جست‌وجوی استاد و پژوهشگر

Michael Bührenمشاهده پروفایل

استاد

• Automation
• Robotics
• Digitalization
• +۷ مورد دیگر

Michael Bühren is a Professor at Westfälische Hochschule, affiliated with the Faculty of Mechanical Engineering Bocholt and the Mechatronik-Institut Bocholt. He serves as Project Manager for the Digital Factory Bocholt and Digi-Up! initiatives and was the speaker of the Mechatronics Institute Bocholt in 2019. His research focuses on automation, robotics, digitalization, and Industry 4.0 . He investigates practical applications of smart manufacturing technologies, including simulation and virtualization, robotics with human-robot collaboration (MRK) capabilities, OPC UA for data acquisition, and machine learning for data and image processing. His work bridges industrial automation with modern digital technologies. His recent publications reflect a strong trend toward integrating industrial systems with digital platforms, particularly through OPC UA and IoT frameworks, while earlier work includes large-scale industrial automation projects in the steel industry and dynamic modeling of marine drive systems. Prof. Bühren is actively involved in technology transfer, represented through his role in the "Effizienz Forum Wirtschaft" and initiatives connecting startups with small and medium enterprises (SMEs). He has no listed scientific awards in the provided text. He teaches courses in control engineering, electrical drive systems, motion control, energy management, and artificial intelligence at the bachelor’s and master’s levels. He advises students, though specific names are not listed. His research is conducted within the Mechatronik-Institut Bocholt, a hub for interdisciplinary research in mechatronics, automation, and digital production technologies.

• Digitalization
• Multi-Agent Systems
• Semantic Web
• +۵ مورد دیگر

Prof. Dr. Thomas Farrenkopf is a full-time Professor in the Department of Business Informatics at the Technische Hochschule Mittelhessen , serving as Dean of Studies . He leads the Business Informatics Bachelor program and specializes in digitalization, multi-agent systems, and AI-driven decision support. Expertise Areas : Industry 4.0, Smart Factory, Semantic Web, full-stack software development Contact : thomas.farrenkopf@mnd.thm.de Research Focus : His work bridges knowledge-based methods with practical applications in artificial intelligence, particularly through multi-agent systems for traffic modeling and business simulations. He developed AGADE Traffic (a knowledge-based traffic simulator) and ATHOS (a domain-specific language for multi-agent simulations), focusing on scalability and complexity reduction. Recent studies explore individual preferences' impact on traffic policies and agent-based feedback mechanisms in business contexts. Academic Contributions : With over 15 publications since 2013, his research spans agent-based modeling, semantic web applications, and smart manufacturing - notably improving throughput times in toolmaking by 90% through Industry 4.0 implementations. Teaching & Supervision : Actively supervises Bachelor's Practical Projects (BPP), providing guidance for internship-related academic work through structured evaluation processes and electronic reporting systems. Collaborations : Works with international researchers like Johannes Nguyen, Simon T. Powers, and Michael Guckert, publishing in venues such as SN Computer Science , Lecture Notes in Computer Science , and Journal of Artificial Societies and Social Simulation .

Peter Waldمشاهده پروفایل

استاد

• Human Resource Management
• Digital Transformation in HR
• Virtual Leadership
• +۴ مورد دیگر

Prof. Dr. Peter Wald serves as Professor for Business Administration with a specialized focus on Human Resource Management at the Leipzig University of Applied Sciences (HTWK Leipzig) since March 2009. He is affiliated with the Faculty of Business Administration and Industrial Engineering, where he maintains office TO 109 and actively contributes to academic and professional development in HR. Prof. Wald organizes the annual HR Innovation Day at HTWK Leipzig and serves on the scientific advisory board of Parität Sachsen, demonstrating his commitment to bridging academic research with industry practice. His research expertise centers on the digital transformation of human resource management, with particular emphasis on virtual leadership, modern recruiting practices, and organizational development in the context of Work 4.0. Prof. Wald investigates how digital technologies are reshaping traditional HR functions and how organizations can adapt their talent management strategies to meet emerging workforce challenges. His work spans theoretical frameworks and practical applications, with a strong focus on candidate experience, social media recruiting, and the evolving expectations of students regarding internships. Analysis of his publication record reveals a clear trajectory toward examining the practical implementation of digital tools in HR processes. His research shows increasing focus on deskless work, flexible scheduling, and the candidate journey, reflecting current workforce trends. His publications demonstrate consistent engagement with both academic scholarship and practical HR challenges, often presented through collaborative industry case studies. Prof. Wald maintains active engagement with students, regularly publishing thesis topics on the OPAL learning platform and welcoming topic suggestions from both students and industry partners. He communicates his expertise through the 'Leipzig HRM Blog' and social media channels, particularly via his Juicer.io feed, maintaining a visible presence in the HR professional community. His approach combines academic rigor with practical relevance, making his work valuable to both scholars and practitioners in the field of human resource management.

Adèle CARRADOمشاهده پروفایل

استاد

• Solid State Physics
• Biomedical Engineering
• Materials Science
• +۳ مورد دیگر

Dr. Adèle Carradò is a Full Professor in Solid State Physics at the University of Strasbourg (UNISTRA), affiliated with the Institute of Physics and Chemistry of Materials (IPCMS). Her research focuses on bioactive coatings, surface characterization of metallic and multi-layer systems, and mechanical properties of hybrid materials. PhD in Mechanics and Material Science (University of Reims, 2001) HDR (University of Strasbourg, 2004) Research Assistant (University of Ancona, 1997-1998) Post-doc (CEA Saclay, 2002) Her work includes over 70 original articles, two patents, and 50+ invited lectures. She specializes in: Residual stress analysis via neutron and synchrotron radiation Functional thin films for biomedical applications Mechanical behavior of metal/polymer/metal systems 3-layered sandwich structures for lightweight design Zn-Mg alloys for orthopedic implants Surface grafting techniques for biomaterials Recent publications highlight advancements in: Biodegradable Zn-Mg alloys with PMMA coatings ATUM-SEM for bone microstructure analysis Forming mechanics of steel-glass fiber-reinforced composites Residual stress optimization in extruded and drawn materials She actively participates in international conferences and serves on executive committees for biomedical materials symposia.

Rainer Heintzmannمشاهده پروفایل

استاد

• Super-resolution microscopy
• Optical microscopy
• Point spread function calculation
• +۴ مورد دیگر

Prof. Dr. Rainer Heintzmann serves as Head of the Microscopy Department at the Leibniz Institute of Photonic Technology (Leibniz-IPHT) in Jena, Germany. His research focuses on advancing optical microscopy techniques, particularly super-resolution methods that surpass the diffraction limit to visualize cellular structures at nanoscale resolution. His primary research interests center on structured illumination microscopy (SIM), point spread function modeling, and computational imaging techniques. He has made significant contributions to developing automated multicolor SIM systems, extreme ultraviolet microscopy approaches, and deep learning-enhanced image analysis methods. His work bridges optical physics, computational algorithms, and biomedical applications, with particular emphasis on making advanced microscopy techniques more accessible through open-source hardware and software solutions. Analysis of his recent publications reveals a strong focus on overcoming fundamental limitations in optical microscopy. His research spans from theoretical modeling of optical systems to practical implementations for biological imaging. Key trends include the development of more accurate point spread function calculations, expansion of super-resolution techniques to new wavelength regimes, and integration of machine learning for image analysis and segmentation. Prof. Heintzmann actively collaborates with researchers across multiple institutions, as evidenced by his co-authorship on numerous interdisciplinary publications. His work has appeared in high-impact journals including Nature Methods, Nature Reviews Molecular Cell Biology, and Optics Express, reflecting the significance of his contributions to advancing microscopy techniques. His laboratory at Leibniz-IPHT appears to focus on developing novel microscopy instrumentation, particularly open-source implementations of super-resolution techniques. Recent projects include the openSIMMO platform for automated multicolor structured illumination microscopy and work on extreme ultraviolet microscopy that could potentially extend super-resolution capabilities into the X-ray regime.

Matthias Jägerمشاهده پروفایل

پژوهشگر

• Optical Fiber Technology
• Photonics
• Laser Physics
• +۳ مورد دیگر

Dr. Matthias Jäger is a Researcher in the Department of Fiber Photonics at the Leibniz Institute for Photonic Technology (IPHT) . His work focuses on advanced optical fiber development, particularly in doped materials and nonlinear laser dynamics. Core technologies: Thulium/Yb/Ho-doped fibers, periodic shadowing for stray light suppression, nonlinear loss management Instrumentation: High peak power laser systems, fluorescence lifetime analysis, multicore emission profiling Research interests span laser physics, materials science, and optical engineering. Recent publications highlight breakthroughs in: Directional stability control for fiber ring lasers (2021-2024) Hybrid Tm:YAG crystal-derived fiber fabrication (2022) Nanoparticle-doped optical fibers (2024) 2 µm eye-safe laser systems (2024) Pr3+-doped nanocrystal fiber integration (2024) Thulium concentration optimization for laser efficiency (2025) His work demonstrates expertise in fiber fabrication methods including: Modified Chemical Vapor Deposition (MCVD) Powder-sinter technology Molten-core processing REPUSIL fiber drawing

Volker Schöppnerمشاهده پروفایل

استاد

• Sustainable Materials and Processes
• Plastics Processing
• Polymer Engineering
• +۴ مورد دیگر

Volker Schöppner is Professor and Head of Plastics Processing at the University of Paderborn, concurrently serving as Professor Member in the Key research area Sustainable Materials, Processes and Products. Previously until 2022, he held the same professorial membership in the Direct Manufacturing Research Center (DMRC). His research centers on sustainable polymer processing innovations, particularly anvil-free ultrasonic welding for single-sided access scenarios and laser transmission welding scale-up rules for thermoplastics. He investigates mixing mechanisms in twin-screw extruders and develops eco-efficient plastics manufacturing methodologies, emphasizing recyclable material systems and energy-optimized processes. Analysis of his 2024 publications reveals concentrated expertise in plastics joining technologies and extrusion process optimization, with multiple conference presentations on ultrasonic welding variants and a significant journal contribution on extruder screw dynamics. This output demonstrates consistent focus on practical industrial applications within polymer engineering. Professor Schöppner actively contributes to the University of Paderborn's Key research area Sustainable Materials, Processes and Products, driving interdisciplinary collaboration on circular economy solutions for polymer materials and manufacturing systems.

Khalil Esperمشاهده پروفایل

پژوهشگر

• Verification and Model Checking
• Energy Optimization
• Real-time Systems
• +۴ مورد دیگر

Khalil Esper is a Researcher at the Department of Computer Science, Faculty of Engineering, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), where he works at the Chair of Computer Science 12 (Hardware-Software Co-Design). His research focuses on verification, energy optimization, and runtime requirement enforcement in embedded systems and MPSoCs. His educational background includes: Informatics Engineering from Aleppo University, Syria (2010-2015) European Master in Embedded Computing Systems (EMECS) from Rhineland-Palatinate University of Technology Kaiserslautern-Landau (Germany) and Norwegian University of Science and Technology (Norway) (2017-2019) Esper's research interests center around verification and model checking, energy optimization on MPSoC, real-time systems and embedded systems, and autonomic computing. His work particularly focuses on runtime requirement enforcement mechanisms for non-functional properties in multi-processor systems-on-chip, with applications extending to medical devices and human-robot interaction systems. He has developed approaches using finite state machines, reinforcement learning, and evolutionary algorithms to ensure system properties are maintained during execution. His publication record shows a strong trend toward applying formal methods and runtime enforcement techniques to increasingly complex systems, with recent work expanding into safety-critical applications like orthoses and human-robot interaction. The interdisciplinary nature of his research bridges computer science, embedded systems engineering, and biomedical applications. Esper has supervised multiple theses including: Sascha H.: Runtime Requirement Enforcement of Non-Functional Requirements on MPSoCs Using Fuzzy Logic (2022) Iana S.: Feedback-Based Control of Non-functional Program Execution Properties on Linux (2023) Philipp L.: Runtime Requirement Enforcement of Functional and Non-Functional Requirements of a Knee Orthosis Based on a Digital Twin (2024) Avinash N.: Runtime Requirement Enforcement of Safety Properties of an Ankle Orthosis Based on a Digital Twin (2024) Zhiyi T.: Generation of Environment FSMs Using Machine Learning Techniques (2025) Moustafa A.: Runtime Requirement Enforcement of Safety Properties of Human-Robot Interaction Based on a Digital Twin (2025) Florian K.: Runtime Requirement Enforcement of Safety Properties of Human-Robot Interaction (2025) He has been actively teaching courses on Approximate Computing and Embedded Systems since the 2021/2022 academic year, demonstrating his commitment to academic instruction alongside his research activities. Esper is involved in the InvasIC research project, part of the DFG Transregional Collaborative Research Center 89 on Invasive Computing, which explores novel approaches to resource management in parallel computing systems.

Matthias Beckerمشاهده پروفایل

استاد

• Human-Computer Interaction
• Simulation and Modeling
• Distributed Systems
• +۶ مورد دیگر

Matthias Becker is a Professor at the Institute for Practical Computer Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover, where he has been a core member of the Human-Computer Interaction group since 2019. He serves as Internship Coordinator for Computer Science and Computer Engineering and holds key roles in the Computer Science Examination Board and Selection Committee, actively shaping academic governance and student development. His academic journey began with PhD studies at the University of Bremen (1996-2000) supported by a DFG grant, followed by a postdoctoral permanent position at Leibniz University Hannover (2000-2019), an Associated Assistant Professor role at École des Mines de Nantes (2000), and a Habilitation in Computer Science in 2013. This foundation enabled his transition to a full professorship in 2019. Becker's research spans Human-Computer Interaction, Simulation and Modeling, and Bio-inspired Computing, with applications in agriculture, renewable energy, and manufacturing. His work integrates distributed systems, optimization algorithms, and wireless sensor networks to solve complex real-world problems, such as greenhouse monitoring, wind farm logistics, and tire noise reduction. Recent publications reveal a strategic focus on practical validation of simulation models and cross-domain applications of nature-inspired algorithms. His 15 most recent publications (2018-2024) demonstrate consistent innovation in applying simulation techniques to offshore wind farm installation, agricultural pest management, and sports science. These works emphasize real-world validation, collaborative problem-solving, and the development of domain-specific optimization frameworks that bridge theoretical algorithms and industrial implementation. As Internship Coordinator, Becker facilitates critical industry-academia connections for students, while his examination board responsibilities ensure rigorous academic standards. His leadership in the Human-Computer Interaction group drives research on interactive systems for agriculture, energy, and health, with particular emphasis on user-centered design in complex operational environments like wind farm logistics and greenhouse automation.

Heidi Hastedtمشاهده پروفایل

پژوهشگر

• Photogrammetry
• Optical 3D Metrology
• Remote Sensing
• +۹ مورد دیگر

Heidi Hastedt is a Researcher at the Institute of Photogrammetry and GeoInformation (IAPG) , part of Jade University of Applied Sciences . Her work spans photogrammetry , optical 3D metrology , and remote sensing , with a focus on camera calibration , Structure from Motion (SfM) , and software development in C++/C# and ESRI ArcObjects . Education : Diploma in Surveying (Dipl.-Ing. (FH)) from University of Applied Sciences Oldenburg/Ostfriesland/Wilhelmshaven (2001). Master of Engineering (M.Eng.) in Geoinformation Systems from Anhalt University of Applied Sciences (2015). Research Interests : Heidi's expertise lies in optical 3D measurement systems for applications like cultural heritage preservation and dynamic process monitoring . She specializes in camera modeling , system development , and quality control in SFM workflows. Her 15 most recent articles (2005–2022) highlight advancements in 3D reconstruction , cultural heritage digitization , and high-dynamic process capture using photogrammetric methods. Projects & Grants : Heidi has led research on geometric monitoring of the Bremen Cog (2017–present, funded by the German Maritime Museum) and accuracy evaluation of SFM methods (2003–2005, AGIP). Earlier work (2000–2002) focused on optical 3D system verification, and she contributed to Lower Saxony Advance initiatives (2005–2010) for dynamic 3D metrology. Laboratory Involvement : Heidi co-manages the Laboratory for Optical 3D Metrology , where she develops and tests photogrammetric tools for large-volume measurements and real-time monitoring of historical and dynamic objects.

Franziska Tobischمشاهده پروفایل

پژوهشگر

• Large-Scale Agile Development
• Knowledge Exchange and Coordination
• Communities of Practice
• +۱ مورد دیگر

Franziska Tobisch is a Research Assistant at the Chair of Informatics 19 (Software Engineering for Business Information Systems) at the Technical University of Munich . She joined the team in April 2022, bringing expertise in large-scale agile software development through her Master's degree in Information Systems and internships at Daimler TSS and Immersight GmbH. Her work includes teaching roles as an Advisor and Organizer for Master's-level courses such as Software Engineering for Business Applications and Strategic IT Management . Research Interests : Large-Scale Agile Development Knowledge Exchange and Coordination in Agile Organizations Communities of Practice Effort Estimation in Agile Projects Publications : Her recent work focuses on CoP dynamics in scaled agile environments , effort estimation challenges , and metric management for large agile organizations , presented at conferences like XP, ICEIS, and HICSS. Advising : She has supervised Master's and Bachelor's theses on topics including knowledge sharing , CoP success measurement , and effort estimation challenges , collaborating with students like Karla Weigelt, Anil Can Kara, and Lixun Dai.

Werner Hemmertمشاهده پروفایل

استاد

• Theoretical Neuroscience
• Technical Applications
• Biomedical Neuroscience
• +۵ مورد دیگر

Professor Werner Hemmert leads the Bio-Inspired Information Processing group at the Munich Institute of Biomedical Engineering (TUM School of Computation, Information and Technology). His research spans theoretical, biomedical, and systems neuroscience, focusing on auditory processing, cochlear implants, and computational modeling of neural coding mechanisms. Primary research focus: Theoretical Neuroscience & Technical Applications Secondary research focus: Biomedical Neuroscience Tertiary research focus: Cellular & Systems Neuroscience His work employs computational modeling , psychophysical and objective nerve potential measurements , vibration analysis , and otoacoustic emission measurements to investigate: Coding of sound into nerve-action potentials Neuronal processing in the auditory brainstem Electrical stimulation of neurons Patient measurements in cochlear implant users Biophysics of sensory organs and neurons Recent publications highlight his contributions to auditory neuroscience, including studies on neural coding dynamics, computational modeling of auditory systems, and biophysical mechanisms of hearing. These works intersect with fields like neural networks , computational modeling , and auditory signal processing . Current or graduated GSN students under his supervision include Miguel Obando, Anna Dietze, Dr. Michael Drews, and Dr. Miguel Eduardo Obando Leitón. Contact: werner.hemmert@tum.de | Website

Kamyar Sarsharمشاهده پروفایل

استاد

• Business Process Management
• E-Business
• IT in Healthcare

Kamyar Sarshar is a Professor of Business Informatics at the Hamburg School of Business Administration (HSBA) since January 2014, serving as Academic Director of the Bachelor's program in Business Informatics within the Department of Technology & Markets. His educational background includes: Computer Science degree from the University of Hamburg MBA from Cardiff University, United Kingdom PhD from the Institute of Business Informatics in Saarbrücken Prior to HSBA, he worked as a Managing Consultant at Logica (now CGI), leading cross-industry process management projects. Research interests focus on: Business Process Management E-Business IT in Healthcare His work emphasizes empirical evaluation of modeling techniques like Event-driven Process Chains and Petri nets, particularly in healthcare applications and end-user usability. Publications from 2004-2008 reveal consistent contributions to business process modeling methodology, with strong empirical validation across healthcare, energy, and construction sectors, highlighting practical applicability and user-centered design principles. No scientific awards are documented in the provided materials. Information regarding student supervision, research grants, laboratories, or collaborative teams is not specified in the source text.

• Energy Systems
• Sustainable Technology
• Carbon Capture
• +۴ مورد دیگر

Niklas von der Aßen is a Professor and Head of the Institute at the Chair and Institute of Technical Thermodynamics, RWTH Aachen University. His research focuses on energy systems, sustainable technology, and carbon capture. University: RWTH Aachen University Institute: Chair and Institute of Technical Thermodynamics Email: niklas.vonderassen@ltt.rwth-aachen.de His recent work includes nationwide heat pump deployment analysis, stochastic energy system optimization, and green chemistry metrics. Publications highlight interdisciplinary approaches to sustainability and thermodynamics. Current affiliations and responsibilities include leading the institute and advancing research in energy and environmental technologies.

• Electronic Structure Theory
• Machine Learning in Materials Science
• Data Driven Materials Science
• +۶ مورد دیگر

Professor Patrick Rinke leads the Chair of AI-based Materials Science at the Technical University of Munich (TUM), within the TUM School of Natural Sciences and Department of Physics. His research group develops advanced electronic structure and machine learning methods to address critical challenges in materials science, surface science, physics, chemistry, and nanoscience. Professor Rinke's research spans multiple cutting-edge domains including electronic structure theory development, machine learning applications for materials science, data-driven materials discovery, biomaterials engineering, atmospheric science applications, clean energy materials, and hybrid materials systems. His work integrates advanced computational methods with practical applications across diverse scientific fields, particularly focusing on how artificial intelligence can transform traditional materials research. Analyzing his recent publications reveals strong trends in applying machine learning techniques to materials discovery, with particular emphasis on Bayesian optimization methods, active learning approaches for molecular data, and efficient dataset generation strategies. His research spans from fundamental electronic structure theory to practical applications in biomaterials, atmospheric science, and renewable energy technologies. Professor Rinke has received several prestigious awards including the August-Wilhelm Scheer visiting professorship (2017), a German Science Foundation research scholarship (2007), the Outstanding Postdoctoral Research Achievement Award from UC Santa Barbara (2009), recognition as an Outstanding Referee for Physical Review journals (2014), and the Institute of Physics Computational Physics Group Thesis Prize (2003). Professor Rinke actively contributes to the academic community through teaching and supervision. For the Winter term 2025/26, he is teaching courses including Academic Writing Skills, Introduction to Machine Learning for Materials Science, Current Topics in AI-Based Materials Science, and Machine Learning for Natural Sciences. His research group includes several team members working on diverse projects spanning the intersection of AI and materials science.