جست‌وجوی استاد و پژوهشگر

• Gravitational Wave Astronomy
• Precision Interferometry
• Instrumental Noise Modeling
• +۳ مورد دیگر

Dr. Olaf Hartwig is a Senior Scientist at the Albert Einstein Institute (AEI) in both Potsdam and Hannover. His research focuses on precision interferometry and fundamental interactions, specifically for the Laser Interferometer Space Antenna (LISA) project. He holds a PhD in Physics from the University of Hannover (2021) and has held postdoctoral positions at SYRTE - Observatoire de Paris and AEI. His work bridges instrumental modeling, data processing, and noise reduction for space-based gravitational wave detection. Education: BSc and MSc in Physics (University of Hannover), PhD in Physics (University of Hannover via AEI Potsdam) Current Roles: Split post-doctoral position between AEI Potsdam (global fit for LISA) and AEI Hannover (Performance and Operations team) Research Interests revolve around space-based gravitational wave detectors, with emphasis on: Instrumental Modeling - Refining noise models, addressing data gaps, and mitigating glitches in LISA data Data Processing - Developing simulations, performance models, and software tools like PyTDI Detector Optimization - Clock synchronization, light-travel time estimation, and onboard optical delay compensation Publication Trends (15 most recent) show a focus on LISA instrumentation, with key topics including time-delay interferometry (TDI), stochastic gravitational wave background reconstruction, instrumental noise characterization, and intersatellite ranging. His work frequently integrates GPU acceleration, Python-based toolchains, and end-to-end simulation pipelines.

Andreas Harthمشاهده پروفایل

استاد

• Semantic Web
• Linked Data
• Knowledge Graphs
• +۸ مورد دیگر

Prof. Dr. Andreas Harth (born 1976) is a leading researcher in decentralized information systems and data portability, holding the Chair of Business Information Systems at Friedrich-Alexander-Universität Erlangen-Nürnberg while heading the Data Spaces and IoT Solutions department at Fraunhofer IIS. His work bridges Semantic Web technologies with industrial IoT applications, focusing on making enterprise data context-independent. Research areas: Semantic Web, Linked Data, Knowledge Graphs, IoT, Industry 4.0 Key projects: i-VISION, ARVIDA, PlanetData, MEREGIOmobil Academic background: PhD from Digital Enterprise Research Institute (2010), Karlsruhe Institute of Technology habilitation (2016) Former affiliations: Stanford University, University of Southern California, University of Heidelberg Harth's research emphasizes data integration through formal logic and graph-based representations, enabling companies to merge shipment data with commercial records or optimize warehouse processes using RFID and near-field detection. His 2019-2023 publications reveal a trend toward entity-centric data fusion and real-time workflow execution in dynamic environments. He advocates cloud alternatives like Nextcloud for SME data sovereignty and explores Solid technology for decentralized data control. Scientific Contributions: Co-developer of YARS2 federated query framework (2007) Key figure in JPEG XS ISO standard development (2025 Joseph von Fraunhofer Prize) Lead architect of FusE data fusion system (ACM Transactions, 2019) Primary investigator in multiple EU research initiatives (PlanetData, NeOn) Harth actively consults with manufacturing companies through Fraunhofer IIS' Supply Chain Services division, applying rapid IoT prototyping for cost-effective digitalization. He leads the Semantic Web Lab, creating machine-readable workflow models for industrial applications.

Hartmut Wiggersمشاهده پروفایل

استاد مدعو

• Nanoparticle Synthesis
• Gas-Phase Synthesis
• Catalysis
• +۴ مورد دیگر

Hartmut Wiggers is an Adjunct Professor at the University of Duisburg-Essen , leading the Nanoparticle Synthesis group within the Institute for Energy and Material Processes - Reactive Fluids . His career spans over three decades, focusing on gas-phase synthesis and functionalization of nanoparticles for energy and environmental applications. Research Interests : Hartmut’s work centers on gas-phase synthesis of nanoparticles using flame, plasma, and laser reactors, enabling precise control over material properties. His research extends to kinetics, in-situ diagnostics, and device engineering, including sensors and battery anodes. Key areas include catalysis , energy storage , and nanomaterials for water remediation . Publications : His recent work (2024-2025) explores advanced nanomaterials for energy conversion, such as perovskite catalysts for oxygen evolution reactions, silicon-carbon composites for lithium-ion batteries, and graphene-based hybrids. The articles highlight scalable synthesis methods and performance optimization through structural engineering. Affiliations & Roles : He is affiliated with the DECHEMA Center for Nanointegration Duisburg-Essen , Materials Research Society , and serves as a scientific advisor at the Institute of Energy and Environmental Technology e.V. (IUTA) .

• Internet of Things (IoT)
• Smart Grids
• Renewable Energy Systems
• +۳ مورد دیگر

Mohamed A. Ahmed is a researcher affiliated with Central Michigan University, School of Engineering & Technology , with additional collaborations across institutions like Ain Shams University, Memorial University of Newfoundland, and Prince Sultan University. His work spans interdisciplinary domains including Internet of Things (IoT) Smart Grids Renewable Energy Systems Machine Learning Recent research focuses on IoT platforms for smart energy management , including electric vehicle charging infrastructure, remote elderly care systems, and large-scale wind turbine monitoring. He has contributed to wireless network architectures for cyber-physical energy systems and developed fuzzy logic algorithms for EV charging prioritization. Publications highlight expertise in time-series forecasting for energy demand, clustering algorithms for smart grid planning, and data aggregation techniques in wind energy applications. Collaborations frequently involve researchers such as Young-Chon Kim, Ali Mohamed Eltamaly, and José Luis Gallardo.

• Machine Learning
• Computer Vision
• Signal Processing
• +۳ مورد دیگر

Chenguang Liu is a researcher at Institut Polytechnique de Paris , France, with a focus on computational methods, machine learning, and control systems. His work bridges theoretical and applied research across multiple domains including computer vision, signal processing, and operations research. Key research areas: Machine Learning, Computer Vision, Computational Physics, Control Theory Notable publication trends: Develops novel algorithms for parallel computing, peridynamic modeling, and real-time systems Recent contributions include Bayesian neural networks for gas-bearing prediction, multi-agent reinforcement learning for UAV swarms, and domain adaptation techniques in object detection. He collaborates extensively with researchers in electrical engineering and applied mathematics disciplines.

• 5G/6G Networks
• Wireless Networks
• Mobility Management
• +۵ مورد دیگر

M.Sc. Anna Prado is a Research and Teaching Associate at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich. She holds a B.Sc. in Information Systems and Communication Engineering from Bauman Moscow State Technical University (2017) and an M.Sc. in Communication Engineering from TUM (2020). She is currently pursuing her Ph.D., focusing on mobility management in 5G/6G networks, simulation of wireless systems, and digital twins for 6G. Her research emphasizes minimizing handover occurrences while ensuring smooth user connectivity through optimization and reinforcement learning techniques. Anna's academic role involves contributing to projects like the BMBF-funded 6G-ANNA initiative, which aims to develop holistic 6G systems prioritizing security, sustainability, and flexibility. She collaborates on network architecture design, resource allocation strategies, and resilient communication frameworks. Her work aligns with German technological sovereignty goals, addressing industrial and societal needs through advanced network technologies. Her research interests span 5G/6G networks, wireless resource management, digital twins, and machine learning applications in networks. She has authored/co-authored peer-reviewed papers on topics like admission control, slice dimensioning, energy-efficient edge orchestration, and secure 6G architectures. Her contributions enhance network efficiency, reliability, and adaptability for future communication systems. Anna is actively involved in the FlexComNetsLab and 6G-IP Lab, testing and demonstrating innovative 6G concepts. She participates in conferences and collaborates with industry partners to bridge academic research and real-world deployment.

Daniel Büscherمشاهده پروفایل

پژوهشگر

• Autonomous Robot Navigation
• Deep Learning
• Computer Vision
• +۱ مورد دیگر

Daniel Büscher is a post-doctoral researcher at the Robot Learning Lab of the University of Freiburg. His work focuses on autonomous robot navigation , deep learning , and probabilistic state estimation . He has contributed to robotics research through projects involving mobile manipulation and audio-visual navigation . Research Interests : Autonomous navigation, deep learning, computer vision, probabilistic estimation Teaching : Lecturer and tutor for Introduction to Mobile Robotics and Robot Mapping (2017–2023) Publication Trends : Recent work emphasizes robot design optimization , language-grounded scene graphs , and uncertainty-aware perception . His research connects reinforcement learning with mobile manipulation and cross-domain navigation challenges.

Dominik Baumannمشاهده پروفایل

استادیار

• Systems and Control Theory
• Machine Learning
• Communication Networks
• +۳ مورد دیگر

Dominik Baumann is an Assistant Professor at the Department of Electrical Engineering and Automation at Aalto University in Espoo, Finland. His research focuses on the interplay of systems and control theory with machine learning and communication networks, with a current emphasis on causal inference in control systems. Education: Diploma in Electrical Engineering from TU Dresden, Germany (2016) PhD from KTH Stockholm, Sweden (2020), supervised by Sebastian Trimpe (Max Planck Institute) and Karl H. Johansson Postdoctoral positions at RWTH Aachen University (1 year) and Uppsala University with Thomas Schön (1 year) Dr. Baumann's research bridges theoretical foundations with practical applications in robotics, wireless networks, and decision-making systems. His work spans safe reinforcement learning, event-triggered control systems, causal inference in dynamical systems, and ergodicity economics perspectives on long-term decision-making. He applies mathematical rigor to address challenges in resource-constrained environments, particularly focusing on safety guarantees and computational efficiency for real-world implementation. His recent publication record demonstrates a strong trajectory in safe learning-based control, with increasing focus on ergodicity economics in reinforcement learning, multi-agent coordination, and human-robot interaction. The research consistently balances theoretical guarantees with practical implementation constraints, particularly in bandwidth-limited wireless control systems and robotics applications. Scientific Awards: Best Paper Award for 'Feedback control goes wireless: Guaranteed stability over low-power multi-hop networks' at ACM/IEEE International Conference on Cyber-Physical Systems (2019) Dr. Baumann maintains extensive international collaborations, evidenced by numerous seminar invitations worldwide including Oxford University, ETH Zürich, University College London, and institutions across Asia. His research program addresses fundamental challenges in cyber-physical systems with applications in industrial automation, robotics, and the Internet of Things, securing research funding for projects focused on safe learning in control systems and wireless cyber-physical systems. His research group at Aalto University develops both theoretical foundations of learning-based control and practical algorithms for real-world deployment, with active software repositories on GitHub related to predictive triggering, causal structure identification, and ergodic reinforcement learning.

• Virtual Reality
• Computer Vision
• Human-Computer Interaction
• +۴ مورد دیگر

Joe K. Kearney is a Professor in the Department of Computer Science at the University of Iowa and the University of Minnesota. His career spans over three decades, focusing on virtual reality, computer vision, and human-computer interaction research. Key affiliations: University of Iowa (Iowa City, IA, USA), University of Minnesota (Minneapolis, MN, USA) Research domains: Virtual environments, perception-action coupling, motion capture systems, pedestrian behavior simulation Research trends show sustained contributions to immersive visualization , autonomous navigation , and human factors in virtual reality . His 2014-2025 work explores AR-based pedestrian safety systems, while earlier studies (1986-2006) established foundational frameworks for virtual environment simulation and optical flow analysis. Long-term collaborations with Jodie M. Plumert (1986-2021), James F. Cremer (1986-2009), and Pooya Rahimian (2015-2017) demonstrate consistent team research in VR cognition and autonomous systems.

• Stochastic Analysis
• Mathematical Finance
• Limit Order Books
• +۳ مورد دیگر

Dörte Kreher is an Assistant Professor at the Department of Mathematics, Humboldt University of Berlin, specializing in stochastic analysis and its applications to mathematical finance. She has led multiple research projects, including MATH+ Project AA4-4 and AA4-9, and is affiliated with the Berlin-Oxford IRTG 2544 and SFB/TRR 388. PhD in Mathematics (University of Zurich, 2014) Diplom in Mathematics (Humboldt University of Berlin, 2009) B.Sc. in Economics (Humboldt University of Berlin, 2009) Her research focuses on stochastic analysis , limit order book modeling , rough volatility models , and optimal control in energy markets . Recent work examines non-negative martingale solutions, second-order approximations of order books, and cross-border electricity market dynamics. She has published extensively in journals such as SIAM Journal on Financial Mathematics, Finance and Stochastics, and Stochastic Processes and their Applications. Co-organized workshops include the Berlin Workshop on Mathematical Finance for Young Researchers and the Junior Female Researchers in Probability series. She has supervised research assistants Konstantins Starovoitovs, Cassandra Milbradt, Wilfried Kenmoe Nzali, and Rahama Sani Abdullahi.

Felix Rempeمشاهده پروفایل

پژوهشگر

• Mobility Systems
• Machine Learning
• Data Exploration and Analyses Methods
• +۱ مورد دیگر

Felix Rempe is a Rudolf Diesel Industry Fellow at the Technical University of Munich Institute for Advanced Study (TUM-IAS) , affiliated with the BMW Group in the field of Autonomous Driving . He holds a PhD in Computational Science and Engineering from TU Munich, awarded summa cum laude in 2018, and an M.Sc. in Mechatronics from DHBW Stuttgart in 2014 with Honours. His research focuses on data-driven approaches to traffic engineering and control , leveraging machine learning and sensor data from vehicles for real-time traffic state estimation and prediction. His work explores the intersection of mobility systems and artificial intelligence , particularly in the domains of traffic flow theory and digital twin development for transportation infrastructure. Felix’s publications highlight advancements in data fusion techniques , deep learning architectures , and statistical modeling applied to autonomous driving and urban mobility challenges. 2018: PhD thesis awarded summa cum laude 2014: M.Sc. with Honours award for completing the Honour’s track at TUM 2012: BayLat grant for study exchange program Latin America

Lasse Ermoneitمشاهده پروفایل

پژوهشگر

• Quantum Computing
• Semiconductor Physics
• Applied Mathematics
• +۳ مورد دیگر

Lasse Ermoneit is a Researcher at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) , focusing on quantum computing and semiconductor physics. His work bridges theoretical and applied research in advanced quantum technologies. Key Affiliations : WIAS, Leibniz Network MMS Research Interests include spin-qubit dynamics, strain engineering in semiconductor materials, and optimal control strategies for quantum devices. His contributions address challenges like random alloy disorder and charged defect interference in silicon-based quantum systems. Recent Publications highlight interdisciplinary efforts at WIAS to model and control quantum transport mechanisms, with applications in next-generation semiconductor technologies and quantum information processing.

• Artificial Intelligence
• Multimedia Systems
• Robotic Interaction
• +۵ مورد دیگر

Wang Yufei is affiliated with Xiamen University, China, holding positions across the School of Informatics, Institute of Artificial Intelligence, Center for Digital Media Computing, and School of Film. The research spans interdisciplinary domains, integrating artificial intelligence, robotics, and multimedia systems for real-world applications. Wang Yufei's research primarily focuses on artificial intelligence , computer vision , robotic interaction , and multimedia systems . Key areas include 3D scene modeling using Gaussian splatting, diffusion models for storytelling and image generation, reinforcement learning for interactive instruction, and AI applications in healthcare, agriculture, and urban planning. The work emphasizes robustness, real-time feedback, and human-centered design. The recent publications demonstrate a strong trend in deep learning applied to vision and multimodal systems , with increasing focus on interactive AI , embodied environments , and domain adaptation . Topics such as differentiable trajectory optimization, backdoor attacks in compression models, and context-aware assistance systems reflect both technical depth and societal relevance. Wang Yufei has not been mentioned in relation to any scientific awards in the provided text. No information is available regarding student advising or research grants. However, the breadth and volume of publications suggest active research leadership and likely involvement in funded projects. Research is conducted in collaboration with teams at Xiamen University, particularly within the Institute of Artificial Intelligence and the Center for Digital Media Computing, focusing on intelligent multimedia and robotic systems. The integration of AI with cultural and educational applications, such as piano instruction and heritage preservation, highlights a unique interdisciplinary lab environment.

Franz Christopher Kunzeمشاهده پروفایل

پژوهشگر

• Industrial Automation
• Alarm Management Systems
• Causal Analysis
• +۳ مورد دیگر

Franz Christopher Kunze is a Researcher at the Department of Automation Technology, Faculty of Electrical Engineering and Information Technology, Ruhr-Universität Bochum. His work focuses on developing advanced alarm management systems for industrial processes using causal directed graphs and machine learning techniques. He collaborates with TU Munich on the DFG-funded CausAlITI project, aiming to improve root-cause analysis during industrial alarm floods. Research interests include causal analysis of alarm patterns, adaptive system modeling, and operator-centric visualization. He teaches courses like Process Automation and Programming for ETIT/ITE students, and supervises bachelor's theses in alarm system development. His publications (2023–2025) address alarm flood dynamics, causal graph applications, and automated model generation using LLMs. Current work emphasizes real-time alarm processing and uncertainty management in industrial systems.

Tobias Guggemosمشاهده پروفایل

استاد

• Controlling in digital business models
• Customer value analyses
• Cost accounting in service companies

Prof. Dr. Tobias Guggemos is a Professor of General Business Administration, specializing in Internal Accounting, at Fulda University of Applied Sciences since 2021. His academic career spans roles as an external lecturer at multiple universities (2016–present) and a research assistant at the Technical University of Dortmund (2010–2014). He earned his doctorate in 2014 with a dissertation on 'Customer Success Calculations as an Instrument of Customer Value Analysis in the Industrial Goods Sector.' Teaching Areas: Management Accounting, Controlling, Business Analytics Academic Affiliation: Fulda University of Applied Sciences; previously associated with Technical University of Dortmund and Steinbeis Network His research focuses on Controlling in digital business models , Customer value analyses , and Cost accounting in service companies . Recent publications highlight the intersection of Controlling and Data Science, digital transformation in corporate governance (e.g., CSRD implementation), and sustainability assessment using decision-theoretic models like the Analytic Hierarchy Process. His work bridges theoretical frameworks with practical applications in industries such as logistics (Deutsche Post DHL) and consulting (KPMG, PwC). Key trends in his publications include: Empirical analysis of data science integration in Controlling Challenges in regulatory compliance (CSRD) and business process adaptation Quantitative methods for sustainability and customer value optimization In his professional career (2014–2021), he held roles such as Head of Finance Master Data at Deutsche Post DHL Group and project manager in the Steinbeis Network, focusing on automated reporting and consulting. His CV reflects strong ties between academic research and industry practice. He can be contacted at tobias.guggemos@w.hs-fulda.de and is based in Room 33, Building 23, Leipziger Straße 123, Fulda, Germany.