Find Academic Supervisors

Volker RodehorstView profile

Professor

• Computer Vision
• Image Analysis
• 3D Reconstruction
• +5 more

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.

Ayush TewariView profile

Assistant Professor

• Computer Vision
• 3D Reconstruction
• Neural Rendering
• +3 more

Ayush Tewari is an Assistant Professor at the University of Cambridge. Previously, he was a postdoctoral researcher at MIT CSAIL under Bill Freeman, Josh Tenenbaum, and Vincent Sitzmann, and completed his Ph.D. at the Max Planck Institute for Informatics under Christian Theobalt. His research focuses on visual perception, developing methods to infer 3D structured representations from images and videos, aiming to bridge the gap between human perceptual capabilities and machine learning systems. Key research interests include neural rendering, inverse rendering, 3D reconstruction, and generative models. Notable contributions include advancements in Neural Radiance Fields (NeRF), diffusion models for inverse problems, and human-centric perception studies. His work has been published in top venues such as SIGGRAPH, CVPR, ICCV, and NeurIPS. Recent research trends emphasize ambiguity-aware inverse rendering, stochastic inverse problem solving using diffusion models, and integrating forward models for 3D scene inference. His work on Diffusion with Forward Models (NeurIPS 2023) proposes a novel framework for solving inverse problems without direct supervision. Awards: Best Paper Honorable Mention at BMVC 2022 (VoRF: Volumetric Relightable Faces). Labs/Projects: Core contributor to the DFM (Diffusion with Forward Models) project, advancing 3D scene understanding via probabilistic methods.

Bernd SturmfelsView profile

Professor

• Algebraic Geometry
• Combinatorics
• Commutative Algebra
• +4 more

Bernd Sturmfels is a leading mathematician serving as Director of the Max Planck Institute for Mathematics in the Sciences in Leipzig since 2017. He is also Professor Emeritus of Mathematics, Statistics, and Computer Science at the University of California, Berkeley, and holds honorary professorships at the Technical University of Berlin and the University of Leipzig. His research bridges pure and applied mathematics, with foundational contributions to algebraic geometry, combinatorics, and computational biology. Education: Sturmfels earned dual Ph.D. degrees in 1987 from the University of Washington and Technische Universität Darmstadt, followed by an honorary doctorate from Goethe University Frankfurt in 2015 and additional honorary doctorates from the University of Bern (2023) and the University of Chicago (2024). Research Interests: His work spans algebraic geometry , combinatorics , commutative algebra , algebraic statistics , convex optimization , and computational biology . He explores deep connections between abstract algebraic structures and practical applications in statistics, optimization, and the life sciences. Publications and Trends: With over 300 research articles and 11 books, his recent work (2022–2025) focuses on advanced topics like Grassmannian geometry, tropical implicitization, quantum chemistry applications, and algebraic statistics. His research increasingly integrates computational methods with theoretical insights, addressing problems in machine learning, phylogenetics, and optimization. Awards and Honors: Sturmfels has received numerous prestigious awards, including: George David Birkhoff Prize in Applied Mathematics (2018) SIAM von Neumann Lecturership (2010) Humboldt Senior Research Prize (2007–2008) David and Lucile Packard Fellowship (1992–1997) Fellowships of the AMS and SIAM Membership in the Berlin-Brandenburg Academy of Sciences and Humanities Mentoring and Grants: He has supervised 60 doctoral students and numerous postdocs, with many securing positions at leading institutions. His mentoring philosophy emphasizes diversity and excellence, as highlighted in his Notices of the AMS article. Funding sources include the NSF, DARPA, and the German National Science Foundation (DFG). Labs and Teams: At the Max Planck Institute, he leads the Nonlinear Algebra group, fostering interdisciplinary collaboration between mathematics and the sciences. His team focuses on developing algebraic methods for data analysis, optimization, and theoretical physics.

Allister LoderView profile

Professor

• Mobility Policy
• Transportation Engineering
• Urban Planning
• +3 more

Prof. Allister Loder is a Professor of Mobility Policy at the Technical University of Munich (TUM), affiliated with the TUM School of Social Sciences and Technology . His research focuses on mobility policy analysis, evaluation of policy measures, and urban transportation innovations. He holds a doctorate in Transportation from ETH Zurich (2019) and has held roles at Swiss Federal Railways (SBB) and TUM's Chair of Transportation Engineering and Technology. Since 2023, he leads a DFG-funded Emmy Noether Research Group. Education: Mechatronics Engineering, Hamburg University of Technology Energy Science and Technology, ETH Zurich PhD in Transportation Engineering, ETH Zurich (2019) Research emphasizes macroscopic fundamental diagrams (MFD) for urban traffic modeling, analysis of Germany's 9-Euro-Ticket and Deutschlandticket policies, and tradable mobility credit schemes. Recent work explores cycling infrastructure in metropolises and accessibility-based road pricing mechanisms. Key Awards : Recipient of the DFG Emmy Noether Research Group Fellowship (2023). Grants and Projects: Founded the Emmy Noether Research Group focused on mobility policy innovation. Active in large-scale empirical studies like the Mobilität. Leben panel tracking mobility behavior across Germany. Labs/Teams: Leads the Emmy Noether Research Group at TUM, collaborating on mobility policy design and evaluation tools.

Benjamin SugerView profile

Researcher

• Robotics
• Autonomous Systems
• Traversability Analysis
• +6 more

Benjamin Suger is a researcher in the Department of Computer Science at the University of Freiburg, affiliated with the Autonomous Intelligent Systems group within the Faculty of Engineering. His work centers on robotics and intelligent systems, particularly in autonomous navigation and environment modeling. Diploma in Mathematics, University of Freiburg (2003–2011) PhD Student, Autonomous Intelligent Systems Group, University of Freiburg (2011–2017) His research interests include traversability analysis, SLAM, 3D modeling, and mobile robotics. He applies machine learning and computer vision techniques to enable robust robot navigation in complex and dynamic environments. His work often integrates sensor data from 3D lidar and visual systems to improve perception and localization. The recent publications highlight a strong focus on long-term autonomy, outdoor navigation, and memory-efficient SLAM algorithms. Key themes include handling perceptual changes, terrain adaptability, and integration of open geospatial data like OpenStreetMap. His work bridges theoretical algorithm development with real-world robotic applications. Scientific recognition includes being a finalist for the Best Conference Paper Award. This reflects the impact and quality of his contributions to the robotics community. Best Conference Paper Award Finalist Benjamin Suger has contributed significantly to research projects such as LifeNav and has served as a teaching assistant for the Introduction to Mobile Robotics course. While no direct advising of students is listed, his collaborative work with prominent researchers like Wolfram Burgard indicates active participation in a larger academic and research team. He has not received external grant mentions in the provided text. He is part of the Autonomous Intelligent Systems lab at the University of Freiburg, a leading group in robotics research, where he contributes to advancing the state of the art in autonomous navigation and environmental understanding for mobile robots.

Wolfram HelmlView profile

Assistant Professor

• Ultrafast Electron Dynamics
• Attosecond Physics
• X-ray Spectroscopy
• +7 more

Jun.-Prof. Dr. Wolfram Helml is a faculty member in the Department of Physics at the Technical University of Dortmund, where he leads a research group at the Center for Synchrotron Radiation (DELTA). His work focuses on probing ultrafast electron dynamics at the attosecond scale using advanced X-ray spectroscopy techniques. His research interests include attosecond physics , ultrafast electron dynamics , and time- and angle-resolved X-ray spectroscopy . He employs X-ray free-electron lasers such as LCLS (USA) and European XFEL (Hamburg) to visualize fundamental excitation processes in atoms, molecules, and biological systems. By combining circularly polarized laser fields with X-ray pulses, his team constructs streaking cameras capable of measuring electron emission with extreme temporal precision. The recent publications highlight a growing integration of artificial intelligence for real-time analysis of ultrashort X-ray pulses, developed in collaboration with researchers at the University of Kassel. These innovations aim to enable online, time-resolved spectroscopy at large-scale FEL facilities. Scientific contributions include: First demonstration of attosecond streaking with FEL pulses at LCLS (2018) Development of AI-based tools for pulse characterization (2022) He is actively involved in experimental development at DELTA and future applications at European XFEL. No information is available regarding students or formal advising roles. He is based in Room DELTA 01 at the Maria-Goeppert-Mayer-Str. 2 facility in Dortmund.

Oliver KarrasView profile

Lecturer

• Data Science
• Artificial Intelligence
• Knowledge Representation
• +4 more

Oliver Karras is a researcher, data scientist, and lecturer at the Data Science and Digital Libraries research group at TIB – Leibniz Information Centre for Science and Technology. He holds a BSc, MSc, and PhD in Computer Science from Leibniz University Hannover. His research focuses on FAIR scientific knowledge, Open Research Knowledge Graph (ORKG), and national research infrastructure projects like NFDI-4Ing and FAIR-DS. He is a member of the German Informatics Society (GI) and spokesperson of the Requirements Engineering (RE) group, contributing to conferences and journals as a reviewer. Previously, he was a research associate and PhD student in the Software Engineering group at Leibniz University, leading the DFG project ViViReq on video integration in requirements engineering. His research interests include Data Science, AI, Knowledge Representation, Software Engineering, Requirements Engineering, Empirical Research, and Open Science. He has published over 60 papers in these areas, with notable contributions to knowledge graphs, FAIR data, and reproducibility frameworks. His work emphasizes organizing scientific knowledge for accessibility and collaboration across disciplines. He is actively involved in initiatives like the ORKG, promoting sustainable literature reviews and open science practices. His professional contributions extend to tool development, such as OntoAligner for ontology alignment and SciKGTeX for semantic annotation in LaTeX. Oliver Karras collaborates with institutions like Leibniz University, contributing to the NFDI consortium and energy research projects. His expertise bridges technical innovation and academic rigor, addressing challenges in knowledge management and reproducibility. His current roles include advancing TIB’s research infrastructure and fostering interdisciplinary collaboration through knowledge graph applications.

Christof RöhrigView profile

Professor

• Robotics
• Mobile Robotics
• Wireless Sensor Networks
• +3 more

Christof Röhrig is a Professor at the FH Dortmund - University of Applied Sciences and Arts , conducting research at the Institute for the Digitalization of Work and Living Environments (IDiAL). He leads the Intelligent Mobile Systems Lab , focusing on robotics, wireless sensor networks, and kinematic modeling. His research spans mobile robotics , indoor localization , and industrial automation , with a strong emphasis on IoT , 5G networks , and rescue robotics . Key trends in his recent work include LoRaWAN localization , modular robot design , and digital twin architecture . He collaborates extensively on motion control , sensor fusion , and energy-efficient systems , though no specific students, awards, or grants are listed in the provided data. The lab at IDiAL explores robotics in emergency response and industrial IoT applications , with a focus on precision localization and collaborative automation .

Jan PfisterView profile

Researcher

• Natural Language Processing
• Deep Learning
• Sentiment Analysis
• +5 more

Jan Pfister is a researcher at the Chair of Data Science (Informatik X) , affiliated with the Faculty of Mathematics and Computer Science at the University of Würzburg . Holding an M.Sc. in Computer Science from 2021, he contributes to the DMIR group while maintaining the BibSonomy platform. His work bridges Natural Language Processing and Deep Learning , with a focus on structured sentiment analysis and German language modeling. His research explores the integration of Large Language Models with Pointer Networks to extract fine-grained sentiment information. He has developed ModernGBERT , a German-only encoder model, and LLäMmlein , advancing NLP capabilities for the language. Pfister's recent publications highlight trends in encoder-decoder architectures, model-agnostic hallucination detection, and multi-label classification frameworks that refine LLM outputs. He has taught courses including Information Retrieval (SS '22), Text Mining (WS '23), and Selected Topics in Machine Learning (SS'21, WS '21, WS'24). His collaborative projects span medical informatics, human-AI interaction, and social media analysis, often involving interdisciplinary teams and real-world data.

Sebastián FerradaView profile

Assistant Professor

• Knowledge Graphs
• Graph Databases
• Multimedia Databases
• +3 more

Sebastián Ferrada is an Assistant Professor at the Data & Artificial Intelligence Initiative of Universidad de Chile. He also serves as Young Researcher at the Institute for Foundational Research on Data (IMFD) and Collaborating Researcher at the National Center for Artificial Intelligence Research (CENIA). His research focuses on Knowledge Graphs, with special emphasis on extraction, management, and applications for querying, browsing, and AI systems. His academic background includes: PhD in Computer Science (2021), Universidad de Chile MSc in Computer Science (2017), Universidad de Chile BEng in Computer Science (2017), Universidad de Chile Sebastián's research explores several key areas: Multimedia Databases with applications to Wikimedia Commons images Graph Databases and Knowledge Graphs construction Federated Data Management across heterogeneous RDF sources SPARQL query extensions for similarity-based operations Graph data management and compression techniques His recent publications demonstrate strong trends in knowledge graph construction, similarity-based querying, and efficient graph data management. These works combine theoretical advancements with practical implementations in real-world systems like IMGpedia and MillenniumDB. Scientific achievements include: Best Paper Award at CoopIS 2023 Best Demonstration Award runner-up at SIGMOD/PODS 2024 Best Student Paper (Resources Track) and Best Poster at ISWC 2017 First prize in CLEI 2017 for his Master's thesis Sebastián currently leads the Fondecyt project on graph data management and contributes to the U-Inicia project on AI processes in graph databases. He serves on the editorial board of Transactions on Graph Data and Knowledge.

Kristoff RitlewskiView profile

Professor

• Intellectual Property Law
• Copyright Law
• Unfair Competition Law
• +6 more

Prof. Dr. Kristoff Ritlewski is a Professor at Berlin University of Applied Sciences (HTW Berlin) in the Department of Economics and Law. He serves as Chair of the Academic Senate and teaches Business Law at both bachelor's and master's levels, holding the title of University Lecturer for Business Law (B) and Business Law (M). His research expertise spans Intellectual Property Law, Copyright, Unfair Competition Law and Antitrust Law. Specific areas of interest include information obligations in unfair competition law, machine learning applications in legal contexts, legal foundations of the certification industry, and art and cultural law with emphasis on cultural heritage protection. His work bridges traditional legal frameworks with emerging technologies, particularly in how machine learning can transform legal practice and enforcement. Prof. Ritlewski has contributed to the field through 19 publications and participation in 8 lectures and events. His research activities include two major projects focusing on the intersection of law and technology, particularly examining how AI systems can be integrated into legal compliance frameworks. Professional memberships: German Association for the Protection of Intellectual Property (GRUR) International Association for the Advancement of Research and Teaching in Intellectual Property - ATRIP Bucerius Alumni eV Order of St. John Current leadership roles include Head of the Academic Council of HTW (2024-2026) and recent Research Semester in Rome focusing on Unfair Competition (2023-2024). He previously served as Member of the Supervisory Board at LegalCore AG (LegalTech) from 2021-2023. Known for his innovative teaching approach, Prof. Ritlewski states: "I love teaching and embracing new technology. My classes will always be taught live, streamed and recorded," making education more accessible while maintaining academic rigor.

Patrick CzorlichView profile

Senior Lecturer

• Neurosurgery
• Traumatic Brain Injury
• Subarachnoid Hemorrhage
• +5 more

Patrick Czorlich is a Senior physician and Medical Specialist in Neurosurgery at the University Medical Center Hamburg-Eppendorf (UKE), working within the Head and Neurocenter Department of Neurosurgery. He holds dual qualifications as a Prüfarzt (clinical trial physician) for both medicinal products and medical devices under German law. His clinical expertise spans neurosurgery with a specialized focus on neurosurgical intensive care. Dr. Czorlich's research interests are extensive within neurosurgical domains, with particular emphasis on traumatic brain injury, subarachnoid hemorrhage, neurocritical care, cerebrospinal fluid dynamics, and intracranial hemorrhage management. His work demonstrates a strong translational approach, bridging clinical practice with research to improve patient outcomes in complex neurosurgical cases. He has developed expertise in areas such as shunt dependency prediction, Terson Syndrome, and the management of complications following aneurysmal subarachnoid hemorrhage. Analysis of his recent publications (2023-2025) reveals a consistent research trajectory focused on improving outcomes in neurocritical care patients. His work spans clinical trials (including the FINISHER trial), predictive analytics using machine learning, management of complications following subarachnoid hemorrhage, and innovative approaches to neurosurgical interventions. Notably, his research often incorporates interdisciplinary collaboration, particularly with ophthalmology for Terson Syndrome studies and with critical care specialists for comprehensive patient management. His scientific contributions demonstrate expertise in both clinical neurosurgery and research methodology, with publications appearing in high-impact journals across neurosurgery, critical care, and related specialties. The consistent output of research and clinical studies indicates active engagement in advancing neurosurgical practice and patient care protocols.

• Emerging Technologies
• Neuromorphic Hardware
• RISC-V for AI
• +3 more

Albi Mema is a researcher affiliated with the Chair of AI Processor Design (AI-Pro) at Technische Universität München (TUM). His work focuses on emerging technologies for AI applications, including neuromorphic hardware, reliability engineering, and quantum computing. University: Technische Universität München Department: Chair of AI Processor Design (AI-Pro) Key research areas include: Emerging Technologies for AI Neuromorphic Hardware Reliability in Semiconductor Devices Quantum Computing RISC-V Architecture Machine Learning Computer-Aided Design His recent publications address fault-tolerant hyperdimensional computing, analog computing for AI, FeFET-based neuromorphic systems, and compact majority gate design using FDSOI technology. No scientific awards are mentioned in the provided text.

• Cancer Biology
• Tumor Biology
• Liquid Biopsy
• +3 more

Prof. Dr. rer. nat. Sabine Riethdorf is a leading researcher at the Institute of Tumor Biology, University Medical Center Hamburg-Eppendorf (UKE). With over 216 publications, her work focuses on circulating tumor cells (CTCs) in liquid biopsy for cancer diagnostics, prognosis, and treatment monitoring across metastatic breast cancer, prostate cancer, NSCLC, and other malignancies. Research Themes : CTC characterization, tumor heterogeneity, treatment resistance mechanisms, PSMA imaging, HER2 status in CTCs, machine learning applications in tumor cell detection. Recent Article Trends : Analysis of CTC transcriptional profiles, PSMA heterogeneity in prostate cancer, machine learning strategies for CTC detection, and comparative CTC studies between blood compartments. Scientific Collaborations : Key partnerships with Klaus Pantel (UKE), Annette Schneeweiss (Heidelberg), and teams across Germany and international institutions. Infrastructure : Utilizes UKE's research information system (FIS), core facilities for molecular analysis, and participates in multicenter clinical trials like DETECT and PREDICT.

• Library and Information Science
• Bibliometrics
• Information Behavior
• +5 more

Brady D. Lund is an active researcher in Library and Information Science with significant contributions to bibliometrics, information behavior, and the ethical implications of artificial intelligence in scholarly communication. His research spans multiple domains including data science ethics, information literacy, and public library services, with particular attention to how digital technologies impact information practices across diverse populations. Lund's research interests focus on the intersection of information science and emerging technologies, particularly examining how AI systems affect scholarly publishing practices, research ethics, and information behavior. His work on ChatGPT's impact on academic writing and AI authorship policies has been particularly influential in library and information science circles. He also investigates information literacy among vulnerable populations, including rural older adults during the pandemic, highlighting the critical role of libraries in community information ecosystems. Analysis of Lund's recent publications reveals a clear trajectory toward examining the ethical dimensions of AI in information contexts, with increasing focus on transparency frameworks, data privacy, and the practical implementation of AI systems in professional settings. His collaborative work spans multiple disciplines, connecting information science with healthcare, cybersecurity, and public policy. Lund demonstrates strong collaborative patterns, frequently working with Ting Wang and Nishith Reddy Mannuru across multiple publications. His research shows methodological diversity, employing both quantitative bibliometric approaches and qualitative investigations of information behavior. While specific grant funding isn't detailed in the publication records, his work addresses significant societal challenges related to information access, digital equity, and ethical technology implementation.