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اطلاعات پروفایل‌ها از صفحات عمومی دانشگاه‌ها گرفته شده و ممکن است به‌روز نباشد.

Mariya Tonevaمشاهده پروفایل

پژوهشگر

Max Planck Institute for InformaticsGermany

Mariya Toneva is a tenure-track faculty member at the Max Planck Institute for Software Systems , conducting groundbreaking research at the intersection of Machine Learning , Natural Language Processing , and Neuroscience . She leads the Bridging AI and Neuroscience (BrAIN) group , focusing on computational models that align AI systems with human brain processes. Her work aims to enhance both AI capabilities and neuroscience understanding through this cross-disciplinary approach. Actively recruiting postdocs, PhDs, and research interns in areas like code/text representation, brain-AI alignment, and neuroimaging data analysis Collaborator on NIH-funded projects using fMRI and neuropixel data Research Themes : Her group explores neural mechanisms of language processing, event segmentation in narratives, memory reactivation via music, and effective human-AI collaboration frameworks. Key methods include LLM analysis, cross-modal similarity metrics, and naturalistic task-based fMRI studies. Key Publications (2024-2025): Brain-tuned speech models (INTERSPEECH 2025) Cognitive event boundaries in LLMs (Behavioral Research Methods 2025) Music-induced memory reactivation (biorxiv 2024) LLM-brain alignment reasons (EMNLP 2024) Advising : Mentors PhD candidates Omer Moussa (speech processing), Camila Kolling (representational similarity), and Gabriele Merlin (LLM alignment). Collaborates with institutions like MIT, NYU, and ETH Zurich.

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Fatma Denizمشاهده پروفایل

استاد

Technical University of Berlin (TU Berlin)Germany

Fatma Deniz is a Full Professor (W3) of Computer Science at Technische Universität Berlin, supported by the Berlin Equal Opportunities Program. She leads the Chair of Language and Communication in Biological and Artificial Systems, and is a member of the Berlin Bernstein Center for Computational Neuroscience. Her roles include membership in TU Berlin's Executive Board and the Berlin University Alliance Steering Committee. She holds a Ph.D. (Dr. rer. nat.) from TU Berlin and a Diploma in Computer Science from Technische Universität München, with research training at Caltech and postdoctoral work at UC Berkeley. Her research focuses on understanding neural mechanisms of language processing, integrating computational neuroscience, cognitive science, and artificial intelligence. Key areas include semantic representation dynamics, cross-modal neural alignment, and language learning in bilingual contexts. She has pioneered studies showing the brain's invariant semantic processing across reading and listening modalities. Her grants include an ERC Starting Grant (2023-2028) for studying language learning shifts and a NSF-BMBF CRCNS grant on bilingual representations. She co-edited The Practice of Reproducible Research: Case Studies in Data Science (UC Press, 2017) and contributed to foundational work on reproducible data science methodologies. She has advised projects in neuroimaging, AI ethics, and computational linguistics, and collaborates with institutions like UCSF and the German Academic Exchange Service. Her lab explores neural correlates of language through fMRI, MEG, and machine learning techniques.

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Jiaoyan Chenمشاهده پروفایل

مدرس ارشد

Schloss Dagstuhl - Leibniz Center for InformaticsGermany

Jiaoyan Chen is a Senior Lecturer (Associate Professor) in the Department of Computer Science at The University of Manchester. She previously held roles as a Lecturer at Manchester, a Senior Researcher at the University of Oxford, and a Postdoctoral Fellow at Heidelberg University. Education: PhD and Bachelor's in Computer Science and Technology from Zhejiang University (2016 and 2011), with a visiting PhD stint at Zurich University's Department of Informatics. Research Interests: Integrating knowledge graphs and ontologies with machine learning and large language models (LLMs), focusing on semantic embeddings, knowledge curation, and explainable AI systems. Publication Trends show emphasis on ontology embeddings (e.g., OWL2Vec*), LLM evaluation with knowledge graphs, and hybrid neural-symbolic reasoning. Her work bridges structured knowledge and modern AI through projects like OntoEm and ConCur . Current Research Team includes postdoctoral researchers, PhD students, and externally co-supervised associates. She actively recruits PhD candidates in areas like Retrieval-Augmented Generation and LLM Explainability , with projects funded by EPSRC and international consortia. Grants & Leadership: EPSRC New Investigator Award (2023-2026) Manchester-Melbourne-Toronto Research Fund (2024-2026) EPSRC ConCur Project (2021-2025) Professional Service: Associate Editor, Transactions on Graph Data and Knowledge EPSRC Peer Review College member OAEI Track Co-organizer at ISWC

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Stefania Degaetano-Ortliebمشاهده پروفایل

دانشیار

Saarland UniversityGermany

Stefania Degaetano-Ortlieb is an Associate Professor of English Linguistics and Corpus Linguistics at Saarland University's Department of Language Science and Technology. She serves as Principal Investigator for the Collaborative Research Center (SFB 1102) 'Information Density and Linguistic Encoding,' leading Project B1 on diachronic information density in English scientific writing (17th century-present). Her interdisciplinary work bridges computational methods with sociolinguistics, focusing on register variation, language change, and digital humanities. Research interests center on text mining, data analytics, and probabilistic modeling of language variation. Key areas include: Diachronic evolution of scientific registers and linguistic densification Information-theoretic approaches to language efficiency Computational sociolinguistics and register diversification AI applications in humanities education (e.g., ChatGPT integration) Her publications show a strong trend toward quantitative diachronic analysis, with recent work emphasizing: interpretable AI models for linguistic change detection; propagandistic narrative analysis in conflict zones; and multi-word expression dynamics in scientific discourse. Cross-disciplinary collaborations frequently intersect with history, psychology, and media studies. Awards include the Fellowship Excellence Program for Young Female Scientists (2015-2018). Current grants: EU Horizon MSCA Doctoral Network 'CASCADE' (€521K to UdS, 2024-2027) Data-Pin Project for AI in education (€50K, 2023-2024) SFB 1102 Project B1 (€595K, 2022-2026) Advises PhD candidates in the EU CASCADE project on computational semantic change. Leads a research team exploring Russian media narratives, personality modeling in LLMs, and multi-word expressions. Directs teaching modules integrating AI tools for humanities students.

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Varsha Sureshمشاهده پروفایل

پژوهشگر

Saarland UniversityGermany

Dr. Varsha Suresh serves as a Postdoctoral Researcher at Saarland University's Computer Science and Computational Linguistics department, affiliated with Prof. Vera Demberg's research group since May 1, 2024. She also contributes to the DFG-funded SFB-1102 project "Information Density and Linguistic Encoding" as part of project B2 focused on "Cognitive modelling of information density for discourse relations". Her research expertise spans multiple dimensions of language technology: Development of knowledge-augmented language models to enhance language understanding capabilities Creation of multimodal language models incorporating non-verbal communication cues Cognitive modeling approaches to information density in discourse relations Integration of gestures, body language, and speech features with linguistic processing Dr. Suresh's work represents an interdisciplinary fusion of computational linguistics, cognitive science, and artificial intelligence, aiming to create language models that more accurately reflect human communication patterns through multimodal data integration. Her research has significant implications for advancing human-computer interaction systems and natural language understanding technologies.

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Heiko Paulheimمشاهده پروفایل

استاد

University of MannheimGermany

Prof. Dr. Heiko Paulheim is a Professor of Data Science and currently serves as University Vice President at the University of Mannheim. He leads the Data and Web Science Group (DWS), which focuses on Web Data Mining, Knowledge Graphs, and Semantic Web technologies. His research group contributes to open source knowledge graphs like DBpedia and develops new knowledge graphs such as WebIsALOD and DBkWik. As of October 1, 2024, he has limited teaching capacity due to his vice presidential duties. Prof. Paulheim's research interests span Knowledge Graphs, Semantic Web, Web Data Mining, Machine Learning, and Natural Language Processing. His work particularly focuses on knowledge graph refinement, embedding techniques (notably RDF2vec), and applications in various domains including news recommendation, biomedical informatics, and environmental monitoring. His group develops practical tools like the RapidMiner Linked Open Data Extension and RDF2vec for knowledge graph applications. His recent publications demonstrate a strong focus on knowledge graph embeddings, with particular attention to RDF2vec variants, applications in news recommendation systems, biomedical data integration, and spatio-temporal knowledge graphs for environmental monitoring. His work bridges theoretical advances in knowledge representation with practical applications across multiple domains. Among his notable achievements are a nomination for the Best Paper Award at CAiSE 2025 and securing an Open Science Grant for the SpatialBenchRAG project. His research has significant impact in both academic and industrial contexts, with multiple papers accepted at top conferences like ISWC and ESWC. Prof. Paulheim has supervised numerous PhD students including Alexander Brinkmann and Michael Schlechtinger, and has led several research projects including the DFG Project Mine@LOD, State of BW Project SyKoW², and BMBF Project DS4DM. His group maintains strong industry connections with partners like SAP AG, Daimler AG, and IDS.

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Akash Kumarمشاهده پروفایل

استاد

University of TrierGermany

Akash Kumar is a Professor at Ruhr University Bochum, Germany, with affiliations to multiple institutions including TU Dresden and National University of Singapore. His research focuses on computer architecture, hardware acceleration, and approximate computing, with a strong emphasis on FPGA-based systems and neural network optimization. He has contributed extensively to embedded systems, mixed-criticality systems, and security in emerging technologies like reconfigurable nanodevices. His work spans cross-layer approximation methodologies, graph neural networks, and energy-efficient processing for edge AI. Collaborations with industry and academia highlight his leadership in VLSI design and secure hardware implementations. Notable contributions include frameworks for bounding time in mixed-criticality systems and resilient logic locking techniques. Research interests include hardware-software co-design, real-time systems, and efficient neural network architectures. His publications in top-tier conferences (DAC, DATE, FCCM) and journals (IEEE Trans. CAD, ACM TECS) underscore his impact in the field.

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Laura Busseمشاهده پروفایل

استاد

Ludwig Maximilian University of MunichGermany

Prof. Laura Busse is a Professor at Ludwig Maximilian University of Munich (LMU), leading the Research Group in the Department of Biology II, Division Neurobiology. She holds roles as a Regular Member of MCN, Full Member of GSN, and Deputy Head of the GSN Examination Board. Her research focuses on cellular and systems neuroscience, particularly investigating how contextual information influences visual perception through neural circuits in mice. Key areas include feedback mechanisms, behavioral state effects, and thalamocortical interactions. Her work employs advanced techniques like high-density extracellular recordings and optogenetics to study active behavior in rodents. Current students include Simon Renner, Gregory Born, and others. Recent research highlights include studies on corticothalamic feedback effects, thalamic spatial integration, and the role of pupil dynamics in neural activity. She leads the Vision Circuits Lab (https://visioncircuitslab.org), exploring how sensory inputs and brain states shape visual processing. Her articles reveal trends in understanding thalamocortical communication, adaptive sensory systems, and the biological basis of neural network models. She coordinates the SPP2411 project on cortico-subcortical loops, emphasizing interdisciplinary neuroscience.

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Konstantin Voigtمشاهده پروفایل

استاد

Julius-Maximilians-Universität WürzburgGermany

Konstantin Voigt, Professor of Musicology II , serves at the University of Würzburg within the Faculty of Philosophy and Institute of Music Research. His research spans medieval Latin song traditions, music theory, notation systems, and digital humanities applications. He also explores 20th-century composers like Arnold Schoenberg and the reception of medieval music in popular culture. Current: Chair of Musicology II, University of Würzburg (2024–) Previous: Tenure-track Professor, University of Freiburg (2020–2024) Education: PhD (Würzburg), MA (Erlangen-Nürnberg), Musicology & Art History Voigt's research bridges premodern music history with digital methodologies, focusing on: Medieval Latin song structures (9th–13th centuries) Development of musical notation and visualization Digital editions as tools for manuscript analysis Intermedial relationships in postmodern composition Stefan George’s poetry in Schoenberg’s works His recent publications analyze scribal practices in Paris 1139 manuscripts and digital approaches to monophonic music. He co-leads the Weave Lead project on French music reception in Central Europe before 1350 and contributes to the Corpus monodicum digital edition. Collaborations include PD Dr. Hana Vlhova-Wörner (Prague) and institutions like the Schola Cantorum Basiliensis.

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Axel Mecklingerمشاهده پروفایل

استاد

Saarland UniversityGermany

Prof. Dr. Axel Mecklinger is a leading cognitive neuroscientist at Saarland University , specializing in the neurocognition of memory and language through spatiotemporal brain imaging (EEG/MEG/fMRI). His career spans over three decades, with significant contributions to understanding visual working memory , associative recognition , and memory development . Key research areas: Memory binding, ERP subsequent memory effects, novelty detection, and cognitive aging Major grants: DFG Research Groups, Collaborative Research Centers, and international collaborations with the Chinese Academy of Sciences Scientific leadership: Organized conferences, edited journals, and served as speaker for research training groups His recent work explores unitization in memory formation , cross-cultural differences in memory processing , and theta neurofeedback interventions . Awards include the Early Career Award of the German Psychophysiology Society (1992) and the European Federation of Psychophysiology Societies' Federation Prize (1994). Current projects investigate the neural mechanisms of semantic surprisal and memory plasticity in aging populations.

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Gaël Kermarrecمشاهده پروفایل

پژوهشگر

Leibniz University HannoverGermany

Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections

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Anton Ehrmanntrautمشاهده پروفایل

پژوهشگر

Julius-Maximilians-Universität WürzburgGermany

Anton Ehrmanntraut is a researcher at the University of Würzburg, affiliated with the Chair of Computational Philology and Modern German Literary History. His work bridges computational methods with literary and linguistic analysis. Institution: University of Würzburg Role: Researcher Location: Emil-Hilb-Weg 23, Campus Hubland Nord Contact: anton.ehrmanntraut@uni-wuerzburg.de Research Focus: Computational Linguistics Digital Humanities German Literary History Natural Language Processing Computer Science Publishing Trends: Recent publications demonstrate a dual focus: (1) advancing NLP techniques for German texts (e.g., ModernGBERT, text normalization, literary pipelines) and (2) theoretical computer science contributions to complexity classes like UP, DisjNP, and DisjCoNP.

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Andreas Herzمشاهده پروفایل

استاد

Ludwig Maximilian University of MunichGermany

Prof. Dr. Andreas Herz is a Chair in Computational Neuroscience at the Faculty of Biology, Ludwig-Maximilians-Universität München (LMU). His research focuses on understanding neural mechanisms underlying spatial navigation, temporal cognition, and sensory processing. He leads the Computational Neuroscience group and collaborates with the Bernstein Center for Computational Neuroscience Munich. Research Interests: Dr. Herz investigates how neural systems encode spatial and temporal information, including grid cells, head-direction systems, and neural coding strategies. His work bridges experimental neurophysiology with theoretical modeling, addressing topics like cognitive maps, neural variability, and synaptic plasticity. Teaching & Mentorship: He oversees advanced courses on computational neuroscience and neurophysiology, fostering interdisciplinary training for graduate students. His research group includes prominent collaborators like Dr. Martin Stemmler and PD Dr. Kay Thurley, focusing on projects involving neural network dynamics and behavioral neuroscience. Publications & Impact: Over 85 peer-reviewed articles highlight his contributions to understanding entorhinal-hippocampal circuits, dendritic processing, and neural representation of space/time. Key work includes studies on grid cell variability, zebrafish spatial memory, and cytoskeletal organization in dendritic spines.

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Matthias Rareyمشاهده پروفایل

استاد

University of HamburgGermany

Prof. Dr. Matthias Rarey is a computer scientist and Professor at the University of Hamburg's Center for Bioinformatics. He holds a Ph.D. in Computer Science from the University of Bonn (1996) and has been leading the Algorithmic Molecular Design working group since 2002. His research focuses on molecular design algorithms, cheminformatics tools, and 3D bioinformatics. Co-founder of BioSolveIT GmbH Former cheminformatics group leader at Fraunhofer SCAI Former researcher at SmithKline Beecham and Roche Bioscience Head of Helmholtz Data Science Graduate School DASHH Director of Center for Data and Computing in Natural Science (CDCS) Research interests span algorithmic molecular design, cheminformatics, structure-based drug discovery, and machine learning applications in bioactivity prediction. His group developed widely used tools like FlexX, PoseView, and SpaceLight for molecular modeling and fragment space analysis. Recent publications focus on geometric pattern matching in protein-ligand interfaces, combinatorial fragment space encoding, adverse drug reaction network analysis, and efficient shape-based virtual screening. The work emphasizes scalable algorithms for billion-sized compound libraries and integration of machine learning with traditional cheminformatics approaches. Scientific awards include: GMD Award 1996 (Best Dissertation) GMD Award 2000 (Best Project) NRW Wissenschaftspreis 2002 Corwin Hansch Award 2005 Emerging Technologies Award 2011 Norddeutscher Wissenschaftspreis 2020 Academic leadership roles: Founding director of Center for Bioinformatics Co-founder of M.Sc. Bioinformatics and B.Sc. Computing in Science programs Chair of doctoral committee at Faculty of Computer Science Member of EMBL-EBI's Molecular and Cellular Structure advisory board Former Associate Editor of Journal of Chemical Information and Modeling

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Eleanor Goerssمشاهده پروفایل

پژوهشگر ارشد

University of TübingenGermany

Eleanor Goerss serves as a Research Fellow at the Institute of Art History within the Faculty of Humanities at the University of Tübingen, working since 2023 on the DFG-funded project 'History as a Visual Concept: Peter of Poitiers’ Compendium historiae' under Prof. Andrea Worm’s direction. Her position involves reconstructing medieval visual epistemology through manuscript analysis and digital editing methodologies. Her academic foundation includes a PhD in History of Art and Architecture from Harvard University (2016–2023) and a dual BA in Art History and Mathematics from Columbia University (2012–2016). This quantitative-humanistic training informs her analytical approach to medieval diagrammatic systems. Goerss specializes in the visual representation of knowledge in 13th–14th century Europe, with particular focus on Lullian art, genealogical diagrams, and manuscript transmission networks. Her research interrogates how medieval thinkers encoded theological and philosophical concepts through recursive visual structures, examining the interplay between mathematical logic and religious epistemology in diagrammatic forms. This work bridges art history, cognitive science, and medieval studies through rigorous paleographic analysis. Her 2024 publications reveal a cohesive trajectory exploring recursive structures in Lullian figures, manuscript adaptation of dialogue forms, and Peter of Poitiers’ historiographical diagrams. Collectively, these works demonstrate how medieval visual systems functioned as cognitive tools for knowledge organization, with particular attention to the materiality of manuscripts and cross-institutional transmission patterns across European intellectual centers. Her scientific recognition includes: Kress Institutional Fellowship at Institut national d’histoire de l’art, Paris (2021–2023) DAAD Research Grant at University of Freiburg (2019–2020) Frederick Sheldon Traveling Scholar Grant from Harvard University (2019–2020) Certificate of Distinction in Teaching, Harvard University (2018–2019) Art History Senior Thesis Prize, Columbia University (2016) As lead researcher on the DFG project, Goerss directs manuscript digitization efforts and develops analytical frameworks for reconstructing Peter of Poitiers’ genealogical systems. Her grant portfolio demonstrates consistent success in securing competitive funding from German, French, and American institutions, reflecting the international significance of her work. Though no current advisees are documented, her Harvard teaching award indicates pedagogical excellence in undergraduate instruction. She operates within the DFG project team at Tübingen’s Institute of Art History, collaborating with Prof. Andrea Worm on the scholarly edition of Peter of Poitiers’ Compendium. This interdisciplinary team integrates codicology, digital humanities, and historical theology to produce critical editions and visual reconstructions of medieval knowledge systems.

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