جست‌وجوی استاد و پژوهشگر

Katrin Patrzekمشاهده پروفایل

استاد

• Business Law
• International Law
• Logistics Law
• +۳ مورد دیگر

Prof. Dr. Katrin Patrzek is a faculty member at Fulda University of Applied Sciences, specializing in Business Law and International Business Law. She holds a full professorship and has contributed extensively to legal research, particularly in areas such as private international law, logistics law, and corporate taxation. Education: Studied at the universities of Gießen and Göttingen, earning a doctorate in international contract law. Research Focus: Her work spans international private law, business law, and eLearning methodologies. She has led projects related to cross-border logistics and legal frameworks for corporate succession. Publications: Authored and co-authored multiple legal textbooks and scholarly articles, including works on UN sales law, insolvency procedures, and post-reunification transitional regulations. Additional Roles: Served as Vice Dean of the Faculty of Business (FB W) and chairs examination boards. Acted as an assessor in the German Women Lawyers' Association. Teaching: Courses in business law, international law, and logistics law, with experience in vocational training and civil proceedings.

• Large Language Models
• Multilingual Machine Translation
• Vision-Language Models
• +۳ مورد دیگر

Xiaocheng Feng is a prominent researcher in computational linguistics and large language models (LLMs), with extensive contributions to multilingual systems, vision-language integration, and knowledge alignment. His work spans from 2016 to 2025, focusing on advanced topics like Mitigating hallucinations in multimodal models Efficient knowledge editing across multiple models Length-controlled text generation for black-box LLMs Improving contextual faithfulness via retrieval heads Cross-lingual connection mechanisms for fine-tuning His recent publications address critical challenges in LLMs, including knowledge misalignment, entity-level unlearning, and Pareto optimization in multilingual translation. He has explored probability density estimation for text control, adaptive context modeling in visual storytelling, and cross-lingual annotation projection for low-resource languages. Collaborations with researchers like Bing Qin, Lei Huang, and Weitao Ma highlight his central role in advancing NLP methodologies.

Erhard Rahmمشاهده پروفایل

استاد

• Data Integration
• Knowledge Graphs
• Privacy-Preserving Data Analysis
• +۴ مورد دیگر

Prof. Dr. Erhard Rahm is a leading computer science academic at the University of Leipzig , affiliated with the Institute of Computer Science under the Faculty of Mathematics and Computer Science. With over 35 years of research contributions, he specializes in scalable data integration, privacy-preserving record linkage (PPRL), and graph analytics for knowledge graphs and digital twins. Key research areas: Data Integration for Knowledge Graphs, Privacy-Preserving Data Analysis, Dynamic Graph Management Recent work focuses on hybrid digital twins, medical image analysis, and secure health data processing 2016-2021: Speaker of GI's Database Systems and Information Systems division Scientific Contributions: His 15 most recent publications (2023-2025) span: Privacy-preserving machine learning (federated learning, PPRL with LLMs) Graph-based data transformations (Temporal Knowledge Graphs, Property Graph Streams) Automated schema matching and entity resolution systems Biomedical data applications (cell confluence assessment, stress detection) Selected Honors: VLDB Ten-Year Best Paper Award (2011) ICDE Influential Paper Award (2013) MSR Outstanding Collaborator Award (2016) Leadership Roles: Currently Vice President of the Gesellschaft für Informatik (since 2022), former DFG reviewer (2016-2024), and active in NFDI infrastructure (2019-2022). He leads research at ScaDS.AI, focusing on big data integration and scalable graph analytics.

• Neural Networks
• Adaptive Resonance Theory
• Machine Learning
• +۵ مورد دیگر

Professor Ah-Hwee Tan is a distinguished faculty member at Singapore Management University's School of Computing and Information Systems, Department of Information Systems. With over 30 years of academic contributions since 1991, his research has significantly advanced neural network architectures, particularly Adaptive Resonance Theory (ART), with applications spanning multiple domains of artificial intelligence. His primary research interests include Neural Networks , Adaptive Resonance Theory , Machine Learning , Reinforcement Learning , Knowledge Graphs , Natural Language Processing , and Multi-Agent Systems . Professor Tan's work bridges theoretical neural computation with practical applications, developing novel approaches for knowledge representation, semantic understanding, and intelligent decision-making systems. His recent publications (2022-2025) demonstrate continued innovation across multiple AI subfields, with particular emphasis on hierarchical reinforcement learning, knowledge graph refinement, sentiment analysis, and federated learning architectures. The research shows a clear trajectory from foundational neural network theory toward increasingly complex real-world applications in healthcare, social media analysis, and multi-agent coordination. Professor Tan has mentored numerous researchers who have become significant contributors in their own right, including Budhitama Subagdja, Shubham Pateria, and Di Wang. His collaborative work spans international institutions, reflecting his standing in the global AI research community. His research has been consistently published in top-tier venues including IEEE Transactions, Neural Networks, ACM journals, and major AI conferences (AAAI, IJCAI), demonstrating both theoretical rigor and practical impact across computer science and interdisciplinary applications.

• Natural Language Processing
• Information Retrieval
• Web Personalization
• +۶ مورد دیگر

Wolfgang Nejdl is a distinguished Professor at Leibniz University Hannover, working within the Faculty of Mathematics and Computer Science and affiliated with the Institute of Information Systems. With an extensive publication record spanning over two decades, he has established himself as a leading researcher in Natural Language Processing, Information Retrieval, and Web Personalization. His work bridges theoretical advances with practical applications, particularly in clinical NLP and semantic web technologies. Nejdl's research interests encompass a broad spectrum of topics including Natural Language Processing, Information Retrieval, Web Personalization, Semantic Web technologies, Machine Learning applications, Clinical NLP, and Recommender Systems. His recent work has focused on critical challenges such as clinical outcome prediction using MIMIC datasets, financial literacy evaluation of large language models, and developing resources for low-resource languages like Tigrinya. He has made significant contributions to understanding data drift in clinical applications and developing interpretable AI systems for healthcare. His publication record shows a consistent trajectory of impactful research, with recent articles demonstrating his ability to tackle emerging challenges in NLP and AI. From his foundational work on web personalization using ODP metadata to his current research on clinical NLP and low-resource language processing, Nejdl has consistently addressed important problems at the intersection of information systems and human needs. His work on stance detection incorporating toxicity and morality analysis represents innovative approaches to understanding social media discourse. Among his notable achievements are the development of the EDUTELLA P2P infrastructure based on RDF, significant contributions to boilerplate detection algorithms, and pioneering work on preventing shilling attacks in recommender systems. His research has been widely cited, reflecting its substantial impact on the fields of web science and natural language processing. Nejdl has supervised numerous students and collaborated extensively with researchers worldwide, particularly with Alexander Loeser, Jens-Michalis Papaioannou, and Paul Grundmann. His work demonstrates a consistent focus on practical applications of theoretical advances, particularly in healthcare and web technologies. He has also worked on important infrastructure projects like the L3S Research Center, contributing to the broader academic and technological ecosystem.

• Computer Vision
• Image Processing
• Biometrics
• +۱۲ مورد دیگر

Pankaj Kumar Sa is an active academic researcher in computer science, specializing in computer vision, biometrics, and artificial intelligence. He has published extensively from 2006 to 2025 in top-tier journals and conferences, with a strong focus on person re-identification, deep learning, image processing, and low-resource language technologies. His collaborative work with researchers like Sambit Bakshi and Banshidhar Majhi highlights his role in a vibrant research community, likely within an Indian academic institution. His research interests span a wide range of topics, including: Computer Vision and Image Processing Biometrics (Iris, Ear, Periocular) Person Re-identification and Surveillance Deep Learning and Neural Networks Natural Language Processing for Indian Languages (e.g., Odia) UAV and Satellite-based Aerial Imaging Video Anomaly Detection His recent publications from 2023 to 2025 showcase a trend toward practical and socially relevant applications, such as emergency crowd monitoring, agricultural prediction, and low-resource language support. These works leverage advanced deep learning models and contribute valuable datasets like RGBT-1K and NITRDrone. The primary themes include multimodal sensing, robustness under real-world conditions, and efficient model design. Pankaj Kumar Sa has mentored and collaborated with several researchers, including Nayan Kumar Subhashis Behera, Tanmay Kumar Behera, and Tusarkanta Dalai, indicating an advisory or supervisory role. His work often addresses challenges in smart cities, security, and healthcare, demonstrating a commitment to impactful research.

• Multiagent Systems
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Gerhard Weiss is a Professor at the Department of Data Science and Knowledge Engineering (DKE) at Maastricht University in the Netherlands. With a research career spanning over three decades, he has made significant contributions to the fields of multiagent systems, artificial intelligence, and machine learning. His work bridges theoretical foundations with practical applications across diverse domains including healthcare, social networks, and negotiation systems. Professor Weiss's research interests center around autonomous systems, particularly those inspired by biological principles. He has extensively explored multiagent coordination, negotiation frameworks, and transfer learning techniques. His work often combines theoretical rigor with practical implementations, as evidenced by his involvement in projects like Swarmlab@Work for RoboCup competitions. More recently, his research has expanded into medical informatics, focusing on drug-drug interactions, adverse reaction prediction, and semantic enhancement of biomedical datasets. An analysis of his recent publications reveals a clear trajectory from fundamental multiagent systems research toward applied data science with significant impact in healthcare domains. While maintaining strong theoretical foundations in areas like reinforcement learning and entity resolution, Weiss has increasingly focused on solving real-world problems through interdisciplinary collaboration with medical researchers and data scientists. Throughout his career, Professor Weiss has maintained an active research program with numerous collaborators, most notably Karl Tuyls with whom he has co-authored over 30 publications. His work demonstrates a consistent pattern of bridging theoretical computer science with practical applications across various domains. Professor Weiss leads research in the Swarmlab at Maastricht University, focusing on swarm intelligence and multi-robot systems. His team develops innovative approaches to complex coordination problems, often drawing inspiration from biological systems and social dynamics.

Yoshiyasu Raiمشاهده پروفایل

استادیار

• Theoretical Econometrics
• Statistical Modeling
• Econometric Theory
• +۳ مورد دیگر

Prof. Yoshiyasu Rai is an Assistant Professor of Theoretical Econometrics and Statistics at the University of Mannheim's Department of Economics. His research focuses on econometrics and statistical modeling, with a strong emphasis on machine learning and knowledge graph embeddings. He holds a Ph.D. in Economics from the University of Wisconsin-Madison and degrees from Keio University, Tokyo. His work bridges theoretical econometrics with computational methods, addressing challenges in large-scale data analysis and distributed systems. Key contributions include advancements in knowledge graph embeddings, parameter server optimization, and scalable machine learning frameworks. Education: BA and MA in Economics (Keio University), Ph.D. in Economics (University of Wisconsin-Madison). Research Interests: Theoretical Econometrics Machine Learning Applications Knowledge Graphs and Embeddings Distributed Systems for Large-Scale Data Optimization Algorithms Articles trends focus on knowledge graph embeddings, parameter server design, and scalable machine learning techniques. Recent work emphasizes adaptive systems, dynamic resource allocation, and reproducible research through libraries like LibKGE. Labs/Teams: Involved in the Junior Professorship for Theoretical Econometrics and Statistics at the University of Mannheim, focusing on interdisciplinary data analysis projects.

Frank Hopfgartnerمشاهده پروفایل

استاد

• Information Retrieval
• Gamification in Education
• Machine Learning
• +۵ مورد دیگر

Prof. Frank Hopfgartner is a Professor at the University of Koblenz's Institute of Computer Science, Department 4. His research focuses on information retrieval, gamification in education, machine learning ethics, digital preservation, and user modeling. He leads projects involving AI-driven healthcare triage systems, bias-aware search engines, and participatory web archiving initiatives. His academic work bridges technical innovation with societal impact, addressing challenges in pandemic response systems, generational engagement in education, and ethical AI development. Key areas of contribution include lifelog data retrieval, knowledge graph alignment, and misinformation analysis during crises. Notable ongoing projects include: FAIR clustering algorithms for ethical machine learning Privacy-preserving email archive exploration Design of gamified IR systems for Gen Z learners He advises external doctoral student Dr. Matthias Lohr and collaborates extensively on international evaluation frameworks for information systems (e.g., NTCIR, CLEF). His research group maintains strong ties with institutions like National Museums Liverpool and NHS data networks.

André Niedostadekمشاهده پروفایل

استاد

• Commercial Law
• Labor Law
• Social Law
• +۷ مورد دیگر

Prof. Dr. André Niedostadek is a Professor at Harz University of Applied Sciences, holding the Chair of Commercial Law, Labor Law, and Social Law. Since the summer semester of 2022, he has served as Vice Dean of the Department and Public Relations Officer at the Halberstadt Department. He is an academic member of the Department Council and Examination Board, actively participating in academic governance. His educational background includes law studies at the Universities of Münster and Aberystwyth (Wales), a research stay at Gonville & Caius College (Cambridge University), and a doctorate from the University of Münster (2000). He also holds an LL.M. in Intellectual Property Law and has completed training as a business mediator (Fernuniversität Hagen) and journalist (Freie Journalistenschule Berlin). Niedostadek's research focuses on: German and European commercial, labor, and social law frameworks Commercial mediation and alternative dispute resolution techniques Legal history and philosophical foundations of law Personal development strategies for academic and professional success Contemporary topics including digitalization in legal practice and workplace culture transformation His publications demonstrate consistent focus on practical legal applications, with recent works addressing digital transformation in legal systems, European regulatory frameworks, and innovative conflict resolution methods. Article themes frequently intersect with contemporary societal challenges such as data privacy, healthcare regulations, and evolving workplace dynamics.

Anjalie Fieldمشاهده پروفایل

استادیار

• Ethics in Artificial Intelligence
• Computational Social Science
• Natural Language Processing (NLP)
• +۳ مورد دیگر

Anjalie Field is an Assistant Professor in the Computer Science Department at the Whiting School of Engineering, Johns Hopkins University. She is also affiliated with the Center for Language and Speech Processing (CLSP), focusing on the intersection of ethics, social science, and natural language processing. Her research examines: Developing language models to address societal challenges like discrimination and propaganda Critical evaluation of AI pipelines Applications of NLP in high-stakes domains (child welfare, police accountability) Interdisciplinary collaborations across social sciences, astronomy, and public policy Notable scientific achievements include the 2022 Wikimedia Foundation Research Award of the Year . Her publications demonstrate expertise in bias detection, ethical AI, and computational social science methods.

• Semantics
• Syntax
• Persian Linguistics
• +۷ مورد دیگر

Fereshteh Modarresi is a Senior Researcher at Humboldt University of Berlin specializing in theoretical and experimental linguistics, with primary focus on semantics and syntax of Persian and German languages. She is actively involved in the DFG-funded project ANAPIN (Anaphoric potential of incorporated nominal and weak definitions) under Research Area 3 'Syntax & Lexicon', collaborating extensively with Professor Manfred Krifka. Her academic work bridges cross-linguistic analysis with empirical methodologies. Her research centers on semantic-syntactic interfaces, particularly investigating anaphora, noun incorporation, weak definites, bare nouns, and generic sentences. She examines how these phenomena manifest in Persian (a differential object marking language) compared to German, revealing universal constraints and language-specific patterns. Recent work explores similative plurals, durative markers, and assertion modifiers through both theoretical frameworks and experimental designs, demonstrating how morphosyntactic structures interact with discourse interpretation and pragmatic inference. Analysis of her 2021-2024 publications reveals three dominant trends: (1) systematic comparison of anaphoric potential across nominal types (weak definites, bare nouns, incorporated nominals), (2) experimental validation of semantic theories using Persian-German contrasts, and (3) investigation of homogeneity effects in plural interpretations. Her work increasingly integrates psycholinguistic methods, as seen in studies on trustworthiness markers and number agreement phenomena, pushing the boundaries of formal semantics with empirical evidence. Scientific Awards: No awards documented in provided materials. Advising and Grants: No student supervision details or grant information appears in available records. Her research is primarily conducted within the DFG ANAPIN project framework. Research Infrastructure: Modarresi operates within Humboldt University's linguistics ecosystem as part of the DFG project ANAPIN team. Her work leverages experimental labs for psycholinguistic testing and maintains strong connections with international Iranian linguistics networks, evidenced by frequent presentations at NACIL conferences. Collaboration with Krifka's research group provides access to theoretical frameworks in formal semantics and cross-linguistic databases.

Johanna Geißمشاهده پروفایل

پژوهشگر

• Event Detection
• Information Extraction
• Information Retrieval
• +۵ مورد دیگر

Johanna Geiß is a postdoctoral researcher at the Institute of Computer Science , Heidelberg University, specializing in Natural Language Processing , Information Extraction , and Event Detection . She contributes to projects like SCIDATOS (sepsis diagnosis) and EventAE (event-based Linked Data exploration). Education: PhD from University of Cambridge (2011), Magister Artium in Computational Linguistics (Heidelberg, 2006) Her research integrates Geoparsing , Social Network Analysis , and Graph Theory for tasks such as toponym disambiguation and entity resolution. Recent work includes frameworks like HeidelPlace and tools for semantic word clouds. Key awards include the 2010 Lundgren Research Award and multiple grants from the EPSRC and Cambridge European Trust. She has taught courses on Information Networks and Data Mining at Heidelberg University. As a postdoc , she advises on scientific computing applications in healthcare and contributes to open-source tools like NECKAr and EventAE .

• Database Systems
• Query Processing
• Data Stream Management
• +۵ مورد دیگر

Mirek Riedewald is a Professor in the Department of Computer Science at Northeastern University's College of Engineering. With a prolific publication record spanning from 1999 to 2025, he has established himself as a leading researcher in database systems, particularly in query processing, join algorithms, and exploratory search. His work bridges theoretical database foundations with practical applications in data visualization and data lake management. Dr. Riedewald's research focuses on innovative approaches to database query processing, with recent work emphasizing ranked enumeration algorithms, relational diagram visualization, and data lake disambiguation. His publications in top-tier venues like SIGMOD, VLDB, and ICDE demonstrate his significant contributions to the field. He has developed novel techniques for efficient computation of quantiles over joins, any-k algorithms for ranked enumeration, and relationship-based semantic table union search through his SANTOS system. His recent publications reveal a growing interest in the intersection of database systems with fairness considerations, as seen in his work on fixing top-k rankings that lack individual fairness. He also explores the visualization of complex database queries through relational diagrams, making query understanding more accessible. His research has evolved from traditional database topics like data cubes and stream processing to more contemporary challenges in large-scale data management and analysis. Dr. Riedewald has maintained a strong collaborative network, with frequent co-authors including Wolfgang Gatterbauer (31 papers), Johannes Gehrke (23 papers), and Nikolaos Tziavelis (15 papers). His work demonstrates both theoretical depth and practical relevance, addressing real-world challenges in data management systems. His research group has made significant contributions to exploratory search in databases through the ExploreDB workshop series, which he co-organized for multiple years. He has also contributed to important reference works, including chapters in the Encyclopedia of Database Systems on topics like event and pattern detection over streams and database techniques for scientific simulations.

Helmut Philipp Austمشاهده پروفایل

استاد

• International Law
• Public Law
• State Responsibility
• +۳ مورد دیگر

Helmut Philipp Aust is a full Professor of Public Law and Internationalization of the Legal System at the Faculty of Law , Freie Universität Berlin, since October 2016. He has held visiting professorships at Georgia State University College of Law (2024), Tel Aviv University (2024), and Université Paris II (2022), alongside senior fellowships at Melbourne Law School (2018/2019). His work bridges international law, constitutional law, and urban governance, with a focus on cities' evolving roles in global legal systems, state responsibility, and human rights. Education : Habilitation (2016) and Dr. iur. (2009) from Humboldt-Universität zu Berlin; legal education at Georg-August-Universität Göttingen and Université Paris XII. Research Themes : Cities in international law, state responsibility, foreign relations law, planetary boundaries, and algorithmic challenges to human rights. Awards : Promotionspreis Humboldt-Universität (2009), Hermann Mosler-Preis (2009). Leadership : Co-Chair of the International Law Association's Committee on Urbanisation (since 2023), Board Member of the European Society of International Law (2023–2025), and editorial roles in Elgar International Law Studies Series and Max Planck Encyclopedia of Comparative Constitutional Law . Recent Articles : Analyze cities' legal autonomy, climate governance, international organizations' accountability, and rule of law erosion in Germany.