Find Academic Supervisors

• Computational Geometry
• Discrete Mathematics
• Graph Theory
• +3 more

Oswin Aichholzer is an Associate Professor in the Department of Algorithms and Theory at TU Graz, Austria. He is affiliated with the Institute of Algorithms and Theory and the Institute of Software Engineering and Artificial Intelligence. His research focuses on computational geometry, graph theory, and combinatorial geometry, with an emphasis on geometric graphs, matching problems, and crossing minimization in graph drawings. He is also involved in teaching theoretical computer science and actively contributes to research projects and courses through the TU Graz's Research Portal (PURE). His recent work explores structures like crossing-free Hamiltonian cycles, bicolored order types, and folding algorithms for polyominoes. Key research interests include algorithmic problems in geometric configurations, graph isomorphisms, and the development of efficient algorithms for problems in discrete mathematics. He has published extensively on topics such as flip operations in graphs, geometric matchings, and the analysis of complete graph drawings. His work often bridges theoretical foundations with practical algorithmic solutions, addressing challenges in both computational geometry and combinatorics. Dr. Aichholzer’s contributions span multiple areas, including the study of polyomino folding, bichromatic matchings, and the characterization of graph rotation systems. He maintains an active research presence, with recent publications in top conferences like the Symposium on Computational Geometry (SoCG). His research portal provides further details on ongoing projects and collaborations.

Josef SchichoView profile

Professor

• Computer Algebra
• Algebraic Geometry
• Symbolic Computation
• +3 more

Josef Schicho is a Professor and Group Leader of the Symbolic Computation group at the Research Institute for Symbolic Computation (RISC) at Johannes Kepler University Linz (JKU) and the Johann Radon Institute for Computational and Applied Mathematics (RICAM). He holds a Ph.D. (1995) and Habilitation (2001) in Mathematics from the University of Linz. His research focuses on computer algebra, algebraic geometry, and their applications in kinematics and robotics. Schicho has contributed significantly to the study of flexible and paradoxical motions of mechanical linkages, algebraic curves and surfaces, and symbolic computation algorithms. He has supervised numerous doctoral students, including Zijia Li and Matteo Gallet, and has been involved in funded projects such as the Doctoral College in Computational Mathematics and research on radical parametrizations of algebraic curves. His work bridges theoretical mathematics with practical applications, particularly in geometric modeling and computational algebraic geometry. Schicho has authored over 140 peer-reviewed publications, including foundational papers on Laman graphs, Bricard octahedra, and the combinatorial aspects of motion generation. His research has been recognized through collaborations with institutions like the Austrian Academy of Sciences and international conferences in computational geometry and kinematics.

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.

Arne WinterhofView profile

Researcher

• Finite Fields
• Number Theory
• Coding Theory
• +5 more

Arne Winterhof is a Senior Fellow at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) of the Austrian Academy of Sciences. He holds the title of University Lecturer (Univ.-Doz.) and has extensive experience in academic leadership, including project leadership roles in multiple FWF-funded research projects. His primary affiliation is with RICAM's Applied Discrete Mathematics and Cryptography group. Winterhof earned his Diploma (summa cum laude) and PhD (summa cum laude) in Mathematics from TU Braunschweig (1994, 1996) and completed his Habilitation at the University of Vienna in 2001. He has held positions at institutions such as Temasek Laboratories (National University of Singapore) and has been a Senior Scientist and Fellow at RICAM since 2003. In 2016, he declined a Full Professorship offer at the University of Rostock. His research focuses on Finite Fields, Number Theory, Coding Theory, Cryptology, Combinatorics, and Cryptography. He has received prestigious awards, including the Edmund and Rosa Hlawka Prize (2004) and the Austrian Mathematical Society Advancement Award (2010). He serves on editorial boards for journals like Finite Fields and Their Applications and Cryptography and Communications . Winterhof has led numerous research projects, including Generalized Cyclotomic Mappings of Finite Fields (2025–2027) and On the Hierarchy of Measures of Pseudorandomness (2014–2018). His work emphasizes pseudorandom sequence design, cryptographic applications, and theoretical foundations in discrete mathematics.

• Applied Mathematics
• Graph Theory
• Combinatorics
• +3 more

Prof. Angelika Wiegele is a full Professor at the Department of Mathematics at Alpen-Adria-Universität Klagenfurt. She serves as a member of the university senate and head of the Institut für Mathematik. Her research focuses on semidefinite optimization, combinatorial optimization, and their applications in graph theory and operations research. She holds a Dipl.-Ing. (2001) and Dr. techn. (2006) from Alpen-Adria-Universität Klagenfurt, with thesis supervision by Franz Rendl. Her academic career includes positions at TU Graz, IASI-CNR Rome, and Universität zu Köln, as well as a visiting professorship at Università di Roma Tor Vergata. Her educational background includes studies at City University London (Erasmus) and TU Eindhoven (Leonardo project). Recent work emphasizes SDP-based methods for graph partitioning, edge expansion, and combinatorial problems, with a focus on high-performance computing solutions. Her research bridges theoretical optimization with practical applications in network design and algorithmic development. Publications from 2021–2024 highlight advancements in semidefinite programming for graph partitioning, SDP-based bounds for cutwidth, and exact solvers for clustering problems. She contributed to the BiqBin and SOS-SDP solvers for quadratic optimization and co-edited special journal issues on mixed-integer nonlinear optimization. Her work often appears in top operations research journals and conference proceedings. Prof. Wiegele has held global faculty positions at the University of Cologne (2022–2024) and is active in international research collaborations through PRACE high-performance computing initiatives. She maintains an ORCID profile and a university webpage with teaching and research materials.

Szemerédi EndreView profile

Professor

• Discrete mathematics
• Combinatorics
• Theoretical computer science
• +1 more

Endre Szemerédi is a Hungarian mathematician and computer scientist, currently serving as a Permanent Research Fellow at the Alfréd Rényi Institute of Mathematics (Hungarian Academy of Sciences) and holding the New Jersey Professor of Computer Science position at Rutgers University since 1986. His career spans prestigious institutions including Stanford, Caltech, and the Institute for Advanced Study. Expertise: Discrete mathematics, combinatorics, theoretical computer science, and number theory. Education: M.Sc. (1965, Eötvös Loránd University), Ph.D. (1970, Moscow State University under Israel Gelfand). Research legacy encompasses foundational contributions to combinatorics, graph theory, and computational complexity. His work on Hamiltonian cycles in random graphs , parallel sorting networks , and the Blow-up Lemma revolutionized extremal combinatorics and algorithm design. Scientific honors include: 2012 Abel Prize and Széchenyi Prize 2008 Rolf Schock Prize and Steele Prize 1982 Member of Hungarian Academy of Sciences , 2010 Member of US National Academy of Sciences 1975 Pólya Prize , 1973 Rényi Prize , multiple Grünwald Prizes .

• Discrete Optimization
• Algorithm Design
• Computer Vision
• +3 more

Prof. Vladimir Kolmogorov is a faculty member at the Institute of Science and Technology Austria (IST Austria), specializing in discrete optimization and algorithm design. He holds a Ph.D. in Computer Science from Cornell University and has held positions at Microsoft Research and University College London. His research focuses on combinatorial optimization, MAP inference in graphical models, and applications in computer vision. Educations: M.S. in Applied Mathematics and Physics, Moscow Institute of Physics and Technology Ph.D. in Computer Science, Cornell University Research Interests: Dr. Kolmogorov's work spans algorithmic optimization, including complexity analysis of constraint satisfaction problems, graph algorithms, and machine learning applications. His contributions include foundational work on graph cuts for computer vision and the development of efficient optimization methods for discrete problems. Publications: His recent work includes advancements in parallel algorithms for Gibbs distributions, semidefinite programming, and combinatorial optimization. These contributions highlight his expertise in bridging theoretical computer science with practical applications. Awards: Royal Academy of Engineering/EPSRC Research Fellowship (2006–2011) ERC Consolidator Grant (2014–2020) Best Paper Award at ECCV 2002 Outstanding Student Paper Award (NIPS 2007) Best Paper Honorable Mention (CVPR 2005) Advising and Grants: He has advised multiple PhD students and leads a research team at IST Austria. His grants include significant funding for exploring optimization in machine learning and discrete systems. Labs/Teams: His lab focuses on theoretical and applied discrete optimization, collaborating with institutions globally. Current projects include developing faster algorithms for graph problems and advancing Gibbs distribution analysis.

• Artificial Intelligence
• Optimization
• Scheduling
• +4 more

Marie-Louise Lackner is a Research Fellow (PostDoc Researcher) in the Department of Databases and Artificial Intelligence at Technische Universität Wien. She holds Diplom-Ingenieur and Dr. techn. degrees and actively contributes to the CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling (2017–2025). Her research focuses on Artificial Intelligence and Optimization , with emphasis on industrial scheduling, constraint programming, and algorithm design. Key domains include: Industrial oven scheduling and production leveling Metaheuristics (simulated annealing, large neighborhood search) Multi-objective optimization in manufacturing systems Combinatorial mathematics and discrete structures Her publications demonstrate a strong trajectory in applied optimization , with recent work concentrating on energy-efficient scheduling algorithms for electronic manufacturing, while earlier research explored permutation patterns and social choice theory. Methodologies consistently integrate theoretical computer science with industrial problem-solving. She supervises graduate researchers, including P. Malik's work on memetic algorithms for production leveling. Grant involvement includes the CD Laboratory project focused on AI-driven planning systems. Lackner is affiliated with the CD Laboratory for Artificial Intelligence and Optimization, conducting applied research in industrial scheduling systems within TU Wien's Databases and AI group.

• Artificial Intelligence
• Knowledge Compilation
• Computational Complexity
• +3 more

Tianwei Zhang is a predoctoral researcher at the Technische Universität Wien (TU Wien) within the Algorithms and Complexity department. His research focuses on theoretical computer science, particularly in the areas of artificial intelligence, knowledge compilation, and computational complexity. Position: PreDoc Researcher Projects: Overcoming Intractability in the Knowledge Compilation Map (2022–2025), REVEAL-AI (2020–2024) Zhang's work explores advanced techniques in satisfiability solving, constraint programming, and universal graph theory. His recent publications highlight contributions to model counting algorithms and SAT-based combinatorial optimization, bridging theoretical challenges with practical applications. His research trends emphasize scalable algorithms , computational intractability , and logic-based AI . Notable collaborations include work with Dr. Stefan Szeider on SAT solver applications for combinatorics. Contact: tianwei.zhang@tuwien.ac.at Phone: +43-1-58801-192154

• Satisfiability (SAT)
• Graph Theory
• Combinatorial Optimization
• +3 more

Markus Kirchweger is a PreDoc Researcher at the Department of Algorithms and Complexity, Faculty of Informatics, Technische Universität Wien. His work spans Satisfiability (SAT) solving, graph theory, and combinatorial optimization, with a focus on symmetry breaking and SAT modulo theories. Research Interests: Developing SAT-based frameworks for graph generation and enumeration Dynamic symmetry breaking in combinatorial problem encodings Integrating user propagators into CDCL solvers Applying SAT techniques to conjectures like Erdős-Faber-Lovász and Rota’s Basis Co-certificate learning and shortest common supersequence optimization Projects: INCR (2021–2024), REVEAL-AI (2020–2024), SLIM (2019–2024), ASK-SAT (2024–2027).

• Distributed Computing
• Graph Algorithms
• Theoretical Computer Science
• +3 more

Yannic Maus is a Professor at Graz University of Technology, affiliated with the Institute of Algorithms and Theory and the Institute of Software Engineering and Artificial Intelligence. His research focuses on distributed computing, graph algorithms, and theoretical computer science. He holds a PhD and multiple bachelor’s and master’s degrees in Computer Science. His work emphasizes distributed graph coloring, locality in algorithms, and massively parallel computing. He has contributed to foundational results in distributed algorithms, including optimal edge coloring and coloring hyperbolic random graphs. His research bridges theoretical insights with practical distributed systems challenges. Education: PhD in Natural Sciences (Dr.rer.nat.), B.Sc. and M.Sc. in Computer Science Key research interests include distributed algorithms for graphs, Lovász Local Lemma applications, and algorithmic efficiency in dynamic networks. His publications explore topics like ruling sets in trees, exponential speedups in MPC models, and adaptive coloring techniques for sparse graphs. He has also investigated the algorithmic small-world phenomenon and connectivity in forests using deterministic approaches. Yannic Maus’s work often addresses theoretical lower bounds and upper limits in distributed computing, with applications to real-world networked systems. His contributions span conferences like DISC and SoCG, focusing on both foundational problems and their algorithmic solutions.

• Randomized Algorithms
• Networking
• Social Networks
• +7 more

Aravind Srinivasan is a Professor of Computer Science at the University of Maryland, College Park, USA. He holds tenure and has held academic positions at the National University of Singapore and Bell Labs. He completed his B.Tech at IIT Madras and his Ph.D. at Cornell University, with postdoctoral research at the Institute for Advanced Study and DIMACS. His research focuses on randomized algorithms, networking, social networks, combinatorial optimization, and their applications to public health, machine learning, and energy systems. He has published over 115 papers in top journals like Nature and the Journal of the ACM, and his work has received significant recognition, including 1,551 citations for his 2004 Nature paper on disease modeling. Education: B.Tech, Indian Institute of Technology Madras Ph.D., Cornell University Awarded Fellowships from ACM, AAAS, IEEE, and EATCS, he also serves as Editor-in-Chief of the ACM Transactions on Algorithms. His students have secured roles in academia, industry, and government, reflecting his impactful mentorship. His contributions span theoretical computer science and applied domains, with notable work in probabilistic methods, network science, and interdisciplinary applications.

Wojciech SzpankowskiView profile

Professor

• Analysis of Algorithms
• Information Theory
• Analytic Combinatorics
• +6 more

Wojciech Szpankowski is the Saul Rosen Distinguished Professor of Computer Science at Purdue University. He holds concurrent positions as a Guest Professor at ETH Zurich and a Professor at Jagiellonian University, Krakow. His research focuses on analysis of algorithms, information theory, analytic combinatorics, and random structures. He has directed major initiatives like the NSF Science & Technology Center on Science of Information (CSoI), a $50M 10-year project. Szpankowski is a Fellow of the IEEE and has received prestigious awards including the Flajolet Prize (2020) and Humboldt Research Award (2010). He has held visiting roles at institutions worldwide, including Stanford University and the Newton Institute, Cambridge. His academic journey includes tenure as Full Professor at Purdue (since 1992), Assistant Professorships at McGill University (1984–1992) and Technical University of Gdańsk (1980–1984). His scholarly contributions span monographs like "Average Case Analysis of Algorithms on Sequences" (2001) and "Analytic Pattern Matching" (2015), with a forthcoming work on Analytic Information Theory (2022). He actively contributes to scientific boards, including HIIT Helsinki and NeuroMat Brazil. Szpankowski’s publications emphasize interdisciplinary research at the intersection of computer science, mathematics, and biology. His work on privacy-preserving data analysis, dynamic network inference, and protein superfamily evolution showcases his broad impact. Keynote talks at major conferences (e.g., SODA 2019, AofA 2016) reflect his leadership in theoretical computer science. His grants and recognitions underscore institutional trust: the NSF Science & Technology Center (2010) and Arden L. Bement Jr. Award (2015) highlight his pioneering role in redefining information science. Collaborations span academia and industry, with affiliations at Hewlett-Packard and INRIA.

• Discrete geometry
• Cryptography
• Extremal combinatorics
• +3 more

Gábor Tardos is a Hungarian mathematician and computer scientist with a career spanning esteemed institutions such as the Alfréd Rényi Institute of Mathematics (since 1991) and Simon Fraser University (2005–2013). He currently holds a professorship at Central European University and leads the Lendület cryptography research group at Rényi Institute. His work bridges discrete mathematics, computer science, and complexity theory. Key fields of interest: Discrete and computational geometry Cryptography Extremal combinatorics Complexity theory Major scientific contributions include probabilistic fingerprinting codes, advancements in the Lovász local lemma, and combinatorial geometry breakthroughs. His awards include the 2020 Gödel Prize and Lendület Grant. He serves as an editor for journals such as Order and Combinatorica .

Matiyasevich YuriView profile

Professor

• Diophantine equations
• Computability theory
• Algorithms
• +1 more

Yuri Matiyasevich is a Russian mathematician and computer scientist affiliated with the Steklov Institute of Mathematics (Leningrad/St.Petersburg Branch) since 1980, where he serves as head of the Laboratory of Mathematical Logic. He also holds part-time professorships at Leningrad/St.Petersburg State University (since 2003) and previously at Polytechnical Institute (1980-1981). His research focuses on Diophantine equations, Computability theory, Algorithms, and Decidability problems. Full member, Russian Academy of Sciences (2008) Corresponding member, Bavarian Academy of Sciences (2007) Docteur Honoris Causa, Université Pierre et Marie Curie (2003) Humboldt Research Award (1997) Markov Prize, Academy of Sciences of the USSR (1980) His recent work involves computational approaches to Riemann's zeta function, probabilistic reformulations of graph theory problems, and algorithmic analysis of Diophantine representations. He has published extensively on connections between number theory and computational models, including studies on exponential Diophantine equations and their applications. Notable contributions include definitive solutions to Hilbert's Tenth Problem through Diophantine representations of recursively enumerable sets, and computational experiments supporting the Riemann Hypothesis. His publications span multiple languages and cover intersections between mathematical logic, number theory, and theoretical computer science.