جستجوی استاد راهنمای دانشگاهی

Prof. Dr. Christian Schulze is a Professor in the Faculty of Mathematics, Natural Sciences and Data Science at the Technical University of Central Hesse (THM), affiliated with the Competence Center for Information Technology (KITE). His research focuses on Artificial Intelligence and Data Analytics for real-world industry applications. Key projects demonstrate expertise in: LEGADA (2022-2024): Developing AI-driven lead generation systems for B2B sales using self-learning algorithms, funded with €386,330 by Hesse's 'Distr@l' program TLDia (2019-2021): Automating medical diagnosis coding through transfer learning in collaboration with Goethe University Frankfurt PAROT (2016-2018): Creating SaaS recommendation engines for e-commerce personalization ADOMIS (2015-2017): Integrating heterogeneous financial data sources for statistical analysis Prof. Schulze secures significant research funding from the State of Hesse (LOEWE-3 and 'Distr@l' programs) and maintains active industry partnerships with Minds-Medical GmbH, Dastani Consulting GmbH, and Content Software GmbH. His work bridges academic research with practical business solutions in AI deployment.

• Artificial Intelligence
• Data Analytics
• Machine Learning
• +۵ مورد دیگر

Prof. Dr.-Ing. Torsten Zesch serves as Deputy Scientific Director, Member of the Executive Board, and Head of the Research Professorship for Computational Linguistics at FernUniversität in Hagen since March 2022. He previously held W2 and W1 Professorships for Sprachtechnologie (Language Technology) at Universität Duisburg-Essen from 2014-2022. Zesch is also Spokesperson of the Advisory Board of the German Society for Computational Linguistics and Language Technology (GSCL) since 2024, having previously served as GSCL President from 2018-2024. Dr. Zesch completed his dissertation (Dr.-Ing.) in Computer Science at Technische Universität Darmstadt in 2009. His research spans robust language processing systems, analysis of non-standard language structures, and educational applications of language technology, with particular focus on automatic content scoring and spelling error correction for learner language. Zesch's recent publications reveal a strong focus on integrating language technology with educational applications. His work demonstrates expertise in developing practical NLP solutions for educational assessment, including transformer-based spelling error feedback systems, hierarchical automatic scoring methods, and leveraging LLMs for educational applications despite cold-start problems. He also maintains significant research in hate speech detection, particularly in multimodal contexts and visio-linguistic models. As leader of the Computational Linguistics research professorship within the CATALPA research center, Zesch directs a team investigating how language technology can support educational processes. His projects DAKODA and KISS-Pro focus on language acquisition and educational applications. He has contributed significantly to the field through numerous publications in top NLP and educational technology venues, with over 100 publications spanning from 2006 to present.

• Computational Linguistics
• Natural Language Processing
• Educational Technology
• +۶ مورد دیگر

Dr. Tim Chen is a Senior Lecturer at the School of Computer Science, University of Adelaide, with research focused on augmenting human capabilities through human-centered AI systems. He leads interdisciplinary teams in projects like the Augmenting Ability CRC and the IMAGENDO Project , which received the Eureka Prize and NHMRC Idea Grant. Affiliation: University of Adelaide Collaborators: Prof. Patrick Baudisch (HPI), Prof. Takeo Igarashi (U of Tokyo), Prof CT Lin (UTS), Dr. Li-Yi Wei (Adobe Research) Research Interests: Human-AI interaction paradigms ( AI as Assistant, Collaborator, Oracle ), virtual reality training, contrastive learning, and data visualization. His work bridges AI/ML, computer graphics, and human-computer interaction to empower knowledge workers. Recent Achievements: Two CHI 2025 papers on VR learning, SIGGRAPH 2025 jury committee role, and ARC DP analysis website development. Funding includes NHMRC (~$2M) and AEA Ignite grants. Scientific Awards: Eureka Prize-winning leadership NHMRC Idea Project Grant AEA Ignite Grant (~$500k)

• Human-Computer Interaction
• Computer Graphics
• Artificial Intelligence
• +۴ مورد دیگر

Goran Glavaš is a Professor at the University of Würzburg's Faculty of Mathematics & Computer Science, holding the Chair for Natural Language Processing (Computer Science XII) and affiliated with the Center for Artificial Intelligence and Data Science (CAIDAS). His research focuses on computational semantics, multilingual/low-resource representation learning, and democratizing language technologies through fairness and sustainability. Former Assistant Professor at University of Mannheim (2017-2021) Interim Associate Professor at LMU Munich (2021-2022) Doctorate in 2014 at University of Zagreb under Jan Šnajder Recent research trends emphasize cross-lingual learning, multilingual knowledge integration, and ethical AI frameworks. His group contributes to robust multilingual models, vision-language systems, and sustainable NLP applications in social sciences. Outstanding Paper Award at ACL 2024 (IRCoder) Outstanding Paper Award at EACL 2024 (Kardeş-NLU) Extensive publications in EMNLP, ACL, NAACL, EACL, and TACL Advises a team of researchers at the University of Würzburg's NLP Chair, including Benedikt Ebing, Gregor Geigle, and Fabian David Schmidt. Leads the WüNLP group within CAIDAS, focusing on democratizing language technologies.

• Computational Semantics
• Multilingual Representation Learning
• Low-Resource NLP
• +۲ مورد دیگر

Alexander Ziem is a Professor of German Linguistics and Chair holder at the Institute of German Studies , Heinrich Heine University Düsseldorf, since 2016. His academic career spans institutions such as the International Computer Science Institute (ICSI) in Berkeley, Universität Basel, and Technische Universität Berlin. Research Focus: Cognitive semantics, construction grammar, FrameNet-Konstruktikon projects, discourse analysis, and socio-cognitive dimensions of language. Projects: Initiator of the long-term ' FrameNet and Constructicon of German ' project; co-editor of Diskursforschung and DiskursNetz handbooks. His recent publications emphasize constructional meanings, semantic frames, and multilingual frameworks. He leads the German Constructicon project and collaborates on digital humanities tools like SimilarCxns and FrameMap3D. Scientific Awards: Preis für Geisteswissenschaften , Akademie der Wissenschaften zu Göttingen (2011). Research Fellow, International Computer Science Institute (ICSI), Berkeley (2013–2014). Ziem’s team at HHU includes 25 members, with 10 research assistants, and he contributes to curriculum development, including the upcoming Digital Cultures degree program. His methodological approach integrates corpus linguistics, frame semantics, and machine learning.

• Cognitive Semantics
• Construction Grammar
• Discourse Analysis
• +۶ مورد دیگر

Prof. Dr. Martin Zacharias serves as Chair of Theoretical Biophysics - Molecular Dynamics at the Technical University of Munich (TUM) within the TUM School of Natural Sciences. His research group employs advanced computational methods to investigate biomolecular structure, dynamics, and interactions at atomic resolution. His research focuses on molecular dynamics simulations of biomolecules, particularly examining protein-protein and protein-DNA interactions, protein folding mechanisms, amyloid structure formation, and thermodynamics of protein-ligand binding. His work integrates computational approaches with experimental validation to understand molecular recognition processes and develop predictive models for biomolecular association. Notable scientific contributions include pioneering work on biomolecular simulation methodologies, with significant publications in Nature Methods , Science , and Journal of the American Chemical Society . His recent research emphasizes implementing FAIR principles in computational biophysics and applying artificial intelligence to complex biomolecular problems. Member of the Faculty of 1000 (2009) Affiliate Member PNNL (1999) DFG habilitation scholarship holder (1996) DFG research fellow (1992) Prof. Zacharias actively supervises graduate students and leads collaborative research projects investigating fundamental biophysical processes. His laboratory develops and applies molecular simulation techniques to address critical questions in structural biology and drug discovery, with particular emphasis on methodological advancements in computational biophysics.

• Molecular Dynamics Simulation
• Biomolecular Dynamics
• Protein-Protein Interactions
• +۵ مورد دیگر

Yan Xia is a Senior Researcher at the Computer Vision Group of the Technical University of Munich (TUM) and a Research Scientist at the Munich Center for Machine Learning. She collaborates with Prof. Daniel Cremers and previously completed her PhD at TUM under supervision of Prof. Uwe Stilla and Prof. Daniel Cremers, with a visiting period at the Visual Geometry Group of the University of Oxford under Dr. João Henriques.

• 3D Vision
• Localization and Navigation
• Robotics
• +۲ مورد دیگر

Stephan Leible is a Researcher at the Department of Computer Science , University of Hamburg (MIN Faculty). Holding both M.Eng. in Business Engineering and an MBA, he focuses on employee-driven digital innovation, intrapreneurship, and leveraging generative AI for organizational transformation. Research Interests : Employee-driven Innovation, Intrapreneurship, Generative AI Governance, Design & Data Thinking, IT Innovation Management Contact : stephan.leible@uni-hamburg.de | Room 117C, Vogt-Kölln-Straße 30, Hamburg His work bridges citizen development with public sector innovation, emphasizing value co-creation, real-time analytics, and ethical AI implementation. Current studies explore: Generative AI adoption patterns and limitations Interpretable machine learning for urban mobility Participatory frameworks for smart city futures Methodologies for continuous improvement in conversational agents

• Employee-driven (Digital) Innovation
• Intrapreneurship
• Employee Engagement
• +۲ مورد دیگر

Camille Castera is an Associate Professor in optimization and machine learning at the Mathematical Institute of the University of Bordeaux (IMB). Her academic journey includes a postdoctoral position at the University of Tübingen (2022-2024) working on the TRINOM-DS project under Peter Ochs and Jalal Fadili, and a PhD at the IRIT laboratory in Toulouse supervised by Cédric Févotte, Edouard Pauwels, and Jérôme Bolte as part of the FACTORY project. Her research focuses on optimization algorithms for machine learning, particularly second-order methods with applications to deep learning, and the emerging field of learning optimization algorithms. Her work spans continuous optimization (convex & non-convex, non-smooth, stochastic), learning to optimize, and optimization for deep learning with automatic hyper-parameter tuning. Her recent publications demonstrate significant contributions to the field of optimization algorithms, particularly in developing novel approaches that bridge classical optimization techniques with learning-based methods. Her research shows a clear trajectory toward creating more adaptive and versatile optimization algorithms that can generalize beyond their training settings. At the University of Bordeaux, she teaches advanced courses including Large-scale optimization (Master 2), Introduction to deep learning (Master 2), Convex optimization (Master 1), and Image processing (Licence 3), while also supervising student projects on image processing and machine learning. Her technical work is supported by substantial implementation efforts, with publicly available code repositories demonstrating practical applications of her theoretical contributions to optimization algorithms.

• Optimization Algorithms
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Dr.-Ing. Frank-Josef Heßeler is a Senior Research Engineer (Geschäftsführender Oberingenieur) and Deputy Institute Director at the Institute of Control Engineering (IRT), RWTH Aachen University . His work focuses on control systems for automotive and urban mobility applications, including model predictive control, vehicle localization, and intelligent infrastructure. He actively contributes to research in autonomous driving, hybrid drivetrains, and thermal systems optimization. Control Engineering Automotive Systems Model Predictive Control Thermal Diagnostics Urban Traffic Simulation His publications highlight advancements in connected vehicle localization, scenario-specific motion modeling, and hybrid drivetrain control. He collaborates extensively with Dirk Abel and other researchers. No scientific awards or student advisement details are explicitly mentioned in the provided texts. He is affiliated with the Institute of Control Engineering, engaging in projects like CERMcity (autonomous urban driving testbed) and Galileo-based navigation systems. His work integrates simulation platforms, Neuro-Fuzzy models, and hardware-in-the-loop testing for automotive control solutions.

• Control Engineering
• Automotive Engineering
• Model Predictive Control
• +۵ مورد دیگر

Prof. Dr.-Ing. Joachim Denzler is a Professor leading the Chair for Digital Image Processing (Lehrstuhl für Digitale Bildverarbeitung) at Friedrich-Schiller-Universität Jena. His research spans computer vision, machine learning, medical imaging, and remote sensing applications across diverse domains including biomedical analysis, environmental monitoring, and facial recognition systems. His research interests focus on explainable AI, causal discovery, physics-informed neural networks, and bias mitigation in deep learning models. He has made significant contributions to fine-grained classification, concept activation vectors, and privacy-preserving techniques in facial recognition. His work often bridges theoretical computer vision with practical applications in medical diagnostics, environmental science, and infrastructure monitoring. His recent publications demonstrate a strong trend toward causal discovery methods, physics-informed neural networks, and addressing bias in machine learning systems. His work spans both theoretical advancements in model interpretability and practical applications in medical imaging, environmental monitoring, and infrastructure safety. The interdisciplinary nature of his research is evident from collaborations with ecologists, neuroscientists, and civil engineers. Best Paper Award at International Conference on Pattern Recognition (ICPR) 2024 Prof. Denzler actively mentors numerous PhD students and postdoctoral researchers, with frequent co-authors including Maha Shadaydeh, Niklas Penzel, Gideon Stein, and Tim Büchner appearing as first authors on significant publications. His laboratory has secured research funding across multiple domains including medical imaging, environmental monitoring, and AI safety. His work on CausalRivers represents a major contribution to benchmarking causal discovery methods with real-world time series data. The Chair for Digital Image Processing maintains strong industry and clinical partnerships, particularly in medical imaging applications for facial palsy analysis and neonatal care. Prof. Denzler's team has developed novel techniques for dam deformation monitoring using remote sensing data and created advanced methods for analyzing plant diversity effects on ecosystem functioning.

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۷ مورد دیگر

Dr. Olya Hakobyan is a Researcher at the University of Bielefeld, working in the Faculty of Engineering within the Human-Centered Artificial Intelligence Group at the Center for Cognitive Interaction Technology (CITEC). She has been with the university since June 2021 as a research associate in the Multimodal Behavior Processing lab. Dr. Hakobyan's educational background includes: PhD in Computational Neuroscience (2016-2020) from the Institute for Neural Computation at Ruhr University Bochum Master's degree in Cognitive Science (2014-2016) from Ruhr University Bochum Bachelor's degree in Linguistics (2010-2014) from Yerevan Brusov State University of Languages and Social Sciences Her research focuses on the intersection of artificial intelligence, cognitive science, and human-computer interaction. Dr. Hakobyan specializes in affective computing, explainable AI systems, and the development of privacy-preserving data donation platforms. Her work on the Dona platform represents a significant contribution to ethical data collection methods for social interaction analysis. She investigates how AI systems can interpret human emotions through audio and visual channels while maintaining transparency in decision-making processes. Her research also extends to cognitive modeling, particularly in understanding memory processes and recognition mechanisms. Dr. Hakobyan's publication record demonstrates a strong trajectory in developing methods for analyzing social interactions through digital footprints while addressing critical privacy concerns. Her work bridges technical innovation with ethical considerations in data collection. Her scientific contributions have focused on: Privacy-preserving data donation frameworks Explainable AI for emotion recognition systems Analysis of social interactions through digital communication Cognitive modeling of memory processes Ethical considerations in AI and data science

• Affective Computing
• Explainable AI
• Data Privacy
• +۴ مورد دیگر

Dr. Marcus Fritze is a researcher in Applied Zoology and Nature Conservation at the University of Greifswald, with a dual affiliation since 2023 at the Competence Center for Bat Conservation Saxony-Anhalt within the South Harz Karst Landscape Biosphere Reserve. His work bridges scientific research with practical conservation applications, focusing specifically on bat ecology and conservation. Dr. Fritze's research spans multiple critical areas in bat conservation. He investigates population trends and demographic parameters through BfN-funded projects 'Threatened Data for Threatened Species' and BATTREND. A major output from these initiatives is BATLAS, an online platform for analyzing bat population data across Germany. His work addresses the 'green-green dilemma' between renewable energy expansion and wildlife conservation, particularly examining wind energy impacts on bats and the ecological consequences of light pollution. His physiological research examines hibernation (winter torpor) mechanisms in bats and how their immune systems function during this energy-conserving state, with special focus on white-nose disease. Through the F.U.N. initiative ('Forschung, Umweltbildung und praktischen Naturschutz'), he integrates research, environmental education, and practical conservation to support biodiversity. Current projects include 'Bats and Biosphere' (human-wildlife interactions) and 'Bats and Ponds' (role of water bodies in ecosystems). Analysis of Dr. Fritze's publication record reveals an interdisciplinary approach addressing conservation challenges at the intersection of ecology, immunology, policy, and technology. His work demonstrates particular expertise in developing evidence-based conservation strategies that effectively bridge scientific research with practical implementation. Dr. Fritze actively supervises numerous Master's and Bachelor's students on bat conservation topics, often in collaboration with other institutions including FH Bernburg, HTW Dresden, and TU Berlin. His current supervisees are investigating ecosystem services provided by bats in fruit orchards, urban pond habitats for bats, wind turbine mitigation measures, and spring activities of bats on orchard meadows. His collaborative approach extends internationally, such as with Universidad Autónoma Metropolitana in Colombia on jaguar conservation perceptions. Through his leadership in the Competence Center for Bat Conservation Saxony-Anhalt and various research projects, Dr. Fritze has developed effective frameworks for collaboration between scientists, amateur researchers, and volunteer conservationists. His work exemplifies how rigorous scientific research can directly inform and improve practical conservation outcomes in complex human-wildlife landscapes.

• Bat Conservation
• Ecosystem Services
• Population Ecology
• +۶ مورد دیگر

Johannes Haller is a Professor of Experimental Particle Physics at the University of Hamburg , affiliated with the Institute of Experimental Physics under the Faculty of Mathematics, Informatics and Natural Sciences. He actively contributes to the CMS experiment at the LHC , focusing on physics beyond the Standard Model, boosted objects, and Higgs boson studies. Since 2023, he chairs the Particle Physics Division of the German Physical Society (DPG) and serves on multiple national and international committees. PhD in Particle Physics (Universität Heidelberg, 2003) Diploma in Physics (Universität Heidelberg, 2000) His research spans collider experiments from LEP (OPAL) to HERA (H1) , ATLAS , and now CMS . His group develops AI-based algorithms for CMS trigger systems and participates in global electroweak fits through the Gfitter collaboration. Recent work explores flavor anomalies , heavy Higgs bosons , and medium effects in heavy-ion collisions . Selected scientific responsibilities include: Spokesperson for BMBF-FSP-104 “Elementarteilchenphysik mit dem CMS–Experiment” (2021–2024) Managing Director of Institute of Experimental Physics (2016–2019) Co-organizer of major conferences like EPS-HEP2023 His research group includes Master’s students Syed Sajal Hasan, Balduin Letzer, Parth Patil, Christian Sammoray, and Emre Toka.

• Particle Physics
• Experimental Physics
• High Energy Physics
• +۳ مورد دیگر

Aysim Toker is a Ph.D. candidate at the Chair for Computer Vision and Artificial Intelligence , affiliated with the Technical University of Munich . She works under the supervision of Prof. Dr. Laura Leal-Taixe and Prof. Dr. Xiaoxiang Zhu on interdisciplinary projects. Research Focus: Deep learning, sequence analysis, and remote sensing. Key Contributions: Advancing video object segmentation, Earth observation models, and anonymization techniques. Collaborations: Partnered with international researchers across multiple institutions. Publications span top venues like eLife , ICCV , NeurIPS , and CVPR , with a focus on: Deep learning architectures for multi-modal tasks Image and video analysis in remote sensing and anonymization Tracking and segmentation algorithms Her work bridges foundational computer vision research with applications in Earth science and privacy-preserving technologies.

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر