جست‌وجوی استاد و پژوهشگر

Zhanli Sunمشاهده پروفایل

پژوهشگر

• Land System Change
• Agent-Based Modeling
• Bayesian Network
• +۴ مورد دیگر

Dr. Zhanli Sun is a Researcher at the Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO), specializing in the Structural Development of Farms and Rural Areas. He holds a PhD in Geography from the Chinese Academy of Sciences (1999) and has expertise in land system change analysis using advanced modeling techniques like agent-based modeling and Bayesian networks. His role also includes coordinating the China International Research Group and serving as Ombudsperson for Good Scientific Practice. Education: PhD in Geography (Chinese Academy of Sciences, 1999) Affiliations: Land Systems Group, China International Research Group Key Projects: CROSSGRASS, German-Sino Agricultural Center (DCZ), KULUNDA Research Interests: Dr. Sun's work focuses on modeling land-use dynamics, integrating spatial analysis and socio-economic factors. His research spans topics such as climate change impacts on grasslands, policy implications of land-use transitions in China and Argentina, and digital transformation in agriculture. He co-developed the LEAM land-use simulation model and has published extensively on agent-based modeling frameworks. Articles: Recent work includes studies on smallholder farming systems, mobile technology adoption in Rwanda, and efficiency analysis of China's crop production. His research emphasizes interdisciplinary approaches to address sustainability challenges in agrarian systems. Grants & Teaching: Leads international collaborative projects and teaches PhD courses annually. Active in policy-oriented research, including contributions to IAMO policy briefs on agricultural markets and digitalization in China. Labs/Teams: Core member of the Land Systems Group, contributing to IAMO's research on global land-use strategies and China's agricultural development.

Federico Furchمشاهده پروفایل

پژوهشگر

• Ultrafast Lasers
• Nonlinear Optics
• Attosecond Science
• +۴ مورد دیگر

Federico Furch is a Researcher at the Max Born Institute in Berlin, Germany, where he serves as Coordinator for Project 4.1 and contributes to Projects 1.2, 2.1, and 4.1. His work focuses on ultrafast laser development for advanced applications, including attosecond pump-probe spectroscopy, strong field physics, and material processing. Current role: Staff Scientist (since 2015) Previous positions: Postdoctoral researcher at MBI (2011-2015) and FOM-AMOLF (2010-2011) Education: PhD in Physics (2010, Colorado State University) and Licenciate degree in Physics (2004, University of Buenos Aires) His research emphasizes high-repetition-rate, high-average-power optical parametric chirped pulse amplifiers (OPCPAs) at 800 nm, capable of delivering sub-4 fs pulses with controlled carrier-envelope phase (CEP) and energies up to 190 µJ. He also explores nonlinear techniques for single-cycle pulse compression and high-order harmonic generation in extreme ultraviolet wavelengths. Recent publications highlight his expertise in few-cycle laser systems, surface waveguide fabrication, and attosecond pulse characterization. Articles span 2025 to 2020, covering topics such as Refractive index sensing , Pulse compression , and Optical vortices , with keywords like Optics, Photonics, and Nonlinear Optics. Scientific award: OSA Ambassador 2018 for global inclusivity efforts in optics Patent: US 9,209,598 B1 for a cooling system in high-average-power lasers His research has produced innovations in laser technology, with applications in attosecond science and advanced material processing. Collaborations include institutions in Germany, the Netherlands, and the USA, reflecting an international scientific network.

Danial Hamedi Jamaliمشاهده پروفایل

پژوهشگر

• Hydrogen Infrastructure
• Renewable Energy Systems
• MINLP Optimization
• +۳ مورد دیگر

Danial Hamedi Jamali is a doctoral researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany, affiliated with the Process Systems Engineering group under Prof. Kai Sundmacher. He holds an M.Sc. from the University of Tehran and was awarded scholarships for his bachelor’s and master’s studies, along with the Dean’s Scholarship from the University of Saskatchewan. His research focuses on topology optimization of pipeline networks using mixed-integer nonlinear programming (MINLP), with recent emphasis on hydrogen infrastructure design and retrofitting of natural gas grids. His expertise spans MINLP optimization, energy-exergy analysis, and sustainable system design. He has authored over ten peer-reviewed publications (over 1,000 citations) and serves as a reviewer for Elsevier and Springer journals. Collaborations include international research teams addressing renewable energy systems and low-temperature solar technologies. Research highlights include work on hydrogen pipeline networks, biogas utilization frameworks, and solar-based multi-generation systems. Awards include scholarships for academic excellence and the prestigious Dean’s Scholarship. His contributions bridge theoretical optimization with practical applications in energy transition and infrastructure sustainability.

Frank Karglمشاهده پروفایل

استاد

• Network Security
• Vehicular Ad-Hoc Networks
• Embedded Systems Security
• +۵ مورد دیگر

Prof. Frank Kargl is a full professor and director of the Institute for Distributed Systems at the University of Ulm. He holds a PhD (2003) and habilitation (2009) from Ulm University. Previously, he was an Associate Professor at the University of Twente (Netherlands, 2009–2012) and later an adjunct professor. He has served as vice dean (2013–2016) and dean (2016–2018) of the Faculty of Engineering, Computer Science, and Psychology. His research focuses on network security, vehicular ad-hoc networks, embedded systems, and blockchain privacy. He is a member of ACM, IEEE, and GI. Research interests include mobile/self-organizing networks (e.g., VANETs), security/privacy in IT systems, secure cloud computing, and crypto-currencies. Key projects intersect vehicular networks with privacy/security, embedded system security, and distributed computing frameworks. Publications span network security, zero-trust architectures, automotive cybersecurity, and privacy-preserving systems. Notable contributions include VeReMi datasets for VANET misbehavior detection and frameworks like ZTSFC for secure service chaining. Prof. Kargl chairs the GUC committee at Ulm University and serves on the KIZ committee. His work bridges academic research with real-world applications in automotive systems, IoT, and decentralized technologies.

• Reinforcement Learning
• Robotics
• Artificial Intelligence
• +۳ مورد دیگر

George Dimitri Konidaris is a Professor at Brown University in Providence, RI, USA, specializing in artificial intelligence and robotics. His research focuses on developing advanced algorithms for reinforcement learning, robotic planning, and hierarchical skill acquisition. He leads investigations into model-based reinforcement learning, temporal abstraction, and human-robot interaction frameworks. Konidaris's research bridges fundamental machine learning concepts with applied robotics. Key interests include: Hierarchical reinforcement learning for complex decision-making Robotic skill transfer and generalization Language-guided agent learning Continuous control in high-dimensional spaces Uncertainty-aware planning systems His publications demonstrate consistent focus on reinforcement learning theory applied to robotic systems, with recent emphasis on language integration and hierarchical abstraction. Work frequently appears in premier venues including ICML, NeurIPS, ICRA, and IROS.

• High Performance Computing
• Parallel Computing
• Computer Architecture
• +۳ مورد دیگر

Wolfgang E. Nagel is a Professor of Computer Science and Director of the Center for Information Services and High-Performance Computing (ZIH) at Technische Universität Dresden. Since 2001, he has held the Chair for Computer Architecture, leading research in parallel computing and high-performance systems. Previously, he served as Dean of the Computer Science Department (2006–2009) and Director of the High-Performance Computing Center (ZHR) at TU Dresden (1997–2005). His professional experience includes roles at the Research Center Jülich and the California Institute of Technology (CACR). Education : 1985: Diplom-Informatics in Computer Science, RWTH Aachen 1993: Dr. rer. nat. in Computer Science, RWTH Aachen Research Focus : Nagel’s work centers on high-performance computing (HPC), parallel system architectures, and performance analysis tools like VAMPIR. He has contributed to exascale computing roadmaps, cache architecture studies, and scalable application development frameworks. His interdisciplinary projects span computational biology (e.g., endocytosis modeling) and physics simulations. Leadership Roles : Chair of Gauss-Allianz e.V. (since 2008) Member of DFG Commission for Computer Infrastructure (2005–2012) Advisory Board roles for HLRS Stuttgart and FIZ Karlsruhe Grants & Collaboration : His leadership in ZIH and ZHR has driven infrastructure development for German HPC networks. He coordinates national and international initiatives in computational infrastructure and education. Labs/Teams : Directs ZIH, a central hub for Dresden’s HPC services, supporting research across engineering and natural sciences.

• Materials Science
• Physics
• Alloy Design
• +۳ مورد دیگر

Achim Kuhl is a Researcher at the Max Planck Institute for Sustainable Materials, located at Max-Planck-Straße 1, 40237 Düsseldorf, Nordrhein-Westfalen, Germany. He is affiliated with the Department of Microstructure Physics and Alloy Design , contributing to the Theory and Simulation group within the institute. His work integrates computational and theoretical methods to advance sustainable materials science. His research interests focus on materials science , physics , and alloy design , with a specific emphasis on microstructure analysis and predictive modeling. He explores how theoretical frameworks and simulation tools can optimize material properties for environmental sustainability and industrial applications. Achim Kuhl actively participates in the Institute's Doctoral Program and Alumni Network , reflecting his commitment to fostering the next generation of researchers. No grants or specific advisees are listed in the provided information, but his involvement highlights collaborative mentorship roles. His research environment emphasizes interdisciplinary teams within the Department and Simulation Group, driving innovation in computational materials engineering.

Chinmay Datarمشاهده پروفایل

پژوهشگر

• Scientific Computing
• Deep Learning
• Partial Differential Equations
• +۳ مورد دیگر

Chinmay Datar is a doctoral candidate at the Technical University of Munich (TUM), affiliated with the Institute of Advanced Study (IAS) in the focus group 'Scientific Machine Learning.' He holds an M.Sc. in Computational Engineering from Friedrich-Alexander University (FAU), Erlangen, and a Bachelor's in Mechanical Engineering from the University of Pune. His research focuses on integrating classical scientific computing methods with deep learning to solve Partial Differential Equations (PDEs). Teaching Responsibilities include: Summer Semester 2025: Seminar on High-Dimensional Methods for Scientific Computing and Lab Course on Machine Learning in Crowd Modeling/Simulation Winter Semester 2024/25: Courses on Scientific Computing & Machine Learning and a Seminar on Ethics in Science Research Interests: Novel neural architectures for dynamical systems simulation Backpropagation-free training of neural PDE solvers Domain decomposition combined with neural networks for PDE solutions Student Supervision: Ongoing: Eray Yildiz (Master's) and Ahmet Semiz (Master's) Completed: Rahma Atamert and Aditya Phopale (Master's) Recognition: FAU Graduation Scholarship (Japan internship support). Labs/Teams: Part of the Chair of Scientific Computing in Computer Science (SCCS), led by Prof. Hans-Joachim Bungartz.

Youness Dehbiمشاهده پروفایل

استاد

• Geoinformatics
• 3D City Modeling
• Remote Sensing
• +۷ مورد دیگر

Prof. Dr.-Ing. Youness Dehbi is a Professor for Computational Methods at HafenCity University Hamburg. His academic career includes roles as a postdoctoral researcher and scientific assistant at the University of Bonn's Institute of Geodesy and Geoinformation. He holds a Ph.D. in Computer Science from the University of Bonn (2016). His research focuses on geoinformatics, 3D city modeling, remote sensing, and applications in urban planning and disaster management. He has led projects such as VisioChick (enhancing animal welfare via mixed reality) and FPOplus (5G-based passenger flow management). Education: Ph.D. in Computer Science, University of Bonn (2016) M.Sc. and B.Sc. in Computer Science and Communication Research, University of Bonn (2008) Research Interests: Prof. Dehbi specializes in computational methods for spatial data analysis, including laser scanning, UAV missions, and semantic segmentation of historical maps. He explores applications in BIM, flood risk communication, and smart city technologies. His work bridges geoinformatics with urban sustainability and mixed reality. Awards: Best Paper Awards at multiple international conferences (2018–2024) Best Reviewer Award, ISPRS Congress (2021) Advising & Projects: He advises projects like NGCN (Next Generation City Networking) and collaborates with institutions like TU München and the University of Osnabrück. His team includes researchers like Dr. Son H. Nguyen and M.Sc. Lukas Arzoumanidis. Lab & Teams: His Computational Methods Lab at HCU develops tools for 3D city modeling and spatial data analysis, contributing to open-source geospatial software and collaboration with industry partners.

Berndt Zeitlerمشاهده پروفایل

استاد

• Building Acoustics
• Technical Acoustics
• Noise Control Engineering
• +۴ مورد دیگر

Prof. Dr.-Ing. Berndt Zeitler is a Professor of Building and Room Acoustics, and Technical Acoustics at HFT Stuttgart, serving as Deputy Director of the Institute for Applied Research (IAF) and head of the Acoustics Laboratory since 2015. He leads the Competence Center for Acoustic and Thermal Building Physics (ZFB) and chairs research initiatives on sustainable construction and urban acoustics. His expertise spans building acoustics, noise control in structures, and innovative materials like CFRP-reinforced concrete. He holds a Magna Cum Laude doctorate in Acoustics from TU Berlin and has held roles at NRC Canada and Rolls-Royce. His research focuses on acoustic insulation, vibration analysis, and smart city infrastructure. Academic Roles: Professor (HFT Stuttgart), Deputy IAF Director, Acoustics Lab Head Educational Background: TU Berlin (PhD Acoustics, 2005; Diplom Elektrotechnik, 1999) Research Focus: Prioritizes noise reduction in buildings, sustainable construction acoustics, and interdisciplinary projects like IMIAD (hemp acoustics) and Eco Box (multi-story sustainable construction). His work integrates acoustic modeling with materials science and urban planning, addressing challenges in low-frequency sound transmission and flanking noise. Projects: Leads initiatives such as Streetmoves4iCity (smart urban logistics) and InDeckLe (clay composite ceilings). Collaborates on acoustic sensor networks for urban noise mapping and UAV-based wildlife monitoring. His research bridges theoretical acoustics with practical applications in building physics. Academic Contributions: Serves as a reviewer for Acta Acoustica , Journal of the Acoustical Society of America , and others. Active in HFT Senate (2019–present) and policy formulation for building codes, particularly in Canada and Germany.

David Spielerمشاهده پروفایل

استاد

• Machine Learning
• Stochastic Systems
• Biochemical Systems Modeling
• +۳ مورد دیگر

David Spieler is a Professor of Machine Learning at the University of Applied Sciences Munich since September 2018. Previously, he served as a product owner for big data topics at Audi AG (2015–2018), a system developer at Bosch SoftTec (2014–2015), and completed his PhD in Modeling and Simulation at Saarland University (2009–2014). His research focuses on stochastic systems, biochemical modeling, parameter estimation, and oscillatory behavior analysis in Markovian systems. He has contributed to numerical methods for steady-state analysis, formal verification techniques, and applications in systems biology. Research interests include stochastic hybrid systems, sensitivity analysis of biochemical networks, geometric bounds for CTMC steady-state distributions, and oscillatory dynamics in chemical reaction networks. He has published extensively on topics like model checking, parameter estimation, and algorithmic solutions for stochastic processes. His work bridges theoretical computer science with practical applications in bioinformatics and engineering. Spieler has taught courses on data networks, quantitative model checking, and stochastic simulation techniques. He has reviewed manuscripts for over 20 conferences including CAV, CMSB, HSCC, and QEST, contributing to the advancement of formal methods and computational systems biology.

Volha Petukhovaمشاهده پروفایل

پژوهشگر

• Computational Semantics
• Dialogue Theory
• Computational Pragmatics
• +۳ مورد دیگر

Volha Petukhova is a Researcher at Saarland University, specializing in computational semantics, dialogue theory, and cognitive modeling. She contributes to ISO standards for semantic annotation frameworks (ISO 24617-2 and -5). Her work focuses on dialogue acts, multimodal communication, and argumentation systems. She has led projects like DialogBank and participated in initiatives such as METALOGUE and DBOX. She teaches courses including Multimodal Dialogue Systems and Computational Pragmatics. Her research interests include dialogue management, belief-intention representation, and context-based reasoning. She has published extensively on topics like metacognitive event classification, argument quality assessment, and negotiation strategies. Her recent projects involve personalized health intervention messages and customer-oriented dialogue analysis. She has advised numerous students on topics like negotiation outcome prediction, argument generation, and multimodal depression detection. She collaborates on creating annotated dialogue corpora, such as the DBOX and Metalogue Debate Trainee Corpus. Her work bridges theoretical dialogue semantics with practical applications in healthcare and education.

Andreas Lübkeمشاهده پروفایل

استاد

• Electronics
• Mechatronics
• Automotive Electronics
• +۵ مورد دیگر

Professor Andreas Lübke serves as Professor of Electronics for Mechatronic Systems at the Faculty of Engineering and Computer Science, Osnabrück University of Applied Sciences since February 2010. With a Doctorate in Engineering from TU Dresden and extensive industry experience at Volkswagen AG, he brings significant practical expertise to his academic role. His educational background includes studies in Electrical Engineering at the University of Hannover (1987-1994) followed by doctoral research at TU Dresden (1995-1999) focused on "Optimization of Vehicle Electrical Network Architecture using Genetic Algorithms." Prior to joining academia, he spent 15 years (1995-2010) conducting electronics research at Volkswagen AG in Wolfsburg. Professor Lübke's research focuses on vehicle communication systems, particularly Car-to-X technology and VANETs (Vehicular Ad-hoc Networks). His work addresses critical challenges in automotive networking, including safety applications, traffic information systems, and infrastructure integration. He has developed a comprehensive CAN laboratory network used for both teaching and research purposes, supporting distributed applications across multiple hardware platforms. His teaching portfolio includes core courses in Electronics for Mechatronics, Analog Electronics, Digital Technology, Industrial Bus Systems, and Automotive Electrical and Electronic Systems. He emphasizes practical experimentation with tools like CANoe, MATLAB/Simulink, and VHDL, preparing students for real-world engineering challenges in automotive electronics. Professor Lübke has contributed significantly to the field through multiple conference presentations between 2008-2009, primarily focusing on vehicle communication systems and network architectures. His publications reflect strong industry-academic collaboration, particularly through the Network on Wheels (NoW) project.

Noomane Ben Khalifaمشاهده پروفایل

استاد

• Sustainable Manufacturing
• Metal Forming Technologies
• Additive Manufacturing
• +۴ مورد دیگر

Prof. Dr.-Ing. Noomane Ben Khalifa is a Professor of Manufacturing – Innovative Manufacturing and Head of the Institute for Production Technology and Systems (IPTS) at Leuphana University. He concurrently leads the Institute for Material and Process Design at Helmholtz Center Hereon. His work focuses on sustainable manufacturing processes, particularly extrusion, sheet metal forming, and additive manufacturing, emphasizing eco-friendly production across material value chains. Education: Awarded a Doctorate in Engineering from TU Dortmund University (2012) with distinction for research on helical profile extrusion. Holds a Mechanical Engineering degree from TU Dortmund (2005), specializing in production engineering and forming technology. Research Interests: Sustainable manufacturing processes; material recycling (e.g., aluminum chips); lightweight material development; composite extrusion; die design optimization; and process simulation. His work bridges advanced manufacturing with environmental impact reduction, leveraging AI and machine learning for material-property modeling. Key Article Trends: Recent studies emphasize machine learning applications in materials science, die design for magnesium alloys, and sustainable recycling processes. His work spans from fundamental material behavior analysis to industrial process optimization. 2025: Focus on AI-driven texture-property modeling in Mg alloys and dieless wire drawing improvements 2024: LCA of aluminum recycling and deep-drawing process reliability Awards: 2009 ISPF Award for extrusion research; 2014 ZukunftErfindenNRW for innovative extrusion press design; invited keynote speaker at ICIT & MPT 2014. Advising & Grants: Oversees OPTUM-MAGNA (magnesium nanocomposites), FERNAPRO (sustainable manufacturing tech), and projects like TrICo (innovation cooperation). Collaborates with industry on tool design and eco-processes. Labs & Teams: Leads IPTS and co-leads Helmholtz material design institute. Supervises interdisciplinary teams focusing on compound casting, incremental forming, and smart manufacturing systems.

Jens Hegerمشاهده پروفایل

استاد

• Manufacturing Engineering
• Production Technology
• Simulation
• +۵ مورد دیگر

Jens Heger is a Professor of Engineering specializing in Modeling and Simulation of Technical Systems and Processes at Leuphana University Lüneburg, Germany. He is affiliated with the Institute for Production Technology and Systems (IPTS) and the Research Center for Digital Transformation. His academic career spans over a decade of research and teaching in production engineering, manufacturing systems, and simulation technologies. Dr. Heger completed his Master of Science in Computer Science with a minor in Business Studies at the University of Paderborn (1999-2006). He then earned his doctorate degree at the University of Bremen in the Department of Production Engineering. His dissertation focused on "Dynamic selection of rules for sequence planning in workshop and flexible flow production" under the supervision of Prof. Scholz-Reiter and Prof. Jürgen Branke from the University of Warwick, UK. Professor Heger's research interests center around the intersection of manufacturing engineering, simulation, and artificial intelligence. His work demonstrates a strong focus on applying advanced computational methods to solve complex production challenges. Key research areas include: Manufacturing process optimization through simulation and modeling Application of machine learning and reinforcement learning in production scheduling Development of intelligent control systems for manufacturing processes Energy efficiency and sustainability in production systems Quality control and prediction in sheet metal forming processes Integration of AI technologies in traditional manufacturing environments Analysis of Professor Heger's recent publications reveals a clear trajectory toward increasingly sophisticated applications of artificial intelligence in manufacturing. His work has evolved from traditional simulation and optimization techniques toward integrating deep learning, reinforcement learning, and computer vision technologies into production systems. A significant portion of his research focuses on dynamic scheduling and optimization problems, particularly using reinforcement learning approaches to address complex manufacturing challenges. His publications also demonstrate a growing interest in sustainable manufacturing practices, energy efficiency, and quality control applications through AI technologies. Professor Heger has contributed significantly to the field through numerous publications in manufacturing engineering, production systems, and AI applications. His work spans both theoretical advancements in scheduling algorithms and practical implementations in industrial settings, particularly focusing on small and medium enterprises.