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Fabian WeinView profile

Researcher

• Topology Optimization
• Structural Optimization
• Computational Mathematics
• +3 more

Dr. Fabian Wein serves as a Senior Scientist at the Chair of Applied Mathematics (Continuous Optimization) within the Department of Mathematics at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His research focuses on advanced optimization techniques with applications in structural design and additive manufacturing. Wein maintains an active research profile with numerous publications in leading optimization journals and collaborates extensively within Michael Stingl's research group. Wein's research interests center on topology optimization methodologies, particularly feature-mapping approaches for structural optimization. His work bridges theoretical mathematics with practical engineering applications, especially in the context of additive manufacturing technologies. He has made significant contributions to two-scale optimization of graded lattice structures, buckling analysis of cellular structures, and optimization of piezoelectric devices. His research demonstrates a consistent focus on developing computationally efficient methods that respect manufacturing constraints while achieving optimal structural performance. Analysis of Wein's recent publications reveals a strong trend toward multiscale optimization approaches that integrate microstructural design with macroscopic performance requirements. His work increasingly addresses the challenges of additive manufacturing, particularly in developing optimization frameworks that account for process-structure-property relationships. The research spans from fundamental mathematical developments to practical applications in electromechanics, fluid dynamics, and structural mechanics. Wein actively participates in academic advising and research supervision, as evidenced by his involvement with master's theses such as 'Optimization of a Solar Air Heater' (2022). His research has received substantial citations, indicating significant impact in the optimization community. The work is often supported through collaborations with institutions like the Max Planck Society and Fraunhofer Institutes, leveraging FAU's strong research ecosystem. Within the research environment at FAU, Wein contributes to the Continuum Optimization group that maintains several computational resources including openCFS (an open-source C++ FEM framework with structural optimization capabilities) and iTop (an interactive educational topology optimization platform). His work connects with broader university initiatives in advanced manufacturing and computational engineering, contributing to FAU's position as one of Germany's leading research universities with over 14,000 staff members across the Nuremberg Metropolitan Region.

Philipp Christoph WederView profile

Researcher

• Isogeometric Analysis
• Numerical Methods
• Computational Mathematics
• +5 more

Philipp Christoph Weder is a Doctoral Assistant and PhD candidate at the Chair of Numerical Modelling and Simulation (MNS) within the Department of Mathematics at École Polytechnique Fédérale de Lausanne (EPFL). He is supervised by Prof. Annalisa Buffa and specializes in isogeometric analysis, analysis-aware defeaturing, and nonlinear model reduction techniques. His academic background includes a Master’s in Computational Sciences and Engineering and a Bachelor’s in Mathematics from ETH Zürich. Research Interests Isogeometric Analysis Numerical Methods for Partial Differential Equations Machine Learning in Scientific Computing Wave Propagation Modeling Computational Physics Fluid Dynamics at Low Reynolds Numbers Recent Publications and Preprints 2025: Galerkin Neural Network-POD for Wave Propagation 2025: Neural Galerkin Schemes on Quadratic Manifolds 2025: Lumped Parameter Modeling for Congenital Heart Syndromes 2022: Stokesian Microswimmer Optimization Scientific Recognition EPFL PhD Excellence Program (2025) Teaching and Collaboration Main Teaching Assistant for Parallel and High-Performance Computing (2025) and Analysis III (2024) at EPFL Contributions to international conferences like the Swiss Numerics Day 2025 and the Functional Imaging and Modeling of the Heart International Conference (2025) Active participation in research networks including the SIAM Student Chapter at EPFL

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

GÜL TUĞ is an Associate Professor in the Department of Mathematics at Karadeniz Technical University's Faculty of Science, specializing in differential geometry and mathematical physics. She has held academic positions at KTU since 2010, progressing from Research Assistant to Associate Professor. Education: PhD in Mathematics, Karadeniz Technical University (2011-2017) Postgraduate studies at Ankara University (2008-2010) and KTU (2010-2011) BSc in Mathematics, Ankara University (2004-2008) Research Interests: Her work focuses on geometric structures in relativistic spaces, including lightlike manifolds, accretive growth kinematics, and curve evolution in Minkowski spacetime. She explores applications in mathematical biology and physics through differential geometry frameworks. Publication Trends: Her 14 recent articles predominantly investigate kinematic surface growth, lightlike hypersurfaces, and curve evolution in Lorentz-Minkowski spaces, blending theoretical mathematics with physics applications. Research consistently utilizes Darboux frames, quaternionic methods, and geometric flow models. Advising: Supervised postgraduate research on Ricci solitons in lightlike hypersurfaces (2021). No significant grants or lab affiliations documented.

Zafeirakis ZafeirakopoulosView profile

Researcher

• Symbolic Computation
• Discrete Mathematics
• Combinatorics
• +4 more

Zafeirakis Zafeirakopoulos is a researcher at the National and Kapodistrian University of Athens (Greece) in the ELIDEK project led by Prof. Maria Chlouveraki. His academic career includes roles as an assistant professor at Gebze Technical University (2016-2022) and postdoctoral research at University of Athens (Greece), Galatasaray University (Turkey), and University of Geneva (Switzerland) under the Eccellenza project of Prof. Jehanne Dousse. PhD in RISC - Research Institute for Symbolic Computation (supervised by Prof. Peter Paule and Prof. Matthias Beck) Current affiliations: Mathematics department of National and Kapodistrian University of Athens Service roles: Information Director of ACM SIGSAM, Associate Editor of ACM CCA His research focuses on symbolic computation, discrete mathematics, and computational geometry. He has developed algorithms for parametric curve topology (PTOPO) and linear Diophantine systems (Polyhedral Omega), emphasizing efficiency and geometric interpretations. Recent work involves Julia/Maple implementations for practical applications. Publication trends highlight interdisciplinary work in symbolic algorithms, polyhedral geometry, and combinatorial optimization. He actively contributes to international conferences like ACA 2025 (co-organizer) and SCALE 2022.

Kamel LahouelView profile

Assistant Professor

• Machine Learning
• Cancer Early Detection
• Cell-free DNA Analysis
• +4 more

Kamel Lahouel is an Assistant Professor at the Early Detection and Prevention Division of the Translational Genomics Research Institute (TGen) . He joined TGen in February 2022 and focuses on mathematical and statistical models applied to cancer biology. Education : Ph.D. in Applied Mathematics and Statistics from Johns Hopkins University (2018). Dr. Lahouel specializes in machine learning and stochastic processes to analyze cell-free DNA for cancer early detection and minimal residual disease testing (MRD) . His methodological work includes branching processes , Markov chains , and non-parametric statistics for tasks like stochastic optimization and multiple hypothesis testing . His research also explores pattern recognition in latent dynamical systems . Recent publications highlight his development of generative models for tumorigenesis timelines (2020), supervised mutational signatures in cancer (2021), and data-driven blood testing combined with PET-CT (2020). His work bridges applied mathematics with clinical oncology , emphasizing computational approaches for early cancer detection.

Polona OblakView profile

Professor

• Matrix Theory
• Graph Theory
• Spectral Graph Theory
• +7 more

Polona Oblak serves as a Full Professor at the Faculty of Computer and Information Science, University of Ljubljana, where she is an integral member of the Laboratory for Mathematical Methods in Computer and Information Science. Her teaching responsibilities span foundational courses including Linear Algebra, Mathematical Modelling, and multiple levels of Mathematics instruction, reflecting her dual expertise in theoretical mathematics and computational applications. Her research centers on advanced Matrix Theory and Graph Theory, with pioneering contributions to Spectral Graph Theory and Inverse Eigenvalue Problems. She investigates structural properties of commuting matrices, nilpotent matrix centralizers, and tropical semiring algebra, extending theoretical frameworks to practical applications in computer vision and statistical analysis. Recent interdisciplinary projects like "DeepBeauty" demonstrate her ability to bridge pure mathematics with industry-relevant solutions in fashion technology. Analysis of her 15 most recent publications (2021-2025) reveals a dominant focus on spectral graph phenomena, particularly the inverse eigenvalue problem across diverse graph structures including trees, block graphs, and unicyclic graphs. Her work on tropical matrix factorization (e.g., Faststmf algorithm) provides efficient computational tools for sparse data, while theoretical breakthroughs like the "liberation set" concept redefine boundaries in spectral graph theory. This research trajectory shows increasing integration of algebraic methods with machine learning applications. Professor Oblak has secured substantial research funding through the Slovenian Research Agency (ARRS) and international collaborations, including the ongoing "Computer Vision" program (2019-2024) and bilateral projects with Bosnia and Herzegovina on nilpotent orbits. Her leadership in computationally intensive statistical methods (2016-2019) and deep generative models for the beauty industry (2020-2023) demonstrates consistent ability to translate theoretical advances into funded research initiatives, though specific student supervision details remain unlisted in available sources. Within the Laboratory for Mathematical Methods in Computer and Information Science, she contributes to a synergistic research environment where algebraic techniques directly inform computational solutions. Her work on Laplacian-integral graphs and tropical factorization algorithms exemplifies the laboratory's mission to develop mathematical foundations for next-generation information systems, with recent outputs showing heightened emphasis on algorithmic efficiency for real-world data challenges.

Marija ĐurkovićView profile

Professor

• Woodworking Machinery
• Tool-Workpiece Interaction
• Computer Numerical Control (CNC) Systems
• +1 more

Marija Đurković is a Full Professor at the University of Belgrade's Faculty of Forestry, Department of Wood Processing. Her career began in 2009 as an assistant professor, progressing to associate professor in 2020 and full professorship. She chairs the Wood Technologies Department Council and Serbia's M039-4 Woodworking Machines Standards Committee. Education: University of Belgrade - Faculty of Forestry (PhD in Wood Processing) Teaching: Undergraduate, master's, and doctoral courses in Woodworking Machines, CNC Technologies, and Vibrational Diagnostics Research Focus spans woodworking machinery, tool-workpiece interactions, and computer numerically controlled systems. Recent work explores cutting force modeling, acoustic emission monitoring, and sustainable energy practices in wood processing. Scientific Output includes SCI-indexed journals like BioResources and conference proceedings. Her 2021 studies on oak milling and beech sawing represent key contributions to CNC machining optimization. Professional Contributions include two Ministry-funded projects, 9 SCI articles, 2 technical solutions, and a co-authored textbook used in master's and doctoral programs. She also mentors over 70 diploma thesis students annually.

• Architectural Informatics
• Computational Design
• Digital Fabrication
• +4 more

Prof. Dr. Mine Özkar Kabakçıoğlu is a leading academic at Istanbul Technical University's Faculty of Architecture, Department of Architecture, with a focus on computational design, digital fabrication, and architectural cultural heritage. She holds a Ph.D. from MIT (1999) and has been a full Professor at ITU since 2016, previously serving as Associate Professor at MIT (2013) and ITU (2011-2015), and Assistant Professor at METU (2006-2011). Research Centers: CMU Code Lab, NAAB Accreditation Committee Expertise: Shape grammars, material manipulation, Seljuk geometric patterns, socio-spatial analysis Her work bridges traditional craftsmanship with computational methods, particularly in Anatolian architectural heritage. She has led projects on brick bond analysis (TÜBİTAK 119K896), medieval stone milling workflows, and digital preservation of polyhedral designs like the Gömeç Hatun tomb. Her pedagogy emphasizes critical technical practice and accountability in computational design education. Scientific contributions include 15+ peer-reviewed articles on topics like Digital workflows for heritage conservation Visual reasoning in brickwork Material-aware shape computation She received the METU Young Researcher Achievement Award (2007) and serves on architectural accreditation boards. Her research group includes students and collaborators such as Sevgi Altun, Begum Hamzaoğlu, and international partners from NYU, MIT, and TU Delft.

Alicia Cantón PireView profile

Professor

• Mathematics
• Applied Mathematics
• Geometry
• +5 more

Alicia Cantón Pire is a Professor at the Department of Mathematics and Computer Science Applied to Civil and Naval Engineering , affiliated with the Higher Technical School of Naval Engineers (ETSIN) at the Polytechnic University of Madrid (UPM) . Her research spans multiple domains within Mathematics, Applied Mathematics, and Computer Science, focusing on geometric modeling, complex analysis, and graph theory. Research Interests : Asymptotic values of meromorphic functions, Gromov hyperbolicity in planar graphs, geometric characteristics of Bézier surfaces, and isoperimetric inequalities. Teaching : Engaged in academic instruction, with access to the Moodle platform for current courses. Professional Affiliations : Member of mathematical societies including the Royal Spanish Mathematical Society (RSME) , Spanish Society of Applied Mathematics (SeMA) , and the American Mathematical Society (AMS) . Her work integrates theoretical mathematics with practical applications in engineering and computer science, reflecting in her collaborative publications and extensive contributions to geometric and analytic problems. Email : alicia.canton@upm.es

Sang Il ParkView profile

Professor

• Computer Graphics
• Character Animation
• 3D Geometry Processing
• +4 more

Sang Il Park is a Professor in the Department of Software at Sejong University, South Korea, where he has been a faculty member since 2007 following postdoctoral work at Carnegie Mellon University's Robotics Institute (2005-2007) and a brief research position at Japan's Digital Human Research Center. Ph.D. in Computer Science, KAIST (2004) M.S. in Computer Science, KAIST (1999) B.S. in Computer Science, Yonsei University (1997) Professor Park's research centers on Computer Graphics , with deep expertise in Character Animation , 3D Geometry Processing , and Image Processing . His research fingerprint shows dominant activity in Motion Capture (100%), Transition Graphs (72%), and Motion Synthesis (72%). His work has evolved from foundational research in human motion capture to incorporating deep learning techniques for image restoration, demonstrating both consistency in core interests and adaptation to emerging technologies. His publication pattern reveals a sustained research program with significant outputs in 2008, 2010, 2014, 2018, and continuing through 2023. The research spans from character animation and motion synthesis to practical applications like document processing and weathering simulation, showing remarkable breadth within his specialized domain. h-index: 12 Total citations: 933 Presented pioneering research at ACM SIGGRAPH Referenced in 4 patents and 2 Wikipedia pages Professor Park leads the Computer Graphics Lab at Sejong University, where he mentors graduate students and conducts research in animation, modeling, rendering, and computational photography. His patent portfolio includes innovations in facial expression restoration and motion synchronization, demonstrating the practical impact of his research beyond academia.

Benedikt WirthView profile

Professor

• Optimisation and calculus of variations
• image processing
• scientific computing
• +9 more

Prof. Dr. Benedikt Wirth is a Professor of Mathematics at the University of Münster, Germany, affiliated with the Institute for Analysis and Numerics within the Department of Mathematics and Computer Science. He is an active researcher and educator specializing in optimization and calculus of variations, with significant contributions to mathematical imaging and shape analysis. His research interests include image processing, scientific computing, numerical analysis, optimization, shape spaces, geodesics in shape space, variational methods, elastic deformation, and optimal transport. Wirth has developed innovative mathematical frameworks for shape analysis, particularly focusing on Riemannian metrics for shape spaces and variational approaches to shape comparison and optimization. His recent publications (2023-2025) demonstrate continued leadership in mathematical optimization, with particular focus on PET reconstruction, dimension reduction techniques, manifold embeddings, and branched transport theory. His work bridges theoretical mathematics with practical applications in medical imaging and computer vision, showing particular strength in connecting geometric analysis with computational methods. CRC 1450 - A05: Targeting immune cell dynamics by longitudinal whole-body imaging and mathematical modelling CRC 1450 - A06: Improving intravital microscopy of inflammatory cell response by active motion compensation EXC 2044 - C1: Evolution and asymptotics EXC 2044 - C2: Multi-scale phenomena and macroscopic structures EXC 2044 - C3: Interacting particle systems and phase transitions EXC 2044 - C4: Geometry-based modelling, approximation, and reduction Prof. Wirth actively supervises numerous bachelor's and master's students, with over 40 theses completed under his guidance since 2015. His teaching portfolio includes courses on inverse problems, numerical methods for partial differential equations, shape spaces, optimization, and optimal transport. He has consistently maintained an active research program while contributing significantly to the education of the next generation of mathematicians.

• Building Information Modeling
• Digital Twinning
• Information Management
• +5 more

Prof. Dr.-Ing. Sebastian Esser serves as Group Lead for Information Management at the Chair of Computing in Civil and Building Engineering at Technical University of Munich. His research focuses on advancing Building Information Modeling (BIM) methodologies, particularly in infrastructure and railway applications. He contributes significantly to international standardization efforts including IFC-Road and IFC-Rail projects, and leads research initiatives such as RIMcomb and BauPuls360. Dr. Esser's research spans several critical areas in digital construction: Graph-based version control systems for BIM collaboration Digital twin development for infrastructure management Semantic modeling of built environments BIM-based regulation checking for railway infrastructure Interdisciplinary model coordination techniques Knowledge representation in civil engineering His work bridges theoretical computer science with practical civil engineering applications, focusing on improving data interoperability and workflow efficiency in construction projects. Analysis of his recent publications reveals a strong emphasis on graph-based approaches to BIM challenges. His research has evolved from foundational work on BIM programming interfaces to sophisticated implementations involving knowledge graphs, semantic reasoning, and digital twin architectures. Key trends include increasing integration of semantic web technologies with BIM standards, development of specialized query interfaces like GraphQL for construction data, and application of formal methods to infrastructure modeling problems. Dr. Esser actively supervises numerous bachelor's and master's theses annually, with recent topics covering graph-based entity alignment, BIM-GIS integration for flood assessment, incremental model updates, and digital twin implementations. His teaching portfolio includes courses such as Bau- und Umweltinformatik, BIM.fundamentals, BIM.infra, and Semantic Modeling of the Built World, demonstrating his commitment to educating the next generation of digital construction professionals. He is involved in multiple research initiatives including DFG FOR 5672 (The information backbone of robotized construction), SPP 2187 (Adaptive modularized constructions), and AM2PM (Additive to Predictive Manufacturing). His laboratory work spans the BIM-Lab and related computational infrastructure supporting his research in digital construction technologies.

• Building Information Modeling (BIM)
• Model-Based Systems Engineering (MBSE)
• Graph-Based Design
• +3 more

Benedict Harder is a Researcher at the Chair of Computing in Civil and Building Engineering, Technical University of Munich, specializing in Building Information Modeling and Model-Based Systems Engineering. He contributes to the DFG SPP 2187 project on modular concrete bridges and maintains active roles in research and teaching. His educational foundation includes a 2024 Master's thesis on algorithmic design of modular precast structures and a 2021 Bachelor's thesis exploring train station design via parametric modeling. These works established his trajectory in computational civil engineering. Harder's research integrates semantic web technologies with infrastructure design, focusing on SysML-OWL interoperability, graph-based modular construction, and formal methods for BIM. His work bridges computer science formalisms with practical civil engineering challenges, particularly in bridge systems and precast structures. Publication trends reveal consistent advancement in formalizing design processes: early work centered on parametric regulation compliance (2021), evolving to SysML-based bridge representation (2024) and semantic reasoning frameworks (2025). Key themes include graph rewriting for modular design, incremental BIM updates, and MBSE applications in structural monitoring. He supervises graduate research including a 2025 Master's thesis on MBSE for bridge monitoring and teaches courses like Computer-Aided Modeling of Products and Processes. His academic activities align with TUM's BIM-Lab and research groups in Digital Twinning and Knowledge Representation.

• Knowledge Representation and Reasoning
• Geometry Processing
• Machine Learning
• +1 more

Dr. Stavros Nousias is a researcher at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich , focusing on applications of Artificial Intelligence in the Built Environment . His work bridges Knowledge Representation and Reasoning , Geometry Processing , and Machine Learning to advance construction informatics and digital twinning. Research Interests: AI for building evacuation prediction, technical drawing segmentation, BIM optimization, and respiratory disease modeling. Publications: 15+ peer-reviewed articles on topics including graph neural networks for construction simulations, pulmonary airflow analysis, and heritage site monitoring. Supervised Theses: Guided projects on AI-based BIM command prediction and robotized construction simulation . Labs: Active in the BIM-Lab and Robotic Fabrication Lab . Teaching: Co-instructor for courses like Artificial Intelligence in Engineering and Computation in Engineering 1 .

• Responsive Architecture
• Shape-Shifting Structures
• Tensegrity Systems
• +7 more

Giuseppe Ruscica is an Associate Professor in the scientific disciplinary sector ICAR/11 (Building Production) at the Department of Engineering and Applied Sciences of the University of Bergamo. He has been with the university since 2012, initially serving as a Researcher until 2023 before being promoted to his current position. Dr. Ruscica earned his PhD in "Architectural, Urban, and Environmental Design and Restoration" from the University of Catania in 2009 and a Degree in Building Engineering with highest honors (110/110 cum laude) from the same institution in 2004. His research focuses on innovative approaches to architectural design and construction, with particular emphasis on responsive and shape-shifting architectures, tensegrity systems, reciprocal structures, and origami-like operations. He also investigates automation for self-supporting masonry shells and develops building components with electromagnetic radiation shielding capabilities using sustainable materials like biochar. His work extends to low-cost IoT sensor systems for environmental monitoring in construction contexts. Dr. Ruscica's publications reveal a strong trend toward integrating sustainable materials with advanced construction technologies, particularly focusing on electromagnetic shielding applications using biochar composites. His research bridges traditional construction methods with cutting-edge digital technologies including Building Information Modeling (BIM), augmented reality, and virtual reality applications for construction sites. He serves as Lecturer for courses including "Technology of Construction Elements and Building Information Modeling" and "Building Ergonomics" for the Building Technologies Engineering program, and co-teaches "Building Information Modeling (BIM)" for the Master's Degree in Construction Engineering.