جست‌وجوی استاد و پژوهشگر

Mandayam A. Srinivasanمشاهده پروفایل

استاد پژوهشی

• Haptics
• Human-Machine Interaction
• Virtual Reality
• +۳ مورد دیگر

Mandayam A. Srinivasan is a Hans Fischer Senior Fellow at the Technical University of Munich (TUM) and holds a position as Senior Research Scientist in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). He directs MIT's Laboratory for Human and Machine Haptics (Touch Lab), part of the Research Laboratory of Electronics. His research focuses on haptics, integrating biomechanics, neurophysiology, and engineering to advance tactile interactions in virtual environments and medical applications. Education: B.E., Bangalore University, 1975 M.E. in Aeronautical Engineering, Indian Institute of Science, 1977 M.S. and Ph.D. in Mechanical Engineering, Yale University, 1979 and 1984 Research Interests: Srinivasan’s work explores the computational and cognitive foundations of touch, with applications in virtual reality, surgical training, and robotics. He pioneers haptic technologies for medical simulations, wearable devices, and autonomous systems, emphasizing the biomechanical and neurophysiological underpinnings of tactile perception. Publications: His articles span haptic rendering algorithms, surgical simulation methodologies, and actuator design, reflecting a focus on interdisciplinary solutions for tactile interaction challenges. Scientific Awards: 2005 Fellowship Award, Engineering and Physical Sciences Research Council (EPSRC), UK 2001 Class 1 NASA Tech Brief Award 1997 and 1998 Computers & Graphics Best Paper Awards Advising & Grants: While no explicit student advisees are listed, Srinivasan collaborates extensively with co-authors on projects such as surgical simulation and haptic robotics. His work is supported by institutional and industry partnerships. Labs & Affiliations: As director of MIT’s Touch Lab, he leads a global hub for haptic innovation, contributing to the MIT Virtual Environment & Teleoperator Research Consortium and fostering cross-disciplinary research.

Eleni Chatziمشاهده پروفایل

دانشیار

• Structural Health Monitoring (SHM)
• Structural Dynamics
• Nonlinear System Identification
• +۴ مورد دیگر

Eleni Chatzi is an Associate Professor and Chair of Structural Mechanics and Monitoring at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering. She leads the ERC-funded WINDMIL project on smart life-cycle assessment of wind turbines. Her research focuses on Structural Health Monitoring (SHM), nonlinear system identification, and data-driven methods for predictive maintenance. Chatzi holds a PhD from Columbia University and has authored over 280 peer-reviewed publications. Research interests include computational mechanics for plasticity/fracture, machine learning applications in SHM, and decision-support systems for infrastructure. She serves as editor for journals such as Journal of Sound and Vibration and Mechanical Systems and Signal Processing . Notable awards include the 2020 ASCE Walter L. Huber Research Prize and EASD Junior Research Prize. Her work bridges theory and practice through projects like VOI4SH (Value of Information for Structural Health Monitoring), advancing methodologies to quantify monitoring benefits. Current research emphasizes integrating sensor data with advanced analytics for intelligent infrastructure management.

• Uncertainty and Sensitivity Analysis
• Computational Modeling
• Non-Invasive Brain Stimulation
• +۳ مورد دیگر

Dr. Konstantin Weise is a Scientific Researcher at the Max Planck Institute for Human Cognitive and Brain Sciences , leading the Methods and Development Group Brain Networks . His work focuses on uncertainty and sensitivity analysis of computational models , developing the pygpc Python package , and advancing numerical models for non-invasive brain stimulation techniques like Transcranial Magnetic Stimulation (TMS) . He specializes in improving localization precision, optimizing stimulation parameters, and addressing microscopic tissue effects in brain stimulation simulations. Research interests include: Modeling TMS-induced electric fields and their cortical effects High-resolution EEG/MEG forward modeling Uncertainty quantification in biomedical simulations Neurostimulation applications for neuropsychological disorders His contributions bridge computational methods with clinical neurotechnology, emphasizing electrical field-based dosing and adaptive stimulation optimization . Recent work addresses microscopic field distortions' impact on neuronal activation thresholds and develops novel protocols for precise motor cortex mapping. Labs/Teams: Core member of the Brain Networks Group , collaborating on interdisciplinary projects integrating engineering, neuroscience, and clinical applications.

Ramón García Alarciaمشاهده پروفایل

پژوهشگر

• Space Mission Design
• Systems Engineering
• Generative AI Applications
• +۳ مورد دیگر

Ramón García Alarcia is a Research Associate and Doctoral Candidate at the Chair of Spacecraft Systems, Technical University of Munich (TUM), under Prof. Alessandro Golkar. He holds dual Bachelor's degrees in Aerospace and Telecommunication Systems Engineering from the Polytechnic University of Catalonia (UPC), and a Master's in Aerospace Engineering (Space Systems specialization) from ISAE-SUPAERO. His research focuses on applying Large Language Models (LLMs) to streamline space mission design, particularly in requirements generation and high-level documentation. This work aims to reduce costs and democratize access to space. Key areas include generative AI for complex systems, autonomous space systems, and federated satellite networks. Ramón teaches courses on spacecraft systems, including 'Design and Simulation of Microsatellites' and 'Systems Engineering – Advanced.' He has authored/co-authored over a dozen peer-reviewed publications, covering topics like AI-driven mission design tools, event-based cameras for situational awareness, and telecommunication network analysis. His doctoral project involves developing a prototype AI-assisted mission design tool, leveraging generative models to enhance efficiency in early-stage spacecraft planning. Collaborations span institutions like ISAE-SUPAERO and UPC, with a focus on interdisciplinary aerospace challenges.

Daniel Wolffمشاهده پروفایل

پژوهشگر

• Structural Engineering
• Reinforced Concrete Construction
• Prestressed Concrete
• +۳ مورد دیگر

Daniel Wolff serves as a Researcher at the Institute of Structural Engineering within the Department of Civil Engineering at Technische Hochschule Mittelhessen (THM), where he has been employed since September 2011. His work focuses on experimental and computational analysis of concrete structures, particularly reinforced and prestressed systems. His academic background includes: Civil Engineering degree specializing in Construction and Structural Design from Giessen-Friedberg University of Applied Sciences (2004-2009) Master of Engineering in Structural Engineering and Project Management from TH Mittelhessen (2009-2011) Wolff's research centers on structural engineering challenges in concrete construction, with emphasis on column connections, cross-sectional transitions, and innovative hybrid systems for wind turbine towers. His methodology integrates experimental testing with numerical simulations to address practical construction issues like reinforcement misalignment and material behavior under load. Key applications include precast concrete assembly and sustainable energy infrastructure development. Publication analysis (2012-2018) reveals consistent focus on concrete structural behavior, particularly butt-jointed columns and hybrid wind turbine towers. His work demonstrates progression from fundamental connection studies toward integrated systems engineering, frequently utilizing Building Information Modeling (BIM) for complex structural solutions in renewable energy infrastructure. Scientific awards: No awards documented in source materials. Wolff participated in the HYWEA research project (2012-2014), a LOEWE 3 initiative funded by the State of Hesse developing hybrid wind turbine towers from precast concrete and steel trusses. While no advisees are listed, his research collaborations with Minnert, Koob, and Blatt indicate team-based investigation approaches within THM's structural engineering framework. He operates within THM's Reinforced and Prestressed Concrete Construction subject area, utilizing university facilities including building materials laboratories and structural testing equipment for experimental validation of concrete systems.

• Neuromorphic Computing
• Reservoir Computing
• Reinforcement Learning
• +۳ مورد دیگر

Prof. Abigail Morrison is a Professor and Group Leader of the Computation in Neural Circuits group at the Institute for Advanced Simulation (IAS-6), part of Forschungszentrum Jülich. Her work focuses on advancing neuromorphic computing, reservoir computing, and spiking neural network simulations. She leads development of the NEST simulator and NESTML modeling language, tools critical for large-scale brain modeling. Key research areas include: Neuromorphic hardware-software co-design Biophysically plausible neural network models GPU-accelerated simulation frameworks Multi-scale brain co-simulation techniques Applications in embodied AI and neuroscience Her lab contributes to the European EBRAINS infrastructure and has pioneered methods for parallel GPU-based network construction. Recent work explores topographic neural circuit architectures for signal processing and reinforcement learning in neuromorphic systems. Notable achievements include: Development of NESTML (v8.0+) ODE-toolbox for ODE solver selection Co-design of HNC neuromorphic compute nodes Advances in dendritic computation modeling Current efforts emphasize exascale computing readiness, neuromorphic system validation, and bridging biological plausibility with computational efficiency in neural network simulations.

Uwe Schlinkمشاهده پروفایل

استاد

• Urban Climate Research
• Thermal Comfort
• Urban Air Pollutants
• +۵ مورد دیگر

Uwe Schlink is a Professor and Scientist at the Department of Urban and Environmental Sociology at the Helmholtz-Zentrum für Umweltforschung (UFZ) in Leipzig. He holds a Diploma in Physics from TU Dresden (1985) and a PhD in Meteorology from the University of Leipzig (1995), followed by a Habilitation (venia legendi) in 2003. His research focuses on urban climate dynamics, thermal comfort, air pollutants, and personal exposure assessment, with expertise in Bayesian statistical methods and environmental sensor technologies. Professional Milestones: 1998: Guest scientist at University of Brescia, Italy. 2003–present: Teaching Biometeorology, Applied Meteorology, and Statistics. 2014–2020: Led the 'Environmental Risks & Vulnerability' work package in the Integrated Project Urban Transformations. Awards: 2009: Honorary Professor at Leipzig University's Institute for Meteorology. His research integrates urban micro-meteorological modeling with socio-environmental systems, emphasizing data assimilation for climate adaptation strategies. He pioneers the use of wearable sensors and smartphone-based monitoring to assess personal environmental exposure, bridging gaps between objective measurements and subjective perceptions in urban environments.

• Aerodynamics
• Fluid Mechanics
• Flow Control
• +۳ مورد دیگر

Dr.-Ing. Peter Scholz is a Senior Research Fellow at the Institute of Fluid Mechanics , Technische Universität Braunschweig. With a PhD in Mechanical Engineering (2009) and a background in Aerospace Engineering from TU Braunschweig, he specializes in aerodynamics , active flow control , and experimental fluid dynamics , particularly using fluidic vortex generators and numerical simulations . He leads research groups and played a pivotal role in designing the university’s large water tunnel. Core Research Areas: Aerodynamics, Flow Control, Fluid Mechanics, Experimental Methods, Numerical Simulations, Aerospace Applications. His recent publications focus on supersonic flow dynamics , laminar flow control , and wake structure analysis , with methodologies spanning Large-Eddy Simulation , PIV measurements , and high-speed flow diagnostics . Though no formal awards are documented, his work is integral to Germany’s flow control research initiatives. Dr. Scholz collaborates extensively with institutions like DLR and Fraunhofer WKI, advancing sustainable propulsion and flow control technologies.

• Aerospace Engineering
• Fluid Dynamics
• Hypersonic Vehicles
• +۳ مورد دیگر

Dr. Hee Yoon is a postdoctoral researcher at the Institute of Fluid Mechanics, Faculty of Mechanical Engineering, Technische Universität Braunschweig. She completed her doctoral studies at the University of Tokyo's Department of Aeronautics and Astronautics and previously earned a master's degree from Seoul National University (SNU) in Mechanical and Aerospace Engineering. University of Tokyo PhD (2024) Seoul National University MSc (2017) Her research focuses on hypersonic flow dynamics and drag reduction technologies for aerospace applications. She conducts both experimental and computational analyses of turbulent transition phenomena in hypersonic inlet designs, with particular emphasis on counter-flow jet mechanisms and low Reynolds number regimes. Recent publications demonstrate her expertise in numerical simulation methods (AIAA AVIATION 2023, Physics of Fluids 2024, AIP Conf. Proc. 2024) and computational fluid dynamics for aerospace systems. Her work spans both fundamental flow physics and applied aerodynamic optimization . Scientific Recognition: 2025: International Strategy Forum (ISF) Fellow (1 of 100 globally) 2024: Korea Foundation Global Fellow Dr. Yoon's practical experience includes two years as a researcher at Korea's Agency for Defense Development (ADD) and teaching roles at Woosong University and Ewha Womans University, where she instructed fluid mechanics and thermodynamics courses. Her current work contributes to TU Braunschweig's strategic research focus on mobility engineering and advanced aerospace technologies .

Henning Schröderمشاهده پروفایل

پژوهشگر

• Chemometrics
• Multivariate Curve Resolution
• Reaction Kinetics
• +۷ مورد دیگر

Dr. Henning Schröder is a researcher at the University of Rostock, actively involved in teaching and research in the fields of chemometrics, numerical methods, and spectroscopic data analysis. He teaches courses such as Numerik 1, Numerik 2, and Mathematics for Engineers and Economics, indicating a strong foundation in applied mathematics and computational science. His research focuses on multivariate curve resolution (MCR) , reaction kinetics , and ambiguity analysis in chemical systems . He applies advanced mathematical and computational techniques to interpret complex spectroscopic data, particularly in reaction monitoring and photochemical systems. His work often addresses challenges such as rotational ambiguity, constraint optimization, and noise reduction in spectral data. The recent publication trends show a consistent focus on chemometric modeling, with applications in NMR data correction, photochemical systems, and synthetic chemistry. His interdisciplinary approach bridges chemistry, mathematics, and data science, contributing to both theoretical advancements and practical algorithms in chemical data analysis. Selected Scientific Contributions: Development of dual Borgen plots for feasible solution analysis Multi-objective optimization for NMR spectral correction Analysis of quantum yields in photoisomerization Soft constraints in MCR for ambiguity reduction Kinetic modeling under rate constant uncertainty Dr. Schröder collaborates extensively with researchers such as K. Neymeyr, M. Sawall, and A. Börner, and has contributed to book chapters in major reference works like Comprehensive Chemometrics . Although no formal advising or grant information is available, his publication record suggests active involvement in research projects and academic supervision. He maintains regular office hours and is reachable via email at the University of Rostock.

• Climate Modeling
• Ocean Dynamics
• Climate Variability
• +۲ مورد دیگر

Helmuth Haak serves as a Researcher at the Max Planck Institute for Meteorology in Hamburg, Germany, where he works within the Department of Climate Variability as part of the Director's Research Group (CVR). His technical expertise as a Scientific Programmer focuses on advanced climate modeling systems, particularly the ICON (Icosahedral Non-hydrostatic) modeling framework. His primary research interests span climate modeling, ocean dynamics, climate variability, and Earth system modeling, with particular emphasis on numerical methods and high-performance computing applications. Haak's work frequently addresses ocean-atmosphere interactions, model parameterization schemes, and the computational challenges of simulating complex Earth system processes at increasingly fine resolutions. Analysis of his recent publications reveals a strong focus on model development and validation, particularly in simulating ocean circulation patterns, sea level changes, and climate feedback mechanisms. His research increasingly incorporates high-resolution modeling approaches to better capture small-scale processes that influence global climate dynamics. As a key contributor to the ICON Earth System Model development, Haak collaborates extensively with an international network of climate scientists. His technical programming expertise supports critical advances in climate modeling capabilities, particularly in ocean model components and coupled system integration.

• Software Engineering
• Agile Methods
• Embedded Systems
• +۳ مورد دیگر

Adilson Marques da Cunha is a Professor at the Brazilian Aeronautical Institute of Technology (ITA), with a focus on software engineering and computational systems. His career spans academic research and development in embedded systems, real-time applications, and machine learning methodologies. Affiliation: Brazilian Aeronautical Institute of Technology Research Interests: Dr. da Cunha's work centers on agile software development , embedded system optimization , and numerical integrator frameworks . He has contributed to deep reinforcement learning for robotics and recommender systems for news, while also exploring climate prediction models using big data. Publication Trends : 2025 papers focus on universal numerical integrators and Python testing frameworks; 2024 work involves autonomous air navigation; 2022 studies include humanoid robotics and climate modeling

• Machine Learning
• Cloud Computing
• Fault Diagnosis
• +۳ مورد دیگر

Chao Yin is a researcher at Shanghai University , Department of Computer Engineering and Science. His work spans multiple domains including Machine Learning, Cloud Computing, Fault Diagnosis, and Supply Chain Optimization. Key research areas: Machine Learning , Cloud Computing , Quantum Computing , Supply Chain Systems , Network Security Scientific Contributions (2024-2025): Developed heterogeneous graph neural networks for automotive supply chain analysis Created MSDF-VAE cloud-edge fault diagnosis framework using transfer learning Proposed quantum metrology methods with Heisenberg-limited precision Designed LARP pseudonym protocol for V2X communication Optimized fog computing resource scheduling with hybrid metaheuristics Prior Work (2012-2023): Contributed to fluid animation feature preservation from single images Developed label distribution learning for facial age estimation Designed erasure coding storage systems for big data Created multi-agent manufacturing networks in cloud environments

• Bioinformatics
• Computational Biology
• Protein Language Models
• +۳ مورد دیگر

Robert Schmirler is a researcher at the Chair for Bioinformatics within the School of Informatics at the Technical University of Munich. His work spans computational biology and fluid dynamics, with a focus on protein language models and porous media simulations. Teaching: Masterlab Data Mining, GoBI (Graduate Training Programme International), Master's Internship, Project-Based Learning (PBL), and Introduction to Computer Science for Computational Biology. Research interests center on Bioinformatics and Computational Biology , particularly leveraging Protein Language Models and Machine Learning to enhance biological data predictions. Earlier work involved Fluid Dynamics and Porous Media Simulation , including validation with X-ray/neutron tomography. His publications reflect this duality: recent studies focus on Protein Language Models (2023-2024), while older work (2013) explores Lattice Boltzmann simulations for two-phase flow. Articles highlight applications of Deep Learning , Neural Networks , and Data-driven Predictions in biology, alongside computational methods in physical systems.

Casimir Katzمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Building Information Modelling & Processing
• Construction simulation and optimization
• +۳ مورد دیگر

Casimir Katz is an Adjunct Professor at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich , specializing in computational mechanics, finite element analysis, and wind engineering. He has contributed extensively to structural simulation, building information modeling (BIM), and digital twinning. Education: Diplom in Civil Engineering (1976, TU Munich) Key research areas: Wind Load Analysis , Nonlinear Structural Mechanics , Computational Fluid Dynamics , Finite Element Method , and Engineering Software Development . His work bridges theoretical advances in Scaled Boundary FEM and CFD modeling with practical applications in bridge engineering , urban wind analysis , and tunneling . He co-founded SOFiSTiK AG , a leader in structural engineering software, and has advised on projects like the Arnulfsteg and Rader Hochbrücke bridges. Current teaching focuses on Computational Mechanics and BIM applications in structural engineering. His recent publications emphasize dynamic soil-structure interaction , polyhedral mesh generation , and nonlinear design methodologies . Collaborations span academia, industry, and research groups like the BIM Lab at TU Munich.