جست‌وجوی استاد و پژوهشگر

• Translation Studies
• Corpus Linguistics
• Machine Translation
• +۵ مورد دیگر

Professor Ekaterina Lapshinova-Koltunski serves as Full Professor (W3) in Multilingual Technical Specialized Communication at the University of Hildesheim since October 2022. She is affiliated with the Institute for Translation Studies & Specialized Communication within Department 3: Linguistics and Information Sciences. Previously, she held positions as Akademische Oberrätin (equivalent to Associate Professor) at Saarland University (2017-2022) and served as Interim Professor at the University of Hildesheim (2020-2021). Her educational background includes: Habilitation in Linguistics, Translation Studies and Corpus Linguistics (2016) from Saarland University PhD in Computational Linguistics (2011) from University of Stuttgart Postgraduate studies in Language Data Processing (2003-2006) from Georg August University of Göttingen Diploma in Translation, Interpreting and Intercultural Communication (1997-2002) from Volgograd State University Professor Lapshinova-Koltunski's research focuses on the intersection of translation studies, corpus linguistics, and artificial intelligence, with particular emphasis on machine translation, plain language communication, and multilingual technical communication. Her work bridges theoretical linguistics with practical applications in healthcare communication, accessibility, and translation technology. She has made significant contributions to understanding cohesion and coherence in translation, cross-linguistic variation, and the cognitive aspects of translation processes. Her recent publications (2024-2025) demonstrate a strong shift toward AI applications in translation, particularly in health communication and plain language translation. These works examine how large language models can support the creation of accessible medical information, analyze gender representation in machine translation, and develop practical frameworks for integrating AI tools into editorial workflows. Her research shows increasing focus on practical applications of translation technology to address real-world communication challenges, especially in healthcare contexts. She actively serves as a reviewer for major funding organizations including DFG and Research Foundation – Flanders, and for numerous prestigious journals and conferences in computational linguistics and translation studies. Her current grant portfolio includes: Project B7 'Translation as Rational Communication' in SFB1102 (2022-2026) 'AI-supported health communication in Plain language' funded by the Ministry of Science and Culture of Lower Saxony (May 2024-August 2025) 'Use of AI tools in intralingual translation of health communication' with Wort & Bild Verlag (October 2023-April 2024) 'Data triangulation in translation process research' startup grant from University of Hildesheim (August 2023-January 2024) Professor Lapshinova-Koltunski holds multiple administrative roles including membership in various examination committees for master's programs in International Communication and Translation, Barrier-free Communication, and Technical Communication, as well as serving on the Faculty Council and Research Committee for Department 3.

• High-Performance Computing
• Automatic distributed memory parallelization
• Communication optimization for CPUs and GPUs
• +۹ مورد دیگر

Anna Mittermair is a researcher at the Chair of Computer Architecture & Parallel Systems at the Technical University of Munich . She is actively involved in teaching and research related to High-Performance Computing (HPC) systems. Teaching Roles : Lab Course Computer Architecture (IN0005), Aspects of Low-Level Programming for Games Development (IN0035) Current Projects : SEANERGYS (EuroHPC), PlasmaPEPS, OpenCUBE, ScalNEXT, and others focused on HPC, quantum computing, and AI hardware. Research Focus : Her work emphasizes automatic distributed memory parallelization and communication optimization for CPUs and GPUs , particularly in ocean models and HPC infrastructure. She supervises thesis topics centered on latency hiding schemes and code block order analysis for performance optimization. Collaborations & Infrastructure : Anna contributes to software projects like QMPI , MOVE-II , and SWEET , leveraging hardware such as CAPS Cloud and HimMUC . She is also affiliated with organizations like the MPI Forum Virtual Institute and Eurolab4HPC .

Jonas Norlinderمشاهده پروفایل

پژوهشگر

• Memory Management
• Virtual Machine Design and Implementation
• Programming Languages
• +۱ مورد دیگر

Jonas Norlinder is a researcher affiliated with Uppsala University in Sweden, specializing in memory management and virtual machine design . He actively contributes to academic conferences such as ECOOP, SPLASH, and PLDI, serving on committees for artifact evaluation and extended review processes.

Shigehiko Schamoniمشاهده پروفایل

مدرس

• Natural Language Processing
• Medical Data Analysis
• Speech Translation
• +۳ مورد دیگر

Shigehiko Schamoni is a Lecturer and Compute Lab Manager at Heidelberg University's Institute of Computer Engineering (ZITI), where he oversees scientific computing infrastructure and teaches computer science courses. He is completing his PhD under Prof. Stefan Riezler in the Statistical NLP group. His dual roles bridge technical management and academic instruction, with teaching responsibilities spanning undergraduate and graduate courses since 2011. Research Focus: Schamoni's work intersects clinical AI and natural language processing, with emphasis on: Machine learning for medical applications (sepsis prediction, clinical validity) Speech translation and automatic speech recognition Cross-lingual information retrieval Data augmentation techniques Multimodal machine learning His 15 most recent publications (2016-2024) demonstrate strong thematic clustering: 47% focus on medical AI (primarily sepsis prediction and clinical data validation), while 53% address NLP challenges (speech translation, ASR, and multimodal systems). This bifurcation reflects consistent collaboration with medical researchers alongside core NLP innovation. Teaching Experience includes instruction across 10+ courses since 2011, such as: Graduate courses: "Tools – Werkzeuge für effizientes wissenschaftliches Arbeiten" (2023-2024) Undergraduate courses: "Einführung in die Nutzung computerlinguistischer Ressourcen" (2021-2022) Programming courses: "Advanced Programming" and "Parallel Programming Paradigms" (2012-2015) He maintains affiliations with both the ZITI infrastructure team and Statistical NLP research group.

• High Performance Computing
• Parallel Programming
• OpenMP
• +۲ مورد دیگر

Matthias S. Müller is affiliated with RWTH Aachen University's IT Center, with additional associations to TU Dresden's Center for Information Services and High Performance Computing and the University of Stuttgart's High Performance Computing Center. His research focuses on parallel computing paradigms, OpenMP optimizations, and energy-efficient high-performance computing. Recent publications demonstrate specialization in parallel pattern compilers, OpenMP runtime optimizations, and energy-aware computing benchmarks. His team develops tools for performance analysis and optimization in heterogeneous computing environments, with applications in computer vision and scientific computing.

• Natural Language Processing
• Speech Recognition
• Machine Learning
• +۵ مورد دیگر

Dietrich Klakow is a prominent researcher at Saarland University in Saarbrücken, Germany, with an extensive publication record spanning from 1997 to 2025. His work primarily focuses on natural language processing, speech recognition, and machine learning with significant contributions to multilingual models and African language processing. His research interests span a wide range of topics within computational linguistics and artificial intelligence. Klakow has made substantial contributions to Natural Language Processing , particularly in multilingual contexts and low-resource languages. His work on African language technologies has been particularly impactful, developing resources and models for languages that are often neglected in mainstream NLP research. He has also conducted significant research in speech recognition , transformer models , and computational linguistics , with a focus on practical applications and theoretical foundations. Klakow's recent publications demonstrate a strong focus on large language models, their capabilities, limitations, and applications across diverse linguistic contexts. His work spans both theoretical investigations of model architectures and practical applications addressing real-world challenges in language technology. His collaborative work spans numerous international partnerships, particularly with researchers working on African language technologies and multilingual NLP systems.

Hendrik Ranochaمشاهده پروفایل

استاد

• Numerical Analysis
• Computational Mathematics
• Partial Differential Equations
• +۶ مورد دیگر

Hendrik Ranocha is a Professor in Numerical Mathematics at Johannes Gutenberg University Mainz, Germany. His research focuses on the analysis and development of numerical methods for partial and ordinary differential equations, with particular emphasis on stability and structure-preserving techniques that transfer results from continuous to discrete levels. His educational background includes: PhD in Mathematics from TU Braunschweig (2016-2018), advised by Thomas Sonar MSc in Mathematics from TU Braunschweig (2014-2016) BSc in Mathematics from TU Braunschweig (2011-2014) Exchange student at Yonsei University, Seoul (2013) BSc in Physics from TU Braunschweig (2010-2013) Hendrik Ranocha's research spans Numerical Analysis and Scientific Computing . His work focuses on developing numerical schemes for hyperbolic balance laws and dispersive-dissipative equations, including Discontinuous Galerkin methods, spectral element methods, finite difference schemes, and flux reconstruction. He specializes in structure-preserving methods that conserve entropy/energy, utilizing summation by parts operators and mimetic properties. His research also encompasses Runge-Kutta methods, stability of time integration schemes, adaptivity in time and space, data-driven approaches, and uncertainty quantification. His recent publications demonstrate a strong focus on entropy-stable numerical methods, structure-preserving discretizations, and high-performance computing implementations in Julia. The research trends show increasing emphasis on practical software implementations (Trixi.jl, SummationByPartsOperators.jl), applications to physical systems like compressible Euler equations and shallow water equations, and addressing fundamental numerical challenges in stability and convergence. Hendrik Ranocha leads a research group at Johannes Gutenberg University Mainz with several PhD students and postdocs, including Louis Petri, Marco Artiano, Sebastian Bleecke, Saurav Samantaray, Arpit Babbar, and Valentin Churavy. He collaborates extensively with researchers such as Gregor Gassner, Andrew R. Winters, Michael Schlottke-Lakemper, and Jesse Chan on numerical methods and software development. He is actively involved in open-source scientific computing, contributing to projects like Trixi.jl (a Julia package for adaptive high-order numerical simulations of conservation laws), SummationByPartsOperators.jl, OrdinaryDiffEq.jl, NodePy, and RK-Opt. He is part of the SciML organization, which develops high-performance Julia libraries for scientific machine learning and computational science.

Isaías A. Comprés Ureñaمشاهده پروفایل

پژوهشگر

• High Performance Computing
• Parallel Programming
• Distributed Systems
• +۳ مورد دیگر

Isaías A. Comprés Ureña serves as a Researcher at the Chair of Computer Architecture and Parallel Systems within the Department of Informatics at the Technical University of Munich (TUM), focusing on advancing exascale computing infrastructure and distributed memory systems. His research centers on High Performance Computing with specialized expertise in parallel programming standards including MPI and PMIx, distributed resource management, batch scheduling optimization, and automatic performance tuning for supercomputing environments. These areas directly support the development of next-generation HPC tools and frameworks for scientific computing workloads. Dr. Comprés actively contributes to international HPC initiatives through membership in the MPI Forum, Virtual Institute - High Productivity Supercomputing, and Eurolab4HPC collaborations, driving standardization efforts for process management and distributed memory programming models.

• Database Systems
• In-Database Machine Learning
• GPU Acceleration for Databases
• +۳ مورد دیگر

Maximilian Schüle serves as Assistant Professor in the Department of Data Engineering at the University of Bamberg's Faculty of Information Systems and Applied Computer Sciences since October 2022. Previously, he held research positions at Technical University of Munich (2017-2022). His research bridges database systems and machine learning through compiler-based approaches. His research focuses on in-database machine learning , GPU-accelerated query processing , and recursive SQL extensions . Key contributions include: Developing MLIR-based compilers for automatic differentiation in SQL (DuoLingo-AutoDiff) Creating GPU code generators for database kernels using NVRTC Designing higher-order lambda functions for expressive query languages Implementing end-to-end neural network training within database engines His recent publications (2023-2025) demonstrate consistent output in top venues including ICDE, VLDB workshops, and BTW conferences, with growing emphasis on hardware-aware optimization and compiler techniques for analytical workloads. He currently leads a DFG-funded project on elastic memory hierarchies for memory-intensive applications (2025-2028), supporting multiple PhD researchers. His supervision emphasizes open-source contributions to database systems like Umbra and practical implementation skills alongside theoretical foundations. As an active member of the database community, he serves as workshop chair for BTW 2025 and regularly reviews for ACM TODS, VLDB Journal, and Information Systems. His work on public transport analytics demonstrates real-world impact through collaborations with urban mobility initiatives in Bamberg.

Johannes Friedrichمشاهده پروفایل

استاد

• Railway Engineering
• Operations Management
• Railway Automation
• +۳ مورد دیگر

Professor Johannes Friedrich serves as Professor of Railway Engineering, specializing in Operations Management and Automation at Erfurt University of Applied Sciences within the School of Economics, Logistics and Traffic. His academic leadership includes membership on the Audit Committee and teaching responsibilities across bachelor's degree programs in Railway Engineering. His research focuses on two interconnected pillars: Railway Operations Management examining stakeholder processes at infrastructure-operator interfaces, and Railway Automation addressing system migration for future challenges. His work emphasizes the integration of automatic systems into existing operational landscapes and the networking between operational management and automation domains. Analysis of his publications reveals a strong emphasis on stochastic modeling of train movements and pricing system impacts on passenger connection selection. His research bridges theoretical modeling with practical railway operations challenges, particularly in infrastructure capacity utilization and tariff structure optimization. Professor Friedrich maintains regular office hours on Thursdays from 10:00-11:00 a.m. by appointment and can be contacted at johannes.friedrich@fh-erfurt.de for academic inquiries or collaboration opportunities.