جستجوی استاد راهنمای دانشگاهی

Andrea Carrara is a Researcher at the Technical University of Munich's Chair of Computing in Civil and Building Engineering, led by Prof. André Borrmann. Holding an M.Sc., she contributes to AI-driven civil engineering research and teaches courses including Professional Software Development. Her work bridges computer science and construction through advanced technical drawing analysis. Her research specializes in applying computer vision and deep learning to construction documentation, with core expertise in graph neural networks for technical drawing segmentation, 3D reconstruction from 2D layouts, and BIM automation. She develops AI solutions for extracting semantic information from architectural drawings to streamline project data management in complex infrastructure development. Analysis of her publications reveals a consistent focus on neural architectures like Vision Transformers and Graph Attention Networks applied to construction drawings. Key trends include multi-view fusion techniques, mono-depth estimation for façade modeling, and material classification systems—collectively advancing digital twinning for sustainable building practices and automated construction documentation. Scientific Awards: No awards or fellowships are documented in available sources. Carrara supervises master's theses including Kairlapova (2024) on material detection in architectural drawings and Ahmed (2022) on bridge element detection. Her research aligns with the DrawOn project for AI-based construction plan analysis, though specific grant funding details remain unpublicized. She actively contributes to TUM's BIM-Lab and research groups in Information Management and Digital Twinning, collaborating on AI integration for civil engineering workflows and participating in the Chair's initiatives for computational methods in infrastructure development.

• Building Information Modeling (BIM)
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Fahad Panolan is a Lecturer in the Algorithms and Complexity group at the School of Computing, University of Leeds, UK, a position he has held since August 2023. Prior to this, he was an Assistant Professor in the Department of Computer Science and Engineering at IIT Hyderabad, India, from July 2019 to August 2023. He conducted postdoctoral research at the Department of Informatics, University of Bergen, Norway, between 2016 and 2019. Education: PhD in Theoretical Computer Science, The Institute of Mathematical Sciences, HBNI, Chennai, India (2012–2015) MSc in Theoretical Computer Science, The Institute of Mathematical Sciences, HBNI, Chennai, India (2010–2012) Master of Computer Applications, National Institute of Technology, Calicut, India (2006–2009) BSc in Physics, DGM MES Mampad College, University of Calicut, India (2002–2005) His research lies at the intersection of theoretical computer science and algorithm design, with core interests in Parameterized Algorithms and Complexity , Graph Theory , Approximation Algorithms , and Streaming Algorithms . He has made significant contributions to kernelization, matroid-based techniques, and the development of subexponential-time algorithms for NP-hard graph problems. His work often bridges structural graph theory with algorithmic efficiency, particularly on sparse and geometric graphs. The recent publications show a strong trend in advancing the frontiers of fixed-parameter tractability, including efficient kernelization, approximation schemes for matrix problems, and reconfiguration algorithms. His work frequently appears in top-tier venues such as STOC, SODA, ICALP, and journals like JACM and Algorithmica. Scientific Service: PC Member: WALCOM 2026, IPEC 2023, ESA 2022, IPEC 2021, AAAI 2021 Scientific Coordinator: Parameterized Complexity 201 Workshop Referee for journals including TALG, SIDMA, TCS, Algorithmica, and conferences like STOC, SODA, ICALP, ESA. Fahad Panolan advises PhD students and interns, including Shubhada Suresh Aute and Seshikanth Varma. He has secured research grants through collaborative projects and has delivered invited talks at international workshops and seminars, including Dagstuhl, DIMAP, and Parameterized Complexity workshops. He has taught courses such as Algorithms, Design and Analysis of Algorithms, and Parameterized Algorithms at both University of Leeds and IIT Hyderabad. He is actively involved in the parameterized complexity and algorithms research community, organizing workshops and contributing to the theoretical foundations of efficient computation on hard problems.

• Parameterized Algorithms and Complexity
• Graph Theory and Graph Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Philipp Kindermann is an Associate Professor in the Department of Computer Science at the University of Trier, Germany, where he leads the Algorithmics team within the Faculty of Mathematics and Computer Science. He holds a PhD from the University of Würzburg and has held academic positions at the University of Waterloo, FernUniversität in Hagen, and Universität Passau. His research is centered on theoretical and applied aspects of graph algorithms, computational geometry, and graph drawing. Research Interests: His work focuses on graph drawing, geometric graph algorithms, planarity, parameterized complexity, and combinatorial optimization. He investigates algorithmic solutions for visualizing graphs with geometric constraints, including rectilinear drawings, layered layouts, and contact representations. His research also extends to computational complexity of graph problems, especially in beyond-planar graph classes. Publication Trends: His recent publications (2022–2024) show a strong emphasis on parameterized algorithms, planarity variants (upward, orthogonal), geometric representations (rectangle contacts, tangles), and algorithmic challenges in graph drawing. His work frequently appears in top venues such as GD, ISAAC, SOFSEM, and Algorithmica, reflecting sustained contributions to theoretical computer science and visualization. Special Issue Editor, Journal of Graph Algorithms and Applications (JGAA) Special Issue Editor, Computational Geometry: Theory and Applications (CGTA) Steering Committee Member, WG (2025–2028) Program Committee Chair, WG 2025 and EuroCG 2020 PC Member for GD, WALCOM, PacificVis, SOFSEM, IWOCA, and others Organizer of ISSEP 2025, WG 2025, IWOCA 2022, EuroCG 2020, GD 2014 Workshop Organizer: Dagstuhl Seminar (2026), GGWeek 2024, PhD Schools Member of PACE Challenge Steering Committee (since 2024); PC Chair PACE 2024 Advisory Committee, Computational Geometry Challenge (since 2020) Graph Drawing Contest Committee (2015–2023), Chair (2018–2022) Philipp Kindermann actively contributes to the academic community through editorial work, conference leadership, and organizing competitive events in algorithmics and visualization. He collaborates extensively with researchers across Europe and North America. He teaches courses such as Algorithms and Data Structures, Algorithms for Programming Contests, and Advanced Algorithms. He maintains an active research lab focused on geometric and graph-theoretic problems, fostering innovation in algorithm design and visualization techniques.

• Graph Drawing
• Graph Algorithms
• Computational Geometry
• +۷ مورد دیگر

Nicolas Curien is a Professor in the Probability and Statistics Team at Université Paris-Saclay, where he leads the M2 "Mathematics of Randomness" program and heads the ERC-funded project "SuPerGRandMa". His office is located in Building 307, Orsay. Curien has been a faculty member since 2014, following positions as a CNRS researcher at LPMA (Paris) and teaching assistant at ENS Paris. He completed his PhD under Jean-François Le Gall in 2011. Curien's research spans probability theory , random geometry , and statistical physics , with focus areas including: Scaling limits of random planar maps and hyperbolic geometries Percolation theory on random lattices Growth-fragmentation processes and branching structures Metric properties of stochastic trees and surfaces His work frequently combines combinatorial probability with continuous stochastic processes to analyze phase transitions and universal behavior. Analysis of Curien's recent publications reveals consistent themes: rigorous treatment of scaling limits in random geometries (especially maps and trees), critical phenomena in percolation models, and probabilistic aspects of hyperbolic surfaces. Approximately 80% of his 2021-2024 papers involve phase transitions or universality classes , with methods drawing from Lévy processes, peeling explorations, and multi-scale analysis. Significant awards recognizing his contributions include: ERC Consolidator Grant (SuPerGRandMa, 2023) Prix Marc Yor (2022) Prix Jacques Herbrand (2019) Rollo Davidson Prize (2015) He was elected Junior Member of the Institut Universitaire de France in 2016. Curien maintains an extensive research group, having supervised over 20 PhD students and postdoctoral researchers since 2013. Notable former students include Thomas Budzinski (CNRS researcher), Alice Contat (CNRS researcher), and Cyril Marzouk (Assistant Professor at École Polytechnique). His ERC project currently supports 4 early-career researchers. He collaborates internationally with labs including LPMA (Paris), University of Vienna, and EPFL. Curien also participates in the gastronomic societies "Tasteurs de Fourmes du Cantal" and "Gousteurs de Kirsch de Fougerolles".

• Probability Theory
• Random Planar Maps
• Scaling Limits
• +۷ مورد دیگر

Dr. Markus Wallinger is a postdoctoral researcher at the Technical University of Munich (TUM) with the Chair for Efficient Algorithms under Prof. Stephen Kobourov. His work bridges computational efficiency and empirical evaluation, focusing on graph drawing, network visualization, and set visualization techniques. Recent research includes edge bundling for clutter reduction and metaphorical representations of sets, validated through user experiments. Education : PhD in Computer Science (2020) and MSc in Visual Computing (2016) from TU Wien; BSc in Computer Science (2014) from University of Innsbruck. Research : Specializes in algorithmic design for data visualization, emphasizing user-centric evaluation and practical applications. Teaching : Courses on information visualization, algorithm design, and data structures at TUM Heilbronn. His accolades include national and international awards for his dissertation and academic contributions. Award of Excellence, BMBWF (2020) Best Poster Award, GD 2023 Best Paper Award, PacificVis 2023 Distinguished Young Alumni Award nominee, TU Wien GD Contest awards (2018, 2019, 2020)

• Graph Drawing
• Network Visualization
• Set Visualization
• +۳ مورد دیگر

Michael Striewe is a prominent academic in the fields of software engineering and educational technology. Currently, he serves as a scientific assistant at the University of Duisburg-Essen, but will transition to a professorial role at Trier University of Applied Sciences in October 2024. He holds a Ph.D. from paluno - The Ruhr Institute for Software Technology, where his thesis focused on automated assessment of programming and modeling tasks. Striewe's research spans integrated e-assessment systems, software engineering methods, and competency-based feedback mechanisms. His work emphasizes technology-enhanced assessment, including automated grading and domain-specific task generation. He has contributed to projects like the JACK e-assessment system and co-authored an anthology on automated assessment in programming education. Striewe is actively involved in academic communities, serving on committees for conferences such as DELFI, ITiCSE, and TEA. He chairs workshops on topics like automatic assessment of programming tasks and software engineering for e-learning systems. His teaching roles include membership in examination boards for computer science and applied computer science programs. He has led master’s project groups on topics like variability in programming tasks and e-assessment using text analysis. Striewe’s research interests include graph grammars, UML modeling, software performance engineering, and educational technologies. His recent publications focus on modularizing e-assessment systems, analyzing collusion in online exams, and developing competence models for graphical modeling. He has addressed challenges in digitalizing chemistry exercises and improving the scalability of assessment frameworks.

• Educational Technology
• Software Engineering
• Automated Assessment
• +۳ مورد دیگر

Dr. Henry Förster is a researcher at the Algorithmics Department, Wilhelm-Schickard Institute of Computer Science, University of Tübingen, specializing in theoretical computer science with a focus on graph algorithms, computational complexity, and information visualization. He moved to TUM Campus Heilbronn in 2022 while continuing his role in Tübingen. Current affiliation: University of Tübingen School: Faculty of Mathematics and Natural Sciences Department: Department of Computer Science Academic rank: Researcher Research Interests His work centers on graph drawing, algorithm design, and visualization techniques for relational data, with applications in engineering, economics, and everyday scenarios like metro-map design. He explores geometric representations of graphs, crossing resolution, and dynamic visualization parameters. Education Dr. rer. nat. (summa cum laude), University of Tübingen (2016–2020) M.Sc. in Computer Science (1.4), University of Tübingen (2014–2016) B.Sc. in Engineering & Computing (1.8), TU Bergakademie Freiberg (2010–2014) High School Diploma, High School "Am Markt" Hettstedt (2010) Scientific Awards First Place, GD Contest 2020 Live Challenge (Automatic Category) First Place (Automatic and Manual Categories), GD Contest 2019 Winner, Algorithms Travel Awards 2019 First Place, GD Contest 2018 (Automatic Category) Teaching and Service He has taught lectures, seminars, and exercises on topics such as algorithmics, graph theory, graph databases, and computational complexity since 2016. He served as a PC member for GD2022 and advocated for SafeToC initiatives.

• Theoretical Computer Science
• Graph Algorithms
• Computational Complexity
• +۳ مورد دیگر

Prof. Dr. Tatiana Landesberger von Antburg serves as Professor and Vice Director of Scientific Domain 1 (Theory of Data and Simulation Science) at the Center for Data and Simulation Science (CDS), University of Cologne, leading the Visual Analytics research group within the Institute of Computer Science. Her pioneering work in interactive visualization and visual analytics tackles complex datasets including graphs, movement data, biomedical information, time series, and multivariate data. She develops integrated systems combining machine learning and interactive interfaces to support decision-making across transportation, finance, journalism, and healthcare domains, with particular emphasis on real-world applications in epidemiology and earth sciences. Recent publications (2019-2021) reveal a strong trajectory toward healthcare applications, especially hospital infection control through pathogen transmission analysis, alongside foundational contributions to multilayer network visualization. Her work consistently bridges theoretical innovation with practical implementation in high-impact fields like epidemiology and climate science. Major recognitions include: 2015 Academia Europaea Burgen Scholar Award 2014 IEEE Transactions on Visualization and Computer Graphics Best Reviewer Award IEEE VAST Best Paper Honorable Mention (2020) She directs significant research initiatives funded through: IMfESS – Intelligent Methods for Earth System Sciences RISK Principe – Risk prediction for infection control in hospitals SANE WarmWorld – Exascale Earth System Modeling Her Visual Analytics group actively mentors students and postdoctoral researchers while collaborating internationally on interdisciplinary projects. The laboratory specializes in creating interactive tools for complex data exploration, with ongoing expansion into exascale computing applications for climate modeling and pandemic response systems.

• Visual Analytics
• Interactive Visualization
• Graph Visualization
• +۴ مورد دیگر

Dr. Isaak Lim is a researcher in the Department of Computer Science at RWTH Aachen University, Faculty of Mathematics, Computer Science and Natural Sciences. His contact information includes Room 109, phone +49 241 8021805, fax +49 241 8022899, and email isaak.lim@cs.rwth-aachen.de. He maintains an active research profile with publications spanning from 2016 to 2025. Lim's research focuses on computer graphics, 3D shape generation, deep learning applications for visual data, and geometry processing. His work bridges computer vision and graphics with machine learning techniques, particularly exploring how to represent and generate visual data more effectively. He has made significant contributions to point cloud processing, feature curve analysis, and vision-language model fine-tuning. His research often addresses the challenge of creating efficient representations of visual data that balance compression with information preservation. His publication record shows a clear trajectory of increasing independence and impact, with recent work (2023-2025) often featuring him as first author on high-impact venues like ICCV and VMV. His research demonstrates a consistent focus on improving the representation and processing of visual data through novel algorithmic approaches that combine traditional computer graphics techniques with modern deep learning methods. Among his notable achievements is the Best Paper Award at VMV 2025 for his work on Quantised Global Autoencoders, which presented a holistic approach to visual data representation inspired by spectral decompositions but enhanced with data-driven basis functions. Lim frequently collaborates with Prof. Leif Kobbelt and other researchers at RWTH Aachen, contributing to a productive research environment in computer graphics. While specific grant information isn't provided in the available text, his consistent publication output across major conferences suggests active research funding support. His work has practical applications in areas including 3D modeling, image generation, and computer vision systems. His research group appears to be part of the Computer Graphics group at RWTH Aachen, focusing on the intersection of traditional computer graphics techniques with modern deep learning approaches. The team's work emphasizes practical solutions for visual data representation that balance computational efficiency with high-quality output.

• Computer Graphics
• 3D Shape Generation
• Deep Learning
• +۴ مورد دیگر

Stefan Felsner is a Professor at the Institut für Mathematik of Technische Universität Berlin , specializing in Algorithmic and Discrete Mathematics . His work focuses on Graph Theory, Combinatorics, Discrete Geometry, and Order Theory. He leads the Discrete Mathematics Group and has been involved in DFG-funded projects on geometric representations of graphs, arrangements, and order geometry. Education & Career: Studied Mathematics at the University of Vienna. Worked as a research assistant at TU Berlin (1988–1993), then at Freie Universität Berlin (1993–2003) before becoming a Professor at TU Berlin in 2003. He earned his Habilitation in 1997 and has held visiting positions in the U.S. and Canada. Research Interests: Graph drawing, geometric graphs, arrangements of lines/pseudolines, order dimension, and combinatorial structures. He authored the book Geometric Graphs and Arrangements and contributes to editorial boards of ORDER and DMTCS . Recent Work: Focuses on contact representations of planar graphs, pseudocircle arrangements, and flip graph connectivity. His recent articles address convex drawings, Hamiltonian cycles in convex graphs, and counting pseudoline arrangements. He actively participates in the Mittagsseminar for discrete mathematics discussions.

• Graph Theory
• Discrete Mathematics
• Combinatorics
• +۳ مورد دیگر

Dr. Henry Förster is a Post-Doc researcher at the Technical University of Munich (TUM) within the Chair of Efficient Algorithms, working under Prof. Stephen Kobourov. His research focuses on graph embeddings and network visualization , with applications in computer engineering, economics, and everyday contexts like metro maps. Ph.D. (Dr. rer. nat.) in Computer Science, summa cum laude, University of Tübingen (2020) M.Sc. in Computer Science, University of Tübingen (2016) B.Sc. in Engineering & Computing, TU Bergakademie Freiberg (2014) His work explores algorithmic efficiency , theoretical bounds for aesthetic criteria , and practical solutions for visualizing relational data. He has contributed to domains such as VLSI layouting, floor planning, and UML/Petri net diagram generation. Henry has received multiple accolades, including: Best Paper Award at GD 2024 First Place in GD Contest Live Challenges (2018–2022) Best Presentation Award at GD 2022 He actively contributes to academic communities as a PC member for GD2025, WG2025, and SafeToC advocate for GD. His teaching includes courses like Advanced Algorithms and Practical Course on Network Visualization .

• Graph Drawing
• Network Visualization
• Algorithm Design
• +۴ مورد دیگر

Benedikt Hofer is a researcher at the Technical University of Munich (TUM), affiliated with the Professorship for Thermofluid Dynamics. His work focuses on the intersection of civil engineering, computer science, and digital modeling. University: Technical University of Munich Role: Researcher Contact: benedikt.hofer@tum.de Hofer’s research interests include Digital Twin , Building Information Modeling (BIM) , Graph Rewriting , and Parametric Modeling . His work emphasizes automated model generation, infrastructure digitization, and optimization through AI-driven methods. Recent publications highlight advancements in BIM collaboration , point cloud analysis for bridges , and graph-based design systems . These studies focus on scalability, version control, and integration of digital fabrication with BIM. The Technical University of Munich’s Thermofluid Dynamics group, led by Prof. Wolfgang Polifke, supports Hofer’s research in thermoacoustic interactions and fluid dynamics.

• Digital Twin
• Building Information Modeling (BIM)
• Graph Rewriting in Engineering Design
• +۳ مورد دیگر

Andre Borrmann is Professor and Chair of Computing in Civil and Building Engineering at the Technical University of Munich (TUM), where he leads cutting-edge research at the intersection of computer science and construction engineering. His work spans over two decades with consistent publication output since 2003, demonstrating sustained academic leadership in computational methods for the built environment. His research focuses on: Building Information Modeling (BIM) and its advanced applications Digital Twin development for infrastructure management Point cloud processing and semantic enrichment Artificial intelligence integration in construction workflows Construction automation and robotics systems Analysis of his 2023-2025 publications shows a clear trend toward sophisticated AI applications in construction engineering, with increasing emphasis on graph neural networks, transformer models, and large language models. His work bridges theoretical computer science with practical construction challenges, particularly in model automation, code compliance checking, and digital documentation of existing structures. Scientific recognition includes: Konrad Zuse Medal (2024) Professor Borrmann leads multiple significant research initiatives including AM2PM (Additive to Predictive Manufacturing for Multistorey Construction), AI4CADCAM (AI-based CAD processing), and BauPuls360 (a public service platform for the construction industry). His research group maintains extensive international collaborations across academia and industry, contributing to UN Sustainable Development Goals related to sustainable cities, industry innovation, and climate action through their technological advancements in construction engineering.

• Building Information Modeling
• Point Cloud Engineering
• Digital Twin
• +۴ مورد دیگر

Prof. Michael Kaufmann is a Professor in the Department of Computer Science at Eberhard Karls University of Tübingen, within the Faculty of Mathematics and Natural Sciences. He is affiliated with the Wilhelm-Schickard Institute of Computer Science and leads the Algorithmics team. His research focuses on algorithms, complexity, computational geometry, graph drawing, and network visualization. He holds a prominent role in advancing theoretical computer science and combinatorial optimization. His research interests span algorithms and complexity, approximations, combinatorial optimization, computational geometry, graph drawing applications, and parallelism. His work bridges theoretical foundations with practical applications in network visualization and algorithmic design. Prof. Kaufmann has published extensively in leading venues, including Graph Drawing (GD), International Symposium on Theoretical Aspects of Computer Science (STACS), and International Workshop on Graph-Theoretic Concepts in Computer Science (WG). His publications address challenges in graph visualization, algorithmic techniques, and computational geometry. He advises students through the Algorithmics team and maintains an office at Room B112, reachable via email or phone. His work contributes to both academic and applied domains within computer science.

• Algorithms and Complexity
• Approximations
• Combinatorial Optimization
• +۴ مورد دیگر

Prof. André Schulz is a Professor at the Faculty MI, Department of Theoretical Computer Science, Distance University. His research focuses on graph theory, computational geometry, and algorithm design, with a strong emphasis on geometric graphs, graph drawing algorithms, and topological representations. He has published extensively in top-tier journals and conferences such as Discrete & Computational Geometry , Journal of Graph Algorithms and Applications , and Graph Drawing and Network Visualization . His work spans topics like adjacency graphs of polyhedral surfaces, Lombardi drawings of knots, and experimental analysis of graph visualization techniques. He collaborates internationally, co-authoring over 30 peer-reviewed articles since 2015. His research addresses challenges in geometric algorithms, graph embeddings, and combinatorial optimization, with applications in social network analysis and geometric topology. Key contributions include minimizing geometric primitives in planar graph drawings and developing efficient algorithms for 1-planar and cubic graphs. His recent work (2023–2024) explores orthogonal circle arrangements and schematic hypergraph layouts. Despite no explicit mention of awards or grants, his prolific publication record underscores his academic influence.

• Graph Theory
• Computational Geometry
• Algorithm Design
• +۳ مورد دیگر