جست‌وجوی استاد و پژوهشگر

Dirk Roosمشاهده پروفایل

استاد

• Machine Learning
• Robust Design Optimization
• Stochastic Analysis
• +۱۰ مورد دیگر

Prof. Dr.-Ing. Dirk Roos is a Professor for Computersimulation und Design Optimization at the Department of Mechanical Engineering and Process Engineering, Niederrhein University of Applied Sciences, where he has served since March 2011. He is also the Head of the Institute for Modeling and High Performance Computing (IMH) since December 2016. His academic career includes previous positions as Head of Robust Design Optimization at DYNARDO Dynamic Software and Engineering GmbH (2002-2011) and Technical Solutions Specialist at CADFEM GmbH (2000-2008). Prof. Roos specializes in machine learning, robust design optimization, stochastic analysis, and probabilistic modeling for virtual product development. His research focuses on developing mathematical methods for stochastic structural and fluid simulation, robustness and reliability analysis, multidisciplinary optimization, and software development for complex system development. He has established strong collaborations with academic institutions including RWTH Aachen, Ruhr-Universität Bochum, and industrial partners like Siemens AG and Robert Bosch GmbH. His recent work explores Probabilistic Intelligence, cyber-physical systems, digital twins, and Big Data Analysis, with applications spanning power plant flexibility, renewable energy, turbomachinery, automotive, aerospace, and medical technology. Prof. Roos has successfully secured numerous third-party funded research projects totaling over 1.8 million euros, including collaborations with Siemens AG, Robert Bosch GmbH, and various universities. optiSLang Award 2012 Weimar Optimization and Stochastic Days Gutachter BMBF im Programm FH-Kooperativ since 2019 Mitglied des Scientific Committee International Probabilistic Workshop since 2017 Mitgliedschaft im Graduierteninstitut für angewandte Forschung der Fachhochschule in NRW since 2017 Prof. Roos supervises multiple doctoral students and has successfully completed several cooperative PhD projects. His current research projects include AI-driven optimization for medical care, reinforcement learning for emergency room planning, and machine learning algorithms for power plant component lifetime prediction. The Institute for Modeling and High Performance Computing (IMH) under his leadership develops mathematical methods and software competence in machine learning and CAE-based robust design optimization for virtual product development.

Masud Rahmanمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence for Software Engineering (AI4SE)
• Software Maintenance and Evolution
• +۱۱ مورد دیگر

Masud Rahman is an Associate Professor in the Faculty of Computer Science at Dalhousie University, Canada, where he leads the RAISE Lab. Previously a tenure-track Assistant Professor, he completed his Ph.D. in Computer Science/Software Engineering from the University of Saskatchewan and a postdoctoral fellowship at Polytechnique Montreal. His academic career demonstrates strong progression with significant research impact in software engineering. Faculty of Computer Science, Dalhousie University (Current) University of Saskatchewan (Ph.D. studies) Polytechnique Montreal (Postdoctoral research) Dr. Rahman's research focuses on the intelligent automation of software maintenance and evolution, particularly targeting software debugging, code search, and code reviews. His work strategically combines Software Engineering with Artificial Intelligence techniques including Machine/Deep Learning, Information Retrieval, Mining Software Repositories, and Natural Language Processing. His industry experience as a professional developer for three years significantly shaped his research direction toward solving practical software maintenance challenges that cost the global economy billions annually. His research program addresses critical problems in software bug detection, diagnosis, explanation, and reproduction, with increasing focus on AI-powered and simulation modeling software. His publications demonstrate consistent output in top-tier venues including 7 papers at ICSE (A*), 3 at FSE (A*), 3 at ASE (A*), 8 at EMSE (A), 6 at ICSME (A), and 9 at MSR (A). The research trends show increasing focus on deep learning applications for software engineering problems, with particular attention to code search, bug localization, and debugging automation. His work has evolved from traditional information retrieval approaches to incorporate advanced neural network techniques and generative AI. Governor General's Gold Medal 2019 U of S Doctoral Thesis Award 2019 CS Best PhD Thesis Award 2019 TCSE Distinguished Paper Award Most Influential Paper Award Dr Keith Geddes Award Dalhousie Belong Research Fellowship President's Gold Medal (Bangladesh) Dr. Rahman has secured $500K+ in competitive research funding as Principal Investigator, including an NSERC Discovery Grant, Mitacs Accelerate International, and Climate Action and Awareness Fund. He actively collaborates with industry partners including Metabob Inc., Mozilla Firefox, and Vendasta Technologies. His service to the community includes extensive program committee work for major conferences and journal reviewing. He leads the RAISE Lab, which focuses on developing AI-powered solutions for software maintenance challenges, with current projects emphasizing sustainable software innovation and sustainable AI as part of Dalhousie's strategic goals.

• Renewable Energies
• Heat Transfer
• Thermodynamics
• +۵ مورد دیگر

Professor Thomas Lex serves as Professor for Renewable Energies and Heat Transfer at Ostbayerische Technische Hochschule Regensburg (OTH Regensburg) within the Faculty of Mechanical Engineering. Currently on sabbatical, he maintains his position as Vice Dean of the Faculty of Mechanical Engineering. His expertise spans renewable energy systems, thermal engineering, and fluid dynamics. Professor Lex directs the Energy Technology Laboratory and Laboratory Power - Heat - Cold, focusing on practical applications of energy conversion and thermal systems. His research interests include thermo-fluid dynamics of energy systems and simulation of process engineering. With extensive industry experience prior to academia, Professor Lex has contributed to major international LNG projects across Norway, Australia, Russia, and other global locations. His background bridges theoretical knowledge with industrial application in energy engineering. He earned his doctorate from Technical University of Munich in 2004 with research on fluid dynamics of gas-liquid mixtures in ball valves, establishing his foundation in complex thermal-fluid systems. Professor Lex teaches courses in renewable energies, thermodynamics, refrigeration technology, and simulation of energy processes. He supervises bachelor's and master's theses in these specialized areas through the LaboRe energy technology laboratory.

Nira Libermanمشاهده پروفایل

استاد

• Psychological Distance
• Construal Level Theory
• Decision Making
• +۷ مورد دیگر

Nira Liberman is a Professor of Social Psychology at Tel Aviv University, where she has been a faculty member since 2001. She completed all her formal education at Tel Aviv University, earning her Bachelor's degree in Psychology and Comparative Literature, Master's degree in Social Psychology, and PhD in 1997. She also completed postdoctoral work at Columbia University and taught at Indiana University, Bloomington before returning to Tel Aviv University. Professor Liberman's research focuses on psychological distance and its effects on decision making, evaluation, motivation, and mental representation. She is particularly known for her work on Construal Level Theory (CLT), which examines how psychological distance influences cognitive processing. Her research also extends to Obsessive-Compulsive Disorder (OCD), where she developed the Seeking Proxies for Internal States (SPIS) model, as well as to essentialism, disgust, and conservatism. Her Social Psychology Lab investigates how people mentally traverse beyond the immediate 'here and now' to consider future and past time, distant locations, other people, and hypothetical (counterfactual) events. The lab examines what enables such expansion of mental scope and the consequences of this expansion, including how psychological distancing affects cognitive performance, working memory, and decision making. Professor Liberman's publication record shows consistent productivity across multiple domains of psychology. Her recent work continues to explore the intersection of Construal Level Theory with OCD mechanisms, moral judgment, and cognitive performance. Her research demonstrates strong theoretical integration across social, cognitive, and clinical psychology domains, with particular attention to the embodied and neural correlates of abstract thinking. Professor Liberman has established productive collaborations with researchers worldwide, most notably with Yaacov Trope with whom she has co-authored numerous foundational papers on Construal Level Theory. Her work has been published in top-tier psychology journals including Journal of Personality and Social Psychology, Psychological Review, and Journal of Experimental Psychology. Her lab continues to investigate fundamental questions about how people navigate between proximal and distal concerns, how abstraction enables traversing psychological distance, and how these processes relate to clinical phenomena like OCD. Professor Liberman's research program represents a sophisticated integration of basic cognitive processes with real-world applications in clinical and social domains.

Gregor Schellenbergerمشاهده پروفایل

استاد

• Maritime Engineering
• Shipbuilding
• Autonomous Systems
• +۳ مورد دیگر

Prof. Gregor Schellenberger serves as a Professor at Bremen University of Applied Sciences, affiliated with Faculty 5, Department 2. His research drives innovation in maritime technology through practical engineering solutions for autonomous shipping and sustainable marine transportation systems. His expertise spans Maritime Engineering, Shipbuilding, and Autonomous Systems with specialized focus on Virtual Reality Applications and Additive Manufacturing. Current projects include developing scale-model autonomous ferries, VR-based ship inspection systems, and hydrofoil optimization for human-powered vessels - demonstrating applied research bridging theoretical principles with real-world maritime challenges. Secured research funding covers multiple high-impact projects through 2026 including wind-force analysis tools for cruise ships, 3D-printing integration in shipbuilding, and holistic lifecycle optimization of vessel design. These grants reflect strong industry collaboration and practical relevance to modern maritime operations while supporting hands-on teaching applications like ship handling simulators.

Uwe Reinertمشاهده پروفایل

استاد

• Finite Element Method
• Material Science
• Structural Analysis
• +۳ مورد دیگر

Uwe Reinert is a Professor at Bremen University of Applied Sciences in Faculty 5, Department 1, based at Neustadtswall 30, 28199 Bremen (room M, 218b). He maintains active office hours by appointment and can be contacted via phone (+49 421 5905 2553) or fax (+49 421 5905 3578). His research centers on Finite Element Method (FEM) simulations for material behavior, spanning linear analyses (e.g., component strength verification), nonlinear processes (e.g., sheet metal bending), plastic molding (e.g., injection molding), and fiber composite modeling (e.g., laminates). This work directly informs industrial applications in structural safety, damage analysis of metals/ceramics/plastics, and nonlinear geometry/material behavior. Professor Reinert has led significant technical projects including the "Energy-efficient solar-powered parking system" feasibility study (2017–2018), "BioBike" for bicycle frame optimization (2017–2018), and development of an electrically operated 4-jaw clamping system (e4-BAS) for machining (2014–2018). His services include regulatory-compliant structural verifications, FEM calculations, and damage diagnostics for industrial components.

Roustiam Chakirovمشاهده پروفایل

استاد

• Control Engineering
• Electromobility
• Mechatronic Vehicle Systems
• +۴ مورد دیگر

Professor Roustiam Chakirov serves as a faculty member in the Department of Engineering and Communication at Bonn-Rhein-Sieg University of Applied Sciences (H-BRS), specializing in control engineering for automotive systems. His work bridges theoretical research and industrial applications in sustainable mobility and energy systems. Education: Doctorate in Electrical Drives/Control Engineering, Nizhny Novgorod University of Technology, Russia Studies in Automation Engineering Research Focus: Chakirov's work centers on electromobility , mechatronic vehicle systems , and renewable energy integration . His expertise spans rapid control prototyping , neural networks for photovoltaic systems , and energy efficiency optimization through adaptive control. Current projects address vehicle electrical system management, wind-to-heat conversion, and smart microgrid integration for electric vehicles. Publication Trends: His 2006-2015 publications reveal a consistent trajectory from foundational control theory toward applied sustainable mobility solutions. Key themes include photovoltaic optimization (2015), multi-bus vehicle power management (2014), and electric vehicle charging coordination (2013), demonstrating interdisciplinary convergence of control engineering, renewable energy, and automotive systems. Scientific Recognition: Honorary Doctorate from Chernihiv National University of Technology (2016) for German-Ukrainian research cooperation in Renewable Energies and Electromobility Research Leadership: Chakirov directs third-party funded projects including the TREE-Energy Lab (TRE³L) partnership with GKN Driveline and GKN Sinter Metals. His work receives support from the German Academic Exchange Service and involves Horizon 2020 collaborations, focusing on hydrogen technology, powder metallurgy, and eco-mobility solutions. Laboratory Infrastructure: He operates within H-BRS's TREE-Energy Lab complex comprising Powder Fabrication-Lab, Mobility-Lab, Hydrogen-Lab, and Simulation-Lab, enabling integrated research from component design to system-level energy management.

Jens Geislerمشاهده پروفایل

استاد

• Control Engineering
• Modeling and Simulation
• Wind Turbine Control
• +۳ مورد دیگر

Prof. Dr. Jens Geisler serves as Professor of Control Engineering, Modelling and Simulation at Flensburg University of Applied Sciences' Department of Energy and Biotechnology since March 2020. His career bridges academic research and industrial wind energy applications with expertise in multivariable control systems and dynamic modeling. His educational background includes: Dipl.-Ing. (FH) in Mechanical Engineering and Computer Science from Osnabrück University of Applied Sciences M.Sc. in Mechatronic Systems Engineering from Osnabrück University of Applied Sciences Geisler's research spans advanced control methodologies for renewable energy systems, specializing in wind turbine grid integration and elastic multibody dynamics . Core competencies include optimal control algorithms, real-time numerical simulation, and microcontroller implementation for industrial applications, with significant contributions to self-optimizing mechanical systems and rail vehicle guidance technologies. His 2022-2025 publications reveal a strategic research trajectory toward AI-enhanced state estimation and automated observer design, emphasizing practical validation with real-world measurements while simplifying complex aerodynamic models for control engineering applications in wind energy systems. No scientific awards were documented in the provided sources. Teaching responsibilities encompass Energy Sciences, Mechanical Engineering, and System Technology programs, with industry-focused curriculum development. No student advisement or grant information was disclosed in available materials. Geisler maintains active research collaborations through projects including the SFB614 'Self-optimising systems in mechanical engineering' and the RailCab initiative, alongside extensive industry experience developing grid-support control systems for wind turbines at Senvion GmbH and DEIF Wind Power.

Laurence Alhrshyمشاهده پروفایل

مدرس

• Wind Energy Engineering
• Wind Turbine Technology
• Flywheel Systems
• +۴ مورد دیگر

Laurence Alhrshy is a Lecturer at Flensburg University of Applied Sciences working in the School of Energy and Life Science with a focus on the Wind Energy Technology Institute (WETI). Alhrshy serves as a scientific employee for the Flywheel research project, focusing on resource efficiency in wind energy systems. Alhrshy's research interests include: Wind Energy Engineering Wind Turbine Technology Flywheel Systems for wind turbines Resource Efficiency in wind energy systems CO2 Footprint Reduction in wind turbine manufacturing Wind Turbine Structural Dynamics Hydraulic-Pneumatic Systems for energy applications Alhrshy's research focuses on innovative approaches to improve wind turbine efficiency through engineering solutions that reduce mechanical loads and environmental impact. The work primarily centers on integrating flywheel systems into wind turbine rotor blades to vary inertia, which enables better power production control and reduced component stress. This research has significant implications for reducing material requirements and the CO2 footprint of wind energy infrastructure. Alhrshy has developed expertise in adapting load simulation tools like OpenFAST to model these innovative systems. Key publications demonstrate a consistent research trajectory from material development (2019) through system integration (2020-2021) to resource efficiency analysis (2023-2025), reflecting a comprehensive approach to sustainable wind energy technology development. Alhrshy teaches in the Wind Energy Engineering program and collaborates with researchers including Prof. Dr. Clemens Jauch, Andreas Gagel, Alexander Lippke, Lennart Vogt, and Peter Kloft. Current research continues to focus on optimizing hydraulic-pneumatic flywheel systems for wind turbine applications with emphasis on achieving net CO2 savings through reduced material usage.

Ralf-Dieter Roglerمشاهده پروفایل

استاد

• Switchgear Technology
• High-Current Technology
• Electrical Safety
• +۵ مورد دیگر

Prof. Ralf-Dieter Rogler serves as Professor of Switchgear Technology at Dresden University of Applied Sciences' Faculty of Electrical Engineering. He teaches core courses including Switchgear Technology, High-Current Technology, Plant Protection, Low-Voltage Systems, Electrical Safety, and Power System Diagnostics, with active modules scheduled through summer semester 2026. His research spans critical power engineering domains: Switchgear testing under short-circuit/continuous operation (DC to 400 Hz) High-current validation (10 kA AC, 5 kA three-phase/DC) High-voltage/partial discharge testing (100 kV AC) Mechanical stress analysis of conductors/supports Infrared diagnostics and arc fault pressure modeling Transformer DGA and fuse/current transformer design Prof. Rogler leads research in Electrical Power Engineering and High-Current Technology laboratories, developing specialized software for thermal/pressure calculations. As a publicly appointed sworn expert, he contributes to EUKS compliance testing through measurement protocols and calibration standards. His recent publications focus on advancing electrical safety standards, switchgear reliability, and diagnostic methodologies for modern power systems.