Luis Vives De Prada serves as Associate Professor of General Management and Strategy at ESADE Business School, concurrently holding leadership positions as Vice-Dean of MBA Programs and Director of Corporate Relations and Engagement. He maintains active research affiliations with the ESADE Entrepreneurship Institute (EEI) and GRIE - Research Group on Entrepreneurial Initiative. Academic Credentials: Doctor in Business Administration, IESE Business School Bachelor in Business Administration, University of Navarra Postdoctoral Fellow, MIT Sloan School of Management Visiting Scholar, Harvard University Diploma in Piano and Music Theory Research Focus: Professor Vives specializes in strategic management with emphasis on digital transformation and business model innovation . His recent work analyzes generative AI's impact on corporate leadership (2024 publications), long-term strategic thinking in volatile markets (2023), and innovation frameworks for SMEs. He bridges theoretical research with practical applications through case studies of multinational corporations, exploring how creative industries and platform economies reshape traditional business models. Publication Trends: Analysis of his 15 most recent works reveals consistent focus on strategic adaptation in digital environments. From 2018-2024, his research evolved from foundational digital transformation concepts (SME innovation, big data adoption) toward cutting-edge AI leadership frameworks. Notably, 60% of recent publications address generative technologies' strategic implications, while maintaining strong connections to international business contexts through collaborations with European and Asian scholars. Professional Engagement: Professor Vives leverages extensive consulting experience with multinational corporations across seven industry sectors to inform his academic work. His corporate partnerships with organizations like Bayer, Samsung, and IKEA provide real-time strategic challenges that fuel both classroom discussions and research agendas. This practitioner perspective enables him to translate complex strategic concepts into actionable frameworks, particularly regarding digital disruption in traditional industries. Research Ecosystem: Through dual appointments at ESADE's Entrepreneurship Institute and GRIE research group, he contributes to studies on venture creation in digital economies and strategic innovation in established firms. These affiliations facilitate collaborations with visiting scholars from top global institutions and provide access to longitudinal datasets on multinational corporate strategies.
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نمایش ۴۹۶-۵۰۷ از ۵۰۷ استاد راهنما
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Hamed Alaviمشاهده پروفایل
استادیار
Hamed Alavi is a tenured Assistant Professor at the University of Amsterdam and founding member of the Digital Interaction Lab. His work bridges computer science, architecture, and urban design to develop inclusive intelligent spaces that reflect human values across architectural and urban dimensions. His educational background includes a PhD in Computer Science from the Swiss Federal Institute of Technology (EPFL) and post-doctoral research at University College London (UCL). Prior to academia, he led an educational technology start-up for eight years with global impact. Alavi's research focuses on Human-Building Interaction (HBI), exploring how intelligent environments can co-create inclusive spaces through biophilic design, physiological sensing, and human-centered methodologies. His work emphasizes socio-technical integration in smart buildings and cities, addressing neurodiversity, environmental comfort, and ethical data practices. His recent publications reveal strong trends in multisensory interaction design, urban computing, and inclusive technology development. Key themes include physiological-environmental sensing integration, AI ethics in urban contexts, and human experience frameworks for smart buildings, with growing emphasis on neurodiverse populations and biophilic elements. Scientific recognition includes: Inclusive City-Making Grant (PI, €3.8M, NWO) Best Paper Award at CHI 2025 As Principal Investigator for the NWO-funded Inclusive City-Making project, Alavi leads large-scale interdisciplinary research translating academic insights into urban solutions. His entrepreneurial background informs practical technology deployment strategies and industry-academia collaboration models. The Digital Interaction Lab, which he co-founded, serves as a research hub for intelligent environment design, bringing together computer scientists, architects, and urban planners to prototype responsive built environments through living lab methodologies and wild deployment studies.
Gerhard Staudeمشاهده پروفایل
استادیار
Gerhard Staude serves as an Assistant Professor and Academic Director at the University of the German Federal Armed Forces Munich, affiliated with the Chair of Information Processing under Prof. Knopp. His academic base is located in Building 35/300, Room 035/2351. His research spans Computer Science , Information Systems , and Engineering Informatics , focusing on computational methodologies and data processing frameworks within technical domains. The integration of theoretical models with practical engineering applications defines his scholarly approach. Dr. Staude maintains active academic engagement through institutional leadership as Academic Director, though specific advising roles or grant activities are not documented in available sources.
Zhou Yangمشاهده پروفایل
استادیار
Zhou Yang is an Assistant Professor at the University of Alberta and Fellow at the Alberta Machine Intelligence Institute (Amii), with research focusing on the intersection of software engineering and artificial intelligence. His academic journey includes a Ph.D. from Singapore Management University, an M.Sc. in Software System Engineering from University College London, and undergraduate studies at Yangzhou University. His research interests span Software Engineering, Artificial Intelligence, AI for Software Engineering (AI4SE), Software Engineering for AI (SE4AI), Large Language Models, and Cybersecurity. Yang's work explores how human and AI collaboration can improve code writing, how AI impacts open-source communities, and how developers build software in emerging environments like VR/AR. His recent publications demonstrate strong trends in code language models, with significant contributions to ASE, ICSE, ISSTA, and top journals like TOSEM and TSE. His research addresses critical challenges including token efficiency in code generation, user perception of AI coding assistants, privacy preservation in code models, and fairness in AI systems. 2024 IEEE Computer Society Best Paper Award (1 out of 183 submissions) ACM Distinguished Paper Award from ISSTA 2024 Distinguished Reviewer Award from Internetware 2024 SMU Research Staff Excellence Award (1 of 4 university-wide) SMU Presidential Fellowship Award SMU Dean's List Award 1st Place in ACM Student Research Competition at ICSE 2024 Yang actively mentors graduate students with regular one-on-one meetings, constructive feedback, and support for top-venue publications. He provides full funding through teaching assistantships and research grants, including travel support for conferences. His lab focuses on responsible research conduct and societal implications of AI work. Though early-career, he actively builds professional networks for students through collaborations and supports diverse career paths in academia and industry. He leads research in the Alberta Machine Intelligence Institute, focusing on practical applications where software engineering principles enhance AI systems and where AI techniques solve real-world software engineering challenges.
Christoph Treude is an Associate Professor of Computer Science at Singapore Management University. His academic journey includes senior lecturer positions at the University of Melbourne and the University of Adelaide, and postdoctoral research at McGill University, the University of São Paulo, and the Federal University of Rio Grande do Norte. Treude's research focuses on improving software quality and developer efficiency through better access to relevant information. His methodology combines empirical studies with tool development that considers natural language artifacts in software repositories. His work spans several key areas of software engineering: Empirical studies of developer behavior and practices Integration of large language models in software development Human-AI collaboration frameworks Software documentation quality and maintenance Reproducibility in scientific software Security practices in code reviews His recent publications demonstrate a strong focus on the intersection of artificial intelligence and software engineering, examining how AI technologies can enhance developer productivity while maintaining code quality and security. His research often involves large-scale empirical studies across various software ecosystems and developer communities. Treude has received significant recognition for his contributions: ARC Discovery Early Career Research Award (2018-2020) Four best paper awards, including two ACM SIGSOFT Distinguished Paper Awards He serves on the Editorial Boards of IEEE Transactions on Software Engineering and Springer's Empirical Software Engineering journal, and holds the role of Open Science Editor for Elsevier's Journal of Systems and Software. Treude has chaired major conferences including ICSME 2020, ICPC 2023, and TechDebt 2023, and regularly participates in software engineering conference program committees. His research has been funded by industry leaders including Google, Facebook, and DST, and he has authored over 150 scientific articles with more than 250 co-authors.
Dr. Sallam Abualhaija serves as a Researcher at the Interdisciplinary Centre for Security, Reliability, and Trust (SnT) at the University of Luxembourg, where she applies cutting-edge AI technologies to software engineering challenges with emphasis on requirements engineering and regulatory compliance. Her work bridges academic research and industry applications through extensive collaboration with corporate partners. She earned her PhD in Computer Science from Hamburg University of Technology (Germany) in 2016, establishing her expertise in computational approaches to software requirements. Her research centers on leveraging natural language processing and large language models for regulatory compliance, particularly GDPR implementation in software systems. Key focus areas include automated compliance checking of privacy policies, data processing agreements, and financial regulations through techniques like question-answering systems and ambiguity resolution. This work directly addresses the critical need for trustworthy AI systems that adhere to legal frameworks while improving software development efficiency. Analysis of her recent publications reveals a strong trend toward practical tool development (e.g., CompAi) and multi-solution studies for GDPR compliance across mobile applications, financial services, and general software systems. Her research consistently integrates industry collaboration, with growing emphasis on LLM-driven approaches since 2023. Dr. Abualhaija actively contributes to the academic community through program committee roles at ASE, ICSE, and RE conferences, and as co-organizer of workshops including MO2RE (Multi-Disciplinary Requirements Engineering) and FinanSE. She has chaired tutorials on replication in NLP for requirements engineering and AI applications in regulatory compliance, demonstrating commitment to knowledge transfer and community building. As a core member of SnT, she contributes to Luxembourg's leading research hub for security, reliability, and trust in ICT systems. Her work aligns with SnT's mission through projects that develop verifiable, privacy-preserving technologies with real-world regulatory impact, particularly in European data protection contexts.
Simone Scalabrinoمشاهده پروفایل
استادیار
Simone Scalabrino is an Assistant Professor at the University of Molise, Italy, where he is part of the STAKE lab. He also serves as CSO at Datasound. His academic career includes teaching courses such as Automated Software Delivery and Object-Oriented Programming at the University of Molise. Dr. Scalabrino received his Ph.D. from the University of Molise in 2019 with a thesis entitled "Automatically Assessing and Improving Code Readability and Understandability," supervised by Prof. Rocco Oliveto. He earned his Master's Degree in Computer Science from the University of Salerno in 2015 and his Bachelor's Degree in Computer Science from the University of Molise in 2013. His research interests focus on Software Quality, Software Testing, Software Security, and Empirical Software Engineering . Dr. Scalabrino's work spans multiple areas including code readability assessment, software testing methodologies, Docker container analysis, game quality assessment, and voice user interface testing. His research often combines empirical methods with machine learning techniques to address practical software engineering challenges. Analysis of his recent publications reveals a strong focus on improving software quality through various approaches. His work spans code readability assessment, Docker container analysis, game quality testing, and voice user interface evaluation. There's a clear trend toward applying machine learning techniques to traditional software engineering problems, particularly in the areas of code understanding, defect prediction, and quality assessment. His research often involves large-scale empirical studies with real-world data from open source projects and commercial applications. Scientific Awards Distinguished Reviewer Award @ FSE 2025 Distinguished Reviewer for TSE (2023) Best Reviewer Award for JSS (2022) ACM Distinguished Paper Award @ MSR 2019 ACM Distinguished Paper Award @ ASE 2017 ACM Distinguished Paper Award @ ICPC 2016 Dr. Scalabrino has been actively involved in mentoring students through research projects, though specific student names are not listed in the provided information. He has served on program committees for numerous prestigious conferences including ASE, ICSE, ICPC, and FSE. His service extends to reviewing for top-tier journals such as Transactions on Software Engineering and Empirical Software Engineering. He leads or contributes to several research projects including DevProDev, which focuses on developer-centered recommendation systems, and ATTICUS, a tele-monitoring system for ambient-assisted living. Dr. Scalabrino has also developed multiple research tools such as Code Readability Predictor, TIRESIAS, OCELOT, CLAP, and ACRyL to address various software engineering challenges.
Donghui Wangمشاهده پروفایل
استادیار
Donghui Wang is an Assistant Professor in the Department of Sociology at the University of Macau. Her academic work centers on demographic research with a focus on China and the United States, employing spatial, longitudinal, and small-area estimation methodologies to address theoretical and policy-relevant questions in population studies. Ph.D. in Demography and Rural Sociology, The Pennsylvania State University (2018) M.S. in Applied Economics, University of Minnesota, Twin Cities (2013) B.S. in Economics, Lanzhou University (2011) Dr. Wang's research spans multiple interconnected domains within demography and sociology. Her substantive interests focus on fertility, aging, family dynamics, international development, and cultural influences on demographic behavior. Methodologically, she specializes in spatial analysis techniques and advanced survey methodology. Her work demonstrates particular expertise in analyzing county-level demographic patterns in China, with emphasis on spatial heterogeneity and cultural influences on fertility decisions. She also investigates cross-national perceptions between China and the US, rural youth development, and international migration patterns. Her recent publications reveal a strong focus on spatial demographic analysis, particularly in the Chinese context. She has made significant contributions to understanding county-level fertility patterns in China, examining both Han and ethnic minority populations. Her methodological innovations include trend analysis with pooled survey data and geographically weighted regression approaches. Her work consistently bridges theoretical demographic concepts with practical policy implications, particularly regarding population aging and fertility trends in East Asia. Dr. Wang maintains an active research agenda with publications in top-tier journals including Demographic Research, Journal of Contemporary China, Population, Space and Place, Rural Sociology, and Sociological Methodology. Her work demonstrates both methodological sophistication and substantive contributions to understanding demographic processes in comparative contexts, particularly between China and the United States. Office: Rm.3007, Humanities and Social Sciences Building (E21), University of Macau Consultation Hours: By appointment Tel: +853 8822 9047
- Demography
- Culture
- Social Stratification
- +۷ مورد دیگر
Michael Mayleمشاهده پروفایل
استاد پژوهش
Michael Mayle is a Research Professor for Applied Computational Physics at Nuremberg University of Applied Sciences. He serves as a member of the Doctoral Center for Physical and Biomedical Engineering (CPaB) and holds a deputy position on the CPaB doctoral committee. His office is located at space KA.434, with contact details including phone +49 (0)911 5880-1309 and email michael.mayle@th-nuernberg.de. His research centers on Computational Physics with specialized focus in Sensor Technologies , Ultracold Quantum Gases , and Acoustics . He leads the Computational Physics for Sensor Technologies research group, developing advanced computational models for physical systems with direct applications in sensor design and analysis. His work bridges theoretical physics with practical engineering solutions. Analysis of his publication trajectory (2006-2025) reveals a distinct evolution from fundamental quantum research to applied sensor technology. Early work (2006-2013) established expertise in ultracold molecules and Rydberg atom physics, while recent publications (2019-2025) demonstrate a strategic pivot toward industrial applications including piezoelectric material analysis, ultrasonic flow metering, and water consumption pattern recognition. Professor Mayle actively contributes to doctoral education through the CPaB framework and teaches core courses including Simulation of Physical Systems (Continuum Mechanics) for M-AMP, Physics (Oscillations and Waves) for B-MED, and Building Physics for B-EGT/B-BI programs. His research group maintains strong industry connections through sensor technology development and applied computational modeling projects.
Gabriele Gühring serves as Professor at Esslingen University of Applied Sciences with dual appointments in the Faculty of Basic Sciences (since 2008) and Faculty of Computer Science and Information Technology (since 2021). She currently holds the executive position of Vice President for Research and Transfer (since September 2022), concurrently directing the Department of Research and Transfer while serving on the Science Commission and Honours Committee. Her academic foundation includes: Mathematics and Physics studies at University of Tübingen (1991-1996) Doctoral research on nonautonomous differential equations (1997-1999) Part-time Master's in Mathematical Finance at University of Oxford (2002-2004) Prof. Gühring's research centers on practical AI applications , specializing in anomaly detection systems for industrial infrastructure and multimodal learning for technical documentation. Her work bridges theoretical mathematics with real-world implementations in renewable energy, urban mobility, and medical diagnostics, demonstrating consistent evolution from pure mathematics to cutting-edge machine learning. Analysis of her 14 publications (1999-2023) reveals a strategic pivot from theoretical differential equations to industrial AI solutions. Recent work (2020-2023) focuses on anomaly detection in energy systems (power plants, vehicle fleets), multimodal neural networks for product analysis, and mobility data anonymization , with methodologies spanning spiking neural networks, graph-based approaches, and Bayesian deep learning. While no scientific awards are documented, her leadership in the BMBF-funded Anomob project demonstrates active grant acquisition in data privacy. Administrative responsibilities likely encompass significant mentorship, though no formal advisees are listed in the provided materials. Her research operates through Esslingen's Department of Research and Transfer, fostering cross-disciplinary collaborations between computer science, engineering faculties, and industrial partners in energy, transportation, and healthcare sectors.
Dr. Gregor Wiedemann serves as a Senior Researcher in Computational Social Science at the Leibniz Institute for Media Research (Hans Bredow Institute) since September 2020, co-heading the Media Research Methods Lab (MRML) with Sascha Hölig. His work bridges computer science and social sciences through methodological innovation in empirical media research. Wiedemann holds a doctorate in computer science from Leipzig University (2016), where his dissertation focused on automating discourse analysis using text mining and machine learning. His educational background combines political science and computer science studies at Leipzig University and the University of Miami, followed by postdoctoral work in Language Technology at the University of Hamburg under Prof. Chris Biemann. His research centers on natural language processing and text mining applications for social and media analysis, with significant contributions in hate speech detection, argument mining, and cross-platform misinformation tracking. Recent work demonstrates a strategic shift toward building research infrastructures for sensitive data handling, including the Community Data Trust model for extremism research and the Social Media Observatory open-science platform. His methodology development specifically targets unsupervised information extraction from large document corpora to support investigative journalism and social science inquiry. Wiedemann's publication trends reveal deepening specialization in computational infrastructure development, with 7 of his 11 most recent works (2024-2025) focusing on data trust frameworks, cross-platform methodologies, and AI-driven analysis systems. His projects consistently intersect computational linguistics with pressing social issues including election integrity, climate discourse, and child safety in digital spaces. He has secured major funding through the German Research Foundation (DFG) for the FAME project on argument mining and evaluation, and leads collaborative initiatives including NOTORIOUS (mis- and disinformation tracking) and ComAI (communicative AI impact studies). His work with state media authorities on family influencing content demonstrates applied policy relevance. As co-director of the Media Research Methods Lab, Wiedemann oversees a dynamic team developing cutting-edge computational approaches for media analysis. The lab functions as an interdisciplinary hub connecting computer scientists with social researchers, with current projects spanning TikTok political campaigning analysis, right-wing extremism data infrastructure, and ethical AI applications in public discourse monitoring.
Christoph Binder is a Professor of Management Accounting and Controlling at ESB Business School, Reutlingen University. He serves as Head of Career Center & Alumni, Programme Director for MA European Management Studies, and Liaison Officer for the German National Academic Foundation. Previously, he served as Dean of ESB Business School from 2019-2024. German-French dual diploma (IPBS) from ESB Reutlingen (1996-2000) Semester at University of Texas at Austin (1997) Management consultant at McKinsey & Company (2000-2008) Doctorate in Management Accounting & Control at European Business School (2004-2006) Professor at Reutlingen University since 2008 Binder's research focuses on management accounting systems with particular emphasis on sustainability controlling, carbon accounting, and geopolitical risk management. His work bridges traditional accounting practices with emerging challenges in risk assessment and sustainable business operations. He has developed frameworks for structured risk identification in SMEs and value-oriented performance measurement systems. His publication record shows consistent contributions to controlling literature since 2014, with increasing focus on geopolitical risks (2023-2025) and sustainability accounting. The articles demonstrate evolution from foundational controlling concepts toward contemporary challenges in risk management and sustainable business practices, reflecting growing industry relevance of these topics. Member of Board of Trustees, International Controller Association Member of Advisory Board, Dieter von Holtzbrinck Stiftung Binder maintains active industry engagement through advisory roles while leading academic programs. His consulting background informs practical applications of controlling frameworks, particularly in energy, logistics, and telecommunications sectors. Current initiatives focus on integrating sustainability metrics into traditional controlling systems and developing risk management tools for volatile geopolitical environments.