Find Academic Supervisors

Matthias SpringsteinView profile

Researcher

• Computer Vision
• Deep Learning
• Multimedia Information Retrieval
• +5 more

Matthias Springstein is a researcher at the Technical Information Library (TIB), which is affiliated with Leibniz University Hannover. He is part of the Visual Analytics research group within TIB's Research & Development department, focusing on advanced computer vision and multimedia information retrieval techniques. His research interests span multiple areas of artificial intelligence with emphasis on computer vision applications. Springstein specializes in web-supervised learning for visual concepts, incremental learning approaches, and methods to minimize manual labeling efforts for training data. His work bridges theoretical machine learning with practical applications in digital humanities, particularly in art-historical image analysis and film/video studies. His publication record shows a consistent focus on multimodal analysis, with recent work exploring knowledge graphs for image classification, large-scale hierarchical classification of art-historical images, and computational tools for film analysis. The research demonstrates progression from foundational work in image-text relations and depth estimation toward increasingly sophisticated applications in cultural heritage and scholarly media analysis. Notable achievements include receiving the Best Paper Award at the International Conference on Multimedia Retrieval (ICMR) in 2019 for his work on semantic image-text relations. Springstein has developed TIB AV-Analytics, a computational platform for scholarly video analysis that has been presented at multiple major conferences (SIGIR 2023, SCSMI 2024), indicating significant impact in both the information retrieval and film studies communities.

Ina WagnerView profile

Visiting Professor

• Computer-Supported Cooperative Work (CSCW)
• Participatory Design
• Work Practices
• +2 more

Dr. Ina Wagner is a Visiting Professor at the University of Technology Vienna, with adjunct roles at Oslo and Sydney University of Technology. Trained in nuclear physics, she pioneered research in CSCW and Participatory Design. Her work examines work practices in healthcare, architecture, and gender dynamics. Key contributions include ethical frameworks for technology design and studies on women in STEM. Awards: Vienna Woman’s Prize (2011), Gabriele Possanner Staatspreis (2011). Editorial roles: Handling Editor for Conservation Biology . Policy engagement: EU Ethics in Science committees (1996-2001); Austrian Bioethics Commission.

• Human-Computer Interaction
• Social Robotics
• Dementia Care
• +5 more

Dr. David Unbehaun is a post-doctoral researcher at the University of Siegen working within Faculty III Information Systems and New Media. His research focuses on designing, implementing, and evaluating ICT-based systems for active and healthy aging, with particular emphasis on dementia care, cognitive and physical frailty, and age-related diseases. Dr. Unbehaun completed his education in business and public economics at the University of Halle-Wittenberg and Siegen, followed by a PhD in Socio-Informatics focusing on "Designing Assistive Technologies to Engage People with Dementia and their Caregivers." Prior to his academic career, he completed a 3-year apprenticeship in professional nursing in Düsseldorf and worked in various healthcare companies specializing in home and institutional care, where he was responsible for project management, quality management, and developing innovations in the healthcare sector. Dr. Unbehaun's research spans the intersection of human-computer interaction, computer-supported collaborative work, and healthcare technology. His work primarily focuses on developing and evaluating social robotics, augmented reality applications, and interactive systems for elderly care, particularly for people with dementia. He investigates how technology can support physical activity, cognitive capabilities, social interaction, and reminiscence therapy for individuals with cognitive impairments. His approach emphasizes participatory design methodologies, working closely with end-users including people with dementia, their caregivers, healthcare professionals, and care students. His recent publications demonstrate a clear trajectory toward increasingly sophisticated applications of social robotics and immersive technologies in healthcare settings. His work spans from foundational research on technology appropriation in dementia care to applied studies evaluating specific interventions in real-world care environments. A notable trend in his recent work is the expansion from dementia-specific applications to broader healthcare contexts including rehabilitation, sports, and education. Since 2016, Dr. Unbehaun has been involved in numerous national and international health-related projects. His work often involves collaboration with interdisciplinary teams across computer science, healthcare, and social sciences. While specific grant information isn't detailed in the provided text, his extensive publication record spanning multiple years suggests sustained research funding. Dr. Unbehaun is affiliated with the PraxLABS research group at the University of Siegen, which appears to focus on practical applications of socio-informatics in real-world settings. His work is closely connected to the university's Fab Lab Siegen and Social Media Observatories, suggesting engagement with hands-on technology development and community-based research approaches.

• Computational Imaging
• Computer Architecture
• Computer Engineering
• +3 more

Guangpu Yang is a Researcher at the Institute of Computer Architecture and Computer Engineering , part of the University of Stuttgart. His work focuses on Computational Imaging Systems within the ITI (Institute for Visualization and Interactive Systems) research group. He holds a position within Faculty 05 of the University, contributing to interdisciplinary projects at the intersection of computer engineering and advanced imaging technologies. Contact details include the institute's address at Universitätstraße 38, 70569 Stuttgart, Germany. No specific email or academic awards/grants are listed in the provided information.

Manfred ReichertView profile

Professor

• Business Process Management (BPM)
• Service-Oriented Architectures
• E-health
• +7 more

Prof. Manfred Reichert is a full professor at the University of Ulm, serving as Director of the Institute of Databases and Information Systems and Dean of Studies at the Faculty of Engineering and Computer Science. He holds dual expertise in Computer Science and Mathematics, with academic leadership roles including chairing examination boards and strategic research initiatives. His interdisciplinary affiliations include co-opted membership in the Faculty of Mathematics and Economic Sciences. Reichert's research focuses on Business Process Management (BPM), IoT-driven processes, service-oriented architectures, and e-health applications. Notable contributions include co-developing the ADEPT process management system and pioneering object-centric process modeling. He has led over 20 international research projects (EU FP7, DFG, Industry) and authored >200 peer-reviewed papers, earning an h-index of 60+ and prestigious awards like the Merckle Forschungspreis. Education: PhD in Computer Science & Mathematics Diploma Leadership: Former associate professor at University of Twente, former director of CTIT research center Service: Conference chair for BPM, CoopIS, EDOC; steering committee member for GI SIG Databases Recent work explores IoT integration in BPM, generative AI for process models, and neuroscience-informed usability studies. His research bridges technical innovation with human-centric design, addressing challenges in process lifecycle management, federated learning, and mobile health interventions. Awards: IFIP TC2 Manfred Paul Award, doIT Software Award Key Projects: BPMN extensions for IoT, data-driven healthcare solutions

Simon ChristView profile

Researcher

• Computational Biology
• Biophysics
• Reproducible Science
• +4 more

Dr. Simon Christ is a Researcher at the Department of Computational Biology within the Institute of Cell Biology and Biophysics at Leibniz University Hannover's Faculty of Natural Sciences. His office is located in Building 4160, Room 110 at Herrenhäuser Str. 2, 30419 Hannover. He can be contacted via phone (+49 511 762 16174) or email (christ@cell.uni-hannover.de). Christ holds a Doctor rerum naturalium (PhD) from the University of Potsdam (2020) and a Master of Science from Humboldt University of Berlin (2014). His doctoral research focused on morphological transitions of vesicles under nonuniform conditions, while his master's thesis examined non-Markovian systems in statistical physics. His research focuses on computational approaches to biological systems, including: Development of reproducible scientific workflows and open-source tools Agent-based simulations of biological processes Numerical solutions of differential equations in biological contexts Computational modeling of membrane dynamics and vesicle behavior Research software engineering practices and tools He is proficient in multiple programming languages including Julia, C/C++, MATLAB, Mathematica, Python, and R, and is a certified instructor for The Carpentries. Christ's recent publications demonstrate a strong focus on research software engineering, computational biology methods, and biophysical modeling of cellular systems. His work frequently appears in computational biology, biophysics, and software engineering journals, with consistent contributions to open science practices and reproducible research methodologies. No specific awards or student advising relationships are mentioned in the available documentation. His current work appears to be conducted within the computational biology research group at Leibniz University Hannover, with collaborations extending to other institutions including the University of Potsdam and Max Planck Institute.

• Algorithms
• Computational Geometry
• Shortest Path Planning
• +4 more

Stefan Funke is a Professor at the University of Stuttgart's Institute for Formal Methods in Computer Science, part of the Faculty of Computer Science, Electrical Engineering and Information Technology. His work focuses on algorithm design and computational geometry with applications in road networks, trajectory analysis, and geographic information systems. He leads the Algorithmics Group, developing efficient algorithms for shortest path planning, network optimization, and privacy-preserving queries. Research interests include geometric algorithms, graph theory, and practical implementations of theoretical results in transportation and spatial data analysis. Notable contributions involve contraction hierarchies for fast shortest path queries, trajectory mining techniques, and methods for preserving privacy in network-based computations. Recent work emphasizes scalable solutions for large-scale road networks, including simplification methods that preserve topological features and energy-efficient routing strategies for electric vehicles. His research often bridges theoretical foundations with real-world applications in navigation systems and smart mobility solutions. Awards and grants are not explicitly listed in the provided data, but his extensive publication record indicates sustained recognition in algorithmic research. He advises on multiple interdisciplinary projects involving spatial data processing and algorithm engineering.

Tiare FeuchtnerView profile

Assistant Professor

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +4 more

Dr. Tiare Feuchtner is a Tenure-Track Assistant Professor of Human-Computer Interaction at the University of Konstanz since 2021. She previously worked as a postdoctoral researcher at the Technical University of Vienna and Aarhus University, where she coordinated the MADE Fast project. PhD: Computer Science, Aarhus University (2018), thesis: 'Designing for Hand Ownership in Interaction with Virtual and Augmented Reality' Master's: Computer Science, Berlin Institute of Technology Bachelor's: Media Informatics, Technical University of Vienna Her research focuses on Human-Computer Interaction, emphasizing embodiment and novel user interfaces for immersive cross-reality (XR) technologies. She investigates embodied user interfaces that enable direct interaction through virtual bodies ('avatars') with transformations, augmentations, and 'superpowers' via multisensory feedback. Current projects include Interoceptive Signalling in Mixed Reality and Real-Time Optimization of XR User Interfaces. Her recent articles explore hybrid input devices, haptic props for 3D manipulation, physiological feedback in collaboration, and adaptive XR interfaces. She has received awards for her work, including the Microsoft Imagine Cup (2013). She actively contributes to academic service through conference organization (e.g., AlpCHI'26, QiVC'23), program committees (CHI, ISMAR), and workshops (Women* in Computing, Hybrid User Interfaces). Her teaching includes courses on human-computer interaction, Unity, and spatially-aware interactive spaces.

Tobias GlasmachersView profile

Professor

• Machine Learning
• Artificial Intelligence
• Optimization Algorithms
• +6 more

Prof. Dr. Tobias Glasmachers is a Full Professor at the Institut für Neuroinformatik , Ruhr-Universität Bochum, Germany, specializing in the Theory of Machine Learning . He leads the Optimization of Adaptive Systems group and holds appointments in both Computer Science and Interdisciplinary AI research. Key Research Areas : Optimization algorithms, evolutionary computation, reinforcement learning, supervised learning, and neural networks Technical Focus : Gradient-based methods, support vector machines, and adaptive coordinate descent Applications : Robotics, waste sorting facilities, 3D game environments (e.g., Doom/Minecraft), and human-centered AI design Notable Contributions : Development of LM-MA-ES evolution strategy, Hessian Estimation Evolution Strategy, and tachAId tool for ethical AI design. His work bridges theoretical analysis with practical implementations across diverse domains. Teaching : Offers courses in Informatik 1 - Programmieren, Machine Learning: Supervised Methods, and Evolutionary Algorithms. Supervises numerous Bachelor's and Master's theses on AI/ML applications.

Benedikt BläsiView profile

Research Professor

• Photovoltaics
• Optics
• Nanoimprint Lithography
• +3 more

Dr. Benedikt Bläsi is Science Manager for Optics for Photovoltaics at Fraunhofer ISE's Photovoltaics Division. His research focuses on optical concepts for solar cells including light trapping structures, nanoimprint lithography, and color engineering for building-integrated PV. Key innovations include the MorphoColor® concept inspired by butterfly wings for colored PV modules, hyperuniform disordered structures for light management, and roller-nanoimprinted textures. Recent work advances III-V/Si multi-junction cells achieving 36.1% efficiency and computational methods for optical modeling. He holds editorial roles at Optics Express and leads projects on terawatt-scale photovoltaics, collaborating globally on optical technology roadmaps for sustainable energy scaling.

Jürgen PfefferView profile

Professor

• Computational Social Science
• Big Data Analysis
• Social Media Dynamics
• +4 more

Prof. Jürgen Pfeffer is a Professor of Computational Social Science & Big Data at the Technical University of Munich (TUM), affiliated with the TUM School of Social Sciences and Technology. His research bridges social and computer science, focusing on large socio-technical systems, algorithmic challenges, and dynamics like online firestorms and hate speech. He holds a doctorate from Vienna University of Technology and has postdoctoral experience at Carnegie Mellon University. Key research areas include computational social science, network analysis, and critical data studies. He leads interdisciplinary projects on online misogyny, disaster communication, and AI ethics. His work addresses methodological rigor in handling big data, visualization of complex networks, and policy implications of social media dynamics. Pfeffer has authored numerous publications in top journals like Science and IEEE, and serves on editorial boards for Frontiers in Big Data and EPJ Data Science. He actively participates in global conferences, advocating for ethical AI and responsible data practices. His research projects span collaborations with institutions worldwide, addressing societal challenges through data-driven insights.

Petra MutzelView profile

Professor

• Graph Algorithmics
• Graph Learning
• Combinatorial Optimization
• +3 more

Petra Mutzel is a Professor of Computer Science at the University of Bonn. Her research focuses on graph algorithmics, temporal networks, and combinatorial optimization with applications in data science and bioinformatics. She holds a PhD in Computer Science from the University of Cologne (1994) and a Diplom in Mathematics from the University of Augsburg (1990). Her work emphasizes algorithmic solutions for complex graph problems, including temporal graph analysis, graph learning, and optimization frameworks for real-world networks. She has contributed to open-source libraries like Tglib for temporal graph processing and frameworks like Scaffold Hunter for medicinal chemistry. Her research spans theoretical foundations and practical implementations, with notable contributions to graph drawing, vehicle routing optimization, and protein complex analysis. Mutzel’s recent publications (2022-2025) explore temporal network dynamics, robust combinatorial optimization, and scalable graph kernel methods. She actively engages in academic leadership, organizing conferences such as WALCOM 2022, and serves on editorial boards for journals in algorithms and computational geometry.

Alexander I. BobenkoView profile

Professor

• Geometry
• Discrete Differential Geometry
• Mathematical Physics
• +3 more

Professor Alexander I. Bobenko is a faculty member at the Institute of Mathematics, Technische Universität Berlin, holding the position of Professor in the Department of Geometry and Mathematical Physics. His research focuses on Discrete Differential Geometry, Integrable Systems, and Mathematical Physics, with notable contributions to the theory of discrete surfaces, circle patterns, and geometric structures. He leads the research group AG Geometrie und mathematische Physik and is involved in the DFG Collaborative Research Center (SFB/TRR 109) 'Discretization in Geometry and Dynamics.' PhD advisor for over 20 students, including Carl O. Lutz and Alexander Fairley. Recipient of extensive funding for projects on discrete geometry and integrable systems. His research interests span geometry visualization, Riemann surfaces, and applications of discrete methods in mathematical physics. Bobenko has published prolifically on topics like discrete conformal maps, minimal surfaces, and integrable systems, with over 130 peer-reviewed articles. His work bridges classical and discrete geometry, emphasizing computational and algorithmic approaches.

Johanna KerchView profile

Lecturer

• Glaciology
• Structural Geology
• Geophysics
• +5 more

Dr. Johanna Kerch is a Lecturer and Postdoctoral Researcher at the University of Göttingen's Faculty of Geoscience and Geography, Department of Structural Geology and Geothermics. Her research focuses on computational structural glaciology, particularly statistical analysis of glacier ice properties, crystal anisotropy effects on ice flow, and geophysical methods for ice body structure analysis. She advocates for open-source software, digital literacy, and FAIR data practices in academia, while supporting gender equality and work-life balance initiatives in STEM. Education & Teaching: Offers 5 bachelor and 2 master's research project opportunities in glaciology and structural geology. Active in curriculum development emphasizing computational tools and ethical data management. Collaborations & Funding: Engaged in projects like the East Greenland Ice Stream (NEGIS) studies and EGRIP ice core research. Collaborates with institutions such as the Alfred Wegener Institute and international glaciology networks. Publications: Over 50 peer-reviewed articles and datasets on ice microstructure, isotopic records, and glacial dynamics. Key contributions include studies on shear margin dynamics in Greenland and Alpine glacier stratigraphy.

• Explainable AI
• Interpretable Machine Learning
• Deep Learning
• +13 more

Wojciech Samek is a Professor in the Department of Electrical Engineering and Computer Science at the Technical University of Berlin and Head of the AI Department at Fraunhofer Heinrich Hertz Institute (HHI), Germany. He holds a joint appointment, bridging academic research and industrial application in artificial intelligence. He is a Fellow at BIFOLD and ELLIS Unit Berlin, and a Principal Investigator in several DFG projects including DeSBi and BIOQIC. PhD (Dr. rer. nat.) with distinction, Technical University of Berlin, 2014 Studies in Computer Science, Humboldt University, Heriot-Watt University, University of Edinburgh His research centers on Explainable AI (XAI) , Trustworthy Deep Learning , and Efficient AI . He pioneered Layer-wise Relevance Propagation (LRP), a foundational method for interpreting deep neural networks. His work spans model interpretation, robustness against adversarial attacks, neural network compression, federated learning, and applications in healthcare, communications, and multimedia. The recent articles highlight a strong trend toward extending explainability beyond deep models , with research on concept-level explanations, unsupervised learning interpretability, and XAI-driven model improvement. There is a consistent focus on robustness, privacy, and efficiency in distributed learning settings, particularly for federated and edge AI. Applications in medical AI and neuroscience are prominent, emphasizing safety and interpretability in high-stakes domains. Best Paper Award, Pattern Recognition (2020) Digital Signal Processing Best Paper Prize (2022) Fellow, BIFOLD - Berlin Institute for the Foundation of Learning and Data Member, Germany's Platform for Artificial Intelligence Senior Editor, IEEE TNNLS; Associate Editor, Pattern Recognition, Digital Signal Processing, PLoS ONE Area Chair, NeurIPS, ICML, NAACL Program Chair, IEEE MLSP 2023 Contributor to ISO/IEC MPEG-17 NNC standard Prof. Samek advises a large group of PhD students and leads a vibrant research team at Fraunhofer HHI and TU Berlin. His group has secured significant funding through DFG, BIFOLD, and industrial collaborations. He has co-authored over 200 peer-reviewed papers, many of which are ESI Hot or Highly Cited. He is deeply involved in organizing workshops and tutorials on XAI, federated learning, and neural compression at top venues like NeurIPS, ICML, CVPR, and IEEE conferences. His lab develops open-source tools such as the LRP Toolbox , Keras Explanation Toolbox , DeepCABAC , and Quantus , promoting reproducibility and adoption of interpretable and efficient AI methods. The team is actively working on next-generation AI that is not only accurate but also transparent, robust, and trustworthy.