جست‌وجوی استاد و پژوهشگر

• Computer Security
• Privacy Engineering
• Data Science
• +۴ مورد دیگر

UnivProf.Dr. Delphine Reinhardt is a Professor of Computer Science at the University of Göttingen, serving as Head of the Computer Security and Privacy group and Head of the Dean's Office of the Faculty of Mathematics and Computer Science. She is a core member of the Institute of Computer Science and the Campus Institute Data Science (CIDAS). Her work focuses on privacy engineering in emerging technologies like smart devices, extended reality (XR), and human-robot interaction. Research interests include privacy-preserving computation, IoT security, and ethical AI applications. Her recent work explores privacy challenges in smart speakers, telepresence robots for hospitalized children, and cross-platform XR privacy solutions. She leads multiple courses on security and privacy, including advanced seminars and lab internships. Her publications analyze user privacy perceptions across cultures and technologies, with a focus on quantifying privacy risks in smart environments. She actively contributes to standards through leadership roles, balancing academic research with institutional governance responsibilities. Lab affiliations include the Computer Security and Privacy research group, which develops tools like PrivXR and SensitivAlert. She collaborates on EU-funded projects addressing privacy in smart workplaces and autonomous systems.

Marlene Altenmüllerمشاهده پروفایل

استادیار

• Science Communication
• Metascience
• Social Psychology
• +۳ مورد دیگر

Marlene Altenmüller is a Junior Professor (Assistant Professor) in Science Acceptance at the Leibniz Institute for Psychology Information (ZPID), holding a PhD from Ludwig-Maximilians-Universität München (LMU Munich). She previously served as a Research Associate at LMU’s Social Psychology Chair from 2018 to 2024. Her academic journey includes a Master’s and Bachelor’s in Psychology and a Bachelor’s in Art History from Philipps University of Marburg (2012–2018). Her research focuses on Trust in science and science communication Metascience analyzing social processes within academia Psychological aspects of art reception and museum experiences Social justice and fairness perceptions Key projects include the BMBF-funded Trust in Citizen Science (TiCS) and the Templeton Religion Trust-supported Art-BEAT initiative. Her work bridges theoretical insights with practical recommendations, such as optimizing science communication strategies and understanding science-religion dynamics. She leads the Science Reception Lab and contributes to interdisciplinary teams like the Social Influence Lab and Metascience Lab at ZPID. Grants include collaborations with TU Braunschweig and Berlin’s Museum für Naturkunde.

• Unsteady aerodynamics
• Flow control
• Rotary aerodynamics
• +۳ مورد دیگر

Dr.-Ing. André Bauknecht is a Senior Scientist at the Institute of Fluid Mechanics, Technische Universität Braunschweig . He leads independent research groups within the Cluster of Excellence for Sustainable and Energy-Efficient Aviation, and collaborates with both academic and industrial partners. Research focus: unsteady aerodynamics, flow control, rotary aerodynamics, aircraft aerodynamics Key collaborations: flow control for gust/aircraft load reduction, multicopter flow field analysis Academic Background: Degree in aerospace engineering, University of Stuttgart Doctorate (2016) for helicopter rotor aerodynamics research at DLR Göttingen Postdoctoral work at Alfred Gessow Rotorcraft Center (University of Maryland) Research Trends: His recent publications (2022-2024) emphasize flow control technologies for load alleviation in fixed-wing and multicopter aircraft. Key areas include Coanda-type actuation , circulation control airfoils , and multicopter aerodynamic characterization through combined experimental and numerical methods. Technical Expertise: Specializes in blade vortex measurements (2015-2017), multi-camera BOS systems , and large-scale aerodynamic simulations . Current work integrates multifunctional leading edge devices and flow-structure deformation analysis for next-generation aircraft.

• Machine Learning
• Computational Chemistry
• Physics of Materials
• +۳ مورد دیگر

Dr. Alice Allen is a Project Leader at the Max Planck Institute of Polymer Research , specializing in machine learning methods for molecular simulations. She holds a PhD in Physics from the University of Cambridge and completed her undergraduate degree in Physics at Imperial College London. Allen previously worked as a research associate at the University of Cambridge and the University of Luxembourg, followed by a postdoctoral position at Los Alamos National Laboratory. Education: BSc in Physics (Imperial College London) PhD in Physics (University of Cambridge) Her research focuses on developing machine learning models for interatomic potentials , enabling accurate and efficient simulations of reactive processes, biological molecules, and material properties. She has published extensively on topics such as permutationally invariant polynomials, data-driven force fields, and meta-learning approaches for foundation models in interatomic potential development. Recent publications highlight her work on integrating experimental data into machine learning potentials, enhancing the transferability of empirical valence bonds, and creating meta-learning frameworks for foundational interatomic models. These studies span applications in molecular dynamics , thermodynamics , and multi-scale simulations . Research Themes: Machine Learning for Atomistic Simulations Reactive Process Modeling Transferable Force Fields Interpretable Models for Material Properties Collaborative Meta-Learning Frameworks Alice Allen leads the Gräter Groups at the institute, where her team advances predictive methodologies for chemical reactions and material science applications. No specific scientific awards or student advisees are mentioned in the provided text.

Tim Puckerمشاهده پروفایل

استاد

• Geotechnical Engineering
• Numerical Modeling
• Soil Mechanics
• +۶ مورد دیگر

Prof. Dr.-Ing. Tim Pucker is a full professor at HafenCity University Hamburg, affiliated with the College of Civil Engineering and the Department of Geotechnical Engineering. His research focuses on numerical modeling of geotechnical systems, particularly in offshore foundations, lunar soil interaction, and pile installation mechanics. Developed modular hypoplastic models for granular soils (2025) Investigated jack-up platform footprints' impact on offshore foundations (2024) Explored lunar soft lander soil interaction (2024) Advanced numerical methods for groundwater flow analysis (2025) His 15 most recent publications (2025-2015) demonstrate expertise in computational geotechnics, foundation dynamics, and structural optimization. Key themes include offshore wind turbine foundations, hypoplastic material modeling, and extraterrestrial geotechnics. Notable subfields: soil-structure interaction, large deformation analysis, and discrete element method applications. Teaching responsibilities include Geotechnics I/II, Water Engineering, and Numerical Methods for both bachelor's and master's programs. Office hours: Thursdays 14:00-15:00 during lecture periods, by appointment otherwise.

André Borrmannمشاهده پروفایل

استاد

• Artificial Intelligence
• Building Information Modeling & Processing
• Digital Twinning
• +۷ مورد دیگر

Prof. Dr.-Ing. André Borrmann is an academic leader at the Technical University of Munich (TUM) , where he has headed the Chair of Computing in Civil and Building Engineering since 2011 (formerly Computational Modeling and Simulation). He serves as Director of the TUM Georg Nemetschek Institute - AI for the Built World since 2025 and Spokesperson for the Leonhard Obermeyer Center since 2013. Research Interests Artificial Intelligence in Civil Engineering Digital Twinning Building Information Modeling (BIM) Pedestrian Dynamics Knowledge Representation Construction Simulation His work focuses on AI application across the built environment lifecycle - from generative design to maintenance prediction - with significant contributions to BIM standardization and buildingSMART International IFC extensions. He co-authored the German Ministry of Transport BIM Roadmap and led the BIM4INFRA2020 project. Awards include the 2024 Konrad Zuse Medal and multiple best paper awards at international conferences.

Michael Coblenzمشاهده پروفایل

استادیار

• Usability of programming languages
• User-centered programming language design
• Type systems for safety
• +۶ مورد دیگر

Michael Coblenz is an Assistant Professor in the Computer Science Department at University of California, San Diego. His research focuses on integrating user-centered design into programming language development, creating safer languages for blockchain and scientific computing. He completed his Ph.D. at Carnegie Mellon University under Jonathan Aldrich and Brad A. Myers, followed by a Basili postdoctoral fellowship at University of Maryland. Specializes in usability of programming languages Created Obsidian language for safer smart contracts Developed PLIERS methodology for iterative language design Active in Rust usability and REST API quality research His work bridges programming languages and human-computer interaction, with recent projects including Kale (safer spreadsheets) and climate change-focused programming tools. He has served on program committees for SPLASH, VL/HCC, and HATRA conferences. 2025: Graduate Consortium Co-chair at VL/HCC 2024: HATRA Organizing Chair 2023: Doctoral Symposium Chair at SPLASH

• Neuroscience
• Physics of Complex Systems
• Computational Neuroscience
• +۵ مورد دیگر

Prof. Viola Priesemann is a physicist and neuroscientist at the Max Planck Institute for Dynamics and Self-organization and University of Göttingen (W3 Professorship, 20% position). Her research spans self-organization in adaptive networks across neural and societal scales, with applications to neural criticality , information processing , and COVID-19 pandemic dynamics . She leads an independent Max Planck Research Group since 2017 and has held affiliations with Caltech , MPI Brain Research , and Bernstein Center Göttingen . Her research combines statistical physics , information theory , and non-equilibrium systems to study: Self-organized criticality in brain networks Subsampling theory for large-scale systems Neural basis of curiosity and learning Test-trace-isolation strategies for epidemics Information spread in social networks Design of energy-efficient AI architectures Key scientific awards include: Communitas Award (Max Planck Society, 2021) Science award of Lower-Saxony (2021) Medaille für naturwissenschaftliche Publizistik (DPG, 2021) Young Scientist Award (DPG, 2024) Her work on cross-scale information flow has influenced both neuroscience and public health policy , including advisory roles in the German government's COVID-19 expert panel .

Oleksandr Perekhozhukمشاهده پروفایل

پژوهشگر

• Industrial Organization
• International Trade
• Applied Econometrics
• +۳ مورد دیگر

Dr. Oleksandr Perekhozhuk is a Senior Research Associate at the Leibniz Institute of Agricultural Development in the Global Food Economy (IAMO) , specializing in Industrial Organization, International Trade, Applied Econometrics , and Microeconomics . He has been affiliated with IAMO since 2007 and holds a PhD in Agricultural Economics from Martin Luther University Halle-Wittenberg (2007), preceded by a Master of Agricultural Science (2000) and a diploma in Business Administration (1996). Education PhD (2007) - Martin Luther University Halle-Wittenberg, Germany Master of Agricultural Science (2000) - MLU Halle-Wittenberg, Germany Diploma in Business Administration (1996) - National Agrarian University of Ukraine, Kyiv His research focuses on market power analysis in agricultural sectors, particularly through residual demand elasticity and price discrimination studies. Recent publications examine Ukrainian pork industry dynamics , Kazakh and Russian wheat exports , and global food security . He leads the UaFoodTrade project on Ukrainian research internationalization and contributes to policy briefs on agricultural trade reform and sustainable development . Scientific Awards are not explicitly mentioned in available data. He participates in international conferences (e.g., Canadian Economics Association , EAAE Congress ) and collaborates on projects like MATRACC , GUCE-SAFE , and VALUMICS . His work spans Ukraine, Russia, Kazakhstan, South Caucasus , and Central Asia , with teaching engagements on econometric methods and scientific publishing .

• Machine Learning
• Artificial Intelligence
• Reinforcement Learning
• +۷ مورد دیگر

Irina Rish is a Research Professor at Mila - Quebec AI Institute, affiliated with Université de Montréal, and maintains a significant research affiliation with IBM Research. With an extensive publication record spanning decades and continuing through 2025, she is an active leader in artificial intelligence research. Primary Affiliation: Mila - Quebec AI Institute, Université de Montréal Secondary Affiliation: IBM Research Research Focus Areas: Machine Learning, AI Systems, and Applications Dr. Rish's research interests encompass machine learning theory and applications, with particular expertise in neural networks, language models, reinforcement learning, and efficient AI systems. Her work bridges theoretical understanding with practical implementations across multiple domains including healthcare, time series analysis, and multimodal systems. Analysis of her recent publications (2023-2025) reveals a strong trend toward efficient AI architectures, with significant contributions to model quantization (particularly ternary models), scaling laws in language models, and novel techniques for continual learning. Her research demonstrates how theoretical insights can translate into practical improvements in model efficiency and performance. Key Publication Trends: Model efficiency, scaling laws, continual learning Application Areas: Healthcare (EEG analysis), time series forecasting, vision-language systems Dr. Rish collaborates extensively with researchers across academia and industry, working with notable colleagues including Guillermo A. Cecchi, Djallel Bouneffouf, Eugene Belilovsky, and Matthew Riemer. Her work appears regularly in top-tier conferences (NeurIPS, ICML, ICLR, AAAI) and journals like Transactions of Machine Learning Research, demonstrating both the quality and impact of her research contributions. She leads research in federated learning techniques, reinforcement learning systems, and multimodal AI architectures, with recent work focusing on making AI systems more robust, efficient, and applicable across diverse real-world scenarios. Her research program demonstrates consistent growth in impact and scope, with increasing publication output in recent years.

Kai Reinhardtمشاهده پروفایل

استاد

• Evidence-Based Organizational Development
• Digital Transformation
• Strategic Human Resources Management
• +۳ مورد دیگر

Kai Reinhardt is a Professor at HTW Berlin, affiliated with the Faculty of Economics and Law and the Department of Work and Human Resources Management. He specializes in evidence-based organizational development, digital transformation, and strategic HR systems, combining academic rigor with industry experience from companies like SAP, Siemens, and Swisscom. Master’s Program Head: 'Work and Human Resources Management' Teaching: Bachelor, Master, and MBA courses on digital transformation, HR technologies, and strategic management His research emphasizes AI-supported decision architectures, causal inference in digital experiments, and competency management frameworks. He has authored several books, including the 2025 publication on 'Future Competencies in Sales,' which provides data-driven models for adapting sales teams to technological changes and customer demands. Recent trends in his work include: Strategic skill management in pharmaceutical and tech sectors Human-Machine collaboration in HR Talent ecosystem analysis in Berlin Future skills and leadership evolution His collaborations with industry leaders and focus on practical applications highlight his commitment to bridging academia and business. Reinhardt’s teaching and research span digital experiments, organizational intelligence, and adaptive leadership. He supervises up to 10 theses per semester, prioritizing topics aligned with his expertise.

Lukas Iffländerمشاهده پروفایل

استاد

• Cybersecurity
• Cryptography
• Network Security
• +۴ مورد دیگر

Prof. Dr. Lukas Iffländer serves as a Professor within the Faculty of Informatics / Mathematics at Westsächsische Hochschule Zwickau, Germany, maintaining an active office (Room U 452) with contactable phone number +49 351 462 3516. His academic profile demonstrates continuous engagement through recent publications extending into 2025, with research appointments scheduled by prior arrangement reflecting his operational availability. His research program centers on cybersecurity with exceptional depth in cryptographic systems and infrastructure protection. Key specialties include homomorphic encryption optimization (notably CKKS scheme implementations), IoT security protocols for resource-constrained environments, and railway system vulnerability analysis. His methodology consistently integrates performance benchmarking with security validation, particularly examining computational overhead in privacy-preserving technologies and physical attack vectors against critical transportation infrastructure. This dual focus on theoretical cryptography and real-world system security establishes him as a bridge between academic research and industrial implementation challenges. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research trajectories: (1) Cryptographic performance evaluation, where he pioneers benchmarking frameworks for homomorphic and attribute-based encryption in practical scenarios like linear regression; (2) Railway security innovation, addressing digital interlocking systems and physical attack mitigation through technology forecasting; (3) IoT security optimization, developing multi-objective recommendation systems for group communication protocols. His work consistently emphasizes measurable performance impacts, with 60% of recent publications containing empirical benchmarking data, reflecting an engineering-driven approach to security research. No scientific awards were documented in the source materials. Information regarding student supervision, research grants, or laboratory affiliations remains unavailable in the provided documentation, though his publication volume suggests active research group leadership. His technical focus on virtual machine introspection and hypercall handling indicates potential involvement in low-level systems security teams, while railway security publications imply collaboration with transportation infrastructure entities.

Peter Michaelisمشاهده پروفایل

استاد

• Environmental Economics
• Resource Economics
• Climate Change Economics
• +۴ مورد دیگر

Prof. Dr. Peter Michaelis is Chair of Environmental and Resource Economics at the Faculty of Business and Economics, University of Augsburg, Germany. He has held this position since April 1999, leading research and teaching in environmental economics, resource management, and climate change policy. His research focuses on the economic aspects of environmental problems, with particular emphasis on climate change economics. Key areas include: Design and effectiveness of economic instruments in environmental policy Emissions trading systems and carbon pricing mechanisms Climate policy and innovation dynamics Resource economics and sustainable development Environmental policy instruments and their economic impacts Prof. Michaelis's publication record demonstrates a consistent focus on environmental economics, with numerous articles in leading journals examining CO2 pricing, emissions trading, climate policy, and environmental regulation. His recent work has particularly emphasized climate change economics, analyzing the economic implications of greenhouse gas accumulation and developing models for optimal climate policies. His research often addresses the theoretical and empirical challenges of climate change due to uncertainties, long-term impacts, and global nature of the problem. Among his notable recognitions: Recipient of the Baden-Württemberg Metal Industry Promotion Prize (1990) for his doctoral work on waste management Member of the Advisory Council on Environmental Issues (August 2000-June 2008) Prof. Michaelis leads the Chair of Environmental and Resource Economics, which includes several research associates and doctoral candidates working on various environmental economics projects. His team has undertaken research projects on economic instruments in environmental policy, environmental policy and innovations, promoting renewable energies, and optimal climate policies. The Chair also publishes the 'Augsburg Writings in Environmental Economics,' a series offering a forum for academic works addressing current topics in environmental economics and environmental policy. The Chair maintains active research collaborations and offers various lectures and seminars on environmental economics topics, though most courses are taught in German. Prof. Michaelis has also contributed to several environmental policy assessments as a member of the Advisory Council on Environmental Issues, providing expert advice to German policymakers.

Christian Kundeمشاهده پروفایل

پژوهشگر

• Process Optimization
• Global Optimization
• Surrogate Modeling
• +۵ مورد دیگر

Dr.-Ing. Christian Kunde is a PostDoc researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in the Process Synthesis and Process Dynamics group since 2021. Previously, he served as a PostDoc at the Chair for Automation/Modeling at Otto-von-Guericke University (OVGU) from 2017-2021, and as a Research Assistant and PhD Student at the same institution from 2009-2017. His educational background includes a Diploma in Systems Engineering and Engineering Cybernetics from OVGU (2004-2009) and a PhD dissertation titled "Global optimization in conceptual process design" completed in 2017. His formal engineering doctorate (Dr.-Ing.) reflects his specialized expertise in process systems engineering. Kunde's research focuses on physics- and data-based hybrid modeling for process optimization and state estimation, with particular emphasis on global optimization techniques and surrogate modeling. His work bridges theoretical computational methods with practical chemical engineering applications, addressing challenges in distillation, crystallization, and fuel cell systems. He has developed innovative approaches combining first-principles models with machine learning for improved process design and control. His publication record demonstrates consistent contributions to chemical process optimization, with recent work expanding into machine learning applications for Power-to-X processes and fuel cell modeling. The research shows a clear trajectory from fundamental optimization methods toward increasingly complex hybrid modeling approaches that integrate physics-based and data-driven techniques. Kunde actively contributes to academic knowledge dissemination through teaching, having instructed courses including Distributed Parameter Systems, State Estimation, and Systems and Control. His teaching portfolio reflects his research expertise in process dynamics and control systems, providing students with both theoretical foundations and practical applications in modern process engineering.

Thomas Grätschمشاهده پروفایل

استاد

• Finite Element Method
• Vibroacoustics
• Mechanical Engineering
• +۳ مورد دیگر

Prof. Dr. Thomas Grätsch is a faculty member at Hamburg University of Applied Sciences within the Faculty of Technology and Computer Science, specifically in the Department of Mechanical Engineering and Production. His office is located in Room 226e at Berliner Tor 21, 20099 Hamburg, with contact number +49 40 428 75-8705. Prof. Grätsch specializes in computational mechanics with a focus on the Finite Element Method (FEM) and its applications in vibroacoustics. His research particularly addresses noise emission from wind turbines, structural vibration analysis, and mechanical system simulations. He has developed sophisticated models for predicting and reducing tonal noise in wind energy systems, with emphasis on gearbox vibrations and acoustic radiation from large structures. His publication record shows a consistent research trajectory focused on wind turbine noise simulation, with recent work (2018-2022) concentrating on hybrid multistep procedures, large-scale finite element modeling, and practical applications for noise reduction in wind energy systems. His work bridges theoretical computational methods with practical engineering applications in renewable energy technology. Prof. Grätsch holds several administrative roles including Program Coordinator for the Master's program 'Calculation and Simulation in Mechanical Engineering', Spokesperson for the Mechanics Group, Member of the Department Council for Mechanical Engineering and Production, and Deputy Member of the Confidence Committee of the Faculty of Technology and Computer Science. He is also a Member of the Editorial Board of Computers & Structures. His research projects focus on vibroacoustics, particularly addressing noise emission from wind turbines through computational simulation and structural analysis. His work has practical implications for the wind energy industry seeking to reduce environmental noise pollution while maintaining energy production efficiency.