جست‌وجوی استاد و پژوهشگر

• Ethics
• Bioethics
• Environmental Ethics
• +۵ مورد دیگر

Thomas Potthast is a full Professor for Ethics, History and Theory of Biosciences at the Faculty of Science, Department of Biology at the University of Tübingen. He serves as the Speaker of the International Center for Ethics in Sciences (IZEW) and has held this position since 2014. Since 2016, he has also been the Speaker of the Thematic Area on Sustainability, Protection and Management of Natural Resources within the Excellence Strategy's Platform 3 on Environmental Systems. His academic journey includes a habilitation at the University of Tübingen in 2010, where he received teaching authorization for Ethics, Theory and History of Sciences. Prior to this, he was a Feodor-Lynen Fellow of the Humboldt Foundation at the University of Wisconsin-Madison (2002-2001) and a Post-Doc Research Scholar at the Max Planck Institute for the History of Science in Berlin (1998). Potthast's research focuses on environmental ethics, bioethics, and the philosophical foundations of sustainability science. His work critically examines the relationship between scientific knowledge and ethical decision-making, particularly in the context of nature conservation, biodiversity, and technological interventions in ecological systems. He has made significant contributions to understanding epistemic-moral hybrids in environmental decision-making and the ethical dimensions of sustainability transformations. His recent publications reveal a strong emphasis on the ethical challenges of emerging technologies (including gene drives and affective computing) in relation to environmental sustainability, the role of universities in sustainability transformations, and transdisciplinary approaches to real-world sustainability challenges. His work consistently bridges theoretical ethics with practical applications in conservation and sustainability contexts. As an educator and mentor, Potthast has supervised numerous doctoral and master's students working on diverse topics spanning sustainable development education, animal ethics, nature conservation, and the ethical dimensions of technological interventions in natural systems. He leads the Competence Center for Sustainable Development, which is part of the Excellence Strategy since 2018, and has been instrumental in developing the whole-institution approach to sustainability at the University of Tübingen. His work connects academic research with practical implementation of sustainability principles across the university's operations, teaching, and research activities.

• Quantum Many-Body Systems
• Rydberg Atoms
• Quantum Simulation
• +۷ مورد دیگر

Prof. Dr. Igor Lesanovsky is a leading researcher in quantum physics at the University of Tübingen, where he heads the Arbeitsgruppe (Research Group) Lesanovsky within the Institute of Theoretical Physics, part of the Faculty of Mathematics and Natural Sciences. His research focuses on quantum many-body systems, particularly utilizing Rydberg atoms for quantum simulation, quantum information processing, and exploring non-equilibrium phenomena. His research interests span quantum many-body physics, Rydberg atom systems, quantum simulation techniques, non-equilibrium quantum dynamics, quantum thermodynamics, and quantum soft-matter physics. His group investigates how highly excited Rydberg atoms can be used to simulate complex quantum processes, study phase transitions, and develop applications for quantum information processing. They're particularly interested in emergent phenomena such as time-crystals, quantum glassiness, and non-ergodic behavior in quantum systems. The publication record shows a consistent stream of high-impact research, primarily in Physical Review Letters, Physical Review A, and other top physics journals. The research trends indicate a strong focus on quantum simulation with Rydberg systems, quantum non-equilibrium dynamics, quantum information applications, and increasingly on the intersection of quantum physics with machine learning. Recent work explores quantum neural networks, quantum measurement theory, and the application of large-deviation methods to quantum trajectory ensembles. Prof. Lesanovsky's research is supported by multiple prestigious projects including the BMBF Quantum Technology project 'Neural quantum networks on NISQ quantum computers', the DFG Excellence Cluster 'Machine Learning: New Perspectives for Science', DFG Research Units on long-range interacting quantum spin systems and quantum thermalization, the EU EIC Pathfinder Project 'Brisk Rydberg Ions for Scalable Quantum Processors', the QuantERA Project CoQuaDis, and The Center for Integrated Quantum Science and Technology (IQST). The group maintains strong connections with experimental teams, particularly in the areas of quantum simulation of interacting many-body systems and the development of matter wave interferometers and collectively enhanced electric field sensors. They collaborate extensively across Germany and internationally, with publications showing co-authorship with researchers from multiple institutions worldwide.

Ondrej Vaculinمشاهده پروفایل

استاد

• Passive Vehicle Safety
• Automated Driving
• Vehicle Dynamics
• +۳ مورد دیگر

Prof. Ondrej Vaculin, Ph.D., is a Professor at Technische Hochschule Ingolstadt (THI), specializing in passive vehicle safety, mechatronic systems, and automated driving. He joined THI in 2018 and previously held roles at TÜV SÜD Prague (2008–2018) as Vice President for Safety and Security in Automotive, and as a researcher at Czech Technical University (2005–2008) and DLR Oberpfaffenhofen (2000–2005). His research focuses on enhancing vehicle safety through advanced simulation, sensor integration, and machine learning applications. Education: Ph.D. in Mechanics of Solids, Deformable Bodies and Continua from Czech Technical University in Prague (2001), and a degree in Technical Cybernetics from the Faculty of Electrical Engineering at the same university (1991). His work bridges theoretical research and practical implementation, addressing challenges in automated driving systems, crash simulation, and human body diversity in safety design. Research interests include passive safety systems, autonomous vehicle dynamics, and infrastructure integration for safety enhancements. Recent publications emphasize collaborative smart infrastructure, sensor fusion for free space detection, and machine learning in crash detection. He actively contributes to FISITA, serving as a Council Delegate and member of technical committees. Awards/memberships: Active in FISITA, holding leadership roles in technical committees. No explicit awards listed, though his contributions to automotive safety standards are notable. Grants and advising: While no specific grants or students are detailed, his extensive industry and academic collaborations (e.g., IN2Lab testing field projects) highlight his role in applied research and development.

Insa Stamerمشاهده پروفایل

پژوهشگر

• Chemistry Education
• Science Education
• Teacher Professional Development
• +۴ مورد دیگر

Dr. Insa Stamer is a Researcher in the Department of Chemistry Didactics at the Leibniz Institute for Science and Mathematics Education in Kiel, Germany. Her work focuses on advancing chemistry education through interdisciplinary approaches, teacher professional development, and innovative educational methodologies. She is involved in projects like the KiFo Kiel Research Workshop and contributes to out-of-school learning initiatives. Her research interests include subject-specific learning in preschool and school settings, professional competence of teachers, science communication, and methodological advancements in education. She actively publishes in journals such as The European Physical Journal B and Natural Sciences in Education - Chemistry , addressing topics ranging from neurotronics education to nanotechnology safety. Dr. Stamer collaborates on projects like Authentic insights into science , exploring the use of scientific videos in informal learning environments. She also engages in methodological research involving machine learning applications in education. Her work bridges formal and informal learning contexts, emphasizing hands-on laboratory programs and intermedial science exploration.

Syed Ali Razaمشاهده پروفایل

پژوهشگر

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

Syed Ali Raza is a researcher affiliated with the University of Technology, Sydney (PhD 2018), with a former affiliation at the Institute of Business Administration, Karachi. His work focuses on reinforcement learning, robotics, and human-robot interaction. Key contributions include studies on social robots' question-answering services, human feedback integration in AI systems, and optimization of robotic movements in multi-agent scenarios. He has collaborated extensively with researchers like Mary-Anne Williams and Sajjad Haider. His research spans theoretical advancements in machine learning algorithms and practical applications in robotics competitions (e.g., RoboCup). Research interests emphasize computational reinforcement learning, reward shaping techniques, and ethical design of autonomous systems. Notable projects include privacy-first approaches for social robots and hybrid methods for humanoid robot locomotion. His work bridges theoretical AI advancements with real-world robotic implementations.

• Artificial Intelligence
• Computational Intelligence
• Neural Networks
• +۵ مورد دیگر

Lakhmi C. Jain is a distinguished academic affiliated with the University of South Australia. As a Professor, she has made significant contributions to the fields of Artificial Intelligence, Computational Intelligence, and Fuzzy Systems. Her research spans neural networks, decision support systems, robotics, and data analysis, with a focus on interdisciplinary applications. Her career includes over 445 publications, including books like Complex Networks in Software, Knowledge, and Social Systems (2019) and E-Learning Systems - Intelligent Techniques for Personalization (2017). She has held editorial roles in journals such as the International Journal of Intelligent Decision Technologies (IDT) and the Journal of Intelligent & Fuzzy Systems. Jain's work emphasizes practical applications of computational intelligence, including efforts in software development, biomedical signal processing, and multi-agent systems. She has collaborated extensively with researchers globally, contributing to advancements in AI-driven technologies and decision-making frameworks.

• Process Systems Engineering
• Chemical Engineering
• Energy Conversion Systems
• +۴ مورد دیگر

Prof. Kai Sundmacher is a Full Professor and Chair of Process Systems Engineering at Otto-von-Guericke University Magdeburg, and Director of the Max Planck Institute for Dynamics of Complex Technical Systems. His expertise spans model-based analysis of complex process systems, integrated chemical processes, energy conversion (fuel cells/electrolysis), and biosystems engineering. He holds a Dr.-Ing. habil. from Clausthal University of Technology and has held visiting positions at institutions worldwide. Research focuses include catalyst design for CO2 methanation, digital twins for power-to-X processes, and sustainable chemical production. Awards include the Arnold Eucken Prize (1999) and Carl Zerbe Prize (1998). He leads initiatives like the Max Planck Research Network for Synthetic Biology and chairs the German Chemical Energy Research group. Teaching covers advanced process systems engineering, fuel cell technology, and bioprocess design. Over 500 publications include 400 peer-reviewed articles, with contributions to journals like Chemical Engineering Science and Fuel Cells. Active in academic service, he reviews ERC grants, chairs selection committees, and advises the Alexander von Humboldt Foundation.

• Telecommunications
• 5G/6G Networks
• Network Slicing
• +۷ مورد دیگر

Christian Wietfeld is a Professor at TU Dortmund, Germany, specializing in telecommunications, 5G/6G networks, and robotics. His research focuses on network slicing, machine learning for communications, vehicular networks, and intelligent reflecting surfaces. Affiliations: TU Dortmund Key Collaborations: Stefan Böcker, Benjamin Sliwa, Manuel Patchou His work spans 6G multi-X communications, private industrial networks, and disaster response robotics. Recent projects include mmWave reflector systems, predictive uplink slicing, and AI-driven network planning. 2024-2025 publications highlight advancements in 6G IRS, energy-efficient 5G, and vehicular connectivity. Sub-fields include beam management, digital twins, and non-terrestrial networks. He contributes to experimental frameworks like Open RAN and ns-3 simulations, emphasizing scalable solutions for industrial and emergency applications.

• Smart Grids
• Energy Transition
• Cybersecurity in Energy Systems
• +۵ مورد دیگر

Prof. Andreas Ulbig is a Universitätsprofessor at RWTH Aachen University's Institute of Electric Installations and Networks, Digitization and Energy Economics (IAEW), situated in Aachen, Germany. His work focuses on advancing smart grid technologies, energy transition strategies, and cybersecurity in power systems. He is affiliated with the Department of Active Energy Distribution Networks within the Faculty of Electrical Engineering and Information Technology. Ulbig's research emphasizes resilient communication protocols, grid topology identification, multi-use energy storage systems, and electrification of transportation. His contributions include co-authoring studies on adaptive protection systems, local energy markets, and cyber-physical resilience frameworks. He leads projects addressing municipal energy system transformations and grid-friendly energy sharing concepts. Ulbig holds a doctoral degree (Dr.) and has extensive experience in energy infrastructure digitization and grid stability. His recent publications span 2023–2025, focusing on technical and economic aspects of energy systems, with particular attention to cyberattack simulations, distribution grid flexibility, and hydrogen integration in gas networks. Collaborations include IEEE conferences and institutions like Westenergie AG, where he contributed to studies on grid-forming converters. His research is methodologically diverse, combining machine learning, stochastic control, and experimental validation with industry partners. In academic service, Ulbig advises on energy policy implications and co-supervises research projects at IAEW. His work bridges theoretical advancements with practical grid solutions, addressing challenges such as curative distribution measures, tariff design for local markets, and infrastructure expansion costs. Key technical interests include broadband powerline communication, digital twin applications, and optimization of DC/AC grid integration.

• Protein Engineering
• Enzyme Engineering
• Biocatalysis
• +۳ مورد دیگر

Prof. Ulrich Schwaneberg serves as a University Professor at RWTH Aachen University's Faculty of Mathematics, Computer Science and Natural Sciences within the Institute of Biotechnology. His research group operates from the Biology Sammelbau facility (Worringerweg 3, Aachen) and maintains strong ties with the DWI - Leibniz Institute for Interactive Materials. His primary research focuses on protein engineering and biocatalysis , with significant contributions to plastic degradation technologies (particularly PET hydrolases), material-binding peptide development , and high-throughput screening methodologies . Key research thrusts include engineering enzymes for plastic recycling, developing anchor peptides for industrial applications, and creating novel biocatalytic systems for sustainable chemistry. Recent publications reveal a strong trend toward computational-guided enzyme design (using MD simulations and machine learning) combined with practical applications in environmental remediation . His team actively develops solutions for microplastic detection, phosphate recovery, and textile functionalization using biohybrid systems. The 2025 article portfolio demonstrates particular emphasis on PET degradation technologies and enzyme immobilization strategies. Prof. Schwaneberg leads the recently launched Materials Lab Incubator (MerLIn) funded with over 7 million euros from BAFA, and coordinates the Bio4MatPro competence center connecting industry partners with academic research. His group actively recruits Chinese students through CSC fellowships and organizes the annual Aachen Protein Engineering Summer School (AcES2) . The Schwaneberg group maintains state-of-the-art facilities for directed evolution, high-throughput screening, and biocatalytic process development, with strong industry partnerships focused on sustainable material innovations. Current initiatives include the development of flame-retardant textile coatings using biohybrid anchor peptides and scalable systems for plastic upcycling.

• Applied Econometrics
• Agricultural Land Markets
• Renewable Energy (Wind Energy)
• +۳ مورد دیگر

Dr. Matthias Ritter is a Senior Researcher at the University of Tübingen's Faculty of Economics and Social Sciences, holding a position at the Chair of Marketing. Previously, he served as an Associate Professor and Assistant Professor at Jönköping International Business School (Sweden) and held roles including Junior Professor of Quantitative Agricultural Economics at Humboldt University Berlin. He earned his PhD in Economics (Dr. rer. oec.) from Humboldt University Berlin in 2011, focusing on econometrics and economic statistics. Education: PhD in Economics, Humboldt University Berlin (2011) Postdoctoral Researcher, Technical University Berlin (2013) Diploma in Mathematics (university unspecified) Research Interests: Ritter’s work centers on applied econometrics, agricultural land markets, renewable energy (especially wind energy), and weather risk management. His research bridges economic theory with practical applications in climate change adaptation, land valuation, and energy policy. Recent studies include analyzing bargaining power in agricultural land markets and modeling wind energy potential in urban areas. Key Awards: Best Paper Award (GEWISOLA, 2021) Humboldt Award for Excellence in Teaching (2020 shortlist) Stifterverband Prize (2018) for land market research Finanzkompass Innovation Award (2013) for dissertation Teaching & Advising: Ritter teaches courses in data science, agricultural economics, and renewable energy economics. He has advised students in both bachelor’s and master’s thesis seminars but no named advisees are listed. His research has explored interdisciplinary topics such as wind turbine efficiency, climate modeling, and digital teaching strategies post-pandemic. Labs/Teams: Engaged with agricultural economics and energy policy research groups, focusing on collaborative projects involving land markets, renewable energy integration, and climate risk assessment.

• Event Cognition
• Human-Robot Interaction
• Visual Working Memory
• +۴ مورد دیگر

Frank Papenmeier is a Professor in the Department of Psychology at the University of Tübingen, within the Faculty of Science. His research focuses on event cognition, human-robot interaction, visual working memory, and visual attention. He coordinates the 'Coordination Cognitive Psychology and Research Methods' research group. His work explores how people perceive and interact with dynamic environments, including studies on event segmentation, cognitive offloading, and aesthetic judgments. He has contributed to over 100 peer-reviewed articles, with recent work addressing topics like the impact of framing on art perception and the role of AI in education. Papenmeier's research integrates experimental methods with interdisciplinary approaches, including collaborations on teleoperation systems and AI-based tutoring. He has presented at major conferences such as the European Society for Cognitive Psychology and the Psychonomic Society. His lab emphasizes methodological rigor, evidenced by contributions to replication databases and open science initiatives. Education: Not explicitly stated in the text, but his titles include Dr. rer. nat. (Doctor of Natural Sciences) and Diplom-Psychologe (Psychology Diploma). Research Interests: His primary areas include event cognition, human-robot interaction (e.g., helping behavior toward robots), visual working memory (e.g., spatial configuration processing), and cognitive offloading (e.g., impact on memory and performance). He also investigates aesthetic judgments and narrative comprehension through eye-tracking and experimental paradigms. Articles Trends: Recent work addresses applied topics like cookie consent interfaces, AI in education (e.g., R programming tutors), and perceptual effects in 3D cinema. His studies often bridge cognitive theory with real-world applications, such as usability design and social robotics. Labs/Teams: Leads the research group 'Coordination Cognitive Psychology and Research Methods' at the University of Tübingen. Collaborates with interdisciplinary teams on projects involving robotics, AI, and human-computer interaction.

• Statistical Relational Learning
• Machine Learning
• Probabilistic Graphical Models
• +۵ مورد دیگر

Lise Getoor is a Professor in the Department of Computer Science at the University of California, Santa Cruz, within the Baskin School of Engineering. She previously held positions at the University of Maryland, College Park and has established herself as a leading researcher in statistical relational learning and neuro-symbolic artificial intelligence. Her research focuses on developing principled approaches to reasoning and learning with rich, relational data. She has made significant contributions to probabilistic soft logic, statistical relational learning, knowledge graph construction, and the integration of symbolic and neural approaches to AI. Her work bridges theoretical foundations with practical applications in areas including social network analysis, sustainable recommendations, cyberbullying detection, and fair machine learning systems. Analysis of her recent publications reveals a strong trend toward neuro-symbolic integration, with increasing focus on combining neural networks with logical reasoning frameworks. Her research demonstrates consistent innovation in developing scalable algorithms for structured prediction across diverse application domains while addressing critical issues of fairness and interpretability in AI systems. Professor Getoor has advised numerous PhD students who have become active contributors to the field, including Connor Pryor, Charles Dickens, Eriq Augustine, and Varun Embar. Her research has been supported by multiple grants from major funding agencies, though specific details aren't provided in the current data. She leads research in the Statistical Relational AI (StaRAI) Lab at UC Santa Cruz, where her team develops frameworks that combine logical reasoning with probabilistic modeling to address complex real-world problems requiring both structured knowledge and statistical learning.

• Power Systems
• Smart Grids
• Renewable Energy Integration
• +۳ مورد دیگر

Prof. Ferdinanda Ponci is a Professor at RWTH Aachen University, leading the Department of Monitoring and Distributed Control for Energy Systems. Her work focuses on smart grid technologies, renewable energy integration, and control systems for modern power networks. She actively contributes to advancing grid resilience, EV charging infrastructure, and cybersecurity in energy systems. Key research interests include hybrid AC-DC grids, distributed energy resources coordination, and application of AI in grid management. She has pioneered frameworks like datafev for EV charging management and SMU platforms for synchronized measurements. Her interdisciplinary approach also addresses diversity in engineering and societal impacts of energy systems. Prof. Ponci’s laboratory activities involve hardware-in-the-loop testing, blockchain-based grid solutions, and development of educational toolboxes for emerging technologies. She collaborates on projects such as submarine transmission systems and grid interoperability testing, contributing to both academic and industrial advancements in power systems engineering.

Tommaso Calarcoمشاهده پروفایل

استاد

• Quantum Optimal Control
• Quantum Computing
• Quantum Technologies
• +۳ مورد دیگر

Tommaso Calarco serves as Director of the Institute for Quantum Control (PGI-8) at Jülich Research Centre, leading cutting-edge research in quantum optimal control methodologies for next-generation quantum technologies. His work focuses on developing transformative computational frameworks applicable to natural sciences, logistics, and high-performance computing through advanced quantum device engineering. His research spans quantum optimal control for computation and many-body systems, emphasizing physical model development, model reduction techniques, and machine learning integration for scalable quantum hardware. Key focus areas include spin-qubit optimization, diamond quantum register engineering, and error suppression in gate operations, with significant contributions to ultracold atom systems and semiconductor-based quantum platforms. Analysis of his 2024-2025 publications reveals concentrated efforts on hardware-specific challenges across multiple quantum modalities: spin shuttling fidelity in semiconductor systems, gate optimization for nitrogen-vacancy centers, and photon-spin interface engineering. This work demonstrates a unifying thread of optimal control solutions tailored to platform-specific decoherence mechanisms and scalability constraints. As Director of PGI-8 within the Peter Grünberg Institut, Calarco oversees a dedicated research team advancing quantum control theory and applications, contributing substantially to European quantum technology roadmaps including the Quantum Flagship initiative and strategic European Commission reports.