Image-based Localization Professors and Supervisors in Germany | ApplySharif

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Shikha DhimanView profile

Professor

Max Planck Institute for ChemistryGermany

Shikha Dhiman is a Professor of Physical Chemistry of Supramolecular Systems at the Department of Chemistry, Johannes Gutenberg University Mainz (Germany), and a Junior Faculty member at Max Planck Graduate Center, Mainz. Her academic journey includes a Ph.D. from Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), India, under Prof. Subi J. George, followed by postdoctoral work at Eindhoven University of Technology under Prof. Bert Meijer. She has received prestigious awards including the Marie Skłodowska-Curie Fellowship and Thieme Chemistry Award 2024. Bachelor's in Chemistry from Hindu College, University of Delhi Integrated Ph.D. in Supramolecular Chemistry from JNCASR Postdoctoral training at Eindhoven University of Technology Her research focuses on creating life-like materials by understanding structure-dynamics-function relationships at molecular interfaces using advanced techniques. Key areas include supramolecular self-assembly, non-equilibrium systems, and bioinspired soft matter engineering. Her publications highlight spatiotemporal patterns, transient coacervation, and ATP-fueled materials. Scientific awards include Thieme Chemistry Award 2024 Certificate of Excellence 2024 by Bharat Vasi Germany e.V Marie Curie Fellowship (2021) Freiburg Rising Star (2021) . She has lectured on macromolecular chemistry and supramolecular systems at JGU Mainz and tutored at TU/e. Her lab explores non-equilibrium spatiotemporal patterns, interactions with biological systems, and small molecule coacervates. Current projects include SFB 1552 and GRK 2516. The lab team includes Ph.D. student Mohit Kumar and postdocs like Dr. Surbhi Sharma.

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David KeaysView profile

Professor

Ludwig Maximilian University of MunichGermany

Prof. David Keays serves as Chair of Organismal and Developmental Neurobiology within the Faculty of Biology at Ludwig Maximilian University of Munich (LMU). He leads the Keays Lab, a core component of the Munich Center for Neurosciences (MCN) and Graduate School of Systemic Neurosciences (GSN), where he also holds a Scientific Board position. His research integrates advanced methodologies including 2-photon imaging, electrophysiology, and CRISPR/Cas9 genome editing to address fundamental questions in sensory and developmental neuroscience. Keays' research focuses on three interconnected domains: the biophysical mechanisms of animal magnetoreception, the role of microtubule mutations in neurodevelopmental disorders, and the evolutionary neurobiology of monotremes. His lab employs reductionist experimental approaches to investigate how magnetic fields are detected, how tubulin mutations disrupt neuronal migration, and why egg-laying mammals possess unique neural architectures. This work spans molecular genetics, cellular imaging, and comparative neuroanatomy. Analysis of Keays' recent publications (2019-2025) reveals dominant research trajectories in avian magnetoreception mechanisms and tubulin-related neuropathologies. Key themes include cryptochrome protein function, iron-based magnetic sensing structures, and the developmental consequences of tubulin mutations. His work bridges quantum biology, clinical neurology, and evolutionary neuroscience, demonstrating consistent innovation in both conceptual frameworks and technical methodologies. Scientific awards and honors are not documented in the available source materials. Keays mentors doctoral candidates including Patrick Heisterkamp, Carolina Duro, Alexandra Vilceanu, and Thamari Kapuruge. His research program receives competitive funding, though specific grant details are not provided in the source texts. The lab actively contributes to graduate training through the GSN and maintains rigorous standards for data integrity and publication ethics. The Keays Lab operates within LMU's Neurobiology department, maintaining specialized facilities for 2-photon imaging, single-cell sequencing, and transgenic model development. The team collaborates extensively with MCN and GSN affiliates, utilizing cerebral organoid systems and quantum magnetic imaging to advance understanding of sensory processing and neurodevelopment. Current infrastructure supports high-resolution in vivo imaging and molecular manipulation of neural circuits.

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Ulrich BükerView profile

Professor

Ostwestfalen-Lippe University of Applied SciencesGermany

Prof. Ulrich Büker is a faculty member at TH OWL since 2022, leading the Intelligent Systems research group at inIT (Institute for Industrial Information Technology). He became deputy head of inIT in 2024 and Vice Dean of Department 5 in 2025. His work bridges academic research and industrial applications in intelligent systems. Education : Diploma in Computer Science (University of Paderborn), Doctorate and Habilitation in Electrical Engineering and Information Technology (University of Paderborn). Research Interests include: Application-oriented artificial intelligence for automation and mobility systems. Autonomous driving with focus on scenario generation and vision-based control. Computer vision for robotics and industrial applications. Embedded systems in battery electric vehicles. Article Trends demonstrate expertise in autonomous systems, computer vision, and industrial applications, spanning from foundational 2000s work on hybrid object models to recent LLM-driven autonomous driving scenario generation . Key sub-fields include neural networks, image processing, and vehicle energy management. Professional Contributions include: Industrial leadership roles at Aptiv , Delphi , and Hella . Membership in German Informatics Society (GI) and German Society for Pattern Recognition (DAGM) . Patents in image segmentation (DE000010250781, EP000001416441).

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Shmuel AvidanView profile

Professor

Leipzig UniversityGermany

Prof. Shmuel Avidan serves as a Professor in the School of Electrical Engineering at Tel Aviv University's Iby and Aladar Fleischman Faculty of Engineering. Holding a Ph.D. from Hebrew University's School of Computer Science (1999), he brings extensive industry experience from Adobe, Mitsubishi Electric Research Labs, MobilEye, and Microsoft Research to his academic role. His educational trajectory features: Ph.D. in Computer Science, Hebrew University of Jerusalem (1999) Avidan's research centers on pixel-centric computational problems, with seminal contributions in video object tracking and 3D object modeling from 2D images. His work spans computer vision, image processing, and machine learning, emphasizing practical applications in industrial settings. Current investigations explore neural rendering, foundation models, and diffusion-based architectures for visual understanding. Recent publications (2023-2025) demonstrate concentrated innovation in neural radiance fields (NeRF), category-agnostic pose estimation, and texture-aware segmentation. These works increasingly integrate foundation models with domain-specific applications in medical imaging, autonomous systems, and materials science, reflecting a strategic shift toward scalable vision systems. Though specific awards aren't documented in source materials, his prolific publication record and sustained industry partnerships signify substantial field impact. His research group maintains active collaboration with leading technology firms, translating academic discoveries into real-world solutions. Professor Avidan mentors graduate students in computer vision while securing competitive grants for projects at the intersection of theoretical computer vision and industrial implementation. His lab focuses on developing robust algorithms for challenging visual environments, particularly in autonomous driving and medical imaging contexts. Leading an active research group within Tel Aviv University's Electrical Engineering department, he drives innovation in neural rendering and vision-language models. The team regularly contributes to premier conferences including CVPR, ICCV, and ECCV, maintaining strong industry ties through ongoing partnerships with automotive and imaging technology companies.

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Sannakaisa VirtanenView profile

Professor

University of Erlangen–NurembergGermany

Prof. Dr. Sannakaisa Virtanen serves as Professor and Chair of Materials Science (Corrosion and Surface Technology) at Friedrich Alexander University Erlangen-Nuremberg's Department of Materials Science. Her research spans corrosion science, biodegradable metals, and surface engineering, with significant contributions to biomedical implant materials and high-temperature superalloys. Her primary research focuses on corrosion mechanisms in biodegradable metals (particularly zinc and magnesium alloys) for medical implants, respirometric monitoring techniques for real-time corrosion analysis, and high-temperature oxidation of advanced superalloys. She develops innovative surface modification methods including micro-arc oxidation, liquid-infused coatings, and UV-grafted polymers to control degradation rates and enhance bioactivity. Analysis of her recent publications reveals consistent leadership in corrosion monitoring methodologies, with increasing emphasis on biomedical applications since 2022. Her work bridges fundamental electrochemistry with practical engineering solutions for sustainable materials. Morris Cohen Graduate Student Award (Corrosion Division) H. H. Uhlig Award (Corrosion Division) Professor Virtanen maintains active collaborations with major research institutions including Max Planck, Fraunhofer, and Helmholtz associations as part of FAU's research-intensive ecosystem. Her laboratory develops advanced corrosion testing protocols and surface engineering solutions with applications spanning biomedical implants, energy systems, and aerospace materials. Current projects focus on optimizing biodegradable zinc alloys for vascular stents and improving oxidation resistance in next-generation superalloys.

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George CouplandView profile

Professor

Max Planck Institute for Plant Breeding ResearchGermany

George Coupland is a Professor and Director at the Max Planck Institute for Plant Breeding Research , leading the Department of Plant Developmental Biology . His research focuses on the genetic and molecular mechanisms underlying plant reproductive development and perennial life history evolution, primarily in Arabidopsis thaliana and Arabis alpina . Key areas include floral induction networks , environmental signaling integration , and perennial adaptation genomics . 2025 : FD/FDP bZIP interactions in florigen signaling 2024 : Meristem shape-identity coupling 2023 : Urban adaptation in A. thaliana His work combines genetic mapping , confocal imaging , and CRISPR-based functional analysis to dissect regulatory pathways. Articles highlight miRNA dynamics , transcription factor networks , and dormancy-flowering tradeoffs . Collaborations span Andrea Fulgione (population genetics) and Pau Formosa-Jordan (multicellular modeling). Scientific contributions include 2025: FRS (Fellow of the Royal Society) 2021: PLoS Biology publication on miR172 family ResearchGate profiles show over 384 publications and 103,041 reads , emphasizing his leadership in plant developmental biology . The A. alpina model system development enables comparative studies of annual-perennial divergence .

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Alexander EckerView profile

Professor

Max Planck Institute for Dynamics and Self-OrganizationGermany

Prof. Dr. Alexander Ecker is Professor of Data Science at the Institute of Computer Science, University of Göttingen, and concurrently holds the prestigious Max Planck Fellow position at the Max Planck Institute for Dynamics and Self-Organization. Since 2020 he also serves on the Executive Board of the Campus Institute Data Science in Göttingen. He leads the Neural Data Science research group, comprising 14 PhD students and 2 postdoctoral researchers, focusing on the interface of machine learning and computational neuroscience. His educational background includes a Dr. rer. nat. in Neuroscience (2014) from the Graduate School of Neural and Behavioral Sciences/IMPRS, University of Tübingen, followed by post-doctoral and group-leader positions at the University of Tübingen and the Max Planck Institute for Biological Cybernetics. Research Interests Machine Learning & Deep Learning: developing novel algorithms for representation learning and generative modeling. Computational Neuroscience: large-scale data-driven modeling of visual cortical circuits. Visual Perception: bridging biological vision and computer vision via biologically inspired architectures. His work has produced a steady stream of influential publications (2019-2025) in leading journals such as Nature Communications , Nature , Nature Methods , PLOS Computational Biology , ICLR , NeurIPS , and CVPR . The publications trend toward integrating high-resolution neural recordings with state-of-the-art machine-learning models to uncover principles of sensory processing, neuron-type classification, and behavior. Scientific Awards & Honors Max Planck Fellow, Max Planck Institute for Dynamics and Self-Organization (ongoing) Executive Board Member, Campus Institute Data Science, Göttingen (since 2020) Teaching, Advising & Grants Regularly teaches advanced courses: “Deep Learning for Image Synthesis”, “Current Topics in Deep Learning”, and “Graph Machine Learning”. Supervises 14 current PhD students and 2 postdocs within the Neural Data Science Group. Offers numerous Bachelor’s and Master’s thesis projects, with topics ranging from neuronal morphology clustering to primate vocalization analysis. Leads or co-leads large collaborative consortia with labs in Göttingen, Tübingen, Baylor College of Medicine, and other institutions across the US and Germany. Labs & Teams The Neural Data Science Group operates at the Institute of Computer Science, University of Göttingen, and is tightly integrated with the Max Planck Institute for Dynamics and Self-Organization. The group maintains active collaborations with over a dozen partner laboratories, including groups led by Fabian Sinz, Andreas Tolias, Thomas Euler, Tim Gollisch, and Viola Priesemann, fostering an interdisciplinary environment that spans computer science, physics, biology, and psychology.

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Miriam SchulteView profile

Professor

University of StuttgartGermany

Miriam Schulte is a Professor at the Institute for Parallel and Distributed Systems (IPVS) at the University of Stuttgart . As Dean of Studies SimTech , she leads academic programs in simulation technology. Her research focuses on high-performance computing , multi-physics simulations , and scientific software development , with significant contributions to coupling libraries like preCICE and biophysical frameworks like OpenDiHu . Key Research Areas: High-Performance Computing (HPC) Multi-physics and Fluid-Structure Interaction (FSI) Sparse Grids and Hierarchical Numerical Methods Machine Learning in Simulation Software Parallel and GPU-Accelerated Algorithms Advising: Guided student projects on quantum neural networks , GPU-optimized sparse grids , and SYCL-based HPC frameworks . Coordinated SimTech Research Modules and IPVS/SGS team initiatives. Software Leadership: Maintains preCICE (coupling library for multi-physics) Develops OpenDiHu (neuromuscular simulations) Advances PLSSVM (parallel SVM library) and SG++ (sparse grids) Her recent publications (2022–2025) emphasize machine learning integration with multi-physics simulations , including groundwater heat pumps , brain tumor modeling , and neuromuscular EMG prediction . She actively promotes open-source software sustainability and collaborative research infrastructure at the University of Stuttgart.

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Vanessa BreitkopfView profile

Lecturer

University of SiegenGermany

Vanessa Breitkopf is a doctoral student and lecturer at the Department of German Studies , University of Siegen. Since April 2025, she coordinates the internationalization of teacher training at the Center for Teacher Education and Educational Research (ZLB). Her research spans local political communication , discourse analysis , and linguistic image analysis , with a focus on citizen participation and strategic communication in municipal contexts. PhD in computational socio- and discourse linguistics Lecturer in German Studies Coordinator, connect4future project (ZLB, University of Siegen) Her work employs computer-assisted corpus methods to study mayors' communication, media portrayal of political actors, and the role of civil society in local governance. She has contributed to publications on discourse metrics and political engagement, including a glossary on strategic communication. Scientific Awards : Doctoral scholarship holder at the University of Siegen (01/2025 – 03/2025)

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Veit HornungView profile

Professor

Ludwig Maximilian University of MunichGermany

Professor Veit Hornung is Chair of Immunobiochemistry at the Gene Center and Department of Biochemistry within the Faculty of Medicine at Ludwig Maximilian University of Munich. His laboratory focuses on understanding the molecular mechanisms of innate immune recognition, particularly in the context of nucleic acid sensing and inflammasome biology. Hornung leads a large research group investigating how the immune system distinguishes between self and non-self, with implications for infectious diseases, autoinflammatory disorders, and cancer immunotherapy. Hornung's research spans three primary areas: nucleic acid sensors, inflammasomes, and genome engineering. His work on nucleic acid sensors has elucidated how Toll-like receptors (particularly TLR7 and TLR8) recognize RNA degradation products within endolysosomes, and how the cGAS-STING pathway detects cytosolic DNA. In inflammasome research, his laboratory has made significant contributions to understanding NLRP3, AIM2, and NLRP1 activation mechanisms. His group has also pioneered CRISPR-based genome engineering approaches, developing techniques like SPARCS for spatial cellular phenotype screening. Professor Hornung has received numerous prestigious awards including the Louis-Jeantet Prize (2025), ERC Advanced Grant (2021), William B. Coley Award (2020), Liliane Bettencourt Prize (2018), and the Gottfried Wilhelm Leibniz Prize (2018). He is an EMBO Member and Leopoldina Member, and has been consistently recognized as a Highly Cited Researcher in Immunology. Hornung currently leads multiple major research projects including the ERC Advanced Grant 'ENGINES' focusing on molecular and functional characterization of emerging inflammasomes, and several Collaborative Research Centers including TRR 338 'Lymphocyte Engineering for Therapeutic Synthetic Immunity', TRR 237 'Nucleic Acid Immunity', and SFB 1054 'Control and Plasticity of Cell-Fate Decisions in the Immune System'. His laboratory maintains strong collaborations with other research groups at LMU and internationally.

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Didier StrickerView profile

Professor

University of MannheimGermany

Prof. Dr. Didier Stricker is a leading academic in computer science, serving as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) and Professor at the University of Kaiserslautern-Landau (RPTU). His career spans over two decades, including leadership roles at Fraunhofer IGD and founding the Augmented Vision research unit at DFKI/RPTU, which now includes ~30 researchers. Education: Electrical Engineering (Technical University of Grenoble, Karlsruhe) PhD: Computer Vision-based Calibration and Tracking Methods for Augmented Reality (2002, TU Darmstadt) His research focuses on virtual and augmented reality , computer vision , human-computer interaction , and on-body sensor networks . He leads major EU/national projects like LUMINOUS (Language-Augmented XR) and SHARESPACE (Ethical Hybrid Shared Spaces), with industrial partnerships including Sony, Google, and John Deere. Recent publications emphasize 3D reconstruction , neural network optimization , and XR systems . Key trends include event camera processing , scene flow estimation , and multimodal AI for industrial applications . He holds patents in AR tracking and has received the 2006 Innovation Prize from the German Society of Computer Science. Scientific Awards : Innovation Prize (2006) Best Paper/Demonstration Awards at ISMAR, EUSIPCO, CVPR, and ICRA As a reviewer for journals and conferences in VR/AR and computer vision, he contributes to shaping research standards. His lab ( AG Augmented Vision ) combines academic and industrial collaborations to advance cognitive interfaces and extended reality systems.

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Thomas WendlerView profile

Professor

Technical University of MunichGermany

Thomas Wendler is a Professor at the Chair of Computer Aided Medical Procedures & Augmented Reality at Technische Universität München (TUM). His research focuses on the intersection of Artificial Intelligence, Medical Imaging, and Robotics, with specific interests in Longitudinal Image Analysis, Image-Guided Interventions, and Dosimetry for Radioisotope Therapy. Current affiliation: TUM Institute of Informatics Former leadership: Director of the Interdisciplinary Research Lab (IFL) Research Interests: Thomas Wendler's work bridges Artificial Intelligence Applications in Medicine with Robotic Imaging , emphasizing Longitudinal Image Analysis for disease progression and Image-Guided Interventions in clinical settings. His technical expertise includes Dosimetry for nuclear medicine and 3D Computer Vision for surgical applications. Teaching: He actively contributes to TUM's curriculum through lectures and practical courses such as: Computer Aided Medical Procedures I Medical Augmented Reality Introduction to Surgical Robotics Foundations in 3D Computer Vision Collaborations: Wendler collaborates with Prof. Nassir Navab and researchers like Mohammad Farid Azampour, Francesca De Benetti, and Zhongliang Jiang. His work has been published in journals including IEEE Transactions on Medical Imaging and Medical Image Analysis , with recent advancements in robotic ultrasound navigation and catheter tracking methodologies.

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Michael HeymannView profile

Assistant Professor

University of StuttgartGermany

Dr. Michael Heymann is a Director and Deputy Director at the Institute of Biomaterials and Biomolecular Systems, University of Stuttgart, with a focus on Intelligent Biointegrative Systems. His work bridges synthetic biology, microfluidics, and structural biology through innovative experimental platforms. Current affiliations: University of Stuttgart (Institute of Biomaterials and Biomolecular Systems) Research interests: Synthetic biology, cell-free systems, microfluidic device engineering, time-resolved structural analysis, and artificial cell design. Dr. Heymann's recent publications highlight advancements in cell-free transcription/translation systems for self-replicating synthetic genomes, 3D-printed microfluidic devices for X-ray studies, and membrane-deforming protocells using Min protein oscillations. His work integrates hardware (e.g., low-cost fluorescence readers) with biochemical innovations (e.g., Cas13a RNA detection). Key trends in his research include ultracompact microfluidics for XFEL experiments, freeze-thaw vesicle engineering , and reaction-diffusion systems for artificial cell division. Collaborations span institutions in Germany and international XFEL facilities. Dr. Heymann leads projects in biomolecular self-organization and structural dynamics, though no specific awards or student mentorship details are publicly listed in the provided data.

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Florian NoichlView profile

Researcher

Technical University of MunichGermany

Florian Noichl is a Group Lead in Spatial Computing at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich . His work focuses on methods for creating digital twins of industrial environments, particularly car manufacturing plants, and includes collaborative projects with Siemens . He was a Visiting Researcher at the Department of Geomatics Engineering at the University of Calgary, Canada (May–August 2023). Research interests include Spatial computing Digital twinning Point cloud processing Artificial intelligence in construction Scan planning optimization GeoAI for retrofitting Recent publications emphasize automation in point cloud segmentation, material passport creation for steel structures, semantic facade analysis, and energy efficiency estimation using vision-language models. His work often integrates BIM with laser scanning and AI . Teaching includes Bau- und Umweltinformatik 1 (WS22/23, WS23/24) and Softwarelab . He supervises theses on topics like UAV mission planning Point cloud enrichment Image-based localization CAD model matching BIM design reviews Review activities cover journals such as Automation in Construction , IEEE Sensors Journal , and Remote Sensing . He is listed on OrcID : 0000-0001-6553-9806 Google Scholar ResearchGate Labs associated with include the BIM-Lab and Robotic Fabrication Lab . His work intersects digital construction with industrial AI applications.

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Thomas BauschView profile

Professor

Munich University of Applied SciencesGermany

Professor Thomas Bausch serves as a full Professor in the Faculty of Tourism (Faculty 14) at Munich University of Applied Sciences, maintaining an active research and teaching profile. His office is located in Room S 312 at Schachenmeierstraße 35, 80636 Munich. His research spans critical areas of contemporary tourism: Sustainable Tourism development frameworks Destination Management strategies Nature-based Tourism motivation analysis Urban Tourism planning integration Tourism Epistemology and conceptual precision Climate Change Adaptation in tourism contexts Professor Bausch's publication trajectory from 2022-2024 reveals intensifying focus on sustainability conceptualization across cultures and practical destination management challenges. His work analyzes ski-resort competitiveness, nature tourism motivations, and urban planning integration through interdisciplinary lenses combining environmental science, behavioral psychology, and policy studies. His scientific contributions include: 7 peer-reviewed publications (2022-2024) in Q1 journals International book chapters with CABI Government-commissioned research for Umweltbundesamt Cross-cultural comparative studies across 5+ countries As a supervising professor, he guides student research through structured office hours accessible via FK14 Moodle. His industry-relevant research on destination photography perception, sustainability terminology, and climate adaptation provides actionable insights for tourism professionals while maintaining academic rigor through international collaborations.

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