جست‌وجوی استاد و پژوهشگر

• Dependability
• Fault Tolerance
• Distributed Systems
• +۷ مورد دیگر

Lukas Pirl is a researcher at the Hasso Plattner Institute (HPI), University of Potsdam, working within the Department of Operating Systems and Middleware. His research focuses on dependability, fault tolerance, and experimental assessments of distributed systems with particular applications in railway technology and IoT systems. His research interests span multiple domains including: Dependability and fault tolerance architectures & protocols Experimental assessments using software fault injection Environmentally aware computing and information management Symmetric peer-to-peer systems and storage operating systems Railway digitalization and safety-critical systems Lukas's recent publications demonstrate a strong focus on applying distributed systems research to railway technology. His work spans from digital train control systems (FlexiDug project) to railway crossing safety (Digital St. Andrew's Cross), and from blockchain applications in railway systems (RailChain, ZugChain) to IoT testing methodologies. A significant portion of his research involves using SUMO for railway simulations and developing test automation frameworks for railway components, showing an evolution from general distributed systems research toward specialized applications in critical infrastructure. He has co-supervised numerous Master's theses at HPI, working with students on topics ranging from railway simulation architectures to blockchain implementations for railway systems. His teaching activities include serving as a teaching assistant for courses on distributed systems, embedded operating systems, and trends in operating systems across multiple semesters. Lukas is actively involved in several major research projects: FlexiDug : Investigating reuse of rail infrastructures in former brown coal mining areas, focusing on software architectures for dependable digital train control and signaling systems RailChain : Exploring distributed ledger technologies for the railway sector with focus on timing predictability and resource constraints DiAK : Digitalization of railway crossings for increased safety through bridging V2X and C-V2X technologies Rail2X : Investigating vehicle-to-everything technologies for the railway sector with focus on wireless technology assessments

• Computational Materials Science
• Crystal Plasticity
• Phase-field Modeling
• +۴ مورد دیگر

Dr. Shanthraj Pratheek is a researcher affiliated with multiple institutions including Aachen Institute for Advanced Study in Computational Engineering Science at RWTH Aachen University Microstructure Physics and Alloy Design at Max Planck Society's Max-Planck-Institut für Eisenforschung GmbH The School of Materials at The University of Manchester Henry Royce Institute at The University of Manchester United Kingdom Atomic Energy Authority (UKAEA) His research focuses on multi-physics computational materials science , particularly in areas like crystal plasticity , phase-field modeling , and microstructure evolution . Key topics include chmo-mechanical coupling , damage mechanics , and multi-scale simulation of metallic systems. He has contributed to the development of the DAMASK simulation software for crystal plasticity and multiphysics problems. Recent publications highlight his work on chmoelastic interactions in alloys precipitation kinetics in aluminum systems dislocation segregation mechanisms multi-sublattice phase modeling grain boundary microchemistry FFT-based damage solvers He maintains active collaborations across institutions including University of Manchester, RWTH Aachen, Max Planck Society, and UKAEA, with a focus on computational simulations for materials design and failure analysis.

Christoph Niemannمشاهده پروفایل

پژوهشگر

• Reliability Engineering
• Nanometer CMOS Technologies
• FPGA Design and Optimization
• +۵ مورد دیگر

Dr.-Ing. Christoph Niemann is a researcher at the Institute of Computer Engineering within the School of Computer Science and Electrical Engineering at the University of Rostock. His work bridges computer engineering and biomedical applications, with a focus on hardware design for medical devices and energy-efficient computing systems. Dr. Niemann's primary research interests include reliability and aging in nanometer CMOS technologies and contributions to increasing the energy efficiency of FPGA-based applications . His work spans both theoretical hardware design and practical biomedical implementations, particularly in the field of deep brain stimulation systems. His research demonstrates a unique intersection of computer engineering principles applied to critical medical technologies. Analysis of Dr. Niemann's recent publications (2020-2025) reveals a strong focus on energy efficiency in implantable medical devices, particularly for deep brain stimulation applications. His work combines FPGA optimization techniques with biomedical requirements, creating hardware solutions that address the stringent power constraints of implantable systems. The publications show consistent collaboration with Dirk Timmermann, Christian Haubelt, and Franz Plocksties, indicating a well-established research group focused on medical device engineering. Dr. Niemann has made significant contributions to the STELLA platform for deep brain stimulation research and has developed novel approaches for sensor-based adaptive voltage scaling on FPGAs. His work demonstrates both theoretical innovation in hardware design and practical implementation in medical contexts.

Sang-Kil Sonمشاهده پروفایل

پژوهشگر

• Theoretical Atomic Physics
• Theoretical Molecular Physics
• Theoretical Optical Physics
• +۹ مورد دیگر

Sang-Kil Son is a Senior Scientist at the Center for Free-Electron Laser Science (CFEL), Deutsches Elektronen-Synchrotron (DESY), Germany, where he has been working since January 2014. He previously served as a Post-Doctoral Fellow at CFEL from 2010 to 2013, advised by Prof. Robin Santra. His academic background includes a Ph.D. in Physical Chemistry from the University of Kansas (2009), an M.S. from KAIST, Korea, and a B.S. in Chemistry from KAIST. Ph.D. in Physical Chemistry, University of Kansas, United States (2003–2009) M.S. in Physical Chemistry, KAIST, Korea (1997–1999) B.S. in Chemistry, KAIST, Korea (1993–1997) Dr. Son's research focuses on theoretical atomic, molecular, and optical physics, particularly in extreme conditions induced by X-ray free-electron lasers (XFELs). His work spans strong-field physics from optical to x-ray regimes, electronic structure under intense radiation, and the development of computational methods such as XATOM, XMOLECULE, and TDVFD. He is deeply involved in simulating XFEL-matter interactions, including ionization dynamics, radiation damage, and ultrafast electron responses. His publication record includes high-impact articles in journals like Nature , Nature Communications , and Physical Review Letters , with a consistent focus on x-ray science, multiphoton processes, and computational modeling. His recent work emphasizes relativistic effects, ionization potential lowering in plasmas, and the use of radiation damage for structural determination in femtosecond crystallography. Multielectron effects in strong-field ionization XFEL-induced dynamics in matter Quantum mechanical modeling of dense plasmas Development of simulation toolkits (XATOM, XMDYN) Theoretical support for ultrafast imaging Dr. Son actively supervises Ph.D. students, postdoctoral researchers, and summer students at DESY, often in collaboration with Prof. Robin Santra. He has organized major scientific events such as the Ultrafast X-ray Summer School (UXSS) and regularly lectures on x-ray interaction with matter for DESY summer students. He also co-organizes the CFEL Theory Seminar series. His research skills include advanced scientific programming (Fortran, C++, Python), code development for quantum dynamics, and the use of computational chemistry packages like Gaussian, GAMESS, and Octopus. He maintains an active presence in the international scientific community through invited talks and conference presentations.

Ayesha Afzalمشاهده پروفایل

پژوهشگر

• High Performance Computing
• Parallel Computing
• Performance Modeling
• +۵ مورد دیگر

Ayesha Afzal is a researcher and PhD student at the Erlangen National High Performance Computing Center (NHR@FAU), part of Friedrich-Alexander University Erlangen-Nuremberg. She holds a master's degree in computational engineering from FAU and a bachelor's degree in electrical engineering from the University of Engineering and Technology, Lahore, Pakistan. Her research focuses on high-performance computing with expertise in analytic performance models, parallel simulation frameworks, and first-principles performance modeling of distributed-memory parallel programs. She investigates multi-core and parallel architectures, parallel computing algorithms, programming models, and domain-specific languages to understand and optimize parallel application performance through advanced modeling techniques. Dr. Afzal's publication record demonstrates consistent innovation in understanding parallel program dynamics, particularly around idle waves, desynchronization phenomena, and performance bottlenecks. Her research has pioneered approaches like the physical oscillator model for supercomputing and developed frameworks such as DisCostiC for simulating MPI applications without code execution, revealing novel insights into hardware-software interactions in HPC systems. ISC PhD Forum Award (1st place, 2021) IEEE TPDS Best Paper Runner-up Award (2023) SC PMBS Best Short Paper Award (2023) SC Best Research Poster Finalist (2024) ISC Best Research Poster Award (1st place, 2025) Top 100 Future Leaders Role Model List (2022-2025) WeAreTheCity's Global Award for Achievement (2023) Dr. Afzal actively contributes to the HPC community through teaching and mentorship. She teaches courses on parallel programming of high-performance systems and supervises multiple bachelor's and master's theses on topics ranging from energy consumption analysis to MPI collective implementation. As vice chair of the IEEE Computer Society Germany Section Chapter and founder of the NHR Women in HPC chapter, she plays a significant leadership role in advancing the field and promoting diversity. She is deeply involved in major HPC initiatives including KONWHIR with the Leibniz Supercomputing Centre on performance optimization and NHR's EEC project focused on enhancing energy efficiency and managing operational costs across NHR centers, demonstrating her commitment to addressing real-world challenges in high-performance computing infrastructure.

Harald Lanigمشاهده پروفایل

دانشیار

• Molecular Dynamics
• Computational Chemistry
• Protein-Ligand Interactions
• +۲ مورد دیگر

Dr. Harald Lanig serves as Executive Secretary at the Erlangen National High Performance Computing Center (NHR@FAU) at Friedrich-Alexander-Universität Erlangen-Nürnberg, while maintaining active research in computational chemistry and molecular modeling. Previously, he was Managing Director of the Central Institute for Scientific Computing (ZISC) from 2013-2019 and has held various research positions at the University since completing his habilitation. Dr. Lanig received his Dr. rer. nat. from the Institute of Physical Chemistry at Julius-Maximilians University of Würzburg, with his thesis focusing on fluorescence spectroscopy and semiempirical model calculations. He completed his habilitation in Pharmaceutical Chemistry at the University of Erlangen-Nuremberg in 2012 with research on molecular dynamics simulations of organic molecules and biopolymers. His research interests center on computational approaches to biomolecular systems, with particular expertise in molecular dynamics simulations, protein-ligand docking, and comparative modeling techniques. His work spans applications in pharmaceutical chemistry, plant biochemistry (particularly cardenolide biosynthesis), structural biology of extracellular matrix proteins, and immunology. Analysis of his recent publications reveals a consistent focus on applying computational methods to solve complex biological problems, with increasing interdisciplinary collaborations spanning biochemistry, plant sciences, and immunology. His work demonstrates strong continuity in methodological approaches while expanding into new biological applications. Dr. Lanig has maintained an active research program alongside his administrative responsibilities, with 15 publications in the last five years (2019-2024) as co-author, demonstrating his ongoing engagement with the scientific community. His research has been supported through Collaborative Research Centers including CRC 814 (Additive Manufacturing) and CRC 1411 (Design of Particulate Products). As Executive Secretary at NHR@FAU, he oversees administrative operations of the National Center for High Performance Computing while continuing his research activities. His dual role bridges computational infrastructure management with active scientific research, positioning him at the intersection of high-performance computing and molecular sciences.

Angela Lauschمشاهده پروفایل

استاد

• Remote Sensing
• Biodiversity Monitoring
• Geodiversity
• +۳ مورد دیگر

Angela Lausch is a Professor at the Department of Landscape Ecology , Helmholtz Centre for Environmental Research - UFZ , Leipzig, Germany. Her work focuses on trait ecology , spectral trait analysis for biodiversity and geodiversity monitoring, and integrating remote sensing with data science in social-ecological systems. Key methodologies: hyperspectral imaging, machine learning for land use intensity quantification, semantic data integration. Collaborations: multiple departments at UFZ, international research teams on ecosystem services and climate resilience. Her recent publications emphasize cross-scale environmental modeling , including applications in forest health, soil carbon dynamics, and urban ecological resilience. She serves as Guest Editor for special issues on Remote Sensing of Inland Waters and Forest Health (MDPI). No formal student advising list is provided, but her research groups include teams working on computational landscape ecology and sustainable land use. Email: angela.lausch@ufz.de

• Optical Wireless Communication
• Visible Light Communication (VLC)
• Hybrid RF/VLC Networks
• +۴ مورد دیگر

Michael B. Rahaim is a Researcher at Boston University , specializing in Optical Wireless Communication (OWC), Visible Light Communication (VLC), and Hybrid RF/VLC Networks . His work focuses on interference mitigation , dynamic field-of-view (FOV) receivers , and integration with 5G systems . He has developed open-source tools like the gr-owc toolkit for optical wireless research and extended ns-3 network simulator for VLC. His collaborations include researchers such as Thomas D. C. Little , Hany Elgala , and Abdallah Khreishah . His scientific contributions span MAC protocol design , outage probability analysis , and low-cost IoT communication systems . He has not been explicitly associated with teaching or administrative roles in the provided records.

Malte Voglمشاهده پروفایل

پژوهشگر ارشد

• Historical Network Research
• Digital Humanities
• Agent-Based Modeling
• +۷ مورد دیگر

Dr. Malte Vogl is a Senior Research Fellow at the Max Planck Institute for Geoanthropology in Jena, Germany. His work bridges the history of science, computational modeling, and digital humanities, focusing on socio-epistemic networks and knowledge evolution. He has previously held research associate positions at the Max Planck Institute for the History of Science in Berlin. PhD in Physics Researcher in ModelSEN (BMBF-funded) Contributor to DARIAH and TOPOI projects Developer of simulation tools like SciCom Research Interests Dr. Vogl investigates knowledge evolution through network analysis and agent-based modeling, particularly in historical contexts. His work explores: Epistemic communities in early modern science Socio-epistemic network frameworks Quantum criticality in many-body systems Temporal network modeling of historical communication Research data infrastructure development Mathematical epistemology of historical knowledge His recent publications focus on simulating historical communication networks and analyzing archival data survival biases. He integrates computational methods with historical scholarship to uncover dynamics of knowledge transformation.

• Chemistry Education
• Educational Technology
• Science Teacher Training
• +۳ مورد دیگر

Prof. Jenna Koenen holds the Chair of Chemistry Education at the Technical University of Munich (TUM), focusing on innovative educational methodologies in chemistry instruction. Her work emphasizes digital tools like SpinDrops simulations, inquiry-based learning frameworks, and teacher professional development. She investigates cognitive processes in scientific inquiry, visual literacy, and the integration of technology in STEM education. Her research spans topics such as: Design of interactive visualizations for organic chemistry concepts Evaluation of digital vs. traditional learning materials Metacognitive strategies in laboratory settings Teacher training programs emphasizing professional knowledge development Key contributions include frameworks for assessing experimental competencies and boundary object approaches to interdepartmental collaboration. Her work bridges chemistry content mastery with pedagogical innovation, particularly in fostering scientific thinking among pre-service teachers. Recent studies explore motivational impacts of narrative-based learning materials, visual literacy training for scientific image interpretation, and equity-focused teacher development initiatives in underserved educational contexts.

Alessio Gagliardiمشاهده پروفایل

دانشیار

• Nanoscale Simulation
• Solar Cell Technology
• Electrochemical Systems
• +۳ مورد دیگر

Professor Alessio Gagliardi is an Associate Professor at the TUM School of Computation, Information and Technology , Technische Universität München. His academic career includes a tenure-track position since 2014 and promotion to Associate Professor in 2020. He contributes to the development of the TiberCAD and GDFTB simulation software and integrates machine learning into materials science research. Education: Engineering degree from the University of Rome Tor Vergata (Italy) Doctorate in Physics from the University of Paderborn (2007) Postdoctoral research at Bremen Center for Computing Materials and Rome Research Interests: Prof. Gagliardi’s work focuses on simulating nanostructured devices for energy conversion, including organic semiconductors, perovskite solar cells, and electrochemical systems. His methods span nanoscale ( density functional theory , quantum Green’s functions), mesoscale ( kinetic Monte Carlo ), and macroscopic ( drift-diffusion models). Recent efforts emphasize machine learning applications for multiscale modeling and experimental-theoretical integration. Articles Overview: Recent publications explore machine learning optimization in materials design, nanoscale simulations for energy devices, and advancements in electrocatalysts. Key themes include improving platinum electrocatalyst efficiency, perovskite solar cell stability, and AI-driven predictions for material performance. Labs/Teams: Active in software development teams for TiberCAD and GDFTB , advancing computational tools for materials science and energy systems.

Christian Stemmerمشاهده پروفایل

استاد

• Hypersonic Aerodynamics
• Fluid Mechanics
• Thermal and Chemical Nonequilibrium Flows
• +۳ مورد دیگر

Prof. Christian Stemmer is a Professor of High-Speed Aerodynamics at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design and the Department of Aerodynamics and Fluid Mechanics. His research focuses on hypersonic flows, boundary layer transition, thermal and chemical nonequilibrium phenomena, and research data management. Stemmer holds a Dr.-Ing. habil. and has extensive international experience, including postdoctoral work at Stanford University and NASA Ames. Career highlights: Appointment as extraordinary professor in 2019, leadership roles in the Collaborative Research Center TRR40 (SFB/TRR40), and membership in editorial boards such as Advances in Aerodynamics . Awards: 2020 NATO AVT Panel Excellence Award for contributions to hypersonic flow research. Key projects: Investigation of hypersonic boundary layer transition under high-enthalpy conditions, development of numerical models for rocket combustion chambers, and leadership in national and international research consortia. His work bridges fundamental fluid mechanics with aerospace engineering applications, emphasizing high-performance computing and data-driven methodologies. Recent contributions include studies on roughness-induced instabilities, shock-wave interactions, and metadata extraction frameworks for HPC workflows.

Markus Kowarschikمشاهده پروفایل

پژوهشگر

• Interventional Imaging
• Blood Flow Quantification
• Perfusion Imaging
• +۷ مورد دیگر

Dr. Markus Kowarschik is a researcher affiliated with the Chair of Computer Science Applications in Medicine at Technical University of Munich under Prof. Nassir Navab. His work focuses on interventional imaging, blood flow quantification, and tomographic reconstruction. He contributes to labs like DHM (Deutsches Herzzentrum München), NARVIS, and IFL, advancing medical imaging and AI applications in healthcare. His teaching includes courses on medical procedures, robotics, and deep learning in medical contexts. Recent research emphasizes AI-driven solutions for endovascular procedures, motion compensation in imaging, and 3D pose estimation. His research interests span medical image analysis, computer vision, and generative models applied to surgical data science. Key projects involve developing datasets for benchmarking, improving X-ray imaging systems, and integrating simulation for medical training. He has no listed awards but maintains an active publication record in top-tier journals and conferences. Labs and collaborations include the NARVIS Lab (navigation and robotics), DHM for cardiac imaging, and GenAI initiatives exploring generative models. His work bridges clinical needs with computational methods, addressing challenges in radiation dosimetry, robotic control systems, and real-time imaging analysis.

• Cloud-Native Network Functions (CNFs)
• Kubernetes Orchestration
• Telecom Cloud Infrastructure
• +۴ مورد دیگر

Razvan-Mihai Ursu is a Researcher at the Chair of Communication Networks (Lehrstuhl für Kommunikationsnetze) at the Technical University of Munich, led by Prof. Wolfgang Kellerer. His research focuses on cloud-native network functions (CNFs), Kubernetes-based orchestration, energy-efficient telecom cloud architectures, and network security in open RAN systems. He holds a Master’s degree in Electrical Engineering and Information Technology from TUM (2023) and has been actively involved in the Chair since June 2023. Key research areas include: Design and optimization of Kubernetes orchestration for telecom core networks Energy-efficient redundancy models for telco applications Simulation frameworks for multi-tier Kubernetes deployments (e.g., using Shadow simulator) Security vulnerabilities in O-RAN nearRT-RIC platforms Autonomous network adaptation via digital twins He supervises master’s theses on topics such as CNF orchestration tools evaluation, energy optimization in Kubernetes clusters, and security testing of FlexRIC platforms. His work aligns with projects like the 6G Future Lab Bavaria and the ERC Network Flexibility initiative. Current projects involve advancing simulations for Kubernetes-based systems and developing mathematical models to optimize telecom cloud redundancy for energy efficiency while maintaining service availability.

Felix Binkowskiمشاهده پروفایل

پژوهشگر

• Nanophotonics
• Quantum Technologies
• Computational Modeling
• +۴ مورد دیگر

Felix Binkowski is a researcher at the Zuse Institute Berlin within the Modeling and Simulation of Complex Processes department and Computational Nano Optics group. His work focuses on computational methods for photonic systems and quantum technologies. Position: Researcher Email: binkowski@zib.de Research Interests include: modal analysis of nanophotonic devices, resonance phenomena in non-Hermitian systems, Purcell effect optimization for quantum emitters, and application of Riesz projections to eigenvalue problems. His projects span from theoretical developments to experimental validation of optical materials. Key methodologies: AAA rational approximation, Riesz projections, Gaussian process optimization Application areas: photovoltaics, nanolasers, plasmonic systems Recent Publications (2024-2025) demonstrate expertise in: computational resonance extraction, pole-zero analysis of photonic systems, and uncertainty-guided design optimization. Notable works include software frameworks for resonance expansion (RPExpand) and studies on Purcell enhancement in 2D material-based nanoresonators. Education includes a doctoral degree (2023) from Freie Universität Berlin under Christof Schütte, and a Master's (2017) from Technische Universität Berlin with advisors Jörg Liesen and Martin Weiser.