جستجوی استاد راهنمای دانشگاهی

Prof. Dr. Bernd Skiera holds the first chair for electronic commerce in Germany at Goethe University Frankfurt am Main since 1999. He serves on the board of efl - The Data Science Institute and the Schmalenbach Society, while representing Germany at the European Marketing Community (EMAC). Chair of Marketing, Goethe University Frankfurt am Main Board member, efl - The Data Science Institute National representative, European Marketing Community (EMAC) His research focuses on MarTech/SalesTech integration, customer value management, online advertising analytics, data-driven pricing models, and the economic implications of internet privacy regulations. He leads the ERC Advanced Grant project on cookie usage restrictions' economic consequences. Recent publications examine dynamic pricing in digital markets, competition visualization using big data, and AI applications in marketing analytics. The ERC Advanced Grant research has produced empirical analyses of GDPR impacts on advertising ecosystems. 2015 Journal of Marketing Best Paper Award 2013 International Journal of Research in Marketing Best Paper Award Multiple MSI/H. Paul Root Award recognitions He has mentored 17 doctoral students who became professors globally, including at London Business School and LMU Munich. His work bridges marketing analytics with financial valuation through customer equity modeling.

• Marketing Analytics
• Electronic Commerce
• Online Advertising
• +۱۱ مورد دیگر

Prof. Dr. Bernd Skiera is a leading Marketing Professor at Goethe University Frankfurt since 1999 and a member of the managing board of the efl - The Data Science Institute. His work bridges information systems and marketing, with a focus on data-driven decision making and digital transformation.

• Marketing Analytics
• Electronic Commerce
• Online Advertising
• +۸ مورد دیگر

Oleg Lashinin is an active researcher in the field of Recommender Systems , with a focus on Machine Learning , Temporal Modeling , and User Behavior Analysis . He has contributed to 15 recent publications spanning 2021–2025, including conference papers at ECIR, SIGIR, RecSys, and workshops like KaRS@RecSys and ORSUM@RecSys. His work explores advanced techniques such as Self-Attention Models , Time-Aware Item Weighting , and Cost-Constrained Recommendations . Key research trends in his publications include Deep Learning for sequential recommendation tasks, Crowdsourcing for explanation evaluation, and Temporal Dynamics in user behavior. Notable projects include the GPT3RecBot Telegram chatbot and the RecBaselines2023 dataset for benchmarking recommender systems.

• Recommender Systems
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

FH-Prof. Mag. Dr. Tassilo Pellegrini is a Professor at the University of Applied Sciences St. Pölten , leading the Institute for Innovation Systems within the Department of Digital Business and Innovation . His work bridges semantic technologies with digital business strategies. Education : Business Economics, Communication Studies, Political Science Research Focus : Semantic Web, Linked Data, Digital Media Economics, Network Neutrality, Data Licensing His publications highlight trends in Semantic Metadata for news production, Linked Data Integration , and Cloud-based Business Models under network neutrality constraints. Recent work explores thesaurus-driven knowledge organization and the economic implications of Big Data. Scientific Awards : Best Paper Award at I-Semantics 2012 Key Projects : ECO-TCO (Digital Data for Sustainability), Corporate Semantic Web initiatives Contact: tassilo.pellegrini@fhstp.ac.at

• Semantic Web
• Linked Data
• Digital Business
• +۴ مورد دیگر

Xin Wang is a Professor at Fudan University's School of Computer Science, specifically within the Department of Communication Science and Engineering and affiliated with the State Key Laboratory of ASIC and System in Shanghai, China. With 185 publications spanning two decades (2003-2025), Wang maintains an exceptionally active research profile, particularly evident in recent high-output years including 22 publications in 2019, 19 in 2021, and 13 in 2024. The research portfolio demonstrates deep collaboration networks, most notably with Yang Chen (45 co-authored papers), Yangfan Zhou, and Qingyuan Gong. Wang's research spans multiple critical areas in computer science, with significant contributions to networking systems (particularly CDN optimization, HTTP/3 implementation, and IPv6 infrastructure), software engineering (focusing on work rhythms, testing methodologies, and GUI analysis), mobile applications (including healthcare implementations and accessibility features), and security (especially account security and fraud detection in e-commerce). The interdisciplinary nature of the work is evident through applications in healthcare, e-commerce, campus safety, and IoT systems. Analysis of recent publications (2023-2025) reveals a strong trend toward practical system implementations addressing real-world challenges. The research demonstrates a consistent pattern of moving from theoretical foundations to deployable solutions, with particular emphasis on optimizing performance in networking systems, enhancing security in digital platforms, and improving user experience across diverse application domains. The work frequently incorporates machine learning techniques to solve complex system problems while maintaining practical applicability. While specific grant information isn't detailed in the publication records, the extensive collaboration network spanning multiple institutions in China and internationally suggests substantial research funding support. The consistent publication output across top venues including IEEE/ACM Transactions, INFOCOM, SIGCOMM, and ICSE indicates sustained research productivity and impact.

• Computer Science
• Networking Systems
• Software Engineering
• +۵ مورد دیگر

Prof. Gabriela Alves Werb, Ph.D. is a faculty member affiliated with the Bundesbank Research Data and Service Centre (RDSC) and holds her academic background from Johann Wolfgang Goethe University Frankfurt am Main. Her research spans interdisciplinary areas at the intersection of finance, machine learning, and digital economy, with a focus on non-financial risks and search engine analytics. Education: Doctoral Dissertation (2020), Goethe-Universität Frankfurt Research Interests include machine learning applications in financial risk assessment, user-generated content analysis, and digital marketplace dynamics. Her work bridges computational methods with economic policy challenges. Recent Publications highlight trends in climate-related financial data, predictive modeling in marketing, and the economic implications of search engine visibility. Key subfields span ESG investing, SEO vulnerability, and digital risk assessment.

• Non-Financial Risks
• User-Generated Content
• Search Engine Analytics
• +۷ مورد دیگر

Dr. Sagit Bar-Gill is an Assistant Professor in the Coller School of Management at Tel Aviv University , specializing in Technology Management and Information Systems . She is also a Digital Fellow at both MIT’s Initiative on the Digital Economy and Stanford's Digital Economy Lab . Currently on sabbatical at NYU’s Stern School of Business , her work bridges economic modeling, econometric analysis, and online experiments to explore the digital economy. Education: PhD in Economics, Tel Aviv University MA in Economics, Tel Aviv University BSc in Mathematics, Tel Aviv University Research Interests : Dr. Bar-Gill focuses on the economics of online markets , examining how digitization affects firms and consumers. Her work spans platform economics, media consumption, and behavioral economics, particularly studying: Digital engagement and its offline consequences Social vs. nonsocial referral channels Platform competition and strategic expansion Echo chamber dynamics and algorithmic bias Data-driven decision-making in SMEs Cultural transmission in digital contexts Article Trends : Her research combines empirical analysis with experimental methods, emphasizing the interplay between digital platforms and economic behavior. Topics include platform rivalry, content choice diversity, and behavioral spillovers in e-commerce. Scientific Awards : Digital Fellow, MIT Initiative on the Digital Economy Digital Fellow, Stanford Digital Economy Lab Advising and Grants : While specific students and grants aren’t listed, her interdisciplinary research has been published in top journals like Management Science and MISQ , reflecting significant academic impact.

• Economics of Digitization
• Online Markets
• Platform Economics
• +۳ مورد دیگر

Alan R. Dennis is a distinguished academic and researcher in the field of Information Systems, with over 230 scholarly publications since 1985. His work spans interdisciplinary areas including decision support systems, social media dynamics, artificial intelligence ethics, and cybersecurity. He has collaborated extensively with researchers such as Joseph S. Valacich, Lingyao (Ivy) Yuan, and Antino Kim. Research interests focus on the societal and organizational impacts of technology, particularly in areas like fake news mitigation, human-robot interaction, and virtual team collaboration. Recent studies address critical challenges such as misinformation on social platforms, anthropomorphic AI agents, and the ethical use of digital humans in healthcare and e-commerce. Publications reflect a strong emphasis on applied research with real-world implications, appearing in top journals like Decision Support Systems , Journal of Management Information Systems , and Information Systems Research . His contributions highlight both technological innovation and human-centric design principles. Notable collaborations include exploring the role of conversational agents in decision-making, analyzing the psychology behind fake news believability, and investigating the cognitive and emotional responses to AI-driven systems. His work often bridges theoretical insights with practical applications, addressing challenges in modern digital ecosystems.

• Information Systems
• Decision Support Systems
• Social Media
• +۷ مورد دیگر

Mideth B. Abisado is an active researcher in the fields of machine learning, data science, and natural language processing. Their work focuses on applications such as pedestrian re-identification, recommendation systems, sentiment analysis, federated learning, and privacy-preserving techniques. Key contributions include enhancing deep learning models for computer vision tasks, optimizing feature selection algorithms, and developing systems for citizen participation and education policy evaluation. Research Interests Machine Learning & Deep Learning Computer Vision & Image Processing Natural Language Processing (Sentiment Analysis, Text Classification) Federated Learning & Privacy-Preserving Methods Data Science Applications in Social & Educational Systems Notable Trends in Publications Recent work emphasizes hybrid deep learning architectures, multimodal data analysis, and real-world applications of AI in education and smart infrastructure. There is consistent focus on improving model accuracy through attention mechanisms, feature engineering, and optimization algorithms. Labs/Teams Collaborations involve interdisciplinary teams addressing challenges in digital systems, citizen participation platforms, and sustainable education systems through data-driven approaches.

• Machine Learning
• Computer Vision
• Data Science
• +۳ مورد دیگر

Professor Heinrich Kuhn serves as Professor of Business Administration, Supply Chain Management & Operations at the Ingolstadt School of Management, Catholic University of Eichstätt-Ingolstadt. His extensive research focuses on planning and control of production systems, flexible production planning, JIT and flow production systems analysis, maintenance, and queueing theory. With a prolific publication record spanning decades, he has established himself as a leading scholar in operations research and supply chain management. His research interests encompass Supply Chain Management, Operations Research, Production Planning, Retail Logistics, Queueing Theory, and Inventory Management. Professor Kuhn has developed innovative approaches for optimizing retail fulfillment processes, managing assortment planning, improving inventory accuracy, and addressing complex production planning challenges. His work bridges theoretical operations research with practical applications in retail and manufacturing industries, with particular emphasis on omnichannel retailing, grocery operations, and sustainable logistics solutions. His research demonstrates consistent evolution from foundational production planning systems to addressing contemporary challenges in digitalized retail environments. Professor Kuhn's recent publications (2021-2024) reveal a strong focus on retail logistics challenges, particularly in grocery retailing during the pandemic, drone delivery systems, vehicle routing optimization, and inventory management. His research shows a clear progression toward addressing digital transformation in retail, sustainable practices, and the integration of physical and online retail channels. The work demonstrates sophisticated methodological approaches including advanced optimization algorithms, simulation modeling, and empirical analysis of retail operations. Throughout his career, Professor Kuhn has maintained extensive collaborations with researchers including A. Holzapfel, A. Hübner, M. Sternbeck, and others. His research provides valuable decision support tools for retail operations, supply chain design, and production planning, with practical applications across multiple industries. His work continues to influence both academic discourse and industry practices in supply chain management and operations research.

• Supply Chain Management
• Operations Research
• Production Planning
• +۴ مورد دیگر

Domenico Cantone is a Professor in the Department of Mathematics and Computer Science at the University of Catania, Italy. With an extensive publication record spanning from 1987 to 2025, he has established himself as a leading researcher in mathematical logic, set theory, and their applications to computer science problems. His research bridges theoretical foundations with practical applications in ontologies, blockchain technology, and quantum computing. Professor Cantone's research interests primarily focus on set theory and mathematical logic, with significant contributions to computational aspects of these fields. His work has evolved from foundational set theory to practical applications in semantic web technologies, blockchain systems, and quantum algorithms. He has made substantial contributions to decidability problems in set theory fragments, developing decision procedures that have applications in automated reasoning systems. His recent work demonstrates a strategic expansion into interdisciplinary areas, particularly the application of formal methods to blockchain technology and the exploration of quantum computing for string algorithms. The trajectory of Cantone's publication record shows a consistent focus on theoretical foundations while gradually incorporating more applied research directions. His early work concentrated on pure set theory and logic, then expanded to include applications in automated reasoning and ontology representation, and more recently has embraced emerging technologies like blockchain and quantum computing. This evolution reflects both his theoretical depth and ability to identify promising intersections between formal methods and cutting-edge technologies. Professor Cantone has maintained exceptionally productive collaborations throughout his career, most notably with Marianna Nicolosi Asmundo (58 joint publications), Simone Faro (54 publications), Daniele Francesco Santamaria (35 publications), and Eugenio G. Omodeo (35 publications). These long-standing collaborations demonstrate his ability to build and sustain research teams focused on complex theoretical problems. His work has appeared in prestigious venues including Theoretical Computer Science, Journal of Automated Reasoning, and Fundamenta Informaticae, among others.

• Set Theory
• Mathematical Logic
• Ontologies
• +۶ مورد دیگر

Clemens Brackmann is a Researcher at the University of Duisburg-Essen, affiliated with the Faculty of Computer Science and the Human-Computer Interactions working group. His work spans machine learning integration in retail and software development. Education: M.Sc. in Applied Computer Science (2017–2021) from Ruhr University Bochum, B.Sc. in Applied Computer Science (2014–2017) from University of Duisburg-Essen. His research focuses on artificial intelligence applications in retail , particularly pricing algorithms and decision-making frameworks. He has contributed to understanding how machine learning shapes both brick-and-mortar and e-commerce environments through theoretical taxonomies and empirical studies. Recent publications highlight trends in AI-driven pricing strategies and ML adoption in retail processes . He has supervised bachelor's theses on topics like customer service chatbots, visual product search AI, and trust in medical AI systems. Contact: clemens.brackmann@icb.uni-due.de

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

Kai Riemer is a Professor at the University of Münster , affiliated with the School of Business and Economics and the Department of Information Systems . His research focuses on Information Systems, E-Collaboration, Social Capital in digital contexts, and Unified Communications. Key projects: DOMINO (Dynamic Organizational Management for Inter-firm Networks, 2001-2003) and IT for Administration and E-Government (2006-2010) His recent publications (2019-2008) explore: Collaboration in the Digital Age Conceptual frameworks for Virtual Organizations Enterprise Social Networking applications Microblogging in professional contexts Unified Communications systems Supervision includes multiple Master's and Bachelor's theses on Digital Humans, Social Capital metrics, and Fintech sectors. Research spans E-Commerce, Supply Chain Management, and ICT-enabled organizational design.

• Information Systems
• E-Collaboration
• Social Capital
• +۷ مورد دیگر

Mingming Li is an active professor at the Chinese Academy of Sciences with extensive research contributions across multiple domains including human-robot interaction, e-commerce systems, and wireless communications. With over 110 publications spanning from 2007 to 2025, Dr. Li demonstrates consistent scholarly productivity and leadership in interdisciplinary research. Dr. Li's research interests span Human-Robot Interaction , Affective Computing , E-commerce Search Algorithms , Machine Learning , and Wireless Communications . Recent work focuses on understanding how humanoid robots' multimodal characteristics (appearance, voice, touch) affect users' emotional responses and cognitive processing, employing physiological measures like ECG and fNIRS. Simultaneously, Dr. Li leads research in e-commerce search optimization, developing novel deep learning architectures for improved recommendation systems. The publication record reveals significant trends toward increasingly sophisticated multimodal analysis in HRI and more efficient neural architectures for practical applications. Dr. Li's work bridges theoretical advancements in machine learning with practical implementations in human-centered systems. Dr. Li has advised numerous graduate students including Jiahao Chen, Aung Naing Win, and Songlin Wang, with whom collaborative publications demonstrate strong mentorship. Research has been supported by substantial funding reflected in the volume and quality of publications across top venues. Current research activities include leading projects on digital twin-based thermal error compensation, multimodal affective robot design, and advanced search algorithms for e-commerce platforms, indicating an active laboratory environment with multiple ongoing research threads.

• Human-Robot Interaction
• Affective Computing
• E-commerce Search Algorithms
• +۴ مورد دیگر

Prof. Dr. Tobias Hagen is a Professor of Economics and Quantitative Methods at Frankfurt University of Applied Sciences since 2010. He directs the Research Lab for Urban Transport (ReLUT) and serves as speaker for the Promotionszentrum Mobilität und Logistik. His research bridges data science, applied econometrics, and policy evaluation in transportation contexts. Academic Background: Studied Volkswirtschaftslehre at Goethe Universität Frankfurt PhD (Dr. rer. pol.) in 2005 from Johann Wolfgang Goethe-Universität Frankfurt am Main Research focuses on data-driven transportation analysis using GPS trajectories, parking search modeling, and AI applications. Key projects include start2park (parking search prediction), DZweI (urban digital twins), and MaKoMo (mobility cohort effects). His work aligns with UN SDGs 1, 3, 9, 11, and 13. Scientific Contributions span parking violation modeling (2023), semantic trajectory clustering (2022), and entropy balancing for commuting pattern decomposition (2025). He pioneered open-source tools like TessPy for geographical tessellation. Awards Dissertationspreis der IHK Frankfurt (2005) Actively supervises PhD candidates Jonas Hamann, Nicole Reinfeld, and Siavash Saki. Collaborates with institutions like Bundesministerium für Digitales und Verkehr, KfW Bankengruppe, and European Central Bank through research projects.

• Data Science
• Transport Economics
• Applied Econometrics
• +۷ مورد دیگر