جست‌وجوی استاد و پژوهشگر

Fabian Ostermannمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Computer Music
• Algorithmic Music Composition
• +۵ مورد دیگر

Fabian Ostermann is a researcher at the Chair 11: ALGORITHM ENGINEERING within the Department of Computer Science at Technical University of Dortmund. His work focuses on the intersection of artificial intelligence and music technology, with particular expertise in algorithmic composition and evolutionary approaches to music generation. His primary research interests include: Artificial Intelligence for Music Applications Computer Music and Algorithmic Composition Reinforcement Learning and Evolutionary Algorithms Neuroevolution and Procedural Content Generation Music Information Retrieval Systems Ostermann's research output demonstrates a strong focus on applying AI techniques to music creation and analysis. His recent work explores the use of large language models in evolutionary music generation, adaptive video game music systems, and novel approaches to instrument recognition in polyphonic audio. He has developed significant resources for the research community including the AAM dataset of artificial audio multitracks, which contains 3,000 algorithmically generated music tracks with rich annotations. His scientific contributions have been recognized through invitations to serve on program committees for major conferences including EvoMUSART (2024, 2025) and IJCAI's Special Track on AI, the Arts, & Creativity. He has also contributed to journals such as Computer Music Journal and Transactions of the International Society for Music Information Retrieval. Ostermann has supervised numerous student theses on topics ranging from transformer-based music generation to evolutionary approaches for recreating vector graphics. His teaching portfolio includes courses on practical optimization, music informatics, and digital entertainment technologies across multiple semesters from WS20/21 through SS25.

Alexander Beetzمشاهده پروفایل

استاد

• Engineering Geodesy
• Construction Machine Guidance
• Indoor Positioning Systems
• +۵ مورد دیگر

Alexander Beetz serves as Professor of Applied Geodesy and Engineering Geodesy at Stuttgart University of Applied Sciences since 2023, following industry roles as Software Development Lead (2016-2023) and Development Engineer (2013-2016) at MTS Schrode AG. His academic foundation includes a Dr.-Ing. in Geodesy and Geoinformatics from the University of Stuttgart (2012) and prior service as academic staff at the Institute of Engineering Geodesy (2006-2013). Education: Dipl.-Ing. in Geodesy and Geoinformatics, University of Stuttgart (1997) Dr.-Ing. in Geodesy and Geoinformatics, University of Stuttgart (2012) Referendariat for higher surveying technical administrative service, completed as Vermessungsassessor (2003) Professor Beetz's research centers on Engineering Geodesy applications in construction automation, with emphasis on machine guidance systems, indoor positioning, and BIM integration. His work develops precision control solutions for construction machinery through sensor integration and real-time positioning, addressing critical challenges in measurement accuracy and control quality separation. Key innovations include hardware-in-the-loop simulators for dozer lateral control and signal-matching techniques for mobile positioning. His publication trajectory (2010-2017) reveals consistent focus on geodetic engineering for construction automation, evolving from machine simulator calibration to BIM implementation in excavation modeling. Core themes include real-time sensor integration, precision guidance algorithms, and quality control frameworks for construction machinery, demonstrating practical translation of geodetic principles into industrial applications. Professional leadership includes membership in FG13 BIM at the Association of German Surveying Engineers (VDV) and chairmanship of Cluster 5 (Machine Assistance Interface) within MIC4.0's System Control Working Group, driving standards for machine control interfaces in construction technology.

Marc-André Keipمشاهده پروفایل

استاد

• Continuum Mechanics
• Computational Mechanics
• Materials Theory
• +۶ مورد دیگر

Prof. Dr.-Ing. Marc-André Keip is a Professor for Materials Theory at the Institute of Applied Mechanics (CE), University of Stuttgart. He serves as the Dean of the Computational Mechanics of Materials and Structures (COMMAS) program and Head of the Chair of Materials Theory. Additionally, he is the Academic Dean of the Department of Civil and Environmental Engineering at the University of Stuttgart since 2019. Prof. Keip earned his Doctoral degree in Engineering Sciences from the University of Duisburg-Essen in 2011 with a dissertation titled "Modeling of electro-mechanically coupled materials on multiple scales" under the supervision of Prof. Dr.-Ing. Jörg Schröder. He completed his Diploma in Civil Engineering from the University of Duisburg-Essen in 2004 after studying there from 1999-2004. His research focuses on Continuum Mechanics , Computational Mechanics , and Materials Theory , with specific interests in: Theory of Porous Media Elasticity and Plasticity Constitutive Modeling at Large Strains Homogenization Techniques Micro-Mechanics Finite Element Formulations Prof. Keip's recent publications (2018-2019) demonstrate a strong focus on phase-field modeling approaches for fracture mechanics, computational homogenization techniques, and multiscale modeling of electro-magneto-mechanically coupled materials. His work bridges theoretical continuum mechanics with advanced computational implementations, particularly in the areas of magneto-electro-active polymers, fracture mechanics, and constitutive modeling of complex materials. Among his recognitions, Prof. Keip received the Teaching Award of the University of Stuttgart in 2018. As Head of the Chair of Materials Theory, Prof. Keip oversees teaching activities covering undergraduate and graduate courses in Civil Engineering, Environmental Engineering, Medical Engineering, Simulation Technology, and Computational Mechanics of Materials and Structures. His research group has supervised numerous Bachelor's and Master's theses on topics related to computational mechanics, materials modeling, and finite element methods.

Jack B. Muirمشاهده پروفایل

پژوهشگر ارشد

• Seismology
• Geophysics
• Inverse Problems
• +۳ مورد دیگر

Jack B. Muir is a Marie Skłodowska-Curie Fellow at the University of Oxford's Department of Earth Sciences and Junior Research Fellow at Wolfson College. His research integrates advanced mathematics with seismology to address inverse problems in Earth imaging and hazard assessment. Education: PhD in Geophysics, Caltech Seismolab (2021) Research focuses on physics-informed neural networks for seismic wavefield simulation (TerraPINN project), nonparametric seismicity rate modeling using deep Gaussian processes, geologically-constrained tomography, and Bayesian methods for wavefield reconstruction. His work targets applications from near-surface structures to Earth's core, emphasizing machine learning acceleration and uncertainty quantification in inverse problems. Recent projects include Distributed Acoustic Sensing (DAS) optimization and seismic swarm analysis. Publication trends (2022-2025) reveal strong emphasis on machine learning integration (PINNs, Gaussian processes) with geophysical inverse problems, particularly for DAS data processing, deep Earth imaging, and probabilistic hazard assessment. Key themes include multi-scale analysis, instrument response calibration, and computational efficiency. Scientific Awards: Marie Skłodowska-Curie Fellowship John Monash Scholarship Junior Research Fellowship at Wolfson College, Oxford Grant-funded projects include TerraPINN for physics-based seismic hazard assessment and collaborations leveraging Caltech's Community Seismic Network. He actively develops open-source tools for core-mantle boundary modeling and DAS data processing. Labs and teams involve Oxford's Seismology group (Tarje Nissen-Meyer), Caltech (Zach Ross), Australian National University (Hrvoje Tkalčić), and JAMSTEC (Satoru Tanaka), with fieldwork utilizing ocean-bottom seismometers and urban sensor networks.

• Computational Mechanics
• Finite Element Analysis
• Material Point Method
• +۳ مورد دیگر

Dr. Veronika Singer is a Postdoctoral Researcher (Akademische Rätin a.Z.) at the Chair of Statics and Dynamics, Technical University of Munich, working under Prof. Dr.-Ing. habil. Roland Wüchner since October 2024. Previously, she served as an Academic Councillor at the Chair of Structural Analysis under Prof. Dr.-Ing. Kai-Uwe Bletzinger from December 2020 to September 2024, and as a Research Assistant from April 2017 to November 2020. Her educational background includes: M.Sc. in Civil Engineering from Technical University of Munich (2014-2017), with thesis on 'Detailed lateral-torsional buckling investigations of steel profiles and frame systems' B.Sc. in Civil Engineering from Technical University of Munich (2010-2014), with thesis on 'Beam elements for linearly variable cross-sections' Dr. Singer's research focuses on advanced computational methods for structural analysis, particularly the Material Point Method (MPM) and its applications in natural hazard simulation. She has pioneered innovative coupling strategies between MPM and Finite Element Method (FEM), as well as MPM and Discrete Element Method (DEM), to address complex multiphysics problems involving large deformations. Her work has significant applications in simulating granular mass flows and designing protective structures against natural disasters, contributing to improved infrastructure resilience. Her publication record shows a consistent trajectory of high-impact research in computational mechanics, with a concentration on partitioned coupling approaches that enable more efficient and accurate simulations of complex engineering problems. The research demonstrates increasing sophistication in handling boundary conditions, large deformations, and multiphysics interactions. Her scientific contributions have been recognized with multiple teaching awards: Doce et Delecta, 3rd prize for Statics 1 in the 'NextGen & Young Talents' category (July 2025) Doce et Delecta, 1st Prize for Statics 2 (July 2024) Certificate of University Teaching at Bavarian Universities (December 2022) Multiple previous Doce et Delecta awards (2018, 2019) Dr. Singer actively supervises student theses across computational mechanics topics, with over 20 completed projects ranging from element formulation to natural hazard simulation. She is involved in research projects including CoDA, MistralWind, WINSENT, and FlexWing, focusing on advanced computational methods for structural analysis and natural hazard mitigation. She is an integral member of the Chair of Statics and Dynamics research team, collaborating on developing more reliable simulation tools for civil engineering applications, particularly in natural hazard contexts. Her work bridges theoretical computational mechanics with practical engineering solutions for infrastructure protection.

• Computational Fluid Dynamics
• Machine Learning in Fluid Dynamics
• Compressible Flow Modeling
• +۳ مورد دیگر

Dr. Deniz Bezgin is a Researcher at the Department of Aerodynamics and Fluid Mechanics of the Technische Universität München (TUM) . Her work focuses on computational fluid dynamics (CFD), machine learning integration in numerical methods, and high-order differentiable solvers for compressible flows. Research specialties include shock-capturing methods, multi-phase flow modeling, and data-driven shape optimization. Developed JAX-Fluids, a fully-differentiable framework for compressible two-phase flows. Key contributions to ENO/WENO schemes and thermodynamically consistent interface models. Current projects explore machine-learned discretizations and GPU-based high-performance computing. Her recent publications address differentiable simulations, data assimilation, and turbulence modeling. She has not received any explicitly listed scientific awards.

Mario Neugebauerمشاهده پروفایل

استاد

• Wireless Sensor Networks
• Mobile Systems
• Robotics
• +۴ مورد دیگر

Prof. Dr.-Ing. Mario Neugebauer is a faculty member at the Faculty of Computer Science/Mathematics at Dresden University of Applied Sciences (HTW Dresden). His teaching areas span fundamental programming, database systems, mobile networks, and communication technologies. Research Focus: Off-road navigation, wearable systems for production/logistics, localization systems, and mobile sensor devices. Thesis Topics: Image analysis for bird conservation, shadow detection on wind turbines, bat monitoring, and mission planning for autonomous robots. Technologies: Rust, ROS2, Kotlin/Spring Boot, Python, Raspberry Pi, C/C++ for microcontrollers, and IEEE 802.15.4 protocols. Teaching Responsibilities: Courses include Programming I/II , Mobile Networks , and Business Informatics and Digitization for Informatik, Medieninformatik, and Umweltmonitoring programs.

Peter Sobeمشاهده پروفایل

استاد

• Parallel and Distributed Systems
• Data Storage Technologies
• Reliability and Fault Tolerance
• +۳ مورد دیگر

Prof. Dr.-Ing. habil. Peter Sobe is a professor at the Faculty of Computer Science/Mathematics of Dresden University of Applied Sciences . His teaching focuses on foundational computer science and programming, with an emphasis on algorithms, data structures, and mathematical methods for technical applications. Research Areas : Parallel and Distributed Systems, Data Storage Technologies, Reliability and Fault Tolerance International Projects : OOP4Fun (object-oriented programming education), ERASMUS+ partnerships with Riga Technical University and Tallinn Technical University Workshops : Organizer of the Fault Tolerance Discussion Group workshops (2018, 2014) His academic work spans distributed storage systems, covering techniques like data deduplication, regenerating codes, and fault-aware protocols. Research trends include reliability modeling, hardware acceleration via FPGA, and performance optimization in parallel computing frameworks. Prof. Sobe is actively involved in the German Informatics Society's PARS (Parallel Algorithms, Computer Structures) and FERS (Fault-tolerant Systems) working groups. He leads teaching platforms and research collaborations across Europe via the Baltic Summer School (BaSoTI) and ERASMUS+ programs.

Tobias Seidlمشاهده پروفایل

استاد

• Bionics
• Biomechanics
• Neuroethology
• +۳ مورد دیگر

Prof. Tobias Seidl serves as Vice Dean at the Westphalian Institute for Bionics within the Department of Mechanical Engineering at the Westphalian University of Applied Sciences in Bocholt, Germany. He has been with the university since January 2011, teaching bionics and sensor technology while leading research in biomimetic applications for robotics and engineering. Education: Bionics studies at Saarbrücken PhD on desert ant navigation systems under Rüdiger Wehner at the University of Zurich with fieldwork in Tunisia Professional experience at the European Space Agency (ESA) in Noordwijk, Netherlands Research Focus: Prof. Seidl's work centers on bionics , translating biological principles into engineering solutions. His expertise spans neuroethology (neural basis of natural behavior), functional morphology (structure-function relationships), and biomechanics . Key application areas include biomimetic robotics inspired by ants and spiders, sensor development, and bio-inspired materials. His research consistently bridges entomology with robotics, aerospace, and materials science to solve complex engineering challenges. Publication Trends: Recent publications (2025-2016) reveal a strong focus on biomimetic applications in robotics, 3D printing, and aerospace. Dominant themes include adaptive biomimetic valves for automotive cooling, force-based path integration in walking robots, hydrophobic surface replication, and satellite deployable structures inspired by insect wings. His work consistently leverages biological observations—particularly from desert ants and spiders—to advance robotic locomotion, adhesion mechanisms, and space technology. Research Infrastructure: As head of the Westphalian Institute for Bionics, Prof. Seidl leads R&D projects such as developing force sensors in ant legs for robotic applications. His institute serves as a hub for interdisciplinary collaboration between biologists and engineers, focusing on translating biological insights into technical innovations for automotive, aerospace, and medical applications.

• Logistics Optimization
• Material Handling Systems
• Discrete-Event Simulation
• +۳ مورد دیگر

Slaheddine Mestiri is a Researcher at the Chair of Material Handling and Logistics (Lehrstuhl für Fördertechnik Materialfluss Logistik) at the Technical University of Munich (TUM), located at Boltzmannstraße 15, Garching. Holding an M.Sc. degree, he actively contributes to logistics research through publications and the PlaKAT project, focusing on simulation-based solutions for transport systems and warehouse automation. Research Profile His work centers on discrete-event simulation, data-driven modeling, and AI applications in logistics. Key contributions include developing frameworks for material handling system modeling, transport system dimensioning, and order assignment strategies for heterogeneous fleets. Recent publications demonstrate increasing focus on warehouse AI scalability and feasibility assessment. Publication Trends Analysis of his 2021-2025 publications reveals consistent methodology: simulation-driven approaches applied to material flow challenges. Dominant themes include transport system optimization (43% of works), warehouse innovation (29%), and decision-support tool development (28%). His research shows progressive integration of AI concepts, particularly in 2024-2025 works addressing warehouse automation scalability. Projects & Collaboration Primary contributor to PlaKAT project (funded by German Federal Ministry for Economic Affairs and Climate Action) developing a transport means selection compass Regular collaborator with Prof. Johannes Fottner and researchers including Soufi, David, and Küster Publications presented at German Material Flow Congress and in journals like Flexible Services and Manufacturing Journal Research Infrastructure Mestiri operates within TUM's Chair of Material Handling and Logistics, a research unit specializing in material flow systems. The chair maintains industry partnerships for applied logistics research, with Mestiri focusing on simulation model development and transport system analysis within this ecosystem.

• Computational Mechanics
• Micromechanics
• FFT-based Methods
• +۴ مورد دیگر

Lennart Risthaus serves as a Researcher at the Department of Engineering Mathematics within the School of Civil Engineering at the University of Duisburg-Essen, Germany. He joined the university in September 2023 after previously working as a Researcher at the Institute of Engineering Mechanics, Continuum Mechanics Division at the Karlsruhe Institute of Technology (KIT) from February 2021 to August 2023. His academic appointments demonstrate a consistent trajectory in computational mechanics research within German technical universities. Dr. Risthaus completed his Bachelor's degree in Mechanical Engineering with a focus on Continuum Mechanics (2014-2018) and Master's degree in Mechanical Engineering with majors in Medical Technology and Applied Mechanics (2018-2021), both from the Karlsruhe Institute of Technology. His educational journey included an Erasmus exchange semester at the Royal Institute of Technology (KTH) in Stockholm and practical experience through internships at Reden B.V. in the Netherlands and Admedes GmbH in Germany, where he worked on finite element simulations and material testing. His research specializes in advanced computational techniques for material science, particularly FFT-based homogenization methods in micromechanics. Risthaus has developed innovative approaches for implementing Dirichlet boundary conditions in FFT-based computational frameworks and pioneered applications of tensor-train formats to enhance computational efficiency. His work bridges theoretical mathematics with practical engineering applications, focusing on solving complex boundary value problems in material behavior analysis. An analysis of his publication record reveals a clear research trajectory toward increasingly sophisticated computational methods for micromechanical simulations. His recent work demonstrates growing expertise in thermal homogenization problems and the integration of tensor-train methods with traditional FFT approaches. The consistent publication in high-impact journals like Computational Mechanics and International Journal for Numerical Methods in Engineering indicates recognition within the computational mechanics community. Risthaus actively contributes to the academic community through presentations at major international conferences including the GAMM Annual Meetings, ECCOMAS Young Investigators Conference, and the International Conference on Computational Plasticity (COMPLAS). His teaching responsibilities include leading exercises and tutorials for Mathematics courses for Civil Engineering students at both undergraduate and graduate levels, demonstrating his commitment to engineering education alongside his research activities.

Liu Junminمشاهده پروفایل

استادیار

• Optical Communication Technologies
• All-Optical Information Devices
• Intelligent Optimization Algorithms
• +۳ مورد دیگر

Dr. Liu Junmin is an Assistant Professor at the School of New Materials and New Energy , Shenzhen University of Technology. He holds a PhD in Engineering from Shenzhen University and has a strong background in optical communication technologies and all-optical information devices. Education: PhD (2016-2019), Shenzhen University, School of Optoelectronic Engineering Master (2010-2013), Hunan University, School of Information Science and Engineering Bachelor (2006-2010), Hunan University, School of Information Science and Engineering His research spans high-speed optical communication systems, orbital angular momentum mode multiplexing, and intelligent optimization algorithms applied to optical signal processing. He has pioneered work in atmospheric turbulence compensation using deep learning and developed novel optical devices for beam shaping and modulation. Recent publications demonstrate expertise in diffractive neural networks (2021), turbulence mitigation (2019), and Q-switched fiber lasers (2018), with a focus on practical implementations for next-generation optical networks. He currently leads multiple high-impact research projects, including the Shenzhen Basic Research Key Project (RMB 2.5M) and Guangdong Natural Science Foundation initiatives, focusing on stable support for photonic innovation and talent development.

Rainer Herpersمشاهده پروفایل

استاد

• Computer Vision
• Face and Gesture Recognition
• Computer Graphics
• +۷ مورد دیگر

Prof. Dr. Rainer Herpers is a full Professor at the Department of Computer Science within the Graduate Institute at Hochschule Bonn-Rhein-Sieg University of Applied Sciences . He serves as Scientific Director of the Graduate Institute and Director of the Institute of Visual Computing (IVC), leading interdisciplinary projects that bridge Computer Vision , Human Perception , and Real-Time Systems . His research explores gravitational effects on spatial orientation, serious games for medical training, and FPGA-based computer vision solutions. Research Interests: Computer Vision and Machine Vision Face and Gesture Recognition Artificial Neural Networks Robotics and Real-Time Systems Medical Informatics Usability in Work Safety Article Trends: Recent work focuses on gravity perception (2023-2024), neural network applications in environmental monitoring, and machine learning for network traffic analysis. Collaborations with York University and DLR highlight his interdisciplinary approach. Scientific Awards: Best Paper Award, IBM Centre for Advanced Studies in Computer Science (2020) Labs: Leads the Computer Vision Lab (C065) and Immersive Visualization Lab (C061) , developing systems like the FIVIS Bicycle Simulator and SimuBridge platform for education and safety evaluation.

• Atmospheric Chemistry
• Aerosol Chemistry
• Chemical Kinetics
• +۵ مورد دیگر

Thomas Berkemeier is a Professor and Group Leader of the Chemical Kinetics & Reaction Mechanisms group within the Department of Multiphase Chemistry at the Max Planck Institute for Chemistry in Mainz, Germany. He leads research on the chemical kinetics of multiphase systems with a focus on the health effects of air pollution and the formation mechanisms of organic aerosols. His work bridges atmospheric chemistry, physiological chemistry, and environmental health through experimental and modeling approaches. Dr. Berkemeier's research interests center on the chemical kinetics of surface and multiphase systems, particularly investigating how air pollutants interact with the respiratory system. His work examines the production of reactive oxygen species in the epithelial lining fluid of lungs, the chemical modification of proteins and lipids due to air pollution, and the formation and oxidative aging of organic aerosols. His research has significant implications for understanding the health effects of air pollution and improving atmospheric models. Analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional chemical kinetics modeling. His work spans from fundamental studies of multiphase reaction mechanisms to applied research on the health impacts of air pollutants. The publications demonstrate expertise in both experimental approaches and computational modeling of complex atmospheric processes, with particular emphasis on reactive oxygen species formation and organic aerosol chemistry. 2016: Otto Hahn Medal of the Max Planck Society 2016: ChBE Postdoctoral Fellowship at Georgia Tech Friedrich Wilhelm Helweg Foundation Award 2012: Best Graduation Award in Chemistry at Bielefeld University Dr. Berkemeier serves in professional capacities including as an Editorial Board member for Atmospheric Chemistry and Physics, Junior Faculty Member of the Max Planck Graduate School, and Ombudsperson at the Max Planck Institute for Chemistry. His research has been supported through prestigious fellowships and institutional funding that enables his interdisciplinary approach to atmospheric chemistry problems. He leads the Chemical Kinetics & Reaction Mechanisms group within the Department of Multiphase Chemistry at the Max Planck Institute for Chemistry. His team collaborates with researchers across disciplines to investigate the complex chemical processes that govern air quality and its impacts on human health, utilizing both experimental and computational approaches to address challenging questions in atmospheric science.

• Scientific Computing
• Machine Learning
• High-Energy Physics
• +۳ مورد دیگر

Prof. Dr. Ralf Keidel is a faculty member at the Chair for Scientific Computing , Rhineland-Palatinate University of Technology Kaiserslautern-Landau (RPTU), since 2022. His academic career spans roles at Worms University of Applied Sciences , where he has served as Professor of Computer Science since 1993, Scientific Director of the Center for Technology and Transfer (ZTT) since 2000, and Head of the Technology Transfer Office since 1996. He is a key figure in international collaborations, including the ALICE Collaboration Board at CERN (2003–2023), Bergen pCT Collaboration (since 2018), and the MODE Collaboration (since 2022). His research merges Computer Science with High-Energy Physics , focusing on machine learning , secure heterogeneous distributed systems , and optimization of detectors in particle physics . Projects like SIVERT (2020–2024) aim to enhance Proton Computed Tomography (pCT) for clinical radiation therapy using AI-driven visualization and real-time reconstruction. He also contributes to serious games for financial education and mobile applications for musical training. Key publications highlight his work on differentiable programming for detector optimization, deep reinforcement learning in particle tracking, and convolutional neural networks for radiation topology analysis. His projects often involve interdisciplinary teams from institutions like the University of Bergen , DKFZ Heidelberg , and Western Norway University of Applied Sciences .