Find Academic Supervisors

• Symbolic Regression
• Genetic Programming
• Emulator Development
• +4 more

Lukas Kammerer is a Research Fellow at the University of Applied Sciences Upper Austria, specifically affiliated with the Research Center Hagenberg Center of Excellence for Smart Production and the Focal area ICT - Information & Communications Technology. His work bridges computer science methodologies with astrophysical applications, particularly in symbolic regression and emulator development. His primary research areas include: Symbolic Regression and its theoretical foundations Genetic Programming efficiency analysis Development of analytic emulators for cosmological simulations Bias-variance tradeoffs in regression methods Precise modeling of matter power spectrum Nonlinear optimization techniques for function extraction Dr. Kammerer's publication record demonstrates strong interdisciplinary work connecting computer science with astrophysics. His recent publications show increasing sophistication in developing symbolic representations of complex physical phenomena, with applications ranging from machine learning benchmarks to cosmological modeling. The dual focus on methodological improvements in symbolic regression and their concrete applications in astrophysics represents a distinctive research trajectory. As a Co-Investigator on major research projects including the Josef Ressel Zentrum für Symbolische Regression (2018-2022) and EREMA Recycling 4.0 (2017-2019), he has secured significant research funding and collaborated with international teams across multiple scientific domains. His work is associated with the HEAL research group at the University of Applied Sciences Upper Austria, which focuses on computational methods for scientific applications, particularly in the domains of symbolic regression and its practical implementations.

Martin EhlerView profile

Associate Professor

• Computational Harmonic Analysis
• Mathematical Data Analysis
• Image Processing
• +3 more

Martin Ehler serves as Associate Professor and Vice-Dean for Teaching at the University of Vienna's Faculty of Mathematics, where he concurrently holds the position of Deputy Head of the Institute of Mathematics. His academic activities are centered at Oskar-Morgenstern-Platz 1, Room 10.128, Vienna, with primary responsibilities spanning research leadership, teaching undergraduate/graduate mathematics courses, and administrative oversight of academic programs. His research program in Computational Harmonic Analysis drives innovations in Mathematical Data Analysis and Medical Image Processing , evidenced by his leadership in the Applied Harmonic Analysis Cluster (AHA) and co-organization of the bi-annual Strobl conference. Core methodologies integrate frame theory, manifold approximation, and spherical design principles to address challenges in neural network stability, medical imaging reconstruction, and signal processing robustness. Analysis of his 2023-2025 publications reveals dominant themes in harmonic analysis applications to deep learning architectures (particularly ReLU-layer injectivity and filterbank design), geometric approximation on manifolds, and medical imaging algorithms. These works demonstrate consistent interdisciplinary collaboration across mathematics, signal processing, and biomedical engineering domains. No scientific awards were documented in the provided materials. While teaching responsibilities for courses like Introduction to Analysis and Mathematics of Data Science are explicitly listed, details regarding graduate student supervision or research grant funding were absent from the source texts. His research ecosystem is anchored in the Applied Harmonic Analysis Cluster (AHA), facilitating cross-institutional collaboration on harmonic analysis applications, with documented partnerships through co-authored publications in venues like IEEE Signal Processing Letters and Mathematics of Computation.

Georg KresseView profile

Professor

• Theoretical Solid State Physics
• Surface Sciences
• Computational Materials Physics
• +5 more

Georg Kresse is a full Professor of Computational Quantum Mechanics at the University of Vienna's Faculty of Physics, leading the Computational Materials Physics group. He developed the Vienna ab initio Simulation Package (VASP), a globally dominant tool for quantum mechanical materials simulations. His research spans theoretical solid-state physics, surface science, and computational materials physics, with recent emphasis on machine learning integration and advanced electronic structure methods. Born in Vienna (1967), habilitated in condensed matter theory Full member of Austrian Academy of Sciences and International Academy of Quantum Molecular Science Recipient of START Grant (2003), Kardinal-Innitzer-Preis (2016), honorary doctorate from Lund (2022) Research focuses include: Density Functional Theory : Development of advanced functionals (hybrid, GW, RPA) Machine Learning : Applications to materials properties and force fields Quantum Monte Carlo : AFQMC methods for solids Surface Physics : Oxidation reactions and catalytic processes His publications show strong representation in: Quantum mechanical simulations Electronic and optical properties Phase transitions and thermodynamics Energy materials and nanotechnology Major projects include: MECS : Materials for Energy Conversion and Storage (2023-2028) TACO : Taming Complexity in Materials Modeling (2021-2029) DCAFM : Doctoral College Advanced Functional Materials (2020-2025) His group maintains VASP, combining first-principles methods with machine learning to advance materials science understanding.

Gundolf HaaseView profile

Professor

• Scientific Computing
• High Performance Computing
• Parallel Algorithms
• +7 more

Gundolf Haase is a Professor at the Department of Mathematics and Scientific Computing at the University of Graz, Austria. His academic career spans several decades with significant contributions to parallel computing and numerical methods for partial differential equations. He maintains an active research profile with numerous publications in high-impact journals and conferences. His research interests primarily focus on Scientific Computing, High Performance Computing, Parallel Algorithms, Domain Decomposition Methods, Finite Element Methods, Multigrid Methods, and GPU Programming. His work has increasingly incorporated biomedical applications, particularly in cardiac electrophysiology modeling and computational fluid dynamics for cardiovascular applications. Haase's recent publications demonstrate a strong focus on many-core parallelization techniques, particularly for GPUs, with applications spanning from computational cardiology to engineering simulations. His research shows a consistent pattern of developing efficient numerical methods for solving complex partial differential equations across various scientific domains. He teaches courses including Scientific Computing and FEM, Computer Mathematics, Programming in C++, and High Performance Computing at both undergraduate and graduate levels, demonstrating his commitment to education alongside research.

• Symbolic Computation
• High-Order Finite Elements
• Special Functions
• +3 more

Veronika Pillwein is an Associate Professor at the Research Institute for Symbolic Computation (RISC) within Johannes Kepler University in Linz, Austria. Her research focuses on symbolic computation, high-order finite elements, special functions, and algorithmic combinatorics. She contributes to advancing computational methods for sequence analysis, recurrence relations, and polynomial systems, with applications in numerical analysis and engineering. Pillwein has authored/co-authored numerous publications in top-tier journals and conference proceedings, including work on C²-finite sequences, hp-FEM element matrices, and positivity proofs for rational functions. She serves as an editor for academic volumes and actively participates in computational mathematics research. Her work integrates symbolic computation techniques with numerical methods, addressing challenges in high-order finite element analysis and algorithm design. Recent research emphasizes generalizing holonomic sequences, optimizing sparse shape functions for finite elements, and developing automated tools for proving mathematical properties. Pillwein collaborates internationally, contributing to interdisciplinary projects in computational mathematics and computer algebra systems. Affiliations: RISC Faculty, Johannes Kepler University (JKU) Key Research Areas: Symbolic computation, finite element methods, combinatorial algorithms, polynomial analysis Technical Contributions: Development of C²-finite sequence theory, hp-FEM element matrix evaluation, algorithmic proofs for positivity

Josef SchichoView profile

Professor

• Algebraic Geometry
• Kinematics
• Robotics
• +4 more

Josef Schicho is a Full Professor at the Research Institute for Symbolic Computation (RISC), Johannes Kepler University in Linz, Austria. His research focuses on algebraic geometry, computational mathematics, and their applications in kinematics, robotics, and geometric modeling. He leads projects exploring flexible polyhedra, mechanism design, and symbolic computation techniques for solving geometric problems. Key research interests include the study of rigid and flexible frameworks, algebraic methods in robotics, and the application of geometric algorithms to problems in computer vision and sensor networks. His work bridges theoretical mathematics with practical engineering solutions, particularly in mechanism synthesis and geometric modeling. Recent contributions include advancements in the theory of flexible polyhedra, classification of linkages with high mobility, and computational tools for analyzing robot kinematics. His publications often address problems at the intersection of algebraic geometry and engineering, such as reconstructing geometric configurations from partial data or optimizing motion planning for robotic systems. Dr. Schicho's affiliations include the RISC Faculty at JKU, where he actively contributes to the development of symbolic computation software and collaborates with international researchers in computational algebraic geometry. His office is located at Schloss Hagenberg, Room 2.6-1.

• Computer Algebra
• Combinatorics
• Special Functions
• +4 more

Carsten Schneider is a Professor and Director of the Computer Algebra and Applications group at the Research Institute for Symbolic Computation (RISC) , part of the Johannes Kepler University Linz , Austria. His work focuses on symbolic summation algorithms, difference rings, and their applications in combinatorics, particle physics, and quantum field theory. Research Interests: His expertise includes Computer Algebra , Special Functions , Perturbative Quantum Field Theory , and Combinatorics . He develops algorithms for simplifying multi-sums and solving recurrences, with applications to Feynman integrals and operator matrix elements in particle physics. Grants & Projects: He leads Austrian Science Fund (FWF) grants such as Symbolic Summation for Computer Science (2024–2028) and Computer Algebra for Multi Loop Feynman Integrals (2021–2025). Past grants include FWF SFB F50 research projects in enumerative combinatorics. Software: He developed the Sigma summation package, used for symbolic computation in multi-loop calculations. His tools are widely applied in particle physics and combinatorics. Teaching & Mentoring: Teaches courses like Algorithmic Combinatorics and Computer Algebra at JKU. Organizes workshops and co-chairs conferences like SYNASC and RADCOR . Active in supervising international training networks such as the SAGEX Marie Curie project. Editorial Roles: Editorial board member of journals like Journal of Symbolic Computation and Annals of Combinatorics . Co-edited volumes on symbolic computation in physics and combinatorics.

Peter PauleView profile

Professor

• Symbolic Computation
• Combinatorics
• Special Functions
• +3 more

Prof. Peter Paule is a retired Full Professor at the Research Institute for Symbolic Computation (RISC) of Johannes Kepler University (JKU) Linz, Austria, succeeding Bruno Buchberger. He served as RISC Director from 2009 to 2023 and as director of the FWF Special Research Program SFB F013 (2003–2008). Since May 2024, he is a Guest Professor at Tianjin University’s Center for Applied Mathematics. Paule holds a Ph.D. from the University of Vienna (1983) and a Habilitation in Mathematics from JKU (1996). His research focuses on symbolic computation, combinatorics, special functions, and algorithmic mathematics. He has contributed to creative telescoping, partition analysis, and Ramanujan-Sato series, with over 100 publications in top journals and books. He served as editor for journals like the Ramanujan Journal , Annals of Combinatorics , and the Journal of Symbolic Computation . His academic leadership includes directing the Doctoral Program in Computational Mathematics (2008–2017). His research group has produced numerous students and postdocs, advancing algorithmic methods in combinatorics and number theory.

• Combinatorics
• Algorithms
• Number Theory
• +3 more

Prof. Michael Drmota is a distinguished academic at TU Wien's Department of Combinatorics and Algorithms, part of the Faculty of Mathematics and Geoinformation. He leads research in discrete mathematics, focusing on combinatorics, number theory, and random discrete structures. His work bridges pure mathematics with applications in computer science and statistical physics. Research Interests: Drmota's expertise spans analytic combinatorics, additive number theory, random graph theory, and the study of automatic sequences. He explores topics like prime number distributions, planar map structures, and stochastic processes in discrete systems. His methods often involve generating functions, singularity analysis, and probabilistic techniques. Key Projects: He coordinates major research initiatives including Arithmetic Randomness , Shape Characteristics of Planar Maps , and Infinite Singular Systems . These projects investigate foundational questions in combinatorics and number theory, with implications for algorithm design and mathematical physics. Advising & Collaboration: Drmota supervises graduate students and collaborates internationally. Notable advisees include Andreas Nessmann (discrete polyharmonic functions), Lucas Unterberger (Erdős-Ko-Rado theorems), and Guan-Ru Yu (pattern occurrences in planar maps). His work appears in top-tier journals and conference proceedings. Labs/Teams: Active in TU Wien's Network Lab , he fosters interdisciplinary research on complex networks and algorithmic combinatorics.

• Numerical Range
• Quadratic Risk
• Matrix Mathematics
• +5 more

Markus Gabl is a researcher at the University of Vienna, Faculty of Mathematics, Department of Mathematics. His work focuses on advanced optimization techniques with strong ties to computational mathematics and operations research. His primary research interests include Numerical Range , Quadratic Risk , Matrix Mathematics , and Rank Theorem , with significant contributions to decision problems and approximation algorithms. His work bridges theoretical mathematics and practical computational applications. Recent publications reveal a concentration on copositive optimization approaches for nonconvex problems (2024), stochastic optimization under uncertainty (2023), and two-stage quadratic models (2022). This trajectory shows increasing sophistication in handling risk-aware optimization frameworks. His collaborative network includes prominent researchers like Immanuel Bomze, Georg Pflug, and Francesca Maggioni, primarily through the Vienna Graduate School on Computational Optimization and current copositive optimization projects.

• Computational Mechanics
• Boundary Element Methods
• Wave Propagation
• +3 more

Prof. Martin Schanz is a full Professor at the Institute of Structural Mechanics, TU Graz, within the Faculty of Civil Engineering. His research focuses on numerical methods in computational mechanics, including boundary element methods (BEM), wave propagation modeling, porous media analysis, and structural optimization. He has authored numerous articles on topics such as fast multipole methods, adaptive cross approximation, and multiphasic modeling in biomechanics. Teaching responsibilities include courses on continuum mechanics and structural optimization. His work integrates advanced numerical techniques with applications in civil engineering, materials science, and biomedical systems. Notable projects include the development of efficient BEM formulations for time-domain problems and studies on thrombus formation using porous media theory. He advises doctoral students in computational mechanics and holds a leadership role in the institute. Research collaborations span structural acoustics, poroelasticity, and cardiovascular biomechanics. Contact: m.schanz@tugraz.at

Christoph KoutschanView profile

Research Professor

• Computer Algebra
• Algorithmic Combinatorics
• Symbolic Summation
• +3 more

Christoph Koutschan is a Senior Fellow in the Symbolic Computation group at the Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences. He holds a PhD in Mathematics from JKU Linz (2009) and a Habilitation in Mathematics (2017). His research focuses on computer algebra, algorithmic combinatorics, and symbolic summation/integration of holonomic functions. Koutschan has held positions at Tulane University (2009–2010), Tulane University (2009–2010), and INRIA (2011–2012) before joining RICAM in 2012. Education: PhD in Mathematics (2009), Research Institute for Symbolic Computation (RISC), JKU Linz Habilitation in Mathematics (2017), JKU Linz M.Sc. in Computer Science (2005), FAU Erlangen-Nürnberg Studies in Computer Science (1999–2005), FAU Erlangen-Nürnberg Research Interests: Koutschan's work revolves around symbolic computation with a focus on holonomic functions, combinatorial identities, and applications in mathematical physics. His tools include algorithmic methods for summation/integration, differential equations, and computational algebra. Publications & Awards: Over 40 journal articles, including work on determinant evaluations, Feynman amplitudes, and combinatorial enumeration. Notable awards include the David P. Robbins Prize (2016), ISSAC's Distinguished Software Presentation Award (2016), and the ACA Early Researcher Award (2021). Grants & Collaborations: Lead or co-PI in projects like 'Certificate-free Summation and Integration' (SFB F50, 2017–2021) and 'Security and Safety for Shared AI' (FFG COMET-K2, 2020–2023). Active in editorial roles at Journal of Symbolic Computation and Annals of Combinatorics . Labs/Teams: Core member of RICAM's Symbolic Computation group, collaborating internationally with institutions like INRIA, Tulane University, and TU Wien.

Thomas TakacsView profile

Researcher

• Isogeometric Analysis
• Computational Mechanics
• Numerical Analysis
• +3 more

Dr. Thomas Takacs is a Project Leader in the Geometry in Simulations research group at the RICAM (Research Institute for Symbolic Computation), part of the Austrian Academy of Sciences. His work focuses on advancing computational methods for solving partial differential equations, particularly through isogeometric analysis and spline-based numerical techniques . His research interests include smooth basis constructions, multi-patch domain coupling, and adaptive mesh refinement strategies. Key contributions involve developing C1-continuous spline spaces over planar mixed meshes and unstructured quadrilateral meshes, with applications to engineering problems like linear elasticity. He explores the integration of machine learning (e.g., CNNs) for optimizing quad meshing and employs artificial neural networks in adaptive optimization frameworks. His work bridges geometric modeling and numerical analysis, addressing challenges such as singularity treatment in isogeometric analysis and approximation properties over self-similar meshes. Dr. Takacs collaborates on multi-institutional projects, including the Geometry in Simulations group at RICAM. His publications span computational mechanics, numerical methods, and geometric algorithms, with a focus on advancing the theoretical foundations and practical implementations of isogeometric analysis.

Dieter FellnerView profile

Professor

• Computer Graphics
• Digital Libraries
• Computational Geometry
• +10 more

Dieter Fellner is a Professor of Computer Science at Technical University of Darmstadt, Germany , and Director of the Fraunhofer Institute of Computer Graphics (IGD) . He also serves as Founding Director of the Institute of Computer Graphics and Knowledge Visualization at Graz University of Technology, Austria. His career spans multiple prestigious institutions including University of Bonn, Memorial University of Newfoundland, and University of Technology Braunschweig. Dr. Fellner's research focuses on algorithms integrating modeling and rendering , digital libraries , virtual/augmented reality , collision detection , and radio wave propagation simulation . His work in digital libraries led to a DFG-funded strategic initiative (1997-2005) involving 50 researchers annually across 21 groups. The 15 most recent articles highlight his expertise in 3D document modeling , stereoscopic projection , subdivision surfaces , and color quantization . His publications include influential textbooks like the German standard on computer graphics (1988) and Digitale Bibliotheken (2000). 2000 Fellow of the Eurographics Association Best Technical Paper Award (Günther Enderle Award) at Eurographics’98 2007 IST Advisory Group (ISTAG) Member for the European Commission 2019 Honorary Doctorate from University of Rostock Dr. Fellner actively participates in editorial boards of journals like Computer Graphics Forum , IEEE CG&A , and JOCCH , and serves on program committees for conferences such as Eurographics, VSMM, and ACM Web3D. His leadership roles include Chairmanship of the Eurographics Association (1999-2000) and Directorship of Fraunhofer IGD (since 2006).

• Stochastics
• Actuarial Mathematics
• Numerical Mathematics
• +3 more

Michaela Szölgyenyi is a Professor at the Institute of Statistics within the Faculty of Technical Sciences at the University of Klagenfurt. Her research focuses on stochastic processes, numerical methods for stochastic differential equations (SDEs), and applications in financial and actuarial mathematics. She specializes in analyzing SDEs with irregular coefficients, including discontinuous drift and jump-diffusion dynamics. Her work emphasizes approximation methods for such equations, with contributions to optimal transport, risk theory, and insurance mathematics. She has published extensively on convergence rates, numerical schemes like the Euler-Maruyama and Milstein algorithms, and their applications in modeling financial and actuarial scenarios. She is affiliated with interdisciplinary projects and teaches courses related to stochastic analysis and mathematical finance.