جست‌وجوی استاد و پژوهشگر

Xiangmin Zhangمشاهده پروفایل

استاد

• Human-Computer Interaction
• User Experience Research
• Artificial Intelligence
• +۶ مورد دیگر

Xiangmin Zhang is a Professor at the School of Information Sciences, Wayne State University, specializing in Human-Computer Interaction (HCI), Human-AI Interaction, User Experience (UX) Research, and Information Retrieval. He teaches courses such as Human-Computer Interaction, UX Design, and Web Development. Education: Ph.D. from the iSchool at the University of Toronto, B.A. and M.S. from Peking University's Department of Information Management Research Interests: Focus on user domain knowledge modeling, personalization of information systems, data analytics, and experimental design Grants: Co-PI on autism diagnosis prediction, digital library personalization, and IEEE-funded projects His publications span topics including large language models, smart wearables, IoT adoption, and autism diagnostic disparities. He actively collaborates with researchers worldwide and serves as a guest editor for journals like International Journal of Information Management Data Insights . Recent trends in his research emphasize ethical AI, user behavior in emerging technologies, and predictive modeling in health informatics. He has contributed to IEEE Transactions, Computers in Human Behavior, and ASIST proceedings.

N. Tintarevمشاهده پروفایل

استاد

• Explainable AI
• Natural Language Generation
• Human-Computer Interaction
• +۵ مورد دیگر

N. Tintarev is a Full Professor in Explainable AI at Maastricht University, serving as Director of Research in the Department of Advanced Computing Sciences (DACS) within the Faculty of Science and Engineering. He co-directs the TAIM lab for trustworthy media (with UvA and RTL) and leads the interdisciplinary Explainable AI (XAI) research theme. He earned his PhD from the University of Aberdeen in 2010. His academic trajectory focuses on human-computer interaction in AI-driven advice systems, particularly recommender technologies where he pioneers transparency and user control mechanisms. Tintarev's research spans natural language generation for explanations, intelligent user interfaces, and mitigation of filter bubbles through diversity-aware design. His work integrates responsible data analytics with practical applications in news, job, and tourism recommendations, emphasizing fairness and user agency in algorithmic systems. Recent publications (2022-2024) reveal a cohesive research program addressing explainable AI's societal impact: analyzing logic-style explanations' effects on decisions, designing stance-aware search interfaces, measuring transparency benefits in news recommendation, and developing normative frameworks for ethical information access systems. He secured major funding including an EU Marie-Curie ITN grant (2.8M) for Interactive Natural Language Technology in XAI and co-founded the ROBUST consortium (10-year, 95M) for trustworthy AI. As a senior ACM member, he examines PhD dissertations and reviews NWO/international grant proposals. Tintarev actively shapes research agendas through the IPN board (incoming 2026), NWO-ENW Computer Science advisory committee (Informaticatafel), and international steering/editorial boards. His TAIM lab collaborations with UvA and RTL drive real-world implementations of trustworthy media technologies.

Giulia Fantiمشاهده پروفایل

دانشیار

• Blockchains
• Distributed Systems
• Privacy-Preserving Technologies
• +۴ مورد دیگر

Giulia Fanti is the Angel Jordan Associate Professor of Electrical and Computer Engineering at Carnegie Mellon University. She holds courtesy appointments in the Computer Science Department and Machine Learning Department, and is affiliated with CyLab Security and Privacy Institute. Her research focuses on security and privacy in distributed systems, blockchain technology, and privacy-enhancing machine learning. Ph.D., Electrical Engineering & Computer Science, University of California, Berkeley (2015) M.S., Electrical Engineering & Computer Science, University of California, Berkeley (2012) B.S., Electrical & Computer Engineering, Olin College of Engineering (2010) Her research spans three major areas: privacy-preserving data sharing using generative models like GANs, privacy in decentralized networks under adversarial conditions, and blockchain scalability with rigorous mathematical modeling. She actively explores privacy-utility tradeoffs in synthetic data generation and secure federated learning frameworks. Recent publications highlight her expertise in blockchain economics, privacy-preserving machine learning, and secure consensus algorithms. Articles span topics like game-theoretic liquidity provisioning, federated learning with synthetic data, and differential privacy in distributed systems. These works demonstrate her focus on bridging theoretical guarantees with practical implementations. Scientific recognition includes: Best Paper Award Finalist @ ACM IMC Best Paper Award Finalist @ SIGMETRICS 2025 ICML 2025 Oral Presentation ICLR 2025 Honorable Mention Atlantic Council Senior Fellowship World Economic Forum Global Future Council Fellowship She advises numerous doctoral students and postdocs, including current advisees Shuaiqi Wang, Sangyun Lee, and former students now at institutions like HKUST, NTU, and University of Ottawa. Her group collaborates extensively through initiatives like the Upanzi Network and Secure Blockchain Initiative. Research teams include CyLab-Africa, which she co-directs, and CMU's Secure Blockchain Initiative. Her work has been funded by NSF awards and industry grants.

Maria Mercedes Rodriguez Garciaمشاهده پروفایل

استاد

• Privacy-Preserving Data Publishing
• Blockchain Technology
• Learning Analytics
• +۴ مورد دیگر

Maria Mercedes Rodriguez Garcia serves as a Professor in the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cadiz, Spain. Her research focuses on critical intersections of data privacy, blockchain security, and educational technology within the PAIDI Information and Communication Technologies framework. She earned her PhD from Universitat Rovira i Virgili in 2017 with the dissertation Semantic perturbative privacy-preserving methods for nominal data , supervised by Dr. Montserrat Batet Sanromà and Dr. David Sánchez Ruenes. Her research methodology consistently combines formal methods with practical cybersecurity applications, particularly through the TIC195 Software Process Improvement and Formal Methods group. Rodriguez Garcia’s research program demonstrates clear evolutionary progression: foundational work on semantic noise addition (2015-2017) matured into blockchain-integrated healthcare privacy systems (2021-2024), with current 2025 publications pioneering ecologically sustainable DLT tendering processes and advanced cybersecurity event detection. Her learning analytics research uniquely bridges educational integrity (fraud detection in online exams) with sequential data protection, while maintaining strong emphasis on utility-preserving privacy techniques across all domains. No scientific awards were documented in the provided materials. Her academic service includes thesis supervision as indicated by profile navigation elements, though specific student names and grant funding details remain unspecified. She actively contributes to the TIC195 research group’s mission of applying formal verification methods to software engineering challenges, with recent work emphasizing sustainable technology implementations and gender-inclusive STEM education initiatives.

Louise Limbergمشاهده پروفایل

استاد

• Information Literacy
• Library and Information Science
• Information Retrieval
• +۳ مورد دیگر

Louise Limberg is a Professor in Library and Information Science at the University of Borås, working within the Department of Library and Information Science under the Academy of Library, Information, Education and IT. With a career spanning since the 1980s, she has established herself as a leading researcher in information literacy and its intersection with learning processes. Her research focuses on the critical relationship between information retrieval and learning, with information literacy serving as the central hub. Limberg employs phenomenographic and sociocultural theoretical frameworks to examine how students search for and use information across various tasks, alongside their interactions with peers and educators. Her work demonstrates that variations in information activity quality directly correlate with learning outcomes, particularly in digital environments. Limberg's publications reveal consistent focus areas across recent years: school library practices (2021-2022), information literacy pedagogy (2021-2022), historical perspectives on library science (2022), and the evolution of information practices in educational contexts (2018-2024). Her research shows strong continuity in examining how information literacy functions as a critical dimension in digital learning. She has secured research funding from major Swedish institutions including the Swedish Research Council, the Swedish Agency for School Development, the Swedish National Agency for Education, and the Knowledge Foundation. Limberg maintains active affiliation with LinCS (The Linnaeus Centre for Research on Learning, Interaction and Mediated Communication in Contemporary Society), a collaborative research center between the University of Gothenburg and University of Borås. Her academic journey includes defending her doctoral thesis 'Seeking information to learn. A study of the interaction between information seeking and learning' at the University of Gothenburg in 1998, followed by a visiting professorship at Queensland University of Technology during 2010-2011. Current projects continue her longstanding investigation into information/media literacy (MIK) while expanding into historical perspectives on library and information science.

• Organizational Psychology
• Personnel Selection
• Team Innovation
• +۳ مورد دیگر

Nikolaou Ioannis is a Professor at the Department of Management Science and Technology, School of Business Administration, Athens University of Economics and Business. His research explores the intersection of organizational psychology, digital recruitment technologies, and team dynamics. Bachelor's Degree: Psychology, University of Crete M.Sc.: Organizational Psychology, University of Manchester Institute of Science & Technology (UMIST) Ph.D.: Organizational Psychology, UMIST His work focuses on: Gamification in personnel selection and assessment Personality dynamics in organizational contexts Team innovation and climate Emotional intelligence in workplace transitions Psychological capital development Legal and ethical frameworks in recruitment Recent research trends reveal expertise in gamified assessment design, applicant reactions to digital selection methods, and team climate validation. His publications span from 2025 back to 1995, showing sustained contributions to organizational psychology.

• Electronic Commerce
• Social Networks
• Online Business Models
• +۳ مورد دیگر

Prof. Gal Oestreicher-Singer is the Mexico Professor of Information Systems and Associate Dean of Research at the Coller School of Management, Tel Aviv University. Her work bridges Information Systems and Marketing , focusing on social media dynamics, consumer engagement, and peer influence in electronic commerce. Ph.D. from Stern School of Business, New York University Her research explores how social cues and digital networks shape consumer behavior and business outcomes, with articles in MIS Quarterly and Sloan Management Review . Recent work includes analyzing crowdfunding dynamics , sales prediction models , and trust mechanisms in online environments. She serves as a Senior Editor at MIS Quarterly and has received prestigious ERC grants for her work on digital commerce and social media impacts.

Anum Afzalمشاهده پروفایل

پژوهشگر

• Text Summarization
• Domain Adaptation
• Efficient Transformers
• +۸ مورد دیگر

Anum Afzal is a Ph.D. candidate and Researcher at the Chair of Software Engineering for Business Information Systems (sebis) within the Faculty of Informatics at Technical University of Munich . Her work focuses on improving efficiency and domain adaptation of Large Language Models (LLMs) , particularly in business contexts through collaborations with SAP and Holtzbrinck Publishing Group.

Juhi Kulshresthaمشاهده پروفایل

استادیار

• Computational Social Science
• Social Computing
• Misinformation
• +۳ مورد دیگر

Juhi Kulshrestha serves as an Assistant Professor in the Department of Computer Science at Aalto University, Finland, specializing in Computational Social Science and Social Computing with a focus on digital ethics, societal impacts of technology, and policy implications. Her research addresses critical challenges at the intersection of human behavior and digital systems. Her scholarly work investigates misinformation propagation, algorithmic bias in search/social media, and AI's societal consequences through interdisciplinary approaches. Key research themes include affect-driven information seeking, Holocaust representation in AI-generated content, digital divides in AI adoption, and cross-national vaccine misinformation dynamics. She employs large-scale data analysis combining computational methods with social science theories. Recent publications (2022-2025) reveal a strong emphasis on real-world societal issues: analyzing ChatGPT user demographics in Germany, examining visual Holocaust representations across search engines, and studying conspiracy theory ecosystems (e.g., flat earth/9-11 theories). Her collaborative work spans public health, political science, and psychology, frequently appearing in top venues like PLOS One and New Media and Society. Kulshrestha leads the Digital Ethics, Society and Policy (Digital-ESP) research group, which examines ethical frameworks and policy interventions for digital technologies. No information regarding student supervision or research grants is provided in the source material.

Yong Geمشاهده پروفایل

دانشیار

• Business analytics
• Data mining
• Machine learning
• +۱ مورد دیگر

Yong Ge serves as Associate Professor of Management Information Systems at the Eller College of Management, University of Arizona, holding the Eller Fellow designation since joining in 2016 after prior faculty positions at the University of North Carolina at Charlotte. His academic foundation includes a PhD in Management Science and Information Systems from Rutgers University (2013). His research program centers on business analytics, data mining, machine learning, and recommender systems, with emphasis on developing scalable algorithms for real-world business applications. Ge's work bridges theoretical advances in data science with practical implementations across transportation, tourism, mobile ecosystems, and social networks, demonstrating consistent innovation from 2011 through 2021. Publication trends reveal evolving focus from foundational customer analytics (2011) to spatial data mining (2015-2019) and cutting-edge quantization techniques (2021), consistently targeting high-impact journals like IEEE TKDE and MIS Quarterly. His work demonstrates strong interdisciplinary connections between information systems, computer science, and business applications. Key honors include: NSF CAREER Award (2019) for foundational research in data mining Dean's Research Award (Eller College, 2020) Ralph E. Powe Junior Faculty Enhancement Award (2015) IEEE ICDM Best Research Paper (2011) Excellence in Academic Research (Rutgers, 2013) Ge secures significant research funding through competitive grants including the NSF CAREER award, supporting his work on algorithmic foundations for business intelligence. His teaching portfolio includes graduate courses in business intelligence (MIS 587) and design science research methodologies (MIS 611A), reflecting his commitment to developing next-generation analytics professionals. No dedicated research laboratory or named research team is specified in available materials, though his collaborative publications indicate active engagement with cross-institutional research groups in data mining and recommender systems.

Nasreen Anjumمشاهده پروفایل

مدرس

• Cybersecurity
• Cyber-Biosecurity
• Artificial Intelligence
• +۷ مورد دیگر

Dr. Nasreen Anjum is a Lecturer in Computer Science at the University of Portsmouth's Faculty of Technology, with a dual appointment at the Institute of Life Sciences and Healthcare. Her work bridges cybersecurity, artificial intelligence, and biomedical data protection, focusing on securing emerging technologies like IoT, digital twins, and next-generation sequencing systems. PhD in Computer Science, King's College London (2014-2019) Specialist in cyber-biosecurity and AI-driven network security Principal Investigator for UK-Saudi Challenge Fund (2024-2025) Her research spans four key areas: IoT Security : Lightweight cryptography, edge computing integration, and AI-based anomaly detection Cyber-Biosecurity : Genomic data protection, AI-bio convergence security, and NGS threat mitigation Digital Twins : Resilient architectures for healthcare and smart manufacturing applications Edge/Cloud Security : Adaptive access control and hybrid ecosystem protection Selected publications demonstrate interdisciplinary breadth: 2025: Foundational work on cyber-biosecurity in genomic sequencing 2024: Malware awareness education through gamification 2023: Cross-national cybercrime deterrence strategies 2022: IoT applications in pandemic monitoring Scientific recognition includes: Schlumberger Faculty for the Future Fellowship Best Paper Award nomination at IEEE WINCOM Fellow of the Higher Education Academy Actively supervising postgraduate research, Dr. Anjum welcomes PhD candidates in cybersecurity, AI, and technology ethics domains.

Louis Papeمشاهده پروفایل

استادیار

• Digital Economics
• Labor Economics
• Applied Econometrics
• +۵ مورد دیگر

Louis Pape is an Assistant Professor in Economics at Télécom Paris, focusing on Digital and Labor Economics, with a secondary specialization in Applied Econometrics. His research bridges empirical analysis and policy evaluation in digital markets and labor markets. His recent work examines the economic implications of competition policies, particularly the European Union’s Digital Markets Act (DMA). Using a difference-in-differences approach, he analyzed how Google’s removal of clickable maps in EU search results affected consumer behavior and competition among mapping services. Other studies explore labor market collusion, price discrimination in digital platforms, and econometric methodologies for handling logged data. Louis’s publications span interdisciplinary topics, combining economics, data science, and industrial organization. Key themes include Digital platform regulation Labor market dynamics Big data applications Empirical econometric methods

Serina Changمشاهده پروفایل

استادیار

• Artificial Intelligence
• Human Behavior
• Public Health
• +۵ مورد دیگر

Serina Chang is an Assistant Professor at the University of California, Berkeley , jointly appointed in Electrical Engineering and Computer Sciences (EECS) and Computational Precision Health , with affiliations to the Berkeley AI Research (BAIR) Lab . Her research addresses AI for public health, focusing on human behavior modeling, network inference, and policy decision support. PhD in Computer Science from Stanford University (2024) Postdoctoral research in Microsoft Research's Computational Social Science group Her work spans three thematic areas: inferring human behaviors from novel data sources (search logs, mobility data), simulating behaviors with LLMs for public health applications, and AI-driven policy support through models for vaccine distribution, epidemic forecasting, and equity-focused reopening strategies. She has pioneered AI models using anonymized mobility data to analyze socioeconomic disparities in pandemic impacts. Recent publications highlight cross-disciplinary innovations: Nature (2025) perspective on AI for infectious disease modeling ACL 2025 work on human-AI interaction evaluation ICWSM 2025 paper demonstrating LLM capabilities in network generation Scientific recognition includes: Google Research Scholar Award (2025) NSF Graduate Fellowship (2024) KDD Dissertation Award (2025) Meta PhD Fellowship (2023) She advises PhD students in EECS and Computational Precision Health , emphasizing skills in ML research , interdisciplinary collaboration , and real-world impact . Her lab integrates computational methods with public health practice through partnerships with WHO , Chan Zuckerberg Biohub , and United Nations Development Programme . Current teaching includes CS 294-286: Machine Learning & Human Behavior . She explicitly invites students with interests in AI , human behavior , network science , and public health applications to apply for PhD advising.

Katarzyna WEGRZYN-WOLSKAمشاهده پروفایل

استاد

• Social Network Analysis
• Web Intelligence
• Machine Learning
• +۵ مورد دیگر

Katarzyna WEGRZYN-WOLSKA serves as Professor of Computer Science and Deputy Director of the Efrei Research Lab at Efrei Paris, with concurrent associate researcher positions at Mines ParisTech (CRI) and Télécom Paris (SAMOVAR laboratory). Her academic leadership spans social network analysis, web intelligence, and AI-driven decision systems development. Her educational foundation includes: Engineer in Electronics, Silesian Polytechnic University (1987) Master in Computer Science, University of Val d'Essonne/ENSIIE/Télécom SudParis (1996) PhD in Automation and Computer Science, MinesParisTech (2001) HDR (Habilitation to Direct Research), University of Val d'Essonne (2012) Dr. WEGRZYN-WOLSKA's research integrates four synergistic domains: Social Network Analysis (influence propagation and reputation metrics), Web Intelligence (search engine evaluation and multimodal sentiment mining), Decision Support Systems (ML-based recommendation and fuzzy logic defuzzification), and Emotion Recognition (contextual analysis via multimodal signals). Her methodological framework combines graph theory, machine learning, and human-computer interaction to address complex real-world challenges. Analysis of her 2022-2025 publications reveals strategic focus on heterogeneous graph neural networks for professional recruitment systems, explainable AI architectures, and cross-domain applications from precision agriculture (bee/horse behavior monitoring) to sustainable Industry 4.0 production. This demonstrates consistent translation of theoretical advances into tangible technological solutions. She actively contributes to major research consortia including COST Actions SHIINE (Management Committee) and cHiPSet, PNAPI digital platform for beekeepers, and EU-funded ENGINE project, demonstrating strong international collaboration capabilities. Holding HDR status since 2012, she supervises doctoral candidates while serving on program committees for premier conferences (WI, SNAA, BESC). Current work emphasizes multimodal emotion detection and AI-driven sustainability frameworks for industrial systems.

• Digital media systems
• Political communication
• Populist rhetoric
• +۵ مورد دیگر

Sina Julia Blassnig is a Full Professor at the Institute of Digital Communication and Media Innovation (IDCMI), University of Fribourg. Her research focuses on digital journalism , populist communication , and news recommender systems . She explores intersections between media systems , AI ethics , and user behavior in digital environments. Research Interests: Digital media systems Political communication Populist rhetoric Algorithmic journalism AI in news production Media effects Projects: Generative Visual AI in Swiss Journalism (FNS-funded, 2026–2030): Examines AI-generated visuals in journalism. Gratis-Abos für Jugendliche (2024–2026): Evaluates free subscription models in Swiss media. Crowding Out (completed 2025): Analyzed SRF News' impact on private media. Labs/Teams: Affiliated with the Medialab and IDCMI , focusing on digital communication innovation.