جست‌وجوی استاد و پژوهشگر

Anne Herrmann-Wernerمشاهده پروفایل

استاد

• Medical Education
• Clinical Simulation
• Educational Research
• +۷ مورد دیگر

Anne Herrmann-Werner is a Professor for Medical Didactics, Clinical Simulation, and Educational Research at the University of Tübingen, Germany. She is affiliated with the TIME – Institute for Medical Education, part of the Medical School at the university. Her work bridges clinical training and educational innovation. Research Interests: Her research spans medical education , peer-assisted learning (PAL) , student burnout , clinical simulation , and the integration of artificial intelligence in medical training . She investigates how digital tools and peer-led instruction can enhance clinical skills, particularly history taking, while also focusing on student well-being and vaccination attitudes. Publication Trends: Her recent publications (2020–2024) highlight a strong focus on AI-driven educational tools, mental health in medical education, and evidence-based teaching methods. There is a clear trajectory toward digital innovation and psychosocial support in medical training. Scientific Contributions: Co-authored influential reviews on PAL and student burnout Published in high-impact journals like Medical Teacher , PLoS One , and JMIR Medical Education Lead and collaborative roles in studies on AI in medical education Advising and Grants: While specific students and grants are not listed in the provided texts, her extensive publication record with junior colleagues suggests active mentorship and likely grant-funded research in medical education and simulation. Her leadership in recent AI-integration studies implies current project funding. Labs and Teams: She works within the TIME – Institute for Medical Education, a hub for educational innovation at the University of Tübingen. Her collaborative network includes researchers such as Stephan Zipfel, Friederike Junne, and Christoph Nikendei, indicating strong interdisciplinary teamwork in psychosomatic medicine and medical training.

Jessica Rehseمشاهده پروفایل

پژوهشگر

• Educational Technology
• Inclusive Education
• Technical Education
• +۷ مورد دیگر

Jessica Rehse (M.Ed.) is a researcher and educator at the University of Potsdam, affiliated with the Faculty of Economics, Work, and Technology. She contributes to the Professorship for Technology and Technical Education, with strong engagement in the Didactics of Economic-Technical Education in inclusive contexts. Her work is centered on innovative educational technologies, including 3D printing, digital games, and virtual reality applications in teaching and learning. Her research interests focus on educational technology , inclusive technical education , and digital innovation in vocational pedagogy . She explores how immersive tools like VR and 3D modeling can enhance student engagement and accessibility in economic and technical subjects. Her work emphasizes hands-on, experiential learning and the integration of maker culture into school curricula. The recent publications of Jessica Rehse reflect a strong trend toward immersive and interactive learning environments . Her work spans virtual heritage tours, ecological simulations, and game-based moral education, demonstrating a multidisciplinary approach that bridges technology, pedagogy, and social inclusion. She frequently collaborates on interdisciplinary projects involving media studies, cultural education, and environmental awareness. She is actively involved in several research and development initiatives, including EDU-VActoRy, InnoWATerSpace, LLiT, and Tekajj—all aimed at shaping the future of inclusive, technology-driven education. These projects support the development of maker spaces, inclusive labs, and digital tools for diverse learners.

Boris Kozyrevمشاهده پروفایل

پژوهشگر

• Macroeconomics
• Forecasting
• Applied Econometrics
• +۳ مورد دیگر

Boris Kozyrev is a Researcher in the Department of Macroeconomics at the Halle Institute for Economic Research (IWH) since September 2021. He holds a bachelor's degree from Lomonosov Moscow State University and a master's degree from Toulouse School of Economics. Previously, he worked as a Junior Researcher at the Russian Presidential Academy of National Economy and Public Administration. His research focuses on macroeconomic forecasting, applied econometrics, and computational economics. Key contributions include developing random subspace regression methods for forecast aggregation and applying neural networks to GDP prediction in volatile environments. His work emphasizes model interpretability and handling high-dimensional data, with applications to German and global economic trends. Recent publications explore topics such as forecast combination techniques neural network-based GDP prediction energy crisis impacts on Germany structural challenges in post-pandemic recovery These articles highlight his expertise in quantitative modeling and real-world economic analysis. His affiliations include collaborations with institutions like the IWH and prior work at the Russian Presidential Academy. Research interests intersect with policy analysis, particularly in energy and trade sectors affecting Germany's economy.

Sarath Menonمشاهده پروفایل

پژوهشگر

• Materials Science
• Machine Learning
• Computational Physics
• +۴ مورد دیگر

Sarath Menon is a computational materials scientist at Ruhr-University Bochum and Max-Planck-Institut für Eisenforschung GmbH. His work focuses on atomistic simulations, machine learning interatomic potentials, and thermodynamic property calculations. He contributes to open-source software like pyiron and pace. Doctor of Engineering, Mechanical Engineering (2021) Master of Science, Materials Science and Simulation (2018) Bachelor of Technology, Mechanical Engineering (2012) His research centers on developing machine learning potentials for thermodynamic modeling, with applications in phase diagrams and nucleation studies. He employs methods like transition path sampling and hyperdynamics. Menon teaches Python programming, electronic structure methods, and atomistic simulation techniques. He has organized workshops on reproducible workflows and quantum mechanics in solid-state physics. Key software contributions include: pyscal : Structural analysis tool for atomic environments pace : High-performance Atomic Cluster Expansion implementation calphy : Free energy calculation library atomRDF : Ontology-based structure manipulation

• Machine Learning
• Process-Based Modeling
• Environmental Science
• +۲ مورد دیگر

Yucong Hu is a Doctoral Researcher at the Max Planck Institute for Biogeochemistry in the Biogeochemical Integration Department . Affiliated with the IMPRS-gBGC graduate school , his work focuses on integrating process-based models with machine learning to address challenges in environmental data analysis. Current projects include upscaling scarce datasets, modeling unmeasurable natural processes, and optimizing hydrological simulations through advanced neural network architectures. Education 2020-2024: MS in Ecology, University of Chinese Academy of Sciences 2018-2020: BEng in Computer Science and Technology, China Agricultural University 2016-2020: BEng in Agricultural Biological Environmental and Energy Engineering, China Agricultural University His research leverages LSTM networks for streamflow and water quality prediction, as well as storm event-based pollutant delivery process analysis. Despite limited publication visibility, his work contributes to environmental data science and hydrological modeling.

Daniel Cigandaمشاهده پروفایل

پژوهشگر

• Demographic Modeling
• Fertility Studies
• Agent-Based Modeling
• +۳ مورد دیگر

Daniel Ciganda is a Researcher at the Max Planck Institute for Demographic Research , leading the Laboratory of Fertility and Well-Being . His work integrates computational models with demographic research to analyze fertility patterns and their societal implications. Research Focus : Fertility dynamics, agent-based modeling, and population forecasting. Collaborations : A. Lorenti, N. Todd, M. Myrskylä, and others. Ciganda's research spans micro-level computational models to macro-level fertility projections. Recent work includes individual-level fertility timing simulations and sensitivity analyses of Schelling's segregation model. His publications emphasize social feedback mechanisms , educational gradients, and policy-relevant demographic trends. Key projects involve COMFERT (Computational Models for Fertility Forecasting) and extensions to agent-based segregation models. He contributes to open science via GitHub repositories like individual_fx for fertility modeling.

• Collective Intelligence
• Collaboration & Group Processes
• Network Analysis
• +۲ مورد دیگر

Nikolas Zöller is a research scientist at the Max Planck Institute for Human Development 's Adaptive Rationality department. His work focuses on collective intelligence, human-AI collaboration, and computational modeling of social systems. He combines methods from physics, computer science, and psychology to study decision-making processes in both natural and artificial collectives. Ph.D. candidate at Constructor University Bremen (2020-2024) Research Associate at Potsdam University of Applied Sciences (2015-2022) Master of Science in Physics from Freie Universität Berlin (2014) Bachelor of Science in Physics from Freie Universität Berlin (2010) His research spans: Collective intelligence frameworks Human-AI collaborative diagnostics Agent-based modeling of social networks Technological co-diffusion patterns Thermodynamic optimization in physical systems Recent publications highlight his work on: Diagnostic accuracy in human-AI collectives GitHub collaboration topology Affect control theory in group dynamics Co-diffusion of complementary technologies Scientific recognition includes: European Press Prize (2022) as part of a team Springer Best Masters Award (2014)

Shanthika Naikمشاهده پروفایل

پژوهشگر ارشد

• Deep Learning
• Geometric Processing
• Neural Garment Simulation
• +۵ مورد دیگر

Shanthika Naik is a Senior Research Fellow at IIT Jodhpur, specializing in Deep Learning and Geometric Processing. She holds a Master’s degree from the Center for Visual Information Technology (CVIT) at IIIT Hyderabad and a Bachelor’s in Computer Science from KLE Technological University. Research Focus: 3D garment retargeting, UV parametrization, neural terrain generation, point cloud processing, and clothed human modeling. Key Projects: Self-supervised 3D surface parameterization, physics-based garment deformation frameworks, and interactive terrain authoring tools. Her work often involves interdisciplinary applications of Deep Learning in computational geometry and multimedia systems. She has contributed to publications at SIGGRAPH Asia, IGARSS, and PReMI conferences, focusing on improving accuracy and efficiency in 3D simulations. Shanthika has collaborated with labs including the VCAI lab (MPI Saarland) and 3DVisLab. Her open-source contributions include repositories for FeatureNet and terrain generation frameworks.

Andrea Ebertمشاهده پروفایل

پژوهشگر

• Computational Toxicology
• Membrane Permeability Modeling
• Environmental Contaminants
• +۳ مورد دیگر

Dr. Andrea Ebert is a researcher in the Department of Computational Biology and Chemistry at the Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. Her work focuses on membrane permeability modeling , ecotoxicology , and computational toxicology . Education: PhD in Biophysics (2012, Johannes Kepler Universität Linz/UFZ), Master of Science in Physics (2009), Bachelor of Science in Physics (2009), both from Ludwig-Maximilians-Universität Munich Professional Experience: PostDoc at UFZ since 2020; Development Engineer at Entropy GmbH (2012-2016) Research interests include intrinsic membrane permeability prediction , bioconcentration of hydrophobic compounds , and mechanistic modeling of environmental contaminants . Her recent publications analyze pH-dependent transport mechanisms , efflux ratios , and toxicokinetic behavior of chemicals using computational approaches.

Florian Holzapfelمشاهده پروفایل

استاد

• Flight System Dynamics
• Flight Control/Flight Guidance
• Trajectory Optimization
• +۴ مورد دیگر

Prof. Dr.-Ing. Florian Holzapfel holds the professorship in Flight System Dynamics at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design. His academic journey includes a doctorate at TUM under Prof. Gottfried Sachs, followed by industry experience at IABG before joining TUM in 2007. He is an Associate Fellow of the AIAA and a DGLR member. Research focuses on flight control systems, trajectory optimization, sensor technology, avionics, and safety-critical systems, with emphasis on collaboration with Bavarian aerospace SMEs. Key contributions include adaptive control strategies, eVTOL trajectory optimization, and urban air mobility applications. Education: Bachelor/Master in Aerospace Engineering from TUM Doctorate (Dr.-Ing.) at TUM's Chair of Flight Mechanics and Flight Control Awards include the AIAA 2004 Best Paper Award and the Willy Messerschmitt Prize. His work bridges industry-academia gaps, addressing practical challenges in flight dynamics and advanced air mobility. Labs/Teams: Leads research in eVTOL trajectory generation, flight control architectures, and safety-critical system design. Grants/Awards: Extensive contributions to AIAA conferences and industry-funded projects.

• Semantic Communication
• Resource Allocation Mechanisms
• 6G Networks
• +۳ مورد دیگر

Alexander Griessel is a Researcher and PhD candidate at the Chair of Communication Networks (Prof. Wolfgang Kellerer) at the Technical University of Munich (TUM). He holds a B.Sc. (June 2020) and M.Sc. (December 2021) in Electrical and Computer Engineering from TUM. His research focuses on Resource Allocation Mechanisms in Semantic Communication , particularly addressing resilience and efficiency in 6G channels. He contributes to the Semantic Communication project and serves as a teaching associate for the Internet Kommunikation course. His work spans semantic resilience strategies , real-time video/image communication , and 6G network design . Recent research includes lossy coding techniques for semantic images, adaptive systems for challenging 6G environments, and non-invasive sensor solutions for infrastructure monitoring. His publications also explore cybersecurity (website fingerprinting) and reinforcement learning for network trace generation. Alexander actively supervises master's theses on topics like semantic symbol prioritization and reliability analysis in 5G/6G channels. He collaborates on TUM's 6G testbed initiatives and contributes to the 6G-life and Flexibility research networks. His interdisciplinary approach bridges communication theory with practical network implementations.

Sara Nazariمشاهده پروفایل

پژوهشگر

• Groundwater Modeling
• Integrated Water Resources Management
• Sustainability Analysis
• +۵ مورد دیگر

Sara Nazari is a Researcher at the Leibniz Center for Tropical Marine Research (ZMT) , affiliated with the Working Group: Submarine Groundwater Discharge . She integrates interdisciplinary methodologies to address climate change, land use, and socio-economic impacts on water resources. Education: MSc in Water Resources Management and Engineering, Isfahan University of Technology (2015–2018) Her research emphasizes: Groundwater modeling Integrated and adaptive water resources management Sustainability analysis Big-Data analysis Conflict resolution theories Her publications focus on global groundwater recharge trends, computational models, and conflict resolution frameworks. She developed open-source tools for hydrological assessments and contributed datasets on global recharge patterns. She is based at Fahrenheitstr. 6, Bremen, Germany, and can be reached at sara.nazari@leibniz-zmt.de .

Hauke Reuterمشاهده پروفایل

دانشیار

• Theoretical Ecology
• Ecosystem Research
• Ecological Modelling
• +۵ مورد دیگر

PD Dr. Hauke Reuter serves as Work Group Leader for Spatial Ecology and Interactions at the Leibniz Centre for Tropical Marine Research (ZMT) in Bremen, Germany, within Programme Area 4 – Ecosystem Co-Design towards a sustainable Anthropocene. Holding a habilitation in Ecology since 2007, he leads research on complex marine ecosystems with emphasis on theoretical approaches and modeling. His academic credentials include: Diploma in Biology (MSc) from University of Kiel (1994) PhD in Ecology from University of Bremen (2000) Habilitation in Ecology from University of Bremen (2007) Reuter's research integrates theoretical ecology with practical conservation challenges, focusing on trophic interactions, food web structure, and biodiversity dynamics in marine systems. His work employs individual-based models and cellular automata to examine cross-scale ecological processes, particularly in coral reefs and seagrass ecosystems. Current investigations address phase shifts in tropical marine habitats under climate change and anthropogenic pressures, with field sites across Southeast Asia and East Africa. This approach bridges fundamental ecological theory with sustainable resource management applications. Analysis of his recent publications reveals strong thematic concentration on marine ecosystem resilience, particularly examining nutrient enrichment effects, species invasions, and socio-ecological dimensions of coastal management. His work demonstrates consistent methodological innovation in ecological modeling while maintaining applied relevance for conservation policy in tropical regions. Reuter contributes to academic training through the International Studies in Aquatic Tropical Ecology (ISATEC) program, teaching courses in ecological modeling, spatial-temporal processes, and specialized topics including biodiversity assessment and environmental risk analysis. His research portfolio includes significant projects such as GeneRisk, SIGMEA, and GenEERA, reflecting interdisciplinary collaboration across ecological, social, and computational domains. As leader of the Spatial Ecology and Interactions working group, he directs integrated research combining field observations with advanced simulation techniques to address Anthropocene challenges in marine ecosystems. The group maintains active field programs in Indonesia, Tanzania, and the Mediterranean, focusing on human-environment interactions in vulnerable coastal zones.

• Quantum Software Engineering
• Cyber-Physical Systems
• Digital Twin Technologies
• +۳ مورد دیگر

Dr. Shaukat Ali is a leading researcher at Simula Research Laboratory (Certus Software V&V Center, Norway), with a PhD from the University of Oslo . His work bridges quantum software engineering and cyber-physical systems (CPS) validation, focusing on digital twins, autonomous vehicles, and healthcare IoT applications. Collaborates with institutions like South Dakota State University, COMSATS University, and Mohammad Ali Jinnah University Co-developed tools: QuCAT (Quantum combinatorial testing), DeepScenario (autonomous driving datasets), and EvoCLINICAL (medical digital twin evolution) Research spans quantum software testing (IBM quantum computers), uncertainty-aware validation of medical devices, and search-based optimization in CPS. His 2025 work introduces quantum circuit mutants, uncertainty-wise test oracles, and foundational models for digital twin creation. Publications in journals like ACM Transactions on Software Engineering and conferences including ICSE , GECCO , and IEEE Quantum Software reflect his interdisciplinary approach. Current projects address quantum software robustness, LLM-driven scenario realism, and safe adaptation in robotics.

Sharad Kumar Guptaمشاهده پروفایل

پژوهشگر

• Remote Sensing
• Ecological Modelling
• Environmental Informatics
• +۳ مورد دیگر

Sharad Kumar Gupta is a Guest Scientist at the Helmholtz-Centre for Environmental Research - UFZ in Leipzig, Germany, and a Scientist at the Center for Advanced Systems Understanding (CASUS) in Görlitz. His research focuses on remote sensing , environmental informatics , and geospatial data analysis with applications in ecological modelling , UAV technology , and environmental risk assessment . Education Ph.D. in Remote Sensing (2015) - Indian Institute of Technology Mandi M.Tech in Geoinformatics (2014) - NIT Bhopal B.Tech in Computer Science (2011) - Uttar Pradesh Technical University Research Highlights Developed Drone4Tree cloud platform for UAV-based tree canopy detection Specialized in hyperspectral data scaling and agricultural stress monitoring Published extensively on environmental data integration , geophysical inversion , and urban green infrastructure Affiliations Dept. Monitoring and Exploration Technologies, UFZ Dept. Earth Systems Research, CASUS (HZDR) Key Publications address landslide susceptibility mapping , UAV-based environmental monitoring , machine learning applications in agriculture, and multi-method data integration for subsurface analysis. His work appears in journals like EGU General Assembly , Permafrost Periglacial Processes , and Environmental Earth Sciences .