Find Academic Supervisors

Johannes SchneiderView profile

Researcher

• Bundle Adjustment
• Visual Odometry
• Multi-camera Systems
• +7 more

Johannes Schneider is a researcher at the University of Bonn, affiliated with the Institute of Geodesy and Geoinformation's Department of Photogrammetry. His role includes scientific research and academic contributions in the field of computer vision and robotics. He holds a Master's degree in Geodesy and Geoinformation from the University of Bonn (2011) and has been a PhD student since 2012, supervised by Wolfgang Förstner, focusing on visual SLAM and multi-camera systems. His research interests span bundle adjustment, visual odometry, multi-camera systems, and unmanned aerial vehicle (UAV) applications. He actively contributes to the 'Mapping on Demand' project (funded by DFG) and has developed software tools like BACS (Bundle Adjustment for Camera Systems). Teaching responsibilities include lectures on '3D Coordinate Systems' and project supervision for master students. Notable achievements include the Karl Kraus Young Scientist Award (2013). His work emphasizes real-time navigation, obstacle detection, and precise 3D reconstruction using UAVs, integrating sensors like RTK-GPS, IMUs, and fisheye cameras. Recent publications highlight advancements in dense stereo matching, SLAM algorithms, and system calibration.

Michael StrauchView profile

Researcher

• Integrated Watershed Modeling
• Multi-Objective Land Use Optimization
• Ecosystem Services Assessment
• +2 more

Dr. Michael Strauch is a researcher at the Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany. He specializes in integrated process-based watershed modeling and multi-objective optimization of land-use allocation, focusing on the impacts of land use intensity, landscape composition, and configuration on water-related ecosystem services, agricultural production, and biodiversity. His work involves coupling simulation models with heuristic search algorithms using the generic model integration tool CoMOLA and advancing the Soil and Water Assessment Tool (SWAT) . Key Research Areas: Trade-offs and synergies among ecosystem services Stakeholder-driven land use strategies Climate change adaptation in water resources SWAT+/CoMOLA tool development Recent publications highlight his contributions to optimizing agri-environmental practices (2025), addressing soil data gaps in European catchments (2024), and modeling climate-deforestation impacts in Amazonia (2025). His work spans projects like BiodivERsA TALE and OPTAIN , with a focus on multifunctional agricultural landscapes.

• Biomedical Engineering
• Medical Statistics
• Ophthalmology
• +3 more

Prof. Konstantin Kotliar is a Professor at Aachen University of Applied Sciences, specializing in Biomedical Engineering and Medical Statistics. He teaches courses in Mathematics, Advanced Medical Statistics, and Space Physiology. His research focuses on retinal vessel analysis to study microvascular dysfunction in diseases such as Fabry disease, diabetes, and Alzheimer’s. Kotliar’s work bridges ophthalmology, neuroscience, and cardiovascular science, with a particular interest in developing non-invasive diagnostic tools for early disease detection. His studies often involve collaborations with global health initiatives and clinical trials, such as the EndoAfrica-NWU Study. He has contributed to understanding neurovascular coupling mechanisms and their implications for neurological disorders. Research interests include retinal vessel dynamics, cardiovascular risk stratification, and the application of statistical methods in medical diagnostics. Kotliar’s methodologies span from biomechanical modeling to machine learning-driven image analysis, emphasizing translational research with clinical relevance. His work has implications for improving therapies and preventive measures in chronic diseases.

Swen GüntherView profile

Professor

• Process Management
• Innovation Management
• Lean Six Sigma
• +4 more

Prof. Dr. Swen Günther holds the Chair of Process and Innovation Management at HTW Dresden within the Faculty of Business Administration . His academic leadership spans teaching and research in production management, project management, process/quality management, and technology/innovation management. He oversees the Bachelor's and Master's programs in Industrial Engineering and collaborates with international partner universities like Satakunta/VAMK (Finland) and FH Burgenland (Austria). Education & Career: Günther earned his PhD (Dr. rer. pol.) from TU Dresden's Market-Oriented Management department. Prior to academia, he worked at Procter & Gamble in manufacturing and quality management (2008-2015). His research focuses on Lean Six Sigma, TRIZ Reverse, transfer indicators, and digitalization. He leads the BMBF-funded 'Transfer_i' project (2019-2021), developing transfer metrics for academia-industry collaboration. Research Interests: His work emphasizes systematic knowledge/technology transfer, digital transformation in processes, and innovative management methodologies. Recent studies address transfer indicators for universities, cost-benefit analyses of digital projects, and empirical research on management trends. Teaching & Advising: Over 50+ theses supervised (2018-2021) across process optimization, quality management, and innovation transfer. He advises companies on Lean/Six Sigma implementation and organizes industry excursions with firms like T-Systems MMS and König & Bauer. Professional Engagement: Member of German Society for Quality (DGQ) and Society for Organisation (GFO). Regularly publishes in journals like Qualität in der Wissenschaft and Zeitschrift für Organisation .

Göran KauermannView profile

Professor

• Nonparametric Models
• Semi- and nonparametric analysis
• Generalized Linear Models
• +2 more

Prof. Dr. Göran Kauermann is a Full Professor of Statistics at the Ludwig-Maximilians-University Munich , holding the Chair of Applied Statistics in Social Sciences, Economics and Business . His research spans nonparametric models, generalized linear models, and network data analysis, with applications in economics, epidemiology, and data science. Education: Diplom in Economic Mathematics (1991, TU Berlin), PhD in Statistics (1994), Habilitation (Venia Legendi) in Statistics (2000) Kauermann’s research interests focus on penalized regression , network analysis , and statistical modeling in economics, social sciences, and public health. Recent work explores label uncertainty in machine learning , spatio-temporal conflict diffusion , and dynamic network models for economic and social data. Scientific trends in his publications include penalized splines for nonlinear modeling, network flow estimation in social and economic contexts, and label variation analysis in machine learning. His collaborations span climate zone classification , Covid-19 mortality modeling , and smart city parking analytics . Scientific Awards: Bruce Russett Award (2020) for political network research Leadership Roles: He served as Dean of the Faculty of Mathematics, Informatics and Statistics (2019–2021), Speaker of the Elite Master Program in Data Science (2016–2026), and Chair of the German Statistical Society (2005–2013). He also held editorial roles in journals like AStA Advances in Statistical Analysis and Statistical Modelling .

• Software Engineering
• Industry 4.0/IIoT Platforms
• Model-Based Software Development
• +7 more

Dr. Holger Eichelberger is part of the Academic Staff in the Software Systems Engineering (SSE) department at the University of Hildesheim's Institute of Computer Science. He is affiliated with Faculty 4: Mathematics, Natural Sciences, Economics and Computer Science. His roles include membership in the Managing Committee of the Institute of Computer Science and the Committee for Student Scholarships. He has extensive experience in model-based software development, Industry 4.0 platforms, and performance engineering. Research Interests: Software Engineering for adaptive systems, Asset Administration Shells (AAS), IIoT platforms, MLOps, container orchestration, and open-source tools like EASy-Producer and SPASS-meter. His work focuses on bridging research and industrial needs, particularly in smart manufacturing and edge computing. Publications highlight contributions to IIoT platform analysis, AI integration in Industry 4.0, and performance benchmarking of communication protocols. He has organized conferences like ICPE and SSP and reviewed for top journals such as IEEE Transactions on Software Engineering. Key projects include the IIP-Ecosphere platform and contributions to standards like AAS. Collaborations involve institutions like the University of the West Indies and industry partners through funded projects like BMBF AI-Lab HAISEM. His research emphasizes reproducibility, interoperability, and scalable solutions for industrial challenges.

Katrin RosenthalView profile

Assistant Professor

• Cell-free protein synthesis
• Enzyme cascades
• Bioprocess sustainability analyses
• +6 more

Prof. Katrin Rosenthal is an Assistant Professor of Biotechnology at the School of Science, Constructor University Bremen. Her research focuses on bioprocess engineering, enzyme cascades, and sustainable bioprocess design. She leads a team of PhD students and postdocs, including Siranjeevi Balakrishnan and Martin Becker, and has secured grants from DFG and BMWK-AiF-ZIM. Notable achievements include the Teacher of the Year Award (2024) and contributions to STRENDA Biocatalysis Guidelines. Her work bridges biocatalysis with environmental sustainability, leveraging cell-free systems and microfluidics. Education: Dr.-Ing (Engineering Doctorate) in Biotechnology Research Interests include: - Cell-free protein synthesis for biocatalysis - Kinetic modeling of enzyme cascades - Microfluidic systems for bioprocess intensification - Early-stage sustainability analysis of bioprocesses Publications highlight innovations in enzyme cascade optimization, biocatalytic screening, and data integration frameworks. Current projects include DFG-funded studies on enzyme stability and ZIM-funded enzymatic synthesis platforms for cGAMP derivatives. Grants/Projects: DFG (Liquid-phase design), BMWK-AiF-ZIM (cGAS-cGAMP platform) Teaching includes courses on Bioprocess Engineering and Biotechnology Lab Techniques. She actively contributes to DECHEMA's Zukunftsforum Biotechnologie and the COZYME COST Action.

Christoph KinkeldeyView profile

Lecturer

• Data Visualization
• Visual Analytics
• Uncertainty Visualization
• +3 more

Prof. Christoph Kinkeldey is a Lecturer at Hamburg University of Applied Sciences, affiliated with the Department of Information, Media and Communication within the Faculty of Design, Media and Information. He holds a doctorate in Geoinformatics from HafenCity University Hamburg (2015) and has conducted research globally, including at PennState University, University of Melbourne, and Inria. His work focuses on data visualization, visual analytics, and uncertainty visualization, emphasizing how visual tools aid decision-making in complex data environments. Education: PhD in Geoinformatics, HafenCity University Hamburg (2015) Research Interests: Interactive visual data analysis Uncertainty communication in visualizations Blockchain data exploration (e.g., Bitcoin network analysis) Evaluation of visualization techniques His research bridges cartography, computer science, and human-centered design to empower diverse stakeholders in understanding complex information. Publications: Recent work emphasizes uncertainty visualization for data analysts, machine learning interpretability, and blockchain analytics. Key contributions include the BitConduite tool for Bitcoin network analysis and participatory design methods for non-technical users. Awards: 2016 VAST Mini Challenge 2: Honorable Mention for Clear Analysis Strategy Advising & Collaboration: Currently on parental leave until August 2024, he collaborates with the gicentre (City, University of London) and Monash University’s Department of Human-Centered Computing. His research teams focus on interdisciplinary projects merging visualization theory with practical applications. Labs/Teams: Active in the gicentre’s visualization initiatives and Monash’s Human-Centered Computing group, contributing to open-source tools and international research networks.

Felix SchneiderView profile

Researcher

• Structural Dynamics
• Uncertainty Quantification
• Bayesian Methods
• +3 more

Felix Schneider is a Researcher at the Chair of Structural Mechanics at Technical University of Munich since 2018. He holds an M.Sc. in Civil Engineering from TU Munich (2018) and completed a semester abroad at the Norwegian University of Science and Technology. His research focuses on uncertainty analysis in structural and acoustic models, Bayesian updating techniques, and stochastic reduction methods in the frequency domain. He has contributed to advancements in rational polynomial chaos expansions and sparse Bayesian learning for structural dynamics applications. Education: 2011-2018: Study of Civil Engineering at Technical University of Munich 2018: Master of Science (M.Sc.) in Civil Engineering 2016: Semester abroad at Norwegian University of Science and Technology 2009: Abitur at Humboldtgymnasium Solingen Research emphasizes computational methods for structural dynamics, including: Bayesian parameter estimation for linear systems Rational surrogate models for uncertainty quantification Frequency-domain stochastic reduction techniques Applications in seismic risk assessment and vibroacoustic simulations Key contributions include a Maurer Söhne Prize for his Master's thesis and a published MATLAB toolbox for rational polynomial chaos expansions on the LRZ Git repository. Teaching responsibilities include courses on random vibrations, structural dynamics, and continuum mechanics. He has participated in research stays at ETH Zurich (2023) and collaborates with international institutions on uncertainty quantification projects.

Wangzhong MuView profile

Senior Lecturer

• Sustainable Metallurgy
• Microstructure Physics
• Alloy Design
• +3 more

Prof. Wangzhong Mu is a Senior Lecturer (Docent) in the Department of Materials Science and Engineering at KTH Royal Institute of Technology, Stockholm. His research focuses on sustainable metallurgy, microstructure physics, and alloy design. He leads the thermo-physical property analysis section in the Hultgren Lab and is affiliated with Digital Futures at KTH. Educations: PhD in Materials Science, KTH Royal Institute of Technology (2015) MSc/Bachelor's in Materials Science, Northeastern University, China Research Interests: Inclusion engineering and microstructure-property correlations in steels High-entropy alloy design using digital tools (AI/thermodynamic modeling) In-situ characterization via confocal microscopy and multiscale analysis Recycling-oriented steel production and CO2 reduction strategies Grants/Projects (selected): SSF Strategic Mobility Grant (2023-2024): Clean steel for sustainable future VINNOVA Mobility Grant (2022-2024): Hydrogen-based metallurgy STINT Project (2022-2023): Inclusion engineering for green steel EIT RawMaterials (ENDUREIT, 2019-2021): Durable steels at intermediate temperatures Labs/Teams: Hultgren Lab (materials characterization), Digital Futures (AI-driven metallurgy), and international collaborations with Hanyang University (South Korea), IIT Bombay (India), and Tohoku University (Japan).

• Science Communication
• Media History
• Health Communication
• +3 more

Prof. Dr. Susanne Vollberg is an Associate Professor of Media and Communication Studies at Martin Luther University Halle-Wittenberg (MLU). Currently serving as Vice Dean of the Faculty of Philosophy II and Chair of the Doctoral Committee, her roles emphasize institutional leadership alongside academic research. She holds a habilitation in Media and Communication Studies (2010) and completed her doctorate in the DFG Collaborative Research Center at the University of Siegen. Her career includes research roles at Leipzig University and leadership in DFG-funded projects on GDR television history. In research, Prof. Vollberg focuses on science communication (especially Public Science and Foresight), sustainability communication, health communication, media literacy, and media history with specializations in GDR/BRD television programming and children’s media worlds. She actively contributes to citizen science initiatives via the Make Science Halle vessel and serves on science communication networks like science2public and the “Blue Ribbon of Science” steering committee. Recent publications explore film music analysis (e.g., Harold and Maude studies), health education through 20th-century German television, and digital media’s role in youth self-optimization. Her work bridges historical media studies with contemporary communication challenges, emphasizing interdisciplinary approaches. Lectures and presentations address topics like YouTube’s role in science education, digital sustainability pedagogy, and media competence in family dynamics. No formal awards are listed, though her extensive editorial and committee roles highlight peer recognition. Prof. Vollberg oversees doctoral candidates and collaborates across institutions, reflecting her commitment to advancing media studies through both scholarly and public engagement.

• Electrocatalysis
• CO2 Reduction
• Energy Conversion Devices
• +3 more

Kazuyuki Iwase serves as Associate Professor at Tohoku University's Institute of Multidisciplinary Research for Advanced Materials since April 2025, following progressive appointments as Senior Assistant Professor (2023-2025) and Assistant Professor (2019-2023). His academic journey includes postdoctoral research at Paul Scherrer Institute (Switzerland) and multiple JSPS Research Fellowships. He maintains active collaborations with prominent researchers including Prof. Itaru Honma and Prof. Takaaki Tomai. Dr. Iwase's research focuses on electrocatalysis for sustainable energy conversion, specializing in carbon dioxide reduction reaction (CO2RR) and oxygen evolution reaction (OER) systems. His work spans nanomaterials engineering, electrocatalyst design, and device integration for renewable energy applications. Key methodologies include supercritical hydrothermal processing, mechanical alloying, and machine learning optimization of electrochemical systems. His publication record demonstrates consistent high-impact output with 36 accepted articles through 2025, featuring 11 as corresponding author and 15 as first/equal-first author. Recent work explores manganese nanospinels for OER, Ag-Sn intermetallics for CO2RR, and machine learning approaches for reaction optimization, showing strong interdisciplinary connections between materials science, electrochemistry, and sustainable engineering. The 5th Symposium for The Core Research Clusters for Materials Science and Spintronics Poster Award (2021) Student Presentation Award, Chemical Society of Japan (2016) International Exchange Support Award, Electrochemical Society of Japan (2016) SIEMME Best Oral Presentation Award (2014) Dr. Iwase has secured significant research funding as Principal Investigator, including a JST PRESTO grant (¥40,000,000) for CO2 conversion research and multiple JSPS Grants-in-Aid totaling over ¥59,000,000. His academic service includes peer review for prestigious journals including Angewandte Chemie and Nature Sustainability. He maintains active international engagement through invited lectures in Japan, India, and Switzerland, focusing on nanomaterials for electrocatalysis.

• Blockchain Technology
• Business Process Management
• Process Mining
• +3 more

Ingo Weber is a Professor affiliated with Technische Universität München (TU Munich) and Fraunhofer Gesellschaft. His research focuses on blockchain technology, business process management (BPM), and artificial intelligence (AI), with a particular emphasis on integrating these fields. He has held former positions at TU Berlin, CSIRO Data61, and other institutions. Current affiliations: TU Munich and Fraunhofer Gesellschaft Former affiliations: TU Berlin, CSIRO Sydney, University of New South Wales, SAP Research, and University of Massachusetts Amherst Research interests include blockchain applications in business processes, process mining, AI-driven systems, and sustainability-oriented process analysis. His work explores topics such as blockchain scalability, data confidentiality, and cost-efficient process execution on next-generation blockchains like Algorand. He has pioneered frameworks like SOPA for sustainability analysis and FhGenie for confidentiality-preserving AI. Key contributions include over 200 publications in journals like IEEE Access, Future Generation Computer Systems, and ACM Transactions on Management Information Systems. Recent work emphasizes AI-augmented BPM systems and the application of large language models (LLMs) in scientific contexts. Notable projects include blockchain-based process execution engines (e.g., Caterpillar), platform architectures for multi-tenant blockchain systems, and frameworks for evaluating payment channel networks. He has collaborated extensively with industry partners and academic institutions globally.

• Distributed Systems
• Blockchain Technology
• Graph Neural Networks
• +5 more

Hans-Arno Jacobsen is a Professor at Technische Universität München (Faculty of Computer Science, Germany) and the University of Toronto (Department of Electrical and Computer Engineering, Canada). His research spans distributed systems, blockchain technology, and machine learning for energy systems. Research Interests : Blockchain consensus algorithms, federated learning, graph neural networks, quantum computing applications, and energy-efficient distributed systems. Publication Trends : Recent work focuses on decentralized consensus in blockchains, energy-aware language model inferencing, quantum chemistry simulations, and graph neural network scalability. Collaborations : Regularly works with Ruben Mayer, Shashank Motepalli, and Gengrui Zhang on blockchain and machine learning projects.

Seifeddine FathalliView profile

Researcher

• Computer Networking
• Software-Defined Networking (SDN)
• Network Security
• +3 more

Seifeddine Fathalli is a PhD student and Researcher in the Internet Architecture department at the Max Planck Institute for Informatics. His work focuses on software-defined networking (SDN), network congestion control, and data plane development. He has contributed to seminal studies on BBRv3 and P4 programming frameworks. Fathalli holds a Master’s in Computer Engineering from the Technical University of Berlin (TU Berlin) and a Dipl.-Ing. in IT Networks and Telecommunications from INSAT, Tunis. Research Interests : - Software-Defined Networking (SDN) and P4 programmability - Network congestion control mechanisms (e.g., BBRv3) - Network security and verification in SDN environments - Public internet performance optimization Teaching : - Tutored Hot Topics in Data Networks (Winter 2020) and Data Networks (Summer 2020) at TU Berlin. Professional Experience : - Working student roles at TU Berlin (Network Verification in SDN), Charité University Medicine Berlin (IT/data management), and United Digital Group (IT Administrator). - Professional certifications: CCNA, P4 training (Barefoot Academy). Key Projects : - Co-designed P4Consist for SDN consistency (IEEE JSAC 2020) - Analyzed BBRv3 deployment implications in public internet (ANRW 2024)