جست‌وجوی استاد و پژوهشگر

Christina Hertelمشاهده پروفایل

استادیار

• Entrepreneurship
• Sustainability
• Collective Action
• +۳ مورد دیگر

Christina Hertel is an Assistant Professor of Entrepreneurship and Director of the Geneva Responsible Entrepreneurship Center (GREC) at the University of Geneva (UNIGE). She holds a PhD from the Technical University of Munich (TUM School of Management) and completed a postdoctoral fellowship at the École Polytechnique Fédérale de Lausanne (EPFL). Her research focuses on the intersection of entrepreneurship, sustainability, and collective action, particularly exploring community-based approaches for sustainable local development and impact measurement for responsible businesses. Christina leads a Swiss National Science Foundation-funded research project on community entrepreneurship and civic wealth creation. Her work bridges academic research with practical applications, collaborating with startups, incubators, and policymakers to design strategies that enhance economic, social, and environmental impact. She aims to establish Geneva and UNIGE as global hubs for responsible entrepreneurship. In teaching, she emphasizes experiential learning, designing courses that empower students to tackle real-world challenges. She organizes GREC events to foster student engagement in responsible entrepreneurship. Her research has been published in top journals like the Journal of Business Venturing and Academy of Management Discoveries, and she actively presents at international conferences such as the Academy of Management Annual Meeting and Social Entrepreneurship Conference. Key initiatives include developing frameworks for community resourcefulness in new ventures and advancing standards for responsible entrepreneurship. Her contributions span academic publications, policy engagement, and educational programs, all aligned with fostering sustainable and impactful business practices.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

Rute C. Sofiaمشاهده پروفایل

دانشیار

• Internet of Things
• Edge computing
• Network architectures and protocols
• +۱۰ مورد دیگر

Rute C. Sofia is Industrial IoT Head at fortiss – the Bavarian research institute for software-intensive systems – and Invited Associate Professor at Universidade Lusófona de Humanidades e Tecnologias (ULHT). She is also an Associate Researcher at ISTAR, Instituto Universitário de Lisboa (Iscte-IUL). Previously she co-founded and served as Scientific Director of COPELABS/ULHT (2013-2017) and was Senior Researcher there from 2010-2019. Education Ph.D. in Computer Science, University of Lisbon, 2004 Visiting Scholar, Northwestern University (ICAIR) & University of Pennsylvania, 2000–2003 M.Sc. in Computer Science, University of Lisbon, 1999 B.Eng. in Computer Engineering, University of Coimbra, 1995 Research Interests Her work spans network architectures and protocols , Internet of Things (IoT) , edge and in-network computing , deterministic wired/wireless industrial networks , and network mining . A current focus is on resilient, AI-driven orchestration across the IoT–Edge–Cloud continuum for 6G and Industrial IoT systems. Scientific Awards & Recognition ACM Europe Councilor (2021–2025) ACM Senior Member & IEEE Senior Member IEEE ComSoc N2Women Awards co-chair (2020–2021) Highly Cited Paper Award, Applied Sciences MDPI (2023) Labs, Teams & Grants She currently leads the Industrial IoT competence field at fortiss, coordinating projects such as SemComIIoT (semantic communications for IIoT) and the open-source ns-3 DetNetWiFi framework. Earlier she co-founded the Portuguese startup Senception Lda (2013-2019) and the research unit COPELABS , driving EU H2020 initiatives like UMOBILE and shaping national strategies for cyber-physical systems.

• Artificial Intelligence
• Healthcare Informatics
• Data Science
• +۵ مورد دیگر

Luís B. Elvas is an Assistant Professor at ISCTE-University Institute of Lisbon's Department of Social and Business Sciences (SINTRA) and a Research Assistant at ISTAR-Iscte Research Center. He holds qualifications including a Technical Specialization in TensorFlow for AI (Coursera, 2021) and certifications in IoT/Blockchain from ISCTE and cybersecurity from Palo Alto Networks. His research spans artificial intelligence, healthcare informatics, smart cities, and blockchain, with applied work in medical imaging, data sharing, and urban analytics. Research interests include: Healthcare AI : Developing deep learning models for cardiac diagnostics, medical imaging analysis, and blockchain-based health data systems Smart Cities : Implementing IoT solutions for urban mobility optimization, disaster management, and sustainable transportation Data Science : Creating predictive analytics frameworks for clinical decision support and urban planning His publications demonstrate a strong focus on AI-driven healthcare solutions (67% of recent works) and smart city technologies (33%), with emerging interests in blockchain and NLP. Research consistently targets real-world applications in clinical settings and urban environments. Awards: Award for best internship, Order of Engineers (2022) Distinction for best internship, Order of Engineers (2021) He leads/contributes to multiple EU research consortia including AMR-EDUCare (antimicrobial resistance education), NEEM (e-health in Nepal), and Blockchain.PT. Coordinates the IEEE Computational Intelligence Society Student Branch Chapter at ISCTE and developed the ManagiDiTH master's program in digital health transformation.

• Migration Policy
• Refugee Policy
• Local Governance
• +۳ مورد دیگر

Hannes Schammann is Professor of Political Science with a focus on migration policy at the University of Hildesheim , where he leads the Migration Policy Research Group since 2018. His work bridges academic research and practical implementation through the Research and Transfer Center for Migration Policy , addressing migration, integration, and refugee policy challenges. In January 2025, he joined the German Council of Experts on Integration and Migration (SVR) as a scientific advisor. Research Focus: Schammann specializes in local authorities' scope for action in refugee-related migration, national migration policy analysis, and educational integration aspects. He co-authored the textbook Migration Policy (2021) and contributes to international journals like Journal of Refugee Studies and Journal of Ethnic and Migration Studies . Key Projects: He leads third-party funded initiatives including Match'In (algorithmic asylum seeker distribution), SOLDISK (solidarity discourses in migration), Country.Home.Future (rural integration), When Mayors Make Migration Policy (municipal EU influence). Expert Engagements: Schammann serves on editorial boards including Zeitschrift für Flucht- und Flüchtlingsforschung , and participates in advisory roles for institutions like the German Federal Ministry for Family Affairs and Robert Bosch Foundation . He also engages in public discourse through media appearances in Deutschlandfunk , ARD , and SWR regarding migration challenges.

Thierry Badardمشاهده پروفایل

دانشیار

• Geospatial Big Data
• GeoAI
• GeoNLP
• +۹ مورد دیگر

Thierry Badard is an Associate Professor at the Department of Geomatics Sciences , Université Laval, where he also serves as Director of the Center for Research in Geospatial Data and Intelligence (CRDIG) . With over 28 years of experience in geospatial science, he leads research initiatives at the intersection of GeoAI , LiDAR processing , and smart city technologies . Director, CRDIG (2016-2022) Steering Committee Member, Big Data Research Centre (CRDM) Researcher, Institute for Intelligence and Data (IID) Research Expertise spans geospatial big data, GeoNLP, and IoT applications for digital twins. His work addresses flood risk modeling , 3D urban analytics , and environmental monitoring through AI-driven solutions. Recent publications focus on contrastive learning for LiDAR segmentation and geospatial ontologies for early warning systems. Grant Leadership includes collaborative projects on smart insurance analytics (2018-2025), Arctic bioaerosol research (2019-2025), and Quebec-Morocco digital twin partnerships (2022-2023). He has advised 15+ graduate students in geomatics and related fields.

Joseph F. Hair, Jr.مشاهده پروفایل

استاد

• Multivariate Data Analysis
• Marketing
• Structural Equation Modeling (SEM)
• +۳ مورد دیگر

Dr. Joseph F. Hair, Jr. is a Distinguished Professor of Marketing and Director of the Ph.D. in Business Administration Program at the Mitchell College of Business, University of South Alabama, Mobile, AL. He has co-authored over 100 book editions and 170+ scholarly journal articles, with expertise in quantitative methods, structural equation modeling, and marketing research. Education: PhD, University of Florida Master of Arts, University of Florida Bachelor of Arts, University of Florida Research Interests: Dr. Hair is a global leader in Multivariate Data Analysis, Structural Equation Modeling (SEM), and Partial Least Squares SEM (PLS-SEM). His work bridges theoretical and applied marketing research, focusing on advanced statistical techniques to solve business problems. His books, including Multivariate Data Analysis (8th edition, 2019) and A Primer on Partial Least Squares Structural Equation Modeling (3rd edition, 2022), are foundational texts in business analytics. Scientific Awards: Dr. Hair has received global recognition with over 500,000 career citations, an H-Index of 132, and an I-10 index of 543, reflecting his significant academic impact. Advising & Grants: As Director of the Ph.D. Program in Business Administration, Dr. Hair leads one of the most rigorous and applications-oriented doctoral programs. The department emphasizes student-centered learning, preparing graduates for careers requiring analytical and communication skills in global business contexts.

Yuzhe Yangمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Healthcare Technology
• +۳ مورد دیگر

Yuzhe Yang is an Assistant Professor of Computational Medicine and Computer Science at UCLA, with a visiting research scientist role at Google Health. He holds a PhD in Computer Science from MIT (2024), advised by Dina Katabi, and a B.S. with honors from Peking University. Research Focus: Machine learning for healthcare, medical AI fairness, and AI-driven biomedical discovery Key Contributions: Ten Notable Advances (Nature Medicine) and Ten Crucial Advances (The Lancet Neurology) His lab develops Trustworthy Learning Algorithms and Generalist Health Models that integrate Multimodal Data for personalized health coaching. Notable projects include AI-based Parkinson's Disease Biomarkers via nocturnal breathing and Foundation Models for Equitable Medicine . Recent publications at ICLR 2025 (wearable foundation models), Nature Medicine 2024 (medical AI fairness), and Science Advances 2025 (vision-language medical bias) highlight his interdisciplinary work. He serves on ML4H workshops and reviews for top conferences like NeurIPS and ICML. Awards include Forbes 30 Under 30 , Takeda Fellowship , and Baidu PhD Fellowship . Advising opportunities: Recruiting PhD students (CS/CompMed) and postdocs in AI for health. Lab: Health Intelligence Lab (HAIL)

• Energy Efficiency in Communication Networks
• Quality of Service (QoS) and Quality of Experience (QoE)
• Network and Service Management
• +۵ مورد دیگر

Dr. Frank Loh is a researcher at the Department of Computer Science III, University of Würzburg, specializing in energy efficiency, network performance, and Quality of Experience (QoE) in communication networks. His work focuses on optimizing LoRaWAN deployments, serverless computing, and edge-cloud environments, with an emphasis on reducing message collisions and improving resource utilization. He actively contributes to methodologies for gateway placement, traffic modeling, and energy consumption metrics. Research Areas Energy Efficiency in Communication Networks Quality of Service (QoS) and Quality of Experience (QoE) LoRaWAN Network Planning Edge and Serverless Computing Network Resource Analysis Recent Publications 2025: Energy modeling for 6G base stations 2025: Server cluster resilience via Markov models 2024: Serverless computing in edge-cloud environments 2024: LoRaWAN channel access optimization

• Journalism and Communication
• Media Phenomenology
• Philosophy of Technology
• +۲ مورد دیگر

Wang Yingji is a tenured professor and doctoral supervisor at the School of Art and Media, Tongji University. He holds a PhD in Literary Studies and has served as director of the China Culture and Art Communication Research Center, member of the China Artists Association, and editorial board member of "Media Criticism" journal. BA: Chinese Language and Literature, Renmin University of China (1995) MA: Journalism, Beijing Normal University (2004) PhD: Literary Studies, Beijing Normal University (2007) His research focuses on the intersections between Journalism and Communication, Media Phenomenology, Philosophy of Technology, and Traditional Chinese Culture. His work explores embodied cognition in media interaction, technological mediation of human perception, and historical epistemology of media systems. The articles demonstrate his expertise in media phenomenology (Hubert Dreyfus analysis), digital reading behavior studies, VR technology ideologies, and historical reconstruction of Chinese communication theories. His publications span from 2016-2022 with consistent CSSCI indexing. National Social Science Fund General Project: "Chinese Modern Public Opinion Thought History" (2021) Major Project Subtopic: "Chinese Media Archaeology in Civilizational Diversity" (2020) Ministry of Education Project: "Husserl's Media and Communication Thought" (2020) Completed NSFC Project: "Rumor Propagation and Governance in Public Emergencies" (2011) As educator, he teaches courses like "Chinese Classical Media Art", "Media Research Methods", and "Communication Theory". His administrative roles include leadership positions in the Chinese Society of Journalism History and multiple journal editorial boards.

• Optimization for Machine Learning
• Collaborative Learning
• Federated Learning
• +۶ مورد دیگر

Sebastian U. Stich is a tenured Professor at CISPA Helmholtz Center for Information Security and a member of the European Lab for Learning and Intelligent Systems (ELLIS). His research focuses on optimization for machine learning, collaborative learning (distributed, federated, and decentralized methods), efficient optimization techniques, adaptive stochastic methods, and privacy/security in machine learning. Recent appointments include ERC Consolidator Grant 2024 for the CollectiveMinds project. Key contributions in federated/decentralized learning, uncertainty estimation, and communication-efficient optimization. Active in workshop organization, including the Optimization for Machine Learning workshop at NeurIPS 2024. Teaching modern optimization methods at Saarland University (2023-2025). His work has been recognized with awards such as the Google Research Scholar Award (2023) and Meta Privacy-Enhancing Technologies Award (2022) . His research group includes postdocs Dr. Anton Rodomanov and Dr. Rotem Mulayoff, and PhD students Xiaowen Jiang and Yuan Gao.

Rebecca Careyمشاهده پروفایل

استادیار

• Social Psychology
• Social Class
• Relationships
• +۳ مورد دیگر

Rebecca Carey is an Assistant Professor in the Department of Psychology at Princeton University's School of Arts and Sciences, where she conducts research on social class as a cultural context that shapes psychological processes through relationships. Her work examines how social class influences close relationships and how these relationships either mitigate or exacerbate social disparities. Dr. Carey received her Ph.D. from Stanford University and maintains the Adversity and Relationships in Context Lab at Princeton. Her research addresses two central questions: how social class shapes the nature of close relationships, and what role close relationships play in mitigating or exacerbating disparities across social class. Her research interests focus on how economic inequality in the U.S. shapes people's experiences through social class, which determines health, happiness, and success. She examines how social class contexts foster different relational realities - with lower class contexts creating dense, interdependent networks that promote survival, and higher class contexts creating diverse, loosely connected networks that promote opportunity. Her work bridges psychology, sociology, and public policy to address social inequality. Dr. Carey's publications reveal a consistent focus on social class as a fundamental cultural context, with recent work examining first-generation college students, pandemic effects on inequality, and the role of cross-race and cross-class interactions in educational settings. Her research demonstrates how relational structures differ across class contexts and how these differences impact educational outcomes, health disparities, and social mobility. Scientific Awards: President's Award for Distinguished Teaching Dr. Carey advises several graduate students including Priscilla Diaz-Gonzalez, Nicole Columbaro Johnson, and Madeline Paxson. Her research has been supported by various grants focused on understanding social class disparities in educational and health contexts. She has developed innovative methodologies for conducting research with people in lower-socioeconomic-status contexts, emphasizing ethical considerations and cultural sensitivity. At Princeton, Dr. Carey leads the Adversity and Relationships in Context Lab, which brings together graduate and undergraduate researchers to investigate how social class shapes relationships and psychological processes. The lab focuses on both theoretical contributions to understanding class-based cultural models and practical applications for reducing inequality through relationship-focused interventions.

Jörg Spenkuchمشاهده پروفایل

دانشیار

• Political Economy
• Applied Microeconomics
• Behavioral Economics
• +۴ مورد دیگر

Jörg Spenkuch is an Associate Professor of Managerial Economics & Decision Sciences at Kellogg School of Management, Northwestern University, where he has been since 2013. He holds a Ph.D. in Economics (2013) and M.A. (2009) from the University of Chicago, and dual B.A. degrees in Economics and Business Administration (2007) from the University of St. Gallen, Switzerland. Education: Ph.D., 2013, Economics, University of Chicago M.A., 2009, Economics, University of Chicago B.A., 2007, Economics, University of St. Gallen B.A., 2007, Business Administration, University of St. Gallen Professor Spenkuch's research bridges political economy and applied microeconomics , with a focus on ideological behavior, strategic decision-making, and social dynamics. His work examines topics like: Political Economy: Campaign finance, electoral accountability, and ideological sorting. Behavioral Economics: Satisficing behavior, memory-driven choices, and strategic voting. Public Policy: School desegregation effects, bureaucratic performance, and immigration-crime linkages. His recent publications analyze: Long-term ideological shifts from 1975 school desegregation (2025 working paper). Memory premiums in decision-making (2025 working paper). Complexity's role in chess strategy (2024 Review of Economic Studies ). Political accountability during natural disasters (2025 American Economic Journal ). Scientific Recognition: MinE Best Paper Award (European Economic Association) Chair's Core Teaching Award Deutschlands "Top 40 unter 40" (Capital magazine) FEEM Award (European Economic Association) Best Paper Award, RGS Doctoral Conference At Kellogg, he teaches Leadership and Crisis Management (PACT-440-5) and Business Analytics (DECS-435-0). His work has been published in top journals like Econometrica , American Economic Review , Quarterly Journal of Economics , and Review of Economic Studies , covering topics from partisan spatial sorting to expressive vs. strategic voting behavior.

Georgios Sermpinisمشاهده پروفایل

استاد

• Machine Learning
• Financial Trading
• Forecasting
• +۳ مورد دیگر

Professor Georgios Sermpinis is a faculty member in Accounting & Finance at the Adam Smith Business School, University of Glasgow. He joined the institution in 2011, bringing expertise in machine learning, financial trading, forecasting, econometrics, and financial risk management. Degrees from National Kapodistrian University of Athens and Liverpool John Moores University Former roles at University of Bedfordshire and Liverpool John Moores University Consultancy for major banks including Goldman Sachs and BNP Paribas Research Interests: Focus on machine learning applications in finance, including portfolio optimization, cryptocurrency markets, and risk modeling. His work integrates AI with traditional financial theories, emphasizing sustainability and behavioral aspects. Scientific Awards: Acanto Research Grant (2017) Santander & University of Oviedo Grant (2017) Mobility Grant, Universidad de La Laguna (2017) University of Oviedo Grant (2014) Early Career Research Grant, University of Bedfordshire (2010) Students: Supervised PhD candidates include Feng Xin and Sun Longguang, focusing on ESG investment and financial markets. Editorial Roles: Senior Editor of Decision Support Systems, Associate Editor of Information Systems and Operational Research, and Guest Editor for journals like Quantitative Finance.

• Hybrid Systems
• Networked Control Systems
• Event-Triggered Control
• +۷ مورد دیگر

Maurice Heemels is a Full Professor at Eindhoven University of Technology (TU/e), leading the Control Systems Technology group. He holds additional professorships in EAISI Mobility, EAISI Foundational, EAISI Health, and EAISI High Tech Systems. His research focuses on hybrid and networked systems, emphasizing resource-aware control, event-triggered strategies, and cyber-physical systems integration. He is an IEEE Fellow and chairs the IFAC Technical Committee on Networked Systems. Academic Background: MSc and PhD in Mathematics (TU/e, 1995 and 1999, both summa cum laude ) Visiting Professorships: ETH Zurich (2001), UC Santa Barbara (2008) Industry Experience: Research & Development at Océ NV Research Interests: Hybrid Systems, Networked Control, Event-Triggered Control Model Predictive Control (MPC) in healthcare and high-tech systems Cyber-Physical Systems for applications like lithography and precision agriculture Key Contributions: Developed Hybrid Integrator-Gain (HIGS) systems and Projection-Based Control methodologies Recipient of a VICI Grant for wireless control systems research Oversaw over €7M in research funding from NWO, EU, and industry Awards & Recognition: Automatica Outstanding Service Award (2014) Best Paper Awards (EBCCSP 2017, etc.) Invited Keynote Speaker at ECC, CDC, and others Grants & Projects: Current Projects: COMEDI (Cost-effective Mechatronics), PROACTHIS (Projection-based Control) Past Projects: Fault Detection in Wafer Scanners, Drone-based Farming Labs & Teams: Active in TU/e’s Cyber-Physical Systems and Systems Engineering research groups, collaborating globally on nonsmooth dynamics and hybrid systems.