View-Based Modeling Professors and Supervisors in Germany | ApplySharif

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Showing 31-45 of 241 supervisors

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Federico TombariView profile

Lecturer

Technical University of MunichGermany

Federico Tombari is a Director of Research at Google Zurich and a Lecturer (Privatdozent) at the Chair of Computer Aided Medical Procedures (CAMP) at TUM. He leads applied research in Computer Vision and Machine Learning, focusing on 3D vision, robotics, augmented reality, autonomous driving, and healthcare applications. His work emphasizes unsupervised learning, large multimodal models, neural radiance fields, and scene graphs. Education & Professional Background: As PD Dr. Ing. Habil., he holds a habilitation in engineering and has been active in academic and industrial research for over a decade. His roles include Area Chair for top conferences like CVPR and ECCV, and Associate Editorships for journals like IJRR. Research Interests: Federico’s research spans 3D scene understanding, object recognition, SLAM, and novel view synthesis. He explores applications in surgical robotics, autonomous systems, and medical imaging. Recent trends in his work include generative models for scene generation and semantic scene graphs for holistic modeling. Grants & Industry Collaborations: He has led projects with Toyota, BMW, Audi, Zeiss, and others, focusing on 3D perception, autonomous driving, and medical vision. His work bridges academia and industry, emphasizing practical applications. Labs & Teams: He contributes to labs like DHM (Deutsches Herzzentrum München), NARVIS Lab, and RobUSt (Robotics and Ultrasound), advancing interdisciplinary research in healthcare and robotics.

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Torsten SteinhoffView profile

Professor

University of SiegenGermany

Torsten Steinhoff is a Professor of Didactics of the German Language at the Department of Germanic Studies, University of Siegen, Faculty of Arts and Humanities. His research and teaching focus on theoretical, methodological, and empirical aspects of language acquisition and instruction from elementary to university levels. His primary research interests include: Writing didactics (Schreibdidaktik) Vocabulary didactics (Wortschatzdidaktik) Language-specific and disciplinary learning (Sprache im Fach) Digital communication and AI in education Development of complex learning arrangements (Lernarrangements) Steinhoff investigates how digital tools like ChatGPT can be integrated into writing instruction, promoting argumentative writing through structured learning tasks. His recent work (2023–2025) analyzes human-AI collaboration in writing, proposing models such as GPT as Ghost, Partner, or Tutor. He emphasizes a post-digital didactic approach, balancing traditional literacy with digital competencies. His publications reflect a strong trend in digital transformation of writing, multilingual education, and empirical interventions in secondary classrooms. He leads research projects funded by BMBF and MKW NRW, including the "AI Writing Arrangements" project tested in 8th-grade classes. Scientific contributions and collaborations: Co-editor of research handbooks on empirical writing didactics Collaborator with scholars like Nicole Marx, Katrin Lehnen, and Joachim Grabowski Active contributor to journals such as Didaktik Deutsch , BiSS-Journal , and Waxmann publications Hosts a research team at lernarrangements.de He advises on academic language development, text procedures, and vocabulary transfer across modalities and subjects. His lab develops open educational resources (OER) for digital writing and communication, contributing to platforms like Twillo.

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Alina RoitbergView profile

Assistant Professor

University of StuttgartGermany

Alina Roitberg is a Junior Professor (Assistant Professor) at the University of Stuttgart , affiliated with the Faculty of Computer Science, Electrical Engineering and Information Technology . Her research focuses on advancing computer vision, machine learning, and robotics applications, particularly in human activity recognition, domain adaptation, and synthetic data generation. She explores challenges in action understanding, cross-domain generalization, and real-world deployment of AI systems in fields like healthcare, autonomous vehicles, and industrial automation. Her work emphasizes robust learning under noisy conditions, multimodal data fusion, and ethical AI applications. Recent projects include foundational studies on large language models in construction (AEC), video-based muscle group estimation, and improving driver activity recognition for autonomous vehicles. She also investigates circular factory design through uncertainty-aware process optimization and human-robot interaction. Dr. Roitberg's contributions span academic publications and industrial collaborations, addressing both theoretical advancements and practical implementations. Her research bridges computer vision techniques with real-world problems, emphasizing scalability and ethical considerations in AI deployment.

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Amr RizkView profile

Professor

University of Duisburg-EssenGermany

Professor Amr Rizk is the Director of the Networks and Communication Systems (NCS) Lab at the University of Duisburg-Essen, where he has been serving as Professor since April 2021. Previously, he was Assistant Professor at Ulm University (2019-2021) and completed his habilitation at TU Darmstadt in 2019. His academic journey includes research positions at prestigious institutions including University of Massachusetts Amherst, University of Warwick, and TU Darmstadt where he was an Athene Young Investigator. Professor Rizk's research spans multiple aspects of networking and communication systems with a particular focus on network performance analysis, stochastic modeling, and practical implementations. His work bridges theoretical foundations with real-world applications, especially in content delivery, video streaming, and network protocols. He has made significant contributions to network calculus, quality of experience optimization, and novel approaches to congestion control and caching mechanisms. His publication record demonstrates consistent high-impact contributions across top networking conferences and journals. Recent work shows a growing emphasis on programmable data planes, AI/ML applications in networking, and advanced techniques for network measurement and performance prediction. His research group at Duisburg-Essen maintains strong connections with both academic and industrial partners in the networking ecosystem. Best Paper Award at ACM MMSys Conference (2023) Distinguished TPC Member for IEEE INFOCOM (2020, 2022) Best Paper Award at ACM/USENIX Middleware Conference (2017) Athene Young Investigator Award, TU Darmstadt (2017) Professor Rizk serves as Associate Editor for Elsevier Computer Communications and has extensive experience with research funding bodies as a reviewer. His leadership extends to conference organization, including roles as PC Co-Chair for IEEE MIPR (2023) and Steering Committee member for Workshop on Network Calculus (2022). He maintains active participation in numerous top networking conferences as Technical Program Committee member, reflecting his standing within the international networking research community.

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Yan ZhangView profile

Lecturer

Max Planck Institute for InformaticsGermany

Yan Zhang is a scientific leader at Meshcapade and a guest lecturer at ETH Zurich's Computer Vision and Learning Group (VLG). He previously served as a postdoctoral researcher at ETH Zurich (2020-2023) and research intern at Max Planck Institute for Intelligent Systems (2018-2020). His research focuses on generative human foundation models, human motion and behavior synthesis, 3D human perception, and applications in AR/VR, embodied AI, and interactive avatars. He has pioneered methods for scene-conditioned motion generation, contact-aware reconstruction, and egocentric interaction modeling. His recent publications (2025-2020) span Real-time motor models for avatars (PRIMAL, ICCV'25) Diffusion architectures for motion (RoHM, CVPR'24) Scene-population algorithms (Odysseus, CVPR'22) Physics-aware reconstruction (EgoHMR, ICCV'23) Whole-body grasping models (SAGA, ECCV'22) Multi-modal datasets (EgoBody, ECCV'22) Scientific recognition includes the Qualcomm Innovative Fellowship Europe 2023 . He organized workshops at CVPR'25, ECCV'24, and ECCV'22, and served on senior program committees (AAAI'26) and area chairs (CVPR'25). As co-supervisor, he mentored student projects on diffusion-based hand motion capture, 3D pose estimation, body-scene interaction, and mixed reality navigation at ETH Zurich (2020-2023). His work bridges computer vision, machine learning, and computer graphics to advance human-centric AI systems.

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Leif KobbeltView profile

Professor

RWTH Aachen UniversityGermany

Leif Kobbelt serves as a University Professor at RWTH Aachen University, leading the Computer Graphics Group within the Department of Computer Science (Informatik 8). His research focuses on advancing geometry processing, interactive visualization, and computer graphics through innovative algorithmic solutions and interdisciplinary collaborations. Professor Kobbelt's research program centers on geometry acquisition and processing, with significant contributions to mesh generation, surface reconstruction, and neural rendering techniques. His work bridges theoretical geometry with practical applications in computer vision, photo-realistic image synthesis, and multimedia data transmission, often involving collaborations with industry partners and international research teams funded by DFG and EU sources. Recent publications (2023-2025) reveal a strategic integration of deep learning with traditional geometry processing, particularly in Gaussian splatting for real-time rendering, NeRF-based 4D content generation, and robust mesh Boolean operations. His group maintains leadership in quad mesh optimization and surface mapping while expanding into immersive visualization techniques for complex data analysis. The group has earned recognition through prestigious awards: Günter Enderle Best Paper Award at Eurographics 2023 Best Paper Award (1st place) at Symposium on Geometry Processing 2022 Honorable Mention for Best Paper at ACM Symposium on Virtual Reality Software and Technology Funding from Deutsche Forschungsgemeinschaft and European Union programs supports the group's research infrastructure and international collaborations. The team actively supervises graduate theses while developing open-source software tools that translate theoretical advances into practical industry applications, particularly in digital fabrication and immersive visualization systems. The Computer Graphics Group operates as a central hub for visual computing research at RWTH Aachen, maintaining strong ties with both academic institutions and technology companies. Their recent work on virtual reality educational tools and high-fidelity 3D reconstruction systems demonstrates commitment to knowledge transfer and real-world impact beyond traditional publication venues.

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Val TannenView profile

Professor

University of TrierGermany

Val Tannen is a Professor at the University of Pennsylvania, specializing in database systems, provenance analysis, and programming languages. His research focuses on data management, query languages, and systems like DBSP and ORCHESTRA. Collaborations include work with co-authors such as Zachary Ives, Susan Davidson, and Todd Green. Key research interests include provenance for databases, incremental view maintenance, and data integration. His work bridges theoretical foundations and practical applications in systems like DBSP for stream processing and ORCHESTRA for collaborative data sharing. Publications span provenance frameworks, query optimization, and distributed systems. While no awards are explicitly listed, his contributions to database theory and systems are widely recognized.

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Steffen BeckerView profile

Professor

University of StuttgartGermany

Steffen Becker is a Professor at the University of Stuttgart's Faculty of Computer Science, Electrical Engineering and Information Technology, affiliated with the Institute for Software Engineering's Software Quality and Architecture group. His work focuses on software engineering, cloud systems, model-driven engineering, and cybersecurity. He leads research in architectural modeling tools like Slingshot, GUI testing frameworks (ViMoTest), and hardware security analysis. Recent studies explore AI integration in testing, education, and automotive systems (CARISMA). Research interests include elasticity modeling, self-adaptive systems, and educational technology. His 2025 publications address issues like end-user hardware comprehension, FPGA security, and LLM-driven test generation. Notable tools developed include the Slingshot Simulator for cloud-native systems and Gropius for cross-component issue management. Becker contributes to both theoretical advancements and practical implementations in software quality, security, and cloud infrastructure. Key Areas: Software Architecture, Cyber-Physical Systems, Testing, Reverse Engineering Tool Developments: ViMoTest, Slingshot, Gropius Education Focus: Online programming pedagogy and curriculum innovation His work bridges foundational research with industry applications, addressing challenges in automotive computing, cloud elasticity, and human-centric security awareness. Recent efforts emphasize explainable hardware (XHW) and AI's role in qualitative analysis automation.

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Wanja HoferView profile

Researcher

University of Erlangen–NurembergGermany

Dr. Wanja Hofer is a former research staff member at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). She specialized in embedded systems, real-time operating systems, and aspect-oriented programming. Her research focused on optimizing hardware-centric systems like Sloth and CiAO, addressing challenges in interrupt handling, scheduling, and software product line variability. Her academic journey includes a PhD in 2014 titled Sloth: The Virtue and Vice of Latency Hiding in Hardware-Centric Operating Systems . She contributed to key projects such as Sloth (time-triggered RTOS) and CiAO (aspect-oriented OS family), emphasizing scalability and configurability for automotive and embedded domains. Hofer also held roles like Web chair for EuroSys 2009 and co-maintained the EuroSys Research Directory. Her teaching involved Basics of Systems Programming in C and OS-related seminars. She advised over 15 graduate students on topics ranging from MPU-based task isolation to filesystem-level variability management. Notable contributions include hardware-accelerated interrupt handling, aspect-oriented OS design, and embedded system energy optimization. Hofer currently works at Brose Fahrzeugteile, applying her expertise in embedded systems and real-time computing to automotive technologies. Her work bridges academic innovation with industrial applications, particularly in safety-critical and resource-constrained environments.

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Jan SalmenView profile

Researcher

Ruhr University BochumGermany

Dr. Jan Salmen is a researcher at Ruhr University Bochum's Faculty of Computer Science, affiliated with the Institute of Neuroinformatics (INI). His work focuses on real-time systems, computer vision, and machine learning. Doctoral thesis: Efficient video-based driver assistance systems Salmen's research spans autonomous driving, traffic sign recognition, stereo vision, and sports analytics. He has contributed to benchmarks in traffic sign detection and soccer analysis. Publications highlight his expertise in image processing, pattern recognition, and sensor fusion for autonomous systems. Key trends include optimization of machine learning algorithms for real-time applications. He collaborates with interdisciplinary teams at INI, which integrates experimental psychology, neurophysiology, and robotics into artificial cognitive systems research.

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Mohammad SadoghiView profile

Professor

University of TrierGermany

Mohammad Sadoghi is a Professor at the University of California, Davis, with former affiliations at Purdue University, IBM T.J. Watson Research Center, and the University of Toronto. His research focuses on distributed systems, blockchain technologies, consensus protocols, and fault-tolerant computing. He has contributed extensively to transaction processing, stream processing architectures, and the integration of edge-cloud systems with blockchain frameworks. Current Affiliation: University of California, Davis Former Affiliations: Purdue University, IBM, University of Toronto Research Interests include consensus algorithms, Byzantine fault tolerance, distributed ledger technologies, and scalable data processing. He has pioneered systems like ResilientDB and ByShard, addressing challenges in global-scale distributed systems and blockchain fabrics. His work bridges theoretical foundations with practical implementations, emphasizing real-world applications in edge computing and hybrid cloud-edge environments. Key publications highlight advancements in consensus protocols, blockchain scalability, and fault-tolerant architectures. Recent trends in his work focus on concurrent consensus mechanisms, DAG-based systems, and secure geo-replication. Contributions span both academic publications and industry-oriented solutions, such as the Bedrock platform for BFT protocol analysis. Grants and advising roles are implied through his extensive research output, though specific grants are not detailed in the provided text. His collaborations include projects on self-curating databases (e.g., L-Store) and systems like SplitJoin for stream processing.

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Kanwarpal SinghView profile

Researcher

Max Planck Institute for the Science of LightGermany

Kanwarpal Singh serves as Group Leader and Head of the Microendoscopy Research Group at the Max Planck Institute for the Science of Light (MPL) in Erlangen, Germany. His research focuses on developing and applying advanced optical imaging techniques, particularly Optical Coherence Tomography (OCT) and related technologies, for biomedical applications. As part of the Max Planck Society, one of Germany's premier research organizations, his work bridges fundamental optical physics with clinical medicine. Dr. Singh's research interests center on biomedical optics and imaging, with particular expertise in endoscopic OCT, optical elastography, and polarization-sensitive imaging techniques. His work spans from developing novel optical systems and probes to applying these technologies in clinical settings for disease diagnosis and monitoring. Key areas include gastrointestinal imaging, dermatological applications, and neurological tissue characterization. His research demonstrates a consistent trajectory from fundamental optical engineering to translational medical applications, with particular emphasis on improving imaging depth, resolution, speed, and clinical usability. Analysis of Dr. Singh's recent publications (2021-2025) reveals a strong focus on overcoming technical limitations in biomedical imaging. His work addresses critical challenges including motion artifacts in in vivo measurements, depth of focus limitations, polarization sensitivity issues, and the development of portable, clinically practical systems. The research shows increasing clinical relevance, with applications spanning inflammatory bowel disease monitoring, esophageal tissue analysis, skin biomechanics, and central nervous system regeneration studies. Dr. Singh leads the Microendoscopy Research Group within the MPL's research structure. While specific lab details aren't provided in the text, his numerous publications describing novel probe designs and imaging systems suggest an active laboratory focused on optical system development, with strong connections to clinical collaborators for in vivo and patient studies. His research appears to involve both theoretical modeling and practical implementation of optical technologies.

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Fangneng ZhanView profile

Research Fellow

Max Planck Institute for InformaticsGermany

Currently a Research Fellow at Harvard University & MIT , Fangneng Zhan specializes in Neural Rendering and Generative AI . His research focuses on developing evolutive rendering frameworks, 3D-aware generative models, and multimodal synthesis techniques. Previously, he was a postdoctoral researcher at the Max Planck Institute for Informatics under Prof. Christian Theobalt. He earned his Ph.D. in Computer Science & Engineering from Nanyang Technological University, Singapore and a Bachelor's in Communication Engineering from the University of Electronic Science and Technology of China . His work spans 3D reconstruction, robotics applications , and lighting estimation , with significant contributions to SIGGRAPH , NeurIPS , and CVPR conferences. Recent research highlights include evolutive gauge transformations for neural fields, generalizable 3D style transfer via Gaussian splatting, and multimodal synthesis frameworks leveraging pre-trained models like CLIP and Stable Diffusion. He has co-authored Top50 Popular Paper in TPAMI 2023 and organized workshops at CVPR 2024 on generative models. Scientific Awards: Top50 Popular Paper, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023 Collaborative Network: Mentored students at institutions like Harvard, NTU, and ETH Zurich. His projects include datasets for lighting estimation and real-time scene text detection systems.

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Detlev MarpeView profile

Researcher

Fraunhofer-GesellschaftGermany

Detlev Marpe is a leading researcher at the Fraunhofer Heinrich Hertz Institute (HHI), serving as Head of the Video Coding & Analytics Department and Head of the Image & Video Coding Group. His work focuses on advancing video compression standards, including HEVC (H.265) and its extensions. He has contributed significantly to tools like entropy coding, transform coding, and scalable video coding. His research emphasizes efficient compression techniques, such as adaptive context models and wavelet-based methods, with applications in multimedia communication and low-delay video encoding. Affiliations: Fraunhofer Institute for Telecommunications HHI, Berlin, Germany Roles: Department Head, Research Group Leader, and Adjunct Lecturer at TU Berlin (2013/14) Research Interests: Video coding standards (HEVC, H.264/AVC), entropy coding (CABAC), wavelet-based compression, scalable video coding (SVC), multiview video coding (MVC), and rate-distortion optimization. His work bridges theoretical advancements with practical implementations, addressing challenges in compression efficiency, scalability, and real-time applications. Publications & Awards: Over 200 publications in top-tier journals and conferences, including IEEE Transactions and SPIE. Notable awards include the Chester Sall Best Paper Award and multiple Best Paper Awards from IEEE journals. His contributions to video coding standards have been adopted in global specifications like MPEG and ITU-T. Grants & Labs: Involved in major research projects on HEVC extensions, 3D video coding, and low-delay applications. Collaborates with industry partners and academic institutions globally. His team at HHI develops reference software and test models for emerging standards.

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Volker RodehorstView profile

Professor

Bauhaus University WeimarGermany

Univ.-Prof. Dr.-Ing. habil. Volker Rodehorst is a full professor of computer vision at Bauhaus-Universität Weimar, holding positions in both the Faculty of Media and Faculty of Civil Engineering. His research focuses on photogrammetric computer vision, image analysis, 3D reconstruction, and structural health monitoring with applications in civil infrastructure inspection and urban modeling. He leads projects like ev.AI.luate and InfraCloud, leveraging AI and UAS technologies for infrastructure assessment. Education: PhD (2003): Technical University of Berlin, Faculty of Civil Engineering & Applied Geosciences Habilitation (2013): TU Berlin, Faculty of Electrical Engineering & Computer Science Computer Science Diploma (1994): TU Berlin Research Interests: UAS-based structural inspection using multi-view stereo and deep learning Crack detection and segmentation in concrete structures Automated building age estimation for energy modeling Flight path planning optimization for complex structures Integration of computer vision into BIM workflows Publications: Recent work emphasizes robust algorithms for crack detection (Omnicrack30k benchmark), UAS flight path optimization, and semantic segmentation challenges in bridge inspections. Key contributions include MVCrackViT and CISOL datasets advancing structural analysis methodologies. Awards: Best Academic Performance Prize (1994) - TU Berlin ISPRS Presidential Citation (2008) for WG III/2 leadership Grants & Labs: Leads Bauhaus' 3D-RealityCapture-ScanLab and coordinates EU projects like AISTEC-PRO. Active in developing modular solutions like smoodPLAN for infrastructure inspection. Teaching: Offers courses in photogrammetric computer vision, geodesy, and parallel systems. Supervises PhD students in structural health monitoring and computer vision.

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