جست‌وجوی استاد و پژوهشگر

Alexander Schwarzمشاهده پروفایل

عضو هیئت علمی

• Computational Mechanics
• Finite Element Methods
• Least-Squares Finite Element Formulations
• +۱۳ مورد دیگر

Dr.-Ing. Alexander Schwarz is a Senior Academic Councillor at the Institute of Mechanics, Faculty of Engineering, University of Duisburg-Essen, Germany. He is actively involved in research and teaching in computational mechanics, with a focus on finite element methods, particularly least-squares formulations for solid and fluid mechanics. He has served as Course Director of the International Master's Program in Computational Mechanics since 2011. PhD in Engineering, University of Duisburg-Essen (2009) Diploma in Civil Engineering, University of Essen and University of Adelaide (2004) Research Assistant, Institute of Mechanics (2005–2009) Academic Councillor (2010), Senior Academic Councillor (since 2013) His research interests center on the development and analysis of mixed finite element methods, especially least-squares approaches, applied to problems in solid mechanics (hyperelasticity, elasto-plasticity, finite deformations), fluid dynamics (incompressible Navier-Stokes), fluid-structure interaction, and porous media. His work emphasizes numerical stability, accuracy, and efficient implementation. The recent publications highlight a strong trend in advancing least-squares finite element formulations for both fluid and solid mechanics. His work spans theoretical development, numerical implementation, and comparative studies, with applications in incompressible flow, hyperelasticity, plasticity, and multi-physics problems like FSI and phase change. The use of stress-velocity or stress-displacement formulations is a recurring theme, aiming to improve conservation properties and solution accuracy. No scientific awards are listed in the provided information. Dr. Schwarz has supervised numerous master’s and bachelor’s theses in computational mechanics, particularly on finite element formulations for Navier-Stokes equations, plasticity, and hyperelasticity. His collaborations with prominent researchers like Jörg Schröder, Carina Nisters, and Solveigh Averweg indicate strong integration into an active research group. While no specific grants are mentioned, his sustained publication output and leadership in the master’s program suggest ongoing research funding and academic responsibility. He is a core member of the Institute of Mechanics at the University of Duisburg-Essen, contributing to both research and academic leadership. His team focuses on advanced computational methods in mechanics, with a strong emphasis on finite element technology and its application to complex material and fluid behavior.

• Mathematics
• Mathematical Modeling
• Applied Mathematics
• +۱ مورد دیگر

Dr. Jonas Flechsig is a researcher at Bielefeld University, affiliated with the Faculty of Mathematics. He is actively involved in research and teaching, with his office located in UHG V4-207, and can be reached via phone at +49 521 106-4981. His research interests lie in the broad domain of mathematics, aligning with the university's strategic focus on the Mathematical World , where fundamental mathematical concepts are developed and applied to solve complex problems in natural sciences and economics. While specific publications and research projects are not detailed in the provided text, his profile includes dedicated sections for research output and teaching activities, indicating active scholarly engagement. No scientific awards or student advisement details are currently listed. Dr. Flechsig contributes to the academic mission of Bielefeld University, an institution known for its interdisciplinary research culture and commitment to transcending boundaries between disciplines, society, and science.

Katja Heinischمشاهده پروفایل

پژوهشگر

• international macroeconomics
• applied time series econometrics
• short-term forecasting
• +۳ مورد دیگر

Katja Heinisch serves as Head of the Research Group "Econometric Tools for Macroeconomic Forecasting and Simulation" at the Halle Institute for Economic Research (IWH) since January 2013, and has been a member of the Department of Macroeconomics since September 2009. Her work focuses on developing advanced econometric methodologies for economic forecasting with practical applications for policymakers. Dr. Heinisch earned her diploma from Chemnitz University of Technology and University of Strasbourg, followed by a PhD from Osnabrück University. Her international research experience includes significant positions at the European Central Bank (ECB) and the International Monetary Fund (IMF), which have shaped her expertise in macroeconomic analysis across different institutional contexts. Her research program centers on international macroeconomics, applied time series econometrics, short-term forecasting, and macroeconometric modeling. A distinctive feature of her work is the rigorous evaluation of forecast accuracy, with particular attention to how assumption errors affect prediction quality. She has developed expertise in advanced statistical techniques including partial linear instrumental variable models and double machine learning approaches to address methodological challenges in forecast evaluation. Analysis of her recent publications reveals a consistent focus on improving forecasting techniques for the German economy and the European Union. Her work demonstrates sophisticated methodological approaches while maintaining strong policy relevance, particularly in evaluating EU Commission GDP forecasts and developing tools like the IWH forecasting dashboard. Her research on economic sentiment analysis has provided novel methods for disentangling private information from public knowledge in survey data, enhancing the utility of consumer surveys for economic forecasting. Developed advanced methods for forecast evaluation using machine learning techniques Created tools for real-time economic analysis and forecast comparison Contributed significantly to understanding the relationship between assumption errors and forecast accuracy Advanced methodologies for economic sentiment analysis in forecasting contexts Dr. Heinisch's leadership of her research group at IWH positions her at the forefront of methodological innovation in economic forecasting, with her work bridging theoretical econometrics and practical policy applications.

• Automata Theory
• Formal Languages
• Weighted Automata
• +۳ مورد دیگر

Erik Paul is a faculty member at Universität Leipzig's Faculty of Mathematics and Computer Science, affiliated with the Institute of Computer Science and the Automaten und Sprachen (Automata and Languages) research group. His primary academic rank is Lecturer, where he teaches courses such as Automata Theory, Logic and Model Theory, and Semantics of Programming Languages. Paul's research focuses on theoretical computer science with specialization in Automata Theory, Formal Languages, and Weighted Automata. His work explores decidability problems, tree automata, and logical characterizations of computational models, with significant contributions to the understanding of sequentiality and ambiguity in max-plus automata. His publications demonstrate a consistent focus on automata theory and formal methods, with recent work addressing weighted HOM problems and sequentiality in finitely ambiguous systems. The research spans foundational theory, algorithmic decidability, and applications in formal verification. Scientific Awards: ICALP 2020 Best Student Paper Track B Paul actively contributes to academic service through seminar organization and thesis supervision within the Automata and Languages research group.

• Mathematics
• Mathematical Modeling
• Theoretical Mathematics
• +۱ مورد دیگر

Dr. Aleksandr Tarasov is a researcher affiliated with the Faculty of Mathematics at Bielefeld University. His work aligns with the university's strategic research areas, particularly the Mathematical World , which focuses on fundamental mathematical concepts and their applications to solve complex problems in economics and natural sciences. Email: atarasov@math.uni-bielefeld.de Office: UHG V5-126 Phone: +49 521 106-4987 Bielefeld University emphasizes Transcending Boundaries as its research principle, fostering interdisciplinary collaboration between disciplines, people, and science with society. Dr. Tarasov's role likely contributes to this culture through mathematical research and potential third-party funded projects.

• Mathematics
• Mathematical Modeling
• Theoretical Mathematics
• +۱ مورد دیگر

Dr. Pavlo Tkachov is a faculty member in the Department of Mathematics at Bielefeld University, Germany. He maintains an active academic position with office location V3-225 (UHG V4-138) and can be reached at +49 521 106-4978. His research interests fall within the broader domain of mathematics, aligning with Bielefeld University's strategic research focus on the Mathematical World, which develops fundamental mathematical concepts and theories while applying them to solve complex problems in economics and natural sciences. His work likely intersects with the university's interdisciplinary approach emphasizing Transcending Boundaries between disciplines and scientific cultures. As part of Bielefeld University's academic community, Dr. Tkachov contributes to the institution's mission of conducting cutting-edge basic research at an international level through interdisciplinary collaboration. The university's research environment includes specialized centers such as the Focus of Research on Mathematical Modelling (FSPM²) which may provide context for his academic activities.

• Natural Language Processing
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Aditya Sharma is a researcher at the University of California Santa Barbara , focusing on Natural Language Processing , Computer Vision , and Artificial Intelligence . His work bridges vision-language models, medical AI evaluation, and knowledge graph reasoning. PhD : Advancing AI Understanding in Language & Vision (UCSB, 2024) Research Interests: • Vision-Language Models for geometric reasoning and mixed reality • Medical LLM evaluation and hallucination reduction • Temporal knowledge graph reasoning and multimodal systems Article Trends: Recent publications emphasize vision-language integration (e.g., GeoCoder, OCTO+), LLM reliability in medical contexts (MedHELM), and temporal reasoning (TwiRGCN). He explores applications in dark web security , healthcare diagnostics , and energy-efficient computing .

• Algebraic Geometry
• Computational Algebraic Geometry
• Integrable Systems
• +۶ مورد دیگر

Türkü Özlüm Çelik is a research group leader at the Max Planck Institute of Molecular Cell Biology and Genetics and the Center for Systems Biology Dresden . Her research bridges abstract algebraic geometry with computational methods and applications in natural sciences. Education : PhD in Mathematics at Institut de recherche mathématique de Rennes (defended in 2018). Her research focuses on algebraic curves, theta functions, and abelian varieties, with applications in integrable systems, biological classification, and optimization. She employs numerical algebraic geometry and computer algebra to extract mathematical structures from scientific data. Notable projects include studies on space sextics, tritangents, and the KP equation. Her group explores bidirectional interactions between mathematics and natural phenomena, emphasizing continuous-discrete duality. Recent collaborations address computational challenges in algebraic geometry, such as Wasserstein distance optimization and eigenpoint analysis of cubic surfaces. In 2024, she received the TUD Young Investigator status and co-organized workshops on computational algebraic geometry and women in mathematics. Her group actively participates in the Elbe Program for postdoctoral opportunities.

• Physical Geodesy
• Satellite Geodesy
• Gravity Field Modeling
• +۵ مورد دیگر

Josef Niedermaier is a researcher at the Chair of Astronomical & Physical Geodesy, Technical University of Munich (TUM), where he contributes to advanced research in geopotential modeling and gravity field analysis. His work is closely tied to major international geodetic initiatives and collaborative research projects including ESA and DFG-funded programs. His research focuses on physical and satellite geodesy , particularly in the areas of gravity field modeling , geoid determination , and error assessment in regional and global models . He investigates challenges in mountainous regions and contributes to the development of high-precision height systems based on geopotential references. His methodological focus includes error tree analysis and validation of state-of-the-art geoid experiments. The recent publications highlight a strong trend toward quantifying uncertainties in gravity field models, improving regional modeling accuracy , and supporting the standardization of global height systems . His collaborative work with Roland Pail, Thorsten Gruber, and others reflects active participation in the international geodetic community. No scientific awards mentioned in the provided text. Josef Niedermaier has supervised at least one bachelor’s thesis, indicating involvement in academic mentoring. While no specific grants are listed, his participation in DFG Research Unit NEROGRAV and ESA projects (MAGIC, QSG4EMT, Baltic+) suggests engagement in externally funded research. He contributes to large-scale scientific collaborations focused on gravity and geoid modeling. He is part of the Engineering Institute for Astronomical and Physical Geodesy at TUM, working within a team focused on satellite geodesy and high-precision gravity field solutions. His work supports broader efforts in Earth system monitoring and reference frame development.

• Requirements Engineering
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

Dr. Başak Aydemir is an Assistant Professor at the Department of Information and Computing Sciences , Faculty of Science, Utrecht University. She works in the Software Production Group , focusing on applying Natural Language Processing , Machine Learning , and Artificial Intelligence to Requirements Engineering problems. She obtained her Ph.D. from the University of Trento in 2016 and previously worked at Bogaziçi University (2018-2024) before rejoining Utrecht University. Software Development Requirements Engineering Conceptual Modeling Natural Language Processing Life Sciences Her research explores Requirements Engineering through NLP and AI, with recent work on Large Language Models for domain model generation, Robotic Tutors for interview training, and Creativity Techniques in requirements workshops. She investigates ethics-aware systems and multi-agent planning , emphasizing software quality and empirical validation. Recent publications span IEEE RE , REFSQ , and Empirical Software Engineering journals. Key trends include NLP-driven requirement analysis , interactive training systems , and gamified platforms for change management. She co-organized the AIRE 2024 and NLP4RE 2021 workshops. She teaches courses in Method and Model-Driven Engineering , contributes to Business Informatics programs, and is available at Room 5.82, Buys Ballot Building, Utrecht.

Thomas Zimmermannمشاهده پروفایل

استاد

• Primary Care Medicine
• Mental Health Integration
• Collaborative Care Models
• +۶ مورد دیگر

Thomas Zimmermann is a Professor at the Department of General Medicine within the Faculty of Medicine at University Medical Center Hamburg-Eppendorf. With a background as a Diplom-Psychologist and holding a doctoral degree, he has established himself as a prominent researcher in primary care medicine with a focus on integrating mental health services, interdisciplinary care approaches, and healthcare system analysis. ORCID: 0000-0002-2047-9907 Affiliation: Institute and Outpatient Clinic for General Medicine Dr. Zimmermann's research primarily centers on mental health integration within primary care settings, with special emphasis on collaborative and stepped care models for patients with mental disorders. His work extends to social prescribing initiatives, self-management support strategies, and the intersection between oral health and general medical care, particularly for elderly patients in home care settings. His research often addresses systemic challenges in healthcare delivery and explores innovative solutions to improve patient outcomes through better care coordination. His publication record demonstrates a clear trajectory toward increasingly complex interdisciplinary research, with recent work focusing on the boundary between dental and medical care for home care patients (InSEMaP study) and the implementation of collaborative care models for mental health conditions in primary care (COMET study). These projects reflect his commitment to addressing gaps in healthcare delivery through evidence-based interventions that bridge traditional sector boundaries. Dr. Zimmermann has been actively involved in multiple significant research projects including the COMET Study (Collaborative and Stepped Care for Mental Disorders), the InSEMaP study (Interactions of Systemic Diseases and Oral Health in Home Care), and contributions to understanding the German healthcare system structure. His work frequently appears in high-impact medical journals and book chapters on general medicine, demonstrating his influence in shaping primary care practices and policies in Germany.

Marlis Hochbruckمشاهده پروفایل

استاد

• Numerical Analysis
• Time Integration of PDEs
• Numerical Methods for Differential Equations
• +۶ مورد دیگر

Professor Marlis Hochbruck is a distinguished faculty member at the Karlsruhe Institute of Technology (KIT), where she serves as Head of the Numerical Analysis Working Group within the Faculty of Mathematics and the Institute for Applied and Numerical Mathematics. Her office is located at Englerstraße 2, 76131 Karlsruhe, Germany, in the Kollegiengebäude Mathematik (20.30), room 3.001. She is actively involved in teaching and research, with courses scheduled through Summer Semester 2025. Her research interests span a wide range of topics in numerical analysis, with a particular focus on time integration methods for partial differential equations , wave equations , Maxwell's equations , and exponential integrators . Her work bridges theoretical numerical analysis with practical computational methods, addressing challenges in computational mathematics and scientific computing. Professor Hochbruck has developed and analyzed numerous numerical schemes that maintain stability and accuracy for complex wave phenomena and electromagnetic simulations. Professor Hochbruck's publications demonstrate a consistent focus on advancing numerical methodologies for time-dependent PDEs. Her recent work shows increasing attention to specialized applications including quantum mechanics (Schrödinger equation), electromagnetic scattering, and nonlinear wave phenomena. She frequently collaborates with researchers across multiple institutions, particularly within the CRC 1173 framework at KIT, which focuses on wave phenomena. Professor Hochbruck has supervised numerous doctoral students who have completed dissertations on topics related to numerical methods for wave equations, exponential integrators, and time integration schemes. Her academic lineage includes researchers who have made significant contributions to computational mathematics. Her teaching portfolio is extensive and consistent, covering core numerical mathematics courses as well as specialized seminars on numerical methods for differential equations, time integration, and wave phenomena. She has taught continuously from Winter Semester 2010/11 through Summer Semester 2025, demonstrating sustained academic engagement.

• Set Theory
• Mathematical Logic
• Ontologies
• +۶ مورد دیگر

Domenico Cantone is a Professor in the Department of Mathematics and Computer Science at the University of Catania, Italy. With an extensive publication record spanning from 1987 to 2025, he has established himself as a leading researcher in mathematical logic, set theory, and their applications to computer science problems. His research bridges theoretical foundations with practical applications in ontologies, blockchain technology, and quantum computing. Professor Cantone's research interests primarily focus on set theory and mathematical logic, with significant contributions to computational aspects of these fields. His work has evolved from foundational set theory to practical applications in semantic web technologies, blockchain systems, and quantum algorithms. He has made substantial contributions to decidability problems in set theory fragments, developing decision procedures that have applications in automated reasoning systems. His recent work demonstrates a strategic expansion into interdisciplinary areas, particularly the application of formal methods to blockchain technology and the exploration of quantum computing for string algorithms. The trajectory of Cantone's publication record shows a consistent focus on theoretical foundations while gradually incorporating more applied research directions. His early work concentrated on pure set theory and logic, then expanded to include applications in automated reasoning and ontology representation, and more recently has embraced emerging technologies like blockchain and quantum computing. This evolution reflects both his theoretical depth and ability to identify promising intersections between formal methods and cutting-edge technologies. Professor Cantone has maintained exceptionally productive collaborations throughout his career, most notably with Marianna Nicolosi Asmundo (58 joint publications), Simone Faro (54 publications), Daniele Francesco Santamaria (35 publications), and Eugenio G. Omodeo (35 publications). These long-standing collaborations demonstrate his ability to build and sustain research teams focused on complex theoretical problems. His work has appeared in prestigious venues including Theoretical Computer Science, Journal of Automated Reasoning, and Fundamenta Informaticae, among others.

• Mathematical modeling
• Biomedical engineering
• Cerebral blood flow
• +۴ مورد دیگر

Dr. Irina Sidorenko is a Researcher in the Department of Mathematics at the Technical University of Munich, working within the School of Computation, Information and Technology. She is affiliated with the Chair of Analysis and Modelling under Prof. Zimmer and is an active member of the Analysis and Mathematical Biology research group. Her work bridges advanced mathematical techniques with critical biomedical applications, particularly in neonatal physiology. Dr. Sidorenko's research focuses on mathematical modeling of physiological systems, with particular emphasis on cerebral blood flow and oxygen transport mechanisms in the developing brain. Her work combines differential equations, inverse problems, and numerical analysis to create sophisticated models that capture complex biological processes. She has made significant contributions to understanding hemodynamics in preterm infants, developing models that account for factors like hematocrit levels, blood gases, and capillary network structures. Her research has evolved from plasma physics in her early career to biomedical applications, demonstrating remarkable interdisciplinary versatility. Analysis of her recent publications reveals a strong focus on neonatal cerebral physiology, with consistent output in high-impact journals spanning mathematics, engineering, and medical disciplines. Her work shows increasing sophistication in modeling approaches, moving from basic continuum models to more complex spatially-averaged network models that incorporate multiple physiological factors. The research demonstrates a clear translational trajectory, with mathematical insights increasingly directed toward solving specific clinical challenges in neonatal care. Dr. Sidorenko maintains active collaborations with medical researchers, particularly in neonatology, creating a productive interdisciplinary research environment. Her work on cerebral blood flow modeling has direct clinical relevance, potentially informing diagnostic and therapeutic approaches for preterm infants at risk of intraventricular hemorrhage. The Analysis and Mathematical Biology group provides a rich research environment where mathematical theory meets biomedical application. Dr. Sidorenko's work exemplifies how sophisticated mathematical modeling can address complex physiological questions, creating quantitative tools that have the potential to improve clinical outcomes for vulnerable patient populations.

Guillaume Ducoffeمشاهده پروفایل

دانشیار

• Algorithmic Graph Theory
• Computation in Large Graphs
• Parameterized Algorithms
• +۱۲ مورد دیگر

Guillaume Ducoffe is an Associate Professor at the Faculty of Mathematics and Informatics, University of Bucharest, Romania, and a Senior Research Scientist at the National Institute of Research and Development in Informatics (I.C.I.), Romania. He is also affiliated with a joint research team between ICI and the Research Institute of the University of Bucharest (I.C.U.B.). Previously, he was a PhD student at Université Côte d'Azur, France, under the supervision of David Coudert, within the COATI project-team at Inria Sophia Antipolis. PhD, Université Côte d'Azur, France (2016) Master's Thesis, MPRI-ENS Cachan (2013) His research centers on algorithmic graph theory , with emphasis on computation in large graphs , including parameterized algorithms for problems like Diameter and Maximum Matching. He investigates metric tree-likeness in real-life networks through Gromov hyperbolicity, which has implications for routing efficiency and congestion. His work extends to information propagation using game-theoretic models such as coloring and hedonic games, and to online targeting detection , where he develops theoretically sound algorithms to uncover sensitive attribute targeting on the web via reductions to PAC learning of k-juntas. He also explores combinatorial topics like proper connectivity and Randic indices with applications in cryptography and chemistry. The analysis of his recent publications reveals a strong trend in theoretical computer science , particularly in the design and complexity of graph algorithms, structural graph properties, and their applications in network science and privacy. His work bridges pure graph theory with practical concerns in data centers, web transparency, and social networks. Guillaume Ducoffe has made significant contributions to both journal and conference literature, publishing in venues such as Discrete Applied Mathematics , SIAM Journal on Discrete Mathematics , ACM SIGMETRICS , and USENIX Security . His research is highly interdisciplinary, combining insights from algorithms, game theory, and network analysis. He actively supervises and mentors students, though specific names are not listed in the provided materials. He has been involved in research grants, including a postdoc grant from I.C.U.B., and has collaborated with prominent researchers such as David Coudert, Nicolas Nisse, Augustin Chaintreau, and Roxana Geambasu. His teaching includes core courses such as Data Structures and Algorithms , Advanced Graph Algorithms , and Advanced Programming Techniques at the University of Bucharest. Guillaume Ducoffe is a key member of collaborative research initiatives, including the joint ICI-I.C.U.B. team and the former COATI project at Inria. His work continues to advance the theoretical foundations of graph algorithms while addressing pressing issues in web transparency and network design.