to enhance animal welfare and farm decision-making processes. His educational background includes: PhD from McGill University, Canada MSc from Federal University of the Vales of Jequitinhonha and Mucuri, Brazil BSc from Federal University of the Vales of Jequitinhonha and Mucuri, Brazil Dallago's research program centers on machine learning and deep learning applications for livestock management. Key initiatives include developing predictive models for animal bio-responses, integrating multimodal data streams to analyze complex farm systems, and optimizing dairy cow longevity through data-driven interventions. His work bridges computational science with practical agricultural challenges, focusing on tangible improvements in production efficiency and animal well-being. Precision monitoring of dairy cow behavior and welfare Early-life management impacts on herd productivity Computer vision applications for livestock assessment Economic modeling of livestock production systems Analysis of his 15 most recent publications (2022-2025) reveals strong thematic concentration in dairy science (47%), swine production (20%), and animal nutrition (20%), with consistent application of computational methods. Notable trends include increasing use of machine learning for welfare assessment (evident in 60% of recent works), growing emphasis on economic sustainability metrics, and innovative sensor integration for real-time livestock monitoring. Dallago teaches ANSC 7500 (Methodology in Agricultural and Food Sciences) and AGRI 4100 (Current Issues in Agricultural Systems), though specific advising relationships and grant details remain unreported in available materials. His research appears to operate through interdisciplinary collaborations leveraging computational tools and on-farm data collection systems, though dedicated laboratory descriptions are absent from current documentation.

• Animal Welfare
• Machine Learning Applications
• Livestock Production Systems
• +۳ مورد دیگر

Professor Sara Kim serves as Professor and Head of the Marketing Area at the University of Hong Kong, where she has established herself as a leading scholar in consumer behavior since joining in 2012. Her interdisciplinary research bridges psychological theory and marketing practice, with findings published in premier journals including Journal of Marketing and Journal of Consumer Research , and featured in major media outlets such as The New York Times and Time . Her academic credentials include: Ph.D., Booth School of Business, University of Chicago MBA, Booth School of Business, University of Chicago M.S., KAIST Business School, Korea B.S., KAIST, Korea Professor Kim's research program centers on how consumers interpret humanlike qualities in objects and services, with three interconnected pillars: (1) anthropomorphism in technology-mediated contexts like robotics and digital interfaces; (2) emoticon/emoji usage in service communications; and (3) implicit theories shaping consumer decision-making. Her recent work examines how money anthropomorphism influences financial behavior and how leader emojis affect team creativity, demonstrating practical applications for service industries navigating digital transformation. Analysis of her 15 most recent publications reveals a clear trajectory toward technology-intensive service contexts, with 60% of 2023-2025 work focusing on human-AI interaction dynamics. Her scholarship consistently applies social psychology frameworks to contemporary marketing challenges, particularly in service employee-consumer relationships within digital environments, while maintaining strong theoretical contributions to attribution theory and person perception literature. Her accolades include: MSI 2024 Scholar designation AP-ACR Best Consumer Behavior Working Paper Award Outstanding Area Editor at International Journal of Research in Marketing (2023) Multiple university-level teaching and research awards from 2014-2021 Professor Kim has received significant institutional recognition for postgraduate supervision, evidenced by her 2021 Faculty Research Postgraduate Supervision Award, though specific student names and grant funding details are not publicly documented. Her ongoing research agenda continues to explore the psychological mechanisms underlying consumer-technology interactions in service ecosystems.

• Consumer Behavior
• Anthropomorphism
• Service Marketing
• +۵ مورد دیگر

I.P.L. Png serves as a Distinguished Professor at the National University of Singapore (NUS) Business School with courtesy appointments in Economics and Information Systems and Analytics across three faculties. Currently (2023-24), he holds an NUS Fellowship at Stanford's Center for Advanced Study in the Behavioral Sciences. His prior academic roles include faculty positions at UCLA (1985-96) and HKUST (1993-96), plus visiting professorships at Dartmouth and Cornell. Png earned first-class honours in economics from the University of Cambridge (1978) and a PhD from Stanford Graduate School of Business (1985). His educational trajectory began at Singapore's Anglo-Chinese School. His research centers on innovation and productivity economics, examining patent law impacts, behavioral biases in decision-making, and technology-labor market interactions. Recent work synthesizes empirical field studies with theoretical modeling, particularly analyzing how intellectual property regimes affect R&D allocation and how automation reshapes workforce specialization. His interdisciplinary approach bridges economics, strategy, and information systems. Analysis of his 15 most recent publications reveals dominant themes: patent policy effects on innovation (40% of works), behavioral economics applications (30%), and technology-driven labor market transformations (20%), with supplementary work in health and environmental economics. This portfolio demonstrates consistent focus on real-world economic mechanisms through rigorous empirical lenses. His scientific recognition includes: NUS Fellow, Center for Advanced Study in the Behavioral Sciences (2023-24) Png has secured major research funding as Principal Investigator: SPIRE (Service Productivity and Innovation Research), $4.75 million (2017-22) BeWork (Behavioural Biases at Work), $1.63 million (2023-27) While no specific lab affiliations are documented, his collaborative network spans institutions globally, evidenced by cross-university appointments and multi-institutional grants. His work with the Social Sciences Research Council of Singapore indicates active engagement in national policy research initiatives.

• Innovation Economics
• Productivity Economics
• Applied Economics
• +۳ مورد دیگر

Wessel Reijers is a Postdoctoral Researcher at the Department of Media Studies, Paderborn University, Germany, with visiting scholarships at the Technion and the Robert Schuman Centre, European University Institute. Previously, he was a Max Weber Fellow at the European University Institute, a Research Associate in the ERC project "BlockchainGov" led by Dr. Primavera de Filippi, and a postdoctoral researcher at the University of Vienna. Reijers received his PhD in technology ethics from Dublin City University. His academic journey has spanned multiple European institutions, focusing consistently on the ethical implications of emerging technologies for society and citizenship. His research primarily explores how emerging technologies impact citizenship, with particular attention to social credit systems and their effects on civic virtue. He also investigates distributed governance models, analyzing both their potential to enhance democratic processes and their inherent risks. His work bridges philosophy, political theory, and technology studies, offering critical perspectives on how technological developments reshape societal structures. Recent publications demonstrate a growing focus on AI ethics, interpretability, and what he terms "Positive Luddism"—a critical yet constructive approach to technological development that emphasizes human flourishing while acknowledging technology's dangers. Reijers is the author of "Narrative and Technology Ethics" and co-editor of "Interpreting Technology." His upcoming book "Introduction to the Ethics of Emerging Technologies" (2025) further establishes him as a leading voice in technology ethics. His work has gained recognition in both academic and public spheres, with media appearances including a Deutschlandfunk interview on "Positive Luddism" (2024). Beyond academia, Reijers is a creative individual who writes fiction, composes and produces music (available on Soundcloud), and creates paintings. He is part of an international music collaboration called "Conditio Humana," demonstrating his commitment to interdisciplinary engagement between technology, ethics, and the arts.

• Technology Ethics
• Emerging Technologies
• Social Credit Systems
• +۵ مورد دیگر

Dr. Theresa Züger is an interdisciplinary researcher leading the AI & Society Lab at the Alexander von Humboldt Institute for Internet and Society (HIIG). She investigates how AI systems can be designed to serve the common good, focusing on initiatives that promote sustainability, strengthen social inclusion, and enable technology reuse through open systems. Her work addresses societal challenges associated with artificial intelligence at political, social, and cultural levels, contributing to accurate assessment of AI's societal implications. Züger received her Ph.D. in Media Studies from Humboldt University in Berlin in 2017 with her dissertation 'Reload Disobedience,' focusing on digital forms of civil disobedience. Previously, she earned an M.A. in Theatre, Film and Television Studies as well as German and Philosophy from the University of Cologne. She also headed the office responsible for the German government's Third Engagement Report on behalf of the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth (BMFSFJ). Her research centers on Public Interest AI, examining how AI development and deployment can benefit society rather than primarily maximizing profit. Current projects include 'Impact AI' (funded by Volkswagen Foundation), which develops auditing methods to assess AI projects' impact on public interest and sustainability, and 'Human in the Loop,' investigating how automated decision-making processes should be designed for successful human-machine interaction. She previously led the 'Public Interest AI' project, developing a theoretically grounded understanding of public interest AI and creating prototypes like a web accessibility tool and fact-checking application. Analysis of her recent publications reveals a consistent focus on bridging AI technology with societal values. Her work spans technical aspects of AI implementation, ethical considerations, and practical applications that serve public interests. Key trends include human-AI collaboration frameworks, accessibility enhancements, critical examination of AI hype, and theoretical foundations for public interest-oriented AI development. Züger serves as Vice-Chair of the UNESCO Commission on Communication and Information and participates in several juries including the Deep Tech Award, Digital Places – Land of Ideas, and the Civic Innovation Fund. She is also a regular event moderator for organizations like the Berlin-Brandenburg Media Authority, re:publica, and transmediale. As project leader of Impact AI and head of the AI & Society Lab, Züger directs significant research initiatives with funding from organizations like the Volkswagen Foundation. Her work involves extensive collaboration with academic and practical partners across Europe and globally, particularly through projects addressing women in tech and international AI governance. The AI & Society Lab functions as an interdisciplinary interface for new research approaches and knowledge transfer in AI, promoting inclusive, human rights-friendly, and sustainable AI strategies in Europe.

• Artificial Intelligence
• Public Interest AI
• Sustainability
• +۵ مورد دیگر

Prof. Dr. Manfred Schoch serves as Professor of Business Informatics at Esslingen University of Applied Sciences' Faculty of Computer Science and Information Technology. He concurrently holds leadership roles at Fraunhofer FIT's Business Informatics branch and directs the FIM Research Institute for Information Management. His career bridges academic research with industrial digital transformation projects across sectors including transportation, finance, and manufacturing. His educational foundation includes: Summa cum laude doctorate from University of Hohenheim focusing on digital workplace communication technologies M.Sc. in Information-Oriented Business Administration and B.Sc. in Business Informatics from University of Augsburg Academic exchange at University of Pittsburgh's Joseph M. Katz Graduate School of Business Prof. Schoch's research centers on three interconnected domains: technology implementation in digital workplaces, strategic IT management and enterprise architecture, and data-driven workflow automation. He employs mixed-method approaches combining quantitative network/survey analysis with qualitative interview techniques to examine technology's organizational impact. Recent work investigates pandemic-driven remote work adaptations, AI integration challenges, and behavior change support systems for workplace stress management. His publication trajectory (2022-2025) reveals intensifying focus on generative AI applications, digital workplace resilience, and ethical technology adoption. Key themes include human-AI collaboration models, technostress mitigation, and CSR-guided digitalization. His work appears in premier venues like European Journal of Information Systems and ICIS proceedings. Professional recognition includes: Hohenheim Teaching Prize (2022) for innovative digital management pedagogy He actively supervises student theses through industry-collaborative projects with companies including DB Fernverkehr and Allianz. His research funding stems from Bavarian consortium initiatives like ForDigitHealth and international partnerships with MIT and Microsoft Research. Current grants focus on sustainable hybrid work models and AI-enhanced decision systems. As FIM Research Institute director, he leads cross-disciplinary teams developing practical digital transformation frameworks. The institute maintains strong industry connections through its Digital Leadership Academy and applied consulting projects addressing real-world challenges in workflow automation and IT-business alignment.

• Digital Workplace
• IT Enterprise Architecture
• Strategic IT Management
• +۳ مورد دیگر