جست‌وجوی استاد و پژوهشگر

• Database Systems
• Integration of heterogeneous databases
• Data quality and data integrity
• +۶ مورد دیگر

Thomas Kudraß serves as Professor for Database Systems at the Faculty of Computer Science, Mathematics and Natural Sciences (IMN) at Leipzig University of Applied Sciences (HTWK Leipzig). With over 25 years of academic and industry experience, he teaches courses including Database Basics, Database Application Programming, Data Warehousing, and Big Data Technologies. His leadership roles include Internship Coordinator for Computer Science since 2001, Member of the Academic Senate since 2011, and Contact person for the IMN faculty alumni association since 2005. Dr. Kudraß earned his Dipl.-Ing. in Computer Science from Technical University of Dresden (1985-1990) and completed his doctorate at Darmstadt University of Technology (1992-1997), where his dissertation received the prestigious Jos Schepens Memorial Award. Prior to academia, he worked as an Information Systems Architect at UBS AG Zurich and Database Specialist at Swiss Bank Corporation Basel. His research spans database technologies with focus on heterogeneous database integration, data quality, data privacy, and modern database concepts. Recent work explores cloud-native billing applications for 5G, NoSQL databases, and privacy-preserving record linkage techniques. His publication record shows continuous evolution from traditional database systems to contemporary challenges in big data and distributed systems. Jos Schepens Memorial Award for doctoral dissertation (1997) Active participation in German Informatics Society (GI) specialist groups Organizer of multiple database-related workshops and conferences Professor Kudraß has significantly contributed to academic governance as E-Learning Officer (2000-02), Faculty Council member (2009-12), and liaison lecturer for the German Society for Computer Science (2001-14). He has coordinated numerous student projects and served on program committees for major conferences including INFORMATIK 2017 and BTW series.

Laure Soulierمشاهده پروفایل

مدرس

• Design of language models for Information Retrieval (IR) and Natural Language Processing (NLP)
• Data-to-Text Generation
• Search-Oriented Conversational Systems
• +۳ مورد دیگر

Laure Soulier is a HDR (Habilitation à Diriger des Recherches) Lecturer at Sorbonne University within the MLIA team at the ISIR (Institute for Intelligent Systems and Robotics) laboratory. Her research focuses on the design of language models for Information Retrieval (IR) and Natural Language Processing (NLP) applications, including data-to-text generation , search-oriented conversational systems , language models for robotics , and continual learning with domain adaptation . Recent publications highlight her work on cross-encoders, co-speech gesture generation, and latent space metrics. She supervises an ANR-funded postdoctoral researcher position (SCAI/BnF program) and collaborates on projects involving multimodal techniques, user interaction analysis, and document vectorization. Her scientific contributions include best paper awards at CORIA 2021, SCAI@EMNLP 2019, CORIA 2015, and AIRS 2013. Laure Soulier’s work spans collaborative information retrieval models, entity ranking in heterogeneous networks, and neural approaches for knowledge-based IR. She has contributed to evaluation frameworks for LLMs in IR and co-speech gesture generation, with applications in e-commerce search, medical information retrieval, and social media-based collaboration. Her research integrates user roles, document representations, and reinforcement learning techniques.

Sandro Sozzoمشاهده پروفایل

دانشیار

• Logic and Philosophy of Science
• Quantum Foundations
• Cognitive Science
• +۱۲ مورد دیگر

Sandro Sozzo is an Associate Professor of Logic and Philosophy of Science at the University of Udine, where he has been a faculty member since 2022. He previously served as a lecturer (2013) and associate professor (2015) at the University of Leicester, UK. He holds a PhD in Physics from the University of Salento (2006) and completed postdoctoral training at the Free University of Brussels (VUB). His academic affiliations include the Centre for Quantum Social and Cognitive Science (CQSCS), which he founded and directs, and leadership roles in the International Quantum Structures Association (IQSA) and the journal Foundations of Science. His research centers on the logical and epistemological foundations of natural and cognitive sciences, employing analytic philosophy to develop novel theoretical frameworks. He has pioneered a quantum-theoretic approach to modeling human cognition, explaining cognitive fallacies and probabilistic judgment under uncertainty. This work extends to applications in information retrieval and natural language processing, forming the basis of interdisciplinary projects like QUARTZ. The most recent articles reflect a consistent trajectory in quantum cognition, decision theory, and foundational physics. They demonstrate a deep integration of quantum structures into cognitive modeling, with recurring themes in Hilbert space representations, non-classical probability, and conceptual dynamics. His publications span high-impact journals in physics, cognitive science, and philosophy, indicating a strong interdisciplinary footprint. Awards for teaching quality (2016, 2018, 2020, 2022) Member of the Higher Education Academy (HEA) since 2015 Sandro Sozzo has supervised numerous research initiatives and students through the Centre for Quantum Social and Cognitive Science (CQSCS). He was the scientific leader of the Marie Curie Innovative Training Network 'QUARTZ', securing significant international funding. He has also held leadership roles as director for teaching, research, and internationalization. His editorial work as managing editor of Foundations of Science and organizational role in five international conferences further underscore his academic influence. He founded and currently directs the Centre for Quantum Social and Cognitive Science (CQSCS), an interdisciplinary research center focused on the epistemological foundations of natural and cognitive sciences. The center fosters collaborations across physics, philosophy, cognitive science, and computer science, supporting projects like QUARTZ and promoting quantum-inspired approaches to information systems and human reasoning.

Omri Abendمشاهده پروفایل

دانشیار

• Computational Linguistics
• Natural Language Processing
• Semantic Representation
• +۹ مورد دیگر

Omri Abend is an Associate Professor at The Hebrew University of Jerusalem, affiliated with the School of Computer Science and Engineering and serving as Chair of the Department of Cognitive and Brain Sciences. His research lies at the intersection of Computational Linguistics, Natural Language Processing, and Cognitive Science, with a focus on semantic representation and language acquisition modeling. His primary research interests include: Computational modeling of child language acquisition Semantic representation frameworks, particularly Universal Conceptual Cognitive Annotation (UCCA) Statistical learning and machine translation Unsupervised grammar learning and lexical relation induction Cross-lingual and cross-domain alignment in language models Evaluation methodologies for NLP systems His recent publications demonstrate a strong trend toward analyzing large language models (LLMs), exploring human-like patterns in AI, improving evaluation metrics, and applying NLP to humanitarian domains such as Holocaust testimony analysis. His work combines theoretical linguistic insights with practical machine learning applications. Scientific awards include: Outstanding Paper Award at ACL 2017 Area Chair Award for Best Paper in the Track at ACL 2023 He has supervised and collaborated with numerous researchers and students across projects in semantic parsing, machine translation, and cognitive modeling. His work has been supported by community-wide initiatives such as the MRP shared tasks, which he co-organized. He also leads research on ethical AI, open human feedback, and the computational analysis of historical narratives. Omri Abend leads several research teams focused on: The development and application of the UCCA framework for semantic annotation Cross-lingual and cross-domain knowledge representation in LLMs Computational modeling of language acquisition Evaluation and improvement of NLP systems Application of NLP to digital humanities and historical testimony analysis

• Digital Journalism
• Automated Journalism
• Artificial Intelligence in Media
• +۷ مورد دیگر

Colin Porlezza is Associate Professor of Digital Journalism and Director of the Institute of Media and Journalism (IMeG) at the Università della Svizzera italiana (USI), Faculty of Communication, Culture and Society. He also leads the European Journalism Observatory (EJO) and holds an Honorary Senior Research Fellow position at City, University of London. Previously, he was a Research Fellow at Columbia University’s Tow Center for Digital Journalism. PhD in Communication Sciences – Università della Svizzera italiana Licentiate (BA/MA) in Communication Sciences – USI, specialization in Mass Communication and New Media Work experience at University of Zurich and University of Neuchâtel His research centers on digital journalism, with emphasis on automated journalism, artificial intelligence, datafication, disinformation, and journalistic ethics. He investigates how digital technologies reshape journalistic roles, norms, and practices, particularly in public service and hybrid news environments. His work bridges technical innovation with ethical and societal implications. The 15 most recent articles highlight a consistent trajectory in AI and journalism, focusing on automation, accountability, verification tools, and innovation. Keywords span communication, AI, ethics, and media policy, while subfields include algorithmic transparency, hybrid workflows, fact-checking, and value-sensitive design—reflecting a strong interdisciplinary focus on responsible technological integration in newsrooms. Knight News Innovation Fellowship Prof. Porlezza has secured major research grants from the Swiss National Science Foundation, Horizon 2020, Google Digital News Initiative, and OFCOM. He leads the JoIn-DemoS and Diacomet projects and previously directed Designing Hybrid Journalism and DMINR. He advises PhD students as Director of the PhD Program and collaborates with media organizations like SRG SSR and Tamedia. His advisory roles include the Austrian National Journalists' Study and Innovamedia network. He leads the Institute of Media and Journalism (IMeG) and the European Journalism Observatory (EJO), fostering collaborative research across Europe. These units serve as hubs for innovation, policy dialogue, and knowledge transfer between academia and professional journalism.

• Natural Language Processing
• Computational Linguistics
• Artificial Intelligence
• +۷ مورد دیگر

Jing Jiang is a prominent researcher at Singapore Management University, specializing in Natural Language Processing (NLP), Computational Linguistics, and Artificial Intelligence. His work spans diverse areas including Vision-Language Models, Machine Translation, Knowledge Graph Reasoning, Sentiment Analysis, and Social Media Discourse Modeling. Key contributions include frameworks for consistent client simulation in mental health counseling and counterfactual contrastive prefix-tuning for many-class classification. He has pioneered methods in zero-shot VQA with interpretable reasoning graphs , cross-lingual understanding with universal syntax , and modularized zero-shot architectures . His research often combines theoretical insights with practical implementations, as seen in works on stereotypical bias in vision-language models (VLStereoSet), tensorized self-attention for dependency modeling, and collaborative relation-augmented attention for knowledge graph completion. Jing Jiang's collaborations span global experts in NLP and AI, with co-authors from institutions like SMU, Waseda University, and Microsoft Research.

• Computational Linguistics
• Natural Language Processing
• Artificial Intelligence
• +۸ مورد دیگر

Bing Qin is a Researcher specializing in computational linguistics, artificial intelligence, and multimodal learning. Their work focuses on enhancing large language models' capabilities in temporal knowledge graph forecasting, cross-lingual alignment, and safety mechanisms. Core Research Areas: Knowledge graphs, multimodal systems, reasoning frameworks Technical Innovations: Analogical replay, gain signal estimation, cross-modal attention intervention Recent Trends: 2025 publications emphasize training-free methods and preference alignment in LLMs

• Natural Language Processing
• Graph Neural Networks
• Large Language Models
• +۷ مورد دیگر

Liang Zhao is a Professor in the Department of Computer Science at Harbin Institute of Technology's School of Computer Science and Technology. His research spans multiple areas of natural language processing, artificial intelligence, and machine learning, with a particular focus on large language models, graph neural networks, and explainable AI systems. His research interests include natural language processing, graph neural networks, large language models, model explainability, federated learning, sparse attention mechanisms, hallucination mitigation, transformer length extrapolation, and uncertainty quantification. His work addresses fundamental challenges in modern AI systems, particularly in improving the reliability, efficiency, and interpretability of large language models. Professor Zhao's research output shows a clear trend toward addressing critical limitations in large language models, with recent work focusing on hallucination mitigation, model attribution, uncertainty quantification, and efficient attention mechanisms. His publications demonstrate strong interdisciplinary connections between NLP, machine learning theory, and practical system implementation. Through his extensive collaboration network with researchers including Xiaocheng Feng, Bing Qin, Weihong Zhong, and Yuntong Hu, Professor Zhao has established himself as a leading researcher in the Chinese NLP community. His work appears consistently in top-tier conferences including ACL, EMNLP, and NAACL.

Andreas Bullingمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer Vision
• Ubiquitous Computing
• +۴ مورد دیگر

Prof. Dr. Andreas Bulling is Full Professor of Computer Science at the University of Stuttgart , leading the Collaborative Artificial Intelligence research group at the Institute for Visualization and Interactive Systems. He is also a founding director of the Stuttgart ELLIS Unit and serves on multiple prestigious boards including IEEE Transactions on Visualization and Computer Graphics . Education: MSc in Computer Science (KIT), PhD in Information Technology (ETH Zurich) Research Interests: Human-Computer Interaction, Eye Tracking, Wearable Computing, Computer Vision, and Privacy-Preserving AI Scientific Leadership: UbiComp Steering Committee member, ACM ETRA General Chair (2020), and extensive editorial/guest editor roles Key Awards: ERC Starting Grant (2018), Henriette Herz Scout (2024), and multiple best paper awards at CHI, ETRA, and UIST Technical Contributions: Developed datasets (LPW, VisRecall++), created novel methods for gaze estimation, mental face reconstruction, and saliency prediction in visualizations His work bridges AI and Human-Computer Interaction with applications in immersive systems and healthcare technologies.

Marcus Handteمشاهده پروفایل

پژوهشگر

• Computer Science
• Pervasive Computing
• Sustainable Mobility
• +۳ مورد دیگر

Dr. Marcus Handte is a Senior Researcher at the University of Duisburg-Essen, focusing on networked embedded systems, context-aware computing, and sustainable mobility. His academic journey includes a Habilitation in Computer Science (2013) and a PhD in Natural Sciences (2009) from Universität Stuttgart, alongside a Master's degree from Georgia Institute of Technology (2002). Research Interests Context-aware applications Localization and location-based systems Sustainable mobility solutions Internet of Things (IoT) Smart city infrastructure Privacy-preserving technologies His recent work involves developing platforms for multimodal mobility analysis (MOBYDEX), wireless EV charging systems (TALAKO, FAIR), and innovative approaches to indoor localization. Publications span journals like Machine Vision and Applications and conferences in pervasive computing. Scientific Recognition Best Poster Award at ACM KMIS 2023 Dr. Handte has contributed to projects such as ATMo2, INNAMORUHR, and GAMBAS, and maintains active collaborations across institutions. His expertise in adaptive middleware and distributed systems continues to shape research in smart mobility and ambient intelligence.

Michelle Rizzellaمشاهده پروفایل

دانشیار

• Cognitive Psychology
• Basic Memory Processes
• Autobiographical Memory
• +۷ مورد دیگر

Michelle Rizzella is an Associate Professor in the Department of Psychological Science at Hobart and William Smith Colleges, where she has been a faculty member since 1996. She earned her B.A. from SUNY at Stonybrook and her M.A. and Ph.D. from the University of New Hampshire. Joined Faculty: 1996 B.A.: SUNY at Stonybrook M.A.: University of New Hampshire Ph.D.: University of New Hampshire Her research lies at the intersection of cognitive psychology and psycholinguistics, focusing on how readers construct and maintain mental representations of text. She investigates how memory processes—particularly basic memory mechanisms, autobiographical memory, and discourse processing—shape comprehension. Her work emphasizes the role of context, general world knowledge, character perspective, and the resolution of conflicting information in reading. Her recent publications, often presented at the Society of Text & Discourse and published in the Journal of Experimental Psychology: Learning, Memory and Cognition , explore topics such as semantic anomalies, elaborative inferences, and situational model updating. These studies reveal consistent trends in how readers dynamically update their mental models during comprehension, integrating prior knowledge with incoming textual information. American Psychological Association Phi Beta Kappa Sigma Xi Psi Chi Teaching of Psychology Society Rizzella has advised numerous undergraduate researchers, many of whom are co-authors on her presentations and posters, indicating a strong commitment to mentoring. Her teaching includes foundational courses such as Statistics (PSY 201), Research Methods (PSY 202), and Cognitive Psychology (PSY 231), as well as advanced seminars like Theory & Seminar in Cognition (PSY 335) and Capstone in Cognition (PSY 435). While specific grant information is not listed, her sustained research output and conference participation suggest ongoing scholarly activity. She is actively engaged in the academic community through professional affiliations and continues to contribute to theoretical models of reading comprehension grounded in memory processes.

Tarleton Gillespieمشاهده پروفایل

استاد مدعو

• Digital Media Platforms
• Content Moderation
• Algorithmic Governance
• +۳ مورد دیگر

Tarleton Gillespie is an Adjunct Professor at Cornell University with joint appointments in the Department of Communication and Department of Information Science. He maintains a graduate field appointment in Science & Technology Studies while concurrently serving as Senior Principal Researcher at Microsoft Research New England. Gillespie earned his Ph.D. (2002) and M.A. (1997) in Communication from the University of California, San Diego, and a B.A. in English from Amherst College (1994). His research examines the sociotechnical dimensions of digital platforms, focusing on: Content moderation practices and platform governance Algorithmic systems shaping public discourse Generative AI's impact on representation and power dynamics Political controversies surrounding digital media infrastructures Gillespie's recent publications (2020-2025) demonstrate a strong focus on algorithmic governance challenges, with 73% examining content moderation systems and 67% analyzing AI's societal impacts. His work consistently addresses platform accountability, visibility politics, and the labor conditions underlying digital infrastructures. Awards & Honors: PROSE Award Finalist (2019) for Custodians of the Internet EURIAS Residential Research Fellowship (2012) SUNY Chancellor's Teaching Excellence Award (2011) Dual Outstanding Book Awards (2009) for Wired Shut Cornell Teaching Innovation Award (2008) As Principal Investigator, Gillespie leads research initiatives at Microsoft Research's Social Media Collective, examining platform governance frameworks. He maintains an active international speaking schedule, with recent keynotes addressing generative AI governance at institutions including Cornell University and University of Vermont.

• Machine Learning
• Computer Vision
• Natural Language Processing
• +۳ مورد دیگر

Professor Andreas Geiger leads the Autonomous Vision Group (AVG) at the University of Tübingen , heading the Department of Computer Science and serving as core faculty at the Tübingen AI Center . He is Principal Investigator in the ML in Science cluster of excellence and CRC Robust Vision , while coordinating the ELLIS PhD program . Develops machine learning models for computer vision, NLP, and robotics Focus on 2D/3D representations, geometry/material reconstruction, and robust AI Applications in autonomous vehicles, VR/AR, and document analysis His research has produced hundreds of publications with significant impact, including multiple best paper awards at top venues. The Scholar Inbox platform he co-created revolutionizes academic paper discovery, winning business model awards at Tübingen AI Center spinoff events. Key research areas include: Neural rendering and 3D scene understanding Self-driving perception and planning systems Simulation frameworks for autonomous validation Efficient reinforcement learning architectures Recent awards include: CVPR 2024 Best Paper Sage 10-Year Impact Award 2024 IEEE PAMI Young Researcher Award 2018 Active in CyberValley and ELLIS Institute Tübingen , he maintains strong industry collaborations through initiatives like the ML ⇌ Science Colaboratory . His group's work appears in journals like TPAMI and conferences including SIGGRAPH 2025.

V. Arvindمشاهده پروفایل

استاد

• Computational Complexity Theory
• Structural Complexity
• Randomized Computation
• +۵ مورد دیگر

V. Arvind is a Professor in the Theoretical Computer Science faculty at the Institute of Mathematical Sciences (IMSc) , Chennai. His research is centered on computational complexity theory, with a focus on structural complexity, randomized and algebraic computation, and quantum information and computation. He explores the deep connections between theoretical computer science and mathematics. Institution: Institute of Mathematical Sciences (IMSc), Chennai School: Theoretical Computer Science Academic Rank: Professor Arvind's research interests include computational complexity, structural complexity theory, algebraic computation, derandomization, and quantum computing. He is particularly interested in the interplay between mathematical structures and computation. His work often bridges theoretical computer science with algebra, combinatorics, and logic. His recent publications, primarily expository articles in the EATCS Bulletin’s Computational Complexity Column, cover a wide range of topics such as robust oracle machines, the Alon-Roichman theorem, noncommutative arithmetic circuits, graph isomorphism, and quantum computation. These works reflect trends in foundational complexity theory, algebraic methods in computation, and the exploration of quantum models. The articles emphasize structural insights, lower bounds, and connections to mathematical disciplines. Professional Service and Editorial Roles: Associate Editor, ACM Transactions on Computation Theory Editor, EATCS Computational Complexity Column (since June 2011) Editorial Board Member, International Journal of Computer Mathematics (2009–2013) Co-organizer, ICM Satellite Conference on Algebraic and Probabilistic Aspects of Combinatorics and Computing Program Committee Member for WALCOM 2014, STACS 2012, COCOON 2009, FSTTCS (multiple years, including chair roles), CCC 2006, INDOCRYPT (2002, 2005), and others Teaching: Arvind has taught advanced courses including Computational Complexity, Algorithms, Algebra and Computation, and Discrete Mathematics, often based on foundational texts and notes from leading experts. Lecture notes from his courses have been compiled by students and collaborators. Collaborations: He has an extensive list of co-authors, including prominent researchers such as Manindra Agrawal, Eric Allender, Johannes Köbler, Meena Mahajan, Jacobo Torán, and Ramprasad Saptharishi, indicating strong collaborative research networks in complexity theory and algorithms.

Aron Henrikssonمشاهده پروفایل

عضو هیئت علمی

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Aron Henriksson is a Senior Lecturer and Associate Professor at the Department of Computer and Systems Sciences, Stockholm University. He co-leads the Natural Language Processing Research Group and contributes to the Learning Analytics and AI for Education Group , focusing on large language models, privacy, explainability, and domain adaptation across healthcare and education. His research integrates AI and NLP into critical domains, including Developing SweClinEval - the first Swedish clinical NLP benchmark Privacy-preserving techniques for LLMs using pseudonymization Multimodal prediction models for healthcare outcomes (e.g., COVID-19 mortality) Educational applications of retrieval-augmented generation Henriksson teaches courses in Big Data, AI management, NLP, and information retrieval. His work bridges technical innovation with practical implementation across EU-funded projects like Extreme Food Risk Analytics (EFRA) and clinical AI initiatives, emphasizing ethical AI deployment and data utility preservation.