جست‌وجوی استاد و پژوهشگر

• Mathematical Statistics
• Stochastic Processes
• Discrete Mathematics
• +۳ مورد دیگر

Priv.-Doz. Dr. Susanne Koch is a Senior Lecturer (Akademische Oberrätin) for Teacher Education in the Department of Mathematics at the University of Hamburg. She holds a PhD in Probability Theory from Georg-August-University Göttingen (2000) and has extensive experience in academic teaching and research. Her primary role involves teacher training in mathematics, focusing on bridging didactic and scientific aspects of problem-solving in education. Research Interests: Mathematical Statistics and Stochastic Processes Applications of Probability Theory in Education Discrete Mathematics and Stochastic Reasoning Development of Digital Tools for Mathematics Education Recent Research Trends: Her work combines foundational stochastic analysis with practical educational methodologies, emphasizing problem-solving frameworks for primary and secondary education. Key contributions include studies on Dirichlet forms, random walks, and pedagogical strategies for integrating advanced mathematical concepts into teacher training programs. Awards: Double Prize Winner of the 2006 Pilot Project for Teaching Excellence at Göttingen University. Advising & Grants: Leads academic advising in mathematics education, coordinating courses like 'Fachwissenschaftliche Hintergründe schulmathematischer Inhalte' and 'Grundkonzepte der diskreten Mathematik'. Active in curriculum development for teacher education programs. Lab/Team: Member of the ST Group (Mathematical Statistics and Stochastic Processes) at the Department of Mathematics, contributing to interdisciplinary research and educational innovation.

Markus Fischerمشاهده پروفایل

استاد

• Food Authentication
• Analytical Chemistry
• Metabolomics
• +۳ مورد دیگر

Professor Markus Fischer is a prominent academic at the University of Hamburg, leading roles as Spokesperson for Research Field A: 'Artefact Profiling' within the Cluster of Excellence 'Understanding Written Artefacts' (UWA), Head of the Container Lab, and Director of the Hamburg School of Food Science. His primary affiliations include the Department of Chemistry under the Faculty of Mathematics, Informatics and Natural Sciences, and the Institute of Food Chemistry. His research focuses on food authentication using advanced analytical techniques like mass spectrometry and spectroscopy, as well as panomics approaches for written artifact analysis. Key projects include mobile container laboratories for global use and paleogenomic studies of artifacts. He also investigates metabolic pathways in food systems and marine biology, particularly hypoxia tolerance in pinnipeds. Prof. Fischer’s publications span food safety, material analysis, and biomolecular studies, with over 266 papers. He collaborates on initiatives like the Palm-Leaf Manuscript Profiling Initiative and has developed aptamers for analytical applications. His work integrates cutting-edge technologies to address challenges in food traceability, cultural heritage preservation, and environmental sustainability. Equipment managed includes ICP mass spectrometers, LC-ESI-IMS-QTOF systems, and Orbitrap mass spectrometers, enabling high-resolution analyses. His contributions extend to academic leadership, including supervising research projects and organizing conferences like the DESY/UWA panel on written artefacts.

Knut Reinertمشاهده پروفایل

استاد

• Algorithmic Bioinformatics
• Genomics
• Proteomics
• +۳ مورد دیگر

Prof. Knut Reinert is a Professor of Algorithmic Bioinformatics at the Freie Universität Berlin (FU) and a Max Planck Fellow at the Max Planck Institute for Molecular Genetics (MPI). He leads the Algorithmic Bioinformatics (ABI) group at FU and the Efficient Algorithms for Omics Data group at MPI. His research focuses on developing mathematical models and algorithms for analyzing biomedical mass data, including sequence analysis, proteomics, and omics data. Reinert is a key contributor to the SeqAn C++ library, a widely used bioinformatics software tool, and has led initiatives such as the Intel® Parallel Computing Center to accelerate NGS data analysis. Education: Diploma in Computer Science (1994, Max Planck Institute for Computer Science & Universität des Saarlandes), PhD (1999, Dr. Ing., Universität des Saarlandes). Postdoctoral research at Celera Genomics (1999–2002). Research interests include algorithm engineering for genome comparison, high-throughput sequencing data analysis, and bioinformatics software development. His work emphasizes scalable solutions for omics data interpretation, with applications in metagenomics, proteomics, and computational biology. Key achievements include leadership in de.NBI (German Network for Bioinformatics Infrastructure), the development of tools like SeqAn, Lambda, Fiona, and Ganon, and collaborations with institutions like the Max Planck Society and international partners. Awards include Max Planck Fellow status and Intel® PCC leadership. Grants and collaborations: German-Turkish research initiatives, DFG-funded RNA research projects, and leadership in EU-funded projects like Predict-IV. His lab actively engages in teaching at undergraduate and graduate levels, emphasizing innovative methods like e-learning and inverted classrooms.

Kay Schäferمشاهده پروفایل

پژوهشگر

• Turbulent Convection
• Climate Modeling
• Computational Fluid Dynamics
• +۳ مورد دیگر

Dr. Kay Schäfer is a scientific assistant at the University of Hamburg's Meteorological Institute within the Faculty of Earth System Sciences. His work focuses on atmospheric turbulence and boundary layer dynamics, particularly in the context of climate modeling and computational fluid dynamics. He contributes to the Warmworld project, advancing turbulence parameterization in weather and climate models like ICON. His research interests include turbulent convection, high-performance computing, and numerical simulations of complex flow phenomena. He has conducted studies on secondary flows in turbulent channels, heterogeneous roughness effects, and parametric forcing approaches for modeling such systems. His work bridges fundamental fluid dynamics with applied climate science, leveraging advanced computational methods. Schäfer collaborates on datasets and validation of numerical approaches for direct numerical simulations (DNS) of rough wall flows. He is affiliated with the Atmospheric Turbulence and Boundary Layers research group and actively maintains profiles on ResearchGate, Google Scholar, and LinkedIn.

• Computer Vision
• Image Processing
• Machine Learning
• +۴ مورد دیگر

Paul L. Rosin is a Professor at Cardiff University, UK, with a focus on computer vision, image processing, and computer graphics. His research spans topics such as digital forensics, 3D modeling, deep learning applications, and benchmark dataset development. He has collaborated extensively with colleagues globally, contributing to advancements in semantic segmentation, video analysis, and image manipulation detection. Rosin has led or co-authored numerous high-impact publications in top-tier conferences like CVPR, ICCV, and ICASSP, and journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence and Computer Vision and Image Understanding. His work emphasizes real-world applications, including medical imaging (e.g., burn region segmentation) and remote sensing (e.g., road detection). He has also explored interdisciplinary areas like aesthetic style transfer and chat-driven 3D modeling with large language models. Rosin’s contributions to the field include benchmark datasets for forensic video analysis and scalable vector graphics synthesis, reflecting his commitment to advancing both theoretical and applied research in computer vision and graphics.

• Virtual Reality
• Human-Computer Interaction
• Affective Computing
• +۴ مورد دیگر

Matias Volonte is a researcher affiliated with Northeastern University , Boston, MA, USA, focusing on virtual reality, human-computer interaction, and affective computing. His work investigates visual attention, emotion contagion, and behavioral modeling in VR environments. Key research areas: Virtual Human behavior, gaze analysis, user perception, and AI-driven interactions Collaborates with experts like Andrew T. Duchowski, Sabarish V. Babu, and Deyrel Diaz Research Trends : Recent publications (2025-2018) emphasize VR-based studies on embodied agents, including path modeling of attention , demographic bias evaluation , and emotional contagion in digital crowds . His work spans healthcare applications, educational AI, and cognitive modeling in immersive environments. Notable Contributions : Co-developed the HeadBox toolkit for facial blendshape animation in VR and explored trust dynamics with AI instructors. He also contributes to standardization of gaze analysis and multimodal interaction frameworks.

• Algebraic Complexity Theory
• Computational Algebra
• Geometric Complexity Theory
• +۴ مورد دیگر

Prof. Dr. Peter Bürgisser is a Professor at the Technical University of Berlin, affiliated with the Institute of Mathematics and the Algorithmic Algebra research group within Faculty II - Mathematics and Natural Sciences. His research focuses on algebraic complexity theory, computational algebra, and geometric methods in computer science. Bürgisser has made significant contributions to topics including invariant theory, numerical analysis of algorithms, and the computational complexity of algebraic problems. He has authored influential books such as *Algebraic Complexity Theory* and has published extensively in top-tier journals like the Journal of the ACM and SIAM Journal on Computing. His work includes developing polynomial-time algorithms for problems in invariant theory, analyzing the condition numbers of algebraic varieties, and studying the computational aspects of semialgebraic sets. Bürgisser's research also intersects with probability theory, particularly in understanding the statistical properties of zeros of random polynomials and the geometry of random algebraic varieties. Recent trends in his publications emphasize geometric complexity theory, non-commutative optimization, and the application of numerical methods to algebraic problems. He has collaborated with researchers such as Felipe Cucker, Michael Walter, and Avi Wigderson on foundational topics in computational mathematics and theoretical computer science. Bürgisser's office is located in room EB 116, and his contact information includes the email pbuerg@math.tu-berlin.de. His research has been supported through grants and collaborations, though specific grant details are not explicitly mentioned in the provided texts.

Stefan Rothمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Semantic Scene Understanding
• +۳ مورد دیگر

Stefan Roth is a Professor of Computer Science at Technische Universität Darmstadt, where he leads the Visual Inference Lab. His research focuses on statistical models for visual inference problems, with expertise in computer vision, machine learning, and deep learning applications. Specific areas include semantic scene understanding, image motion estimation, and probabilistic models for low-level vision tasks. Key research areas: Semantic scene understanding and segmentation Optical flow and scene flow estimation Deep learning architectures for vision Probabilistic modeling in computer vision Video analysis and understanding Professor Roth's recent publications explore transformer-based scene graph generation, unsupervised segmentation techniques, and foundation models for depth estimation. His work demonstrates strong interdisciplinary connections between computer vision, machine learning, and autonomous systems, with applications in urban scene understanding and intelligent transportation systems.

Mariami Gachechiladzeمشاهده پروفایل

استادیار

• Quantum Computation
• Quantum Networks
• Quantum Entanglement
• +۲ مورد دیگر

Mariami Gachechiladze is a Tenure-Track Assistant Professor in Quantum Computing at TU Darmstadt, leading research at the Quantum Computing Group. Previously, she conducted postdoctoral research at the University of Cologne after completing her PhD in Theoretical Quantum Optics at the University of Siegen. Education includes: PhD in Theoretical Quantum Optics, University of Siegen MSc in Computer Science, University of Oxford BA in Computer Science/Mathematics, American University in Bulgaria Research explores quantum computation certification, quantum network architectures, entanglement theory foundations, and quantum-classical computing interfaces. Her work bridges theoretical quantum mechanics and practical computational applications. Recent publications demonstrate a focus on quantum algorithm verification, correlation boundaries in quantum systems, and entanglement state optimization. Research consistently advances quantum information processing frameworks. Awards and honors: Messer Foundation Prize (2024) Grace Hopper Tech Awards Finalist (2024) Forbes 30 Under 30 Nominee (2020) International Physics Tournament Medalist (2009) Directs the Visual Studies and Learning Design research center while maintaining collaborations across European quantum research initiatives.

Stefan Gumholdمشاهده پروفایل

استاد

• Computer Graphics
• Visualization
• Medical Imaging
• +۳ مورد دیگر

Professor Stefan Gumhold is a leading academic in computer graphics and visualization at TU Dresden. He has held roles including Head of the Chair for Computer Graphics and Visualization since 2005 and served as Dean of the Faculty of Computer Science from 2010 to 2012. His expertise spans visualization techniques, medical imaging, and immersive technologies. Gumhold earned his Ph.D. in 2000, focusing on mesh compression, and later received a Dissertation Award in the same year. He has contributed to projects like the Heisenberg Scholar Research Group and led the Kommission Umwelt at TU Dresden. His teaching includes courses such as Introduction to Computer Graphics, Data Visualization, and Scientific Visualization. Gumhold’s research emphasizes visualization platforms (e.g., ISAAC), image fusion, and neural network applications in medical diagnostics. His work often integrates virtual reality for data analysis, as seen in tools like VRCellLabeler and ExtremeWeatherVis. Education: Diploma in Computer Science (University of Tübingen, 1998), M.Sc. in Applied Physics (University of Massachusetts Boston, 1996). Research Highlights: Development of visualization frameworks, 3D reconstruction, and invertible neural networks for outlier detection. Awards: Dissertation Award 2000. Grants & Labs: Leadership in TU Dresden’s Computer Graphics lab and contributions to collaborative research projects like Fast-Haptic.

Hannelore Ehrenreichمشاهده پروفایل

استاد

• Translational Neuroscience
• Neuropsychiatric Diseases
• Neuroprotection and Neuroregeneration
• +۳ مورد دیگر

Prof. Hannelore Ehrenreich is a distinguished academic in clinical and experimental medicine, holding dual roles as Professor of Neurology & Psychiatry at the University of Göttingen and Head of Experimental Medicine at the Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University. She also leads the Clinical Neuroscience department at the Max Planck Institute for Multidisciplinary Sciences (until 2023). Her expertise spans translational neuroscience, focusing on neuropsychiatric disease mechanisms, neuroprotection, and autoimmune processes. Education: Doctor of Veterinary Medicine (1981), University of Munich Doctor of Medicine (1989), University of Munich Habilitation in Neurology/Psychiatry (1994), University of Göttingen Research Interests: Genetic/environmental underpinnings of neuropsychiatric diseases Endogenous neuroprotection via the brain erythropoietin system Autoimmune/inflammatory contributions to neuropsychiatric phenotypes Key Contributions: Her lab has pioneered work on erythropoietin's role in neuroplasticity, functional hypoxia in brain activity, and autoantibody mechanisms in encephalitis. Recent publications highlight translational research bridging basic science and clinical applications. Awards: Jean Delay Prize (WPA, 2020) Leopoldina Membership (2016) 2008 Honorary Professorship (University of Göttingen) Leadership & Collaborations: She has served as Vice President of the University of Göttingen (2000-2002), led major research institutes, and maintains affiliations with the Max Planck Society and Göttingen's IMPRS neuroscience training programs.

Erika Roldan Roaمشاهده پروفایل

استادیار مهمان

• Stochastic Topology
• First Passage Percolation
• Extremal Topological Combinatorics
• +۳ مورد دیگر

Erika Roldán Roa is a mathematician with academic affiliations at Ohio State University (Visiting Assistant Professor, 2019-2020) and Technische Universität München (Marie Skłodowska-Curie Fellow, 2020-2022). She holds a Ph.D. in Probability and Statistics from CIMAT (2018) and has conducted postdoctoral research at institutions like EPFL and Ohio State. Her work bridges stochastic topology, combinatorics, and educational technology, focusing on topics like cubical sliding puzzles, Eden growth models, and extremal topological problems in polyominoes. Education: Ph.D. in Probability and Statistics, CIMAT (2018) M.Sc. in Mathematics, CIMAT (2014) B.Sc. in Mathematics, Universidad de Guanajuato (2010) Research Interests: Her research spans stochastic topology, extremal combinatorics, and applications of discrete geometry to puzzles and games. She explores configuration spaces, topological properties of random structures, and innovative educational approaches like the Music Math Project, which integrates music and mathematics. Awards: Includes the Marie Skłodowska-Curie Fellowship (2020-2022), Arana-Ordaz Prize (2019), and Sofia Kovalevskaia Prize (2019). She has also received grants from CONACYT and CIMAT. Grants & Outreach: Developed workshops in marginalized communities using music and math, and contributed to software tools like the Eden Model analysis package. Active in science popularization through articles and outreach programs. Labs/Teams: Collaborated on projects like the Eden Model (topology analysis software) and extremal animal configurations, often involving interdisciplinary teams in mathematics and computer science.

Haye Hinrichsenمشاهده پروفایل

استاد

• Quantum Information Theory
• Exactly Solvable Systems
• Tensor Networks
• +۴ مورد دیگر

Prof. Haye Hinrichsen holds a C3 professorship at the University of Würzburg within the Chair of Theoretical Physics III . His academic journey includes roles as Acting Professor at the University of Wuppertal (2001), Senior Assistant at Duisburg-Essen (2000), and postdoctoral research at institutions like the Weizmann Institute of Science (1995–1997). He earned his PhD in 1993 from the University of Bonn under Prof. V. Rittenberg, focusing on quantum groups. His research interests span quantum information theory , exactly solvable systems , statistical physics far from equilibrium , reaction-diffusion processes , and non-equilibrium phase transitions . Notable achievements include the 2007 Award for Good Teaching and contributions to understanding entropy-based tuning systems in music. His recent work explores topics like causal set propagators in anti-de Sitter spacetime, eigenmodes on hyperbolic lattices, and renormalization techniques in quantum field theories. He has also applied physics principles to music acoustics, developing adaptive tuning schemes using entropy maximization. Key Research Themes: Quantum gravity, non-equilibrium dynamics, topological complexity, and interdisciplinary applications in music. Teaching: Courses include Theoretical Physics I, Computational Physics, and General Relativity. Lab/Affiliation: Chair of Theoretical Physics III at Hubland South, Building M1.

• Theoretical Physics
• Condensed Matter Physics
• Quantum Materials
• +۳ مورد دیگر

Dr. Moritz Fuchs is a former academic member of the Theoretical Physics IV group at the University of Würzburg. He holds a Diplom in Physics (2010) and a PhD in Physics (2016) from the same institution. His research focuses on theoretical physics with an emphasis on quantum materials and computational methods, reflecting the group's specialization in condensed matter physics and many-body systems. While affiliated with the department, he contributed to the research activities of the Theoretical Physics IV group, collaborating with senior faculty such as Prof. Björn Trauzettel and Prof. Ewelina Hankiewicz. Though no specific publications or awards are listed in the provided text, his work aligns with the group's broader interests in theoretical and computational approaches to complex physical systems. Dr. Fuchs' subsequent professional activities are not detailed here, though he appears to have transitioned out of the academic group's active membership. His educational background and prior association with a leading theoretical physics group at the University of Würzburg highlight his expertise in foundational and applied theoretical physics.

Tobias Straußمشاهده پروفایل

مدرس

• Mathematics Education
• Historical Document Analysis
• Machine Learning
• +۵ مورد دیگر

Dr. Tobias Strauß is a Lecturer at the Institute of Mathematics, Faculty of Mathematics and Natural Sciences, University of Rostock. He teaches courses such as Elementary Algebra and Number Theory and Analytical Geometry, focusing on foundational mathematical concepts and their applications. His research interests span historical document analysis, machine learning, and neural networks, with a particular emphasis on handwritten text recognition (HTR) and computational solutions for cultural heritage digitization. He actively contributes to the Mathematics Society RHO eV, supporting students in mathematics competitions and enrichment programs. Dr. Strauß’s research combines computer vision and machine learning to address challenges in document analysis, including text line detection, cursive script recognition, and keyword search in historical manuscripts. His work also explores semi-supervised learning techniques and neural network architectures tailored for HTR tasks. Through RHO eV, he promotes mathematics education through weekend seminars, district clubs, and game-based learning activities, fostering student engagement and problem-solving skills. His publications highlight advancements in HTR systems, such as the CITlab Recognition & Retrieval Engine, and address topics like regular expression-based decoding and Arabic handwriting recognition. These contributions underscore his expertise in bridging theoretical mathematics with practical applications in digital humanities and education. Dr. Strauß can be contacted via tobias.strauss@uni-rostock.de or through the university’s chat platform. No formal awards or grants are noted in the provided materials, though his involvement in international competitions (e.g., ICFHR, ICDAR) reflects his scholarly engagement.