جست‌وجوی استاد و پژوهشگر

Kislaya Raviمشاهده پروفایل

پژوهشگر

• Multifidelity Uncertainty Quantification
• Gaussian Process
• Sparse Grids Methods
• +۲ مورد دیگر

Kislaya Ravi is a Doctoral Candidate at the Technical University of Munich (TUM), affiliated with the Chair of Scientific Computing within the TUM School of Computation, Information and Technology. She holds an M.Sc. in Computational Science and Engineering from TUM and degrees in Mechanical Engineering from the Indian Institute of Technology (BHU). Her research focuses on multifidelity uncertainty quantification, Gaussian processes, sparse grids methods, machine learning, and stochastic optimization. Education: M.Sc., Computational Science and Engineering, Technical University of Munich (202X) M.Tech., Machine Design, Indian Institute of Technology (BHU) (20XX) B.Tech., Mechanical Engineering, Indian Institute of Technology (BHU) (20XX) Research Interests: Kislaya’s work bridges computational methods and stochastic systems, emphasizing efficient uncertainty quantification techniques in physics and engineering. She explores multifidelity approaches to enhance computational efficiency in complex simulations and data-driven modeling. Teaching and Advising: Core instructor for Scientific Computing II and Algorithms for Uncertainty Quantification . Supervised multiple Master’s and Bachelor’s theses on topics like black-box optimization, surrogate modeling, and plasma instability analysis. Publications highlight contributions to multi-fidelity Gaussian processes, No-U-Turn sampling, and kinetic modeling. Her work appears in journals like Machine Learning: Science and Technology and conferences such as SIAM CSE and MCQMC.

Stefan Alexander Schneiderمشاهده پروفایل

استاد

• Autonomous Driving
• Driver Assistance Systems
• Vehicle Simulation
• +۳ مورد دیگر

Affiliations & Roles Prof. Dr. Stefan Alexander Schneider holds a professorship in Autonomous Driving and Driver Assistance Systems at the Faculty of Electrical Engineering of Kempten University of Applied Sciences. He also serves as Program Coordinator and Academic Advisor for the Master's program in Driver Assistance Systems. Additionally, he is a Visiting Professor at Shibaura Institute of Technology (Tokyo, Japan) . Education & Academic Background He completed his doctoral thesis "Adaptive Solution of Elliptic Partial Differential Equations by Hierarchical Tensor Product Finite Elements" in 2000, laying groundwork for his later research in computational methods. Research Focus His work centers on autonomous driving technologies , including: Simulation methodologies for vehicle systems Safety validation of driver assistance systems Human-machine interface design for elderly mobility solutions Standardization of testing frameworks (e.g., Open Simulation Interface) Key Contributions Recent projects include: ZuMoBe: Exploring autonomous electric vehicles in mountain valleys Development of Virtual Systems Prototyping frameworks for automotive innovation Cross-border collaboration via the VIVID German-Japanese initiative Teaching & Mentorship As a leader in one of the world's few Master's programs dedicated to ADAS/AV technologies, he mentors students in cutting-edge topics like monocular depth estimation, trajectory modeling, and interface design. His advisees have produced impactful works on autonomous scooter usability, localization algorithms, and motion planning validation.

Lambert Theisenمشاهده پروفایل

پژوهشگر

• Partial Differential Equations (PDEs)
• Numerical Analysis
• Computational Fluid Dynamics
• +۵ مورد دیگر

Lambert Theisen is a PhD student and Researcher at RWTH Aachen University's Applied and Computational Mathematics (ACoM) department. He holds a BSc (2014–2018) and MSc (2018–2019) in Computational Engineering Science from RWTH Aachen. His research focuses on PDE eigenvalue problems, asymptotic analysis, directional homogenization, and numerical methods for rarefied gas dynamics. He has held research roles at RWTH Aachen, the University of Stuttgart's NMH/IANS, and ABB Corporate Research. His research spans computational fluid dynamics, domain decomposition methods, and preconditioning techniques for eigenvalue algorithms. Notable contributions include finite element solvers for electrolyte models and FEniCS-based simulations of rarefied gas flows. His work often integrates advanced mathematical frameworks with high-performance computing. Teaching roles include assistantships for courses like 'Mathematical Aspects in Computational Chemistry' and 'Higher Mathematics for Engineers.' His publications are tracked via ORCid and emphasize scalable eigensolvers, mesh generation, and tensorial methods. He maintains a personal website at thsn.dev for research updates.

Annemarie Verkerkمشاهده پروفایل

استادیار

• Linguistic Typology
• Historical Linguistics
• Phylogenetic Comparative Methods
• +۷ مورد دیگر

Jun.-Prof. Dr. Annemarie Verkerk is a linguistic typologist affiliated with Saarland University's Department of Language Science and Technology. Her research focuses on corpus-based and phylogenetic methods to study language diversity, with particular expertise in Bayesian statistics, diachronic explanations for universals, and information-theoretic modeling. She leads projects like SFB 1102 (C7), investigating communicative efficiency in word order, and SocioBaGS, exploring Bantu grammatical gender systems through sociolinguistic correlates. Her work spans Indo-European, Dravidian, and Bantu languages, employing phylogenetic comparative methods to analyze topics like numeral typology, motion event encoding, and negative existentials. Key collaborations include Numeralbank and BDPROTO, databases central to her research. She has published extensively on topics such as the evolutionary dynamics of negative existentials in Indo-European, differential rates of consonant/vowel change, and the impact of non-native speakers on lexical diversity. Her projects emphasize cross-linguistic comparison, functional explanations, and computational methods. Research highlights include: Phylogenetic analysis of Dravidian language diversification Investigation of motion event encoding typology using parallel corpora Development of BDPROTO for historical phonological data Studies on sociolinguistic factors in Bantu gender systems Her work integrates historical linguistics, computational modeling, and typological analysis to address fundamental questions about language evolution and variation. Current projects emphasize interdisciplinary approaches to understanding functional and environmental pressures shaping linguistic diversity.

• Public Finance
• Budget Law
• Regional Economic Policy
• +۳ مورد دیگر

Prof. Ronny Freier is a Professor of Public Finance and Budget Law at the Wildau University of Applied Sciences since 2017. He holds a doctorate in political economy from the Stockholm School of Economics and has held visiting professorships at Humboldt University Berlin (2012/13) and the University of Potsdam (2017). His research focuses on municipal finance, regional economic policy, and public administration, with notable contributions to understanding fiscal sustainability, school governance, and cross-border economic dynamics. Freier has led projects for institutions like the Bertelsmann Stiftung and contributed to international comparative studies on school administration autonomy. His academic journey includes a Diplom in Economics from the Free University of Berlin (2006), doctoral studies at Stockholm School of Economics, and postdoctoral research at DIW Berlin. He teaches economics, mathematics, and political science at Wildau, emphasizing applied microeconomics and quantitative methods. Freier’s work bridges theoretical research and policy practice, addressing real-world challenges such as post-pandemic municipal finances and regional development disparities. Recent research highlights include analyzing the impact of school closures on local economies and exploring convergence patterns along the Polish-German border. His advisory roles include serving on the Mittelstandsrat der KfW and contributing to policy discussions on fiscal reforms and democratic participation. Freier actively mentors students and researchers, supervising numerous theses and doctoral candidates in public finance and political economy.

Christian Gawronمشاهده پروفایل

استاد

• Internet Technologies
• Software Engineering
• Natural Language Processing
• +۳ مورد دیگر

Prof. Dr. Christian Gawron is a Professor of Internet Technologies at the University of Applied Sciences Südwestfalen since 2019. He leads the Master's program in Applied Computer Science and has held roles as Department Head and Practice Group Leader at IBM Global Business Services (2014–2018), focusing on Watson AI, chatbots, and text mining. Previously, he was a Senior IT Architect at IBM (1999–2014), specializing in business process digitalization for the insurance sector. He earned his Dr. rer. nat. in 1999 with a dissertation on Simulation-Based Traffic Assignment , and held research roles at the Center for Applied Computer Science (ZAIK) and the Universities of Cologne and Bonn. His research spans internet technologies, software engineering, natural language processing (NLP), and traffic simulation. His academic journey includes a physics degree from the Universities of Cologne and Bonn (1989–1995). His work bridges theoretical computer science and practical AI applications, including projects like BERT-DE-NER for NLP and traffic simulation models for large networks. He advises students on theses and projects, emphasizing real-world applications of technology. Prof. Gawron’s research trends reflect a shift from foundational traffic simulation (1990s) to modern AI-driven solutions (2020s), with notable contributions to transformer models and toxic comment detection. His IBM experience underscores practical IT architecture and AI implementation. Consultations are arranged via Calendly or email. He is a prolific researcher, with key contributions in traffic flow theory (e.g., dynamic user equilibrium algorithms) and NLP (e.g., BERT-based models). His work frequently addresses interdisciplinary challenges, such as environmental impact modeling in traffic simulations (FVU cooperative, 1998). Advising & Grants: Supervised numerous theses in internet technologies and AI. Prior IBM projects included grants for AI-driven insurance process optimization and real-time traffic simulation infrastructure. Labs/Teams: Leads the Internet Technologies research group at FH Südwestfalen, collaborating with industry partners on AI and NLP applications.

• Geophysics
• Hydrogeochemistry
• Digital Rock Physics
• +۴ مورد دیگر

Frieder Enzmann is an Associate Professor and Academic Director at the Institute of Geosciences, Johannes Gutenberg University Mainz. He leads the Computed Tomography Laboratory (currently out of service) and oversees projects like HyINTEGER, ReSKIN, ReSALT, ReSKIN_Move, BIOPORE, MABEIS I/II, and others. His research focuses on geophysical imaging, porous media dynamics, and subsurface processes using advanced computational and tomographic techniques. Research Interests: Computed tomography (CT) applications in geosciences Pore-scale modeling of fluid flow and mineral precipitation Rock physics and reservoir characterization Geomorphological hazards (e.g., landslides, debris flows) Climate-related studies involving ice dynamics and sediment flux Projects highlight interdisciplinary collaboration, such as analyzing rockfall risks in Rhineland-Palatinate and modeling geothermal dynamics in flooded mines. His work bridges geology, engineering, and computer science, with applications in energy storage and environmental risk assessment. Publications span over 20 years, with recent emphasis on AI-driven image analysis and pore-scale simulations. He collaborates internationally on projects like HyINTEGER (hydrogen storage) and ReSalt (reactive reservoir systems).

• Probabilistic Forecasting
• Statistical Evaluation
• Climate Science
• +۳ مورد دیگر

Prof. Tilmann Gneiting is a Professor of Computational Statistics at Karlsruhe Institute of Technology (KIT) and Head of the Computational Statistics Working Group at the Heidelberg Institute for Theoretical Studies (HITS). His research focuses on probabilistic forecasting, statistical evaluation of predictive models, and applications in environmental science, epidemiology, and renewable energy. He has held academic roles in mathematics and statistics departments across multiple institutions. His work emphasizes rigorous statistical methodology for forecasting systems, including ensemble models, uncertainty quantification, and validation frameworks. Notable contributions include developing scoring rules for probabilistic predictions, Bayesian model averaging techniques, and geostatistical methods for weather and climate modeling. Courses taught include Forecasting: Theory and Practice and Time Series Analysis . Prof. Gneiting’s research spans diverse areas such as earthquake forecasting, solar energy prediction, and pandemic modeling. He has contributed to R packages like ensembleMOS and ProbForecastGOP , advancing computational tools for statistical analysis. His work bridges theoretical statistics with practical applications in environmental and public health domains. Professional awards and recognitions are not explicitly listed in the provided texts. His advising and grants involve collaborations in interdisciplinary projects, though specific student names or grant details are not mentioned. He leads computational statistics teams at HITS and actively publishes in top-tier statistical and applied journals.

• Database Systems
• Information Systems
• Conceptual Modeling
• +۵ مورد دیگر

Ivan Lukovic is a Professor at the Faculty of Technical Sciences, University of Novi Sad, specializing in database systems, information systems, and conceptual modeling. His research spans over two decades with consistent publication output, demonstrating expertise in domain-specific languages, business process modeling, and data science education. His educational background isn't explicitly detailed in the provided sources, but his extensive publication record and editorial roles suggest advanced academic training in computer science. His research primarily focuses on database systems, information modeling, and applications of these technologies in various domains including education and industry. Lukovic's research interests center around database systems, conceptual modeling, and domain-specific languages. His work demonstrates particular expertise in form-based modeling approaches, integrity constraints, and model-driven development methodologies. He has made significant contributions to the understanding of business application modeling, production process modeling in Industry 4.0 contexts, and educational approaches in computer science. His recent publications show a strong focus on practical applications of database and information systems research, particularly in the areas of production process modeling, educational technologies, and data integration. The articles demonstrate increasing sophistication in methodology and application scope, with recent work addressing contemporary challenges in AI-powered literature review assistance and explainable AI methods. Lukovic has served as guest editor for multiple journal issues, including special editions on computer science applications in management and sustainability, and explainable AI methods. His editorial work reflects recognition of his expertise by the academic community. His collaborative work spans numerous projects with colleagues at the University of Novi Sad and international partners. He has contributed to educational initiatives in data science, particularly through the development of academic study programs at his institution. His work on students' preferences in computer science education indicates active engagement with educational research and curriculum development. Lukovic's research has practical applications in industry settings, particularly in manufacturing and business process domains. His recent work on production process modeling for Industry 4.0 demonstrates how his theoretical research translates into real-world applications that address contemporary industrial challenges.

• Database Systems
• Temporal Data Management
• Time Series Analysis
• +۳ مورد دیگر

Anton Dignös is an Associate Professor at the Free University of Bozen-Bolzano, Italy. His research focuses on temporal databases, time series analysis, and database system optimization. He has co-authored numerous papers in top venues such as VLDB, ICDE, and ACM Computing Surveys, with a strong emphasis on query processing, indexing techniques, and benchmarking tools for database systems. Notable contributions include the SEER toolkit for time series benchmarking and foundational work on temporal anomaly detection in healthcare systems. His work spans theoretical advancements in join algorithms and practical applications in manufacturing and monitoring systems. He has collaborated extensively with researchers like Johann Gamper and Michael H. Böhlen, contributing to projects like TSM-Bench and the development of efficient interval join methods optimized for modern hardware.

Manuel Landstorferمشاهده پروفایل

پژوهشگر

• Mathematical Modeling
• Lithium Ion Batteries
• Solid Electrolytes
• +۴ مورد دیگر

Manuel Landstorfer is a researcher at Ulm University's Department of Numerical Mathematics. His work focuses on mathematical modeling of lithium-ion batteries, particularly solid electrolyte systems, and numerical methods like finite element analysis (FEM) and MPI parallelization. He collaborates with the Theoretical Electrochemistry Group led by PD Dr. Timo Jacob and participates in the BMBF-funded LISA project. His research includes ion transport in solid electrolytes, impedance spectroscopy simulations, and free energy functional-based transport equations. Education: Diploma in Mathematics (FH Regensburg, 2007) Professional Experience: Research associate since 2007, PhD scholarship since 2010 Research interests span numerical solutions to Laplace equations via Schwarz-Christoffel mapping, space charge layer effects, and full-cell battery simulations. He has presented at conferences including the ECS Meetings and DPG Spring Meetings, focusing on battery modeling and electrochemical systems. Technical expertise includes parallel computing (C++, MPI), mesh generation, and PDE-based modeling. His work bridges applied mathematics with electrochemical engineering, emphasizing first-principles-derived parameters in battery models.

• Planetary Science
• Astrophysics
• Geophysics
• +۳ مورد دیگر

Wieland Dietrich is a Researcher and Research Coordinator at the Max Planck Institute for Solar System Research (MPS) , affiliated with the Planetary Science Department. His expertise lies in planetary dynamics, particularly the magnetic fields and atmospheric flows of exoplanets like Hot Jupiters, as well as convection processes in planetary cores and gas giants. Education & Employment : PhD in Physics (2009-2012): IMPRS program at MPS, Katlenburg-Lindau Postdoctoral Research Fellow (2013-2019): University of Leeds (School of Applied Mathematics) and MPS Current roles since 2022: Research Coordinator at MPS Research Focus : Investigates dynamo processes, zonal winds, and satellite measurement correlations with planetary interiors. Recent work emphasizes Hot Jupiter atmospheres and gravity dynamics of gas giants like Jupiter. Publications : Focused on exoplanet magnetism, zonal wind mechanisms, and computational models of planetary convection. Key contributions include studies on KELT-9b's magnetic fields and Jupiter's gravity moments. Awards : None explicitly mentioned in the provided texts. Labs & Teams : Active within the Planetary Science Department at MPS, contributing to interdisciplinary research on solar system and exoplanetary dynamics.

• Computational Economics
• Agent-Based Modeling
• Innovation Economics
• +۹ مورد دیگر

Herbert Dawid is a Professor of Economic Theory and Computational Economics at the Faculty of Business and Economics , Bielefeld University , Germany. He holds multiple roles including Chair Holder, Subproject Manager for SFB 1283, and Founding Director of the Center for Uncertainty Studies (CeUS) . His research focuses on Computational Economics , Agent-Based Modeling , and Innovation Dynamics , with emphasis on uncertainty management and digitalization. Current Appointments Professor (W3), Faculty of Business and Economics, Bielefeld University (since 2010) Subproject Manager, SFB 1283 (Innovation Dynamics in Market Uncertainty) Founding Director, Center for Uncertainty Studies (CeUS) Research Themes Digitalization and Intelligent Products Investing Under Uncertainty Agent-Based Modeling in Economics Dynamic Analysis of Economic Policy Control Theory and Differential Games His work spans economic policy modeling , technological innovation , and financial constraint analysis , with notable publications on AI integration in economic systems and autonomous vehicle policy frameworks. He contributes to interdisciplinary initiatives like AI*IM (Interactive Inclusive AI for People with Cognitive Disabilities) through economic expertise.

• Continual Learning
• Few-Shot Learning
• Domain Adaptation
• +۷ مورد دیگر

Mahardhika Pratama is a Professor in the Department of Computer Science at Universitas Indonesia's Faculty of Computer Science, where he leads research in machine learning and artificial intelligence. His work bridges theoretical advancements with practical applications across various domains including time series analysis, autonomous systems, and resource-constrained environments. Pratama's research focuses on overcoming fundamental challenges in machine learning systems, particularly in the areas of continual learning and few-shot learning. His work addresses the critical problem of catastrophic forgetting in neural networks while developing efficient learning systems that can adapt to new tasks with minimal data. His publications reveal a strong emphasis on developing practical solutions for real-world applications where data is scarce or constantly evolving. Analysis of his recent publications (2023-2025) shows a clear research trajectory toward more sophisticated approaches for continual learning under data scarcity, with increasing focus on transformer architectures, multi-agent reinforcement learning, and cross-domain adaptation techniques. His work demonstrates a consistent pattern of addressing both theoretical foundations and practical implementations of adaptive learning systems. His research has been supported through numerous collaborative projects with international institutions including UNSW Canberra, Swinburne University of Technology, and University of Alberta, reflecting the global impact of his work in the machine learning community.

Motagh M.مشاهده پروفایل

پژوهشگر

• Remote Sensing
• Geodesy
• Seismology
• +۳ مورد دیگر

Motagh M. is a Researcher at the Deutsches GeoForschungsZentrum (GFZ) in Potsdam, Germany. With expertise in Remote Sensing and Geodesy , their work focuses on geohazard assessment through satellite-based interferometric techniques. Current research explores land subsidence in Afghanistan and Iran using Sentinel-1 data Developing hybrid machine learning models for landslide susceptibility assessment Pioneering quantum machine learning applications in deformation detection Investigating mining-induced subsidence in Germany's Hambach region Contributing to multi-sensor InSAR integration for complex geological analysis Publications since 2011 demonstrate sustained contributions to: Earthquake source modeling (e.g., Christchurch 2011, Maule Chile 2010) Volcanic deformation studies in Iceland Environmental geoscience applications across three continents Collaborations span institutions in: New Zealand (University of Canterbury, GNS Science) Iran (University of Tehran, K. N. Toosi University) Germany (GFZ Potsdam, Technical University Munich) USA (University of Miami)