جست‌وجوی استاد و پژوهشگر

Monika Henzingerمشاهده پروفایل

استاد

• Combinatorial algorithms
• Data structures
• Algorithmic game theory
• +۱ مورد دیگر

Monika Henzinger is a Full Professor of Computer Science at the University of Vienna since 2009. Previously, she held faculty positions at the Ecole Polytechnique Federale de Lausanne (2005-2009) and the University of the Saarland (1999-2005). She has also worked as a Director of Research at Google Inc and as a Research Staff member at Digital Equipment Corporation . Education: Ph.D., Computer Science, Princeton University (1993) Diploma, Computer Science, University of the Saarland (1989) Her research focuses on combinatorial algorithms , data structures , algorithmic game theory , and web information retrieval , with significant contributions to dynamic graph algorithms and probabilistic verification. Her work addresses problems in sponsored search auctions, web mining, and formal verification of stochastic systems. Key trends in her publications include web algorithmics , dynamic graph processing , probabilistic verification , and online optimization . Her research has been recognized through prestigious grants like the ERC European Young Investigator Award and the NSF CAREER Award . Scientific Awards: ERC Advanced Grant (2013) Honorary Doctorate, Technical University Dortmund (2013) European Young Investigator Award (2004) NSF CAREER Award (1995) She has advised PhD students at EPFL and the University of Vienna , including Paul Dütting and Veronika Loitzenbauer . Her editorial roles include serving as Editor of EATCS Monographs in Theoretical Computer Science and on the ACM Research Highlights board. She has led projects such as the Doctoral School Computational Science and Dynamic Graph Algorithms in Directed Graphs .

Marek M. Karpinskiمشاهده پروفایل

استاد

• Theory of computation
• Design of efficient algorithms
• Computational complexity
• +۱۰ مورد دیگر

Marek M. Karpinski is a Chair Professor of Computer Science at the University of Bonn and a founding member of the Hausdorff Center for Mathematics . He has held visiting or professorial positions at institutions such as Princeton University, Carnegie-Mellon University, and the University of Edinburgh. His affiliations also include the B-IT Research School on Applied Informatics and the Lab for Foundations of Computing . His research spans efficient algorithms , combinatorial optimization , computational complexity , randomized approximation techniques , and applications in network design , quantum computation , and molecular biology . Recent work focuses on approximation hardness for NP-hard problems, graph algorithms , and algebraic computational complexity . His scientific contributions include polynomial time approximation schemes for dense NP-hard problems and key publications in randomized algorithms , VC dimension , and network optimization . He has advised numerous researchers and received honors such as the Humboldt Research Award and the Max Planck Research Prize .

• Theoretical Computer Science
• Mathematical Logic
• Automatic Structures
• +۶ مورد دیگر

Bakhodyr Khoussainov is a Professor and the Head of the Algorithms and Logic Lab at the University of Electronic Science and Technology of China (UESTC) , since 2021. He has also been a Professor at the University of Auckland (1996–present), with prior roles including Visiting Professor at institutions like Kyoto University, National University of Singapore, and Cornell University. His work spans Theoretical Computer Science and Mathematical Logic , focusing on automatic structures, algorithmic randomness, and computability. Education: PhD in Mathematics from Novosibirsk University (1988), Diploma in Mathematics (1984), BSc in Mathematics (1981). His research interests include Automatic structures , Computable model theory , Algorithmic randomness , and Games on graphs . He has contributed to the theory of automatic groups and solved problems related to algorithmically random structures. The trends in his recent publications highlight advancements in Parity Games (2022), Infinite Strings (2022), and Quasi-polynomial time complexity (2017). His work often bridges Computability , Automata Theory , and Game Theory , with interdisciplinary applications. Scientific Awards: Research Excellence Award, New Zealand Mathematical Society (2002) Humboldt Fellowship (2002) JSPS Invitation Fellowships (2001, 2012, 2016) Fellow of The Royal Society of New Zealand (2005) Aitken Lectureship (2019) Humboldt Research Award (2019) Humboldt Prize (2020) EATCS Nerode Prize co-winner (2021) He supervises numerous PhD and Master's students and has secured significant grants, including Marsden Fund grants (2000–2016), NSFC grant (2022–2026) , and MoE Singapore grant (2016–2020) . He served as Editor of the Journal of Symbolic Logic (2014–2021) and contributed to major conferences like LICS and ICALP.

• Distributed Computing
• Graph Algorithms
• Theoretical Computer Science
• +۳ مورد دیگر

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.

Saket Saurabhمشاهده پروفایل

استاد

• Computer Science
• Theoretical Computer Science
• Algorithms
• +۷ مورد دیگر

Saket Saurabh is a Professor in Algorithms at the Department of Informatics, University of Bergen, Norway, since 2013, and a Professor at the Institute of Mathematical Sciences, India, since 2009. His research focuses on fundamental areas of algorithms and graph theory, particularly parameterized algorithms and kernelization. Research Interests: Parameterized algorithms, kernelization, exact exponential time algorithms, matroid algorithms, algorithmic graph minors, treewidth, and approximation algorithms. Scientific Awards: He has been recognized with the Fellow of Indian Academy of Sciences (2020), the Meltzer Award for Outstanding Young Researcher in Norway (2019), and the Swarnajayanti Fellowship in Mathematical Sciences (2017-18) from the Government of India. Grants: Principal Investigator (PI) for the European Research Council (ERC) Starting Grant 'PARAPPROX' (2013-2017) and the ERC Consolidator Grant 'LOPRE' (2019-2024). His scholarly output includes over 140 articles in top-tier journals like Journal of ACM, SIAM Journal on Computing, and ACM Transactions on Algorithms, as well as 220 conference papers at venues such as FOCS, STOC, and AAAI. As of recent data, his work has garnered 7508 citations (5003 in the last 5 years) with an H-index of 44.

• Randomized Algorithms
• Networking
• Social Networks
• +۷ مورد دیگر

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 Szpankowskiمشاهده پروفایل

استاد

• Analysis of Algorithms
• Information Theory
• Analytic Combinatorics
• +۶ مورد دیگر

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
• +۳ مورد دیگر

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 .

Pietro Lio'مشاهده پروفایل

استاد

• Computational Biology
• Bioinformatics
• Machine Learning
• +۲ مورد دیگر

Pietro Lio' is a Professor of Computational Biology at the University of Cambridge's Department of Computer Science and Technology, where he has held academic positions since 2003. He progressed from Lecturer to Senior Lecturer, Reader, and ultimately Professor (2018-present). His career includes prior roles as Associate Professor of Genetics at the University of Teramo and research positions at the European Bioinformatics Institute, University of Cambridge (Genetics/Zoology), and University of Southampton. Education: 1989: BSc in Electronic Engineering and Biology, University of Firenze 1995: PhD in Theoretical Genetics, University of Pavia 2007: PhD in Engineering (Non-Linear Dynamics & Complex Systems), University of Firenze Research Focus: Professor Lio' specializes in interdisciplinary approaches bridging computer science and biology. His primary research domains include computational biology, bioinformatics algorithms, machine learning (particularly graph neural networks), deep learning architectures, and complex network analysis. His work spans molecular to ecological scales, with applications in genomics, systems biology, and environmental modeling. Publication Trends: Recent work (2018-2020) demonstrates strong emphasis on graph neural networks (Graph Attention Networks, Deep Graph Infomax) and blockchain applications. Earlier publications (2015-2017) focus on ecological modeling, multi-omics integration, molecular communications, and single-cell genomics, reflecting consistent cross-disciplinary innovation. Awards and Honors: 2018: BITS Award (Bioinformatics Italian Society) 2017: Visiting Professorship at University of Padova 2016: BYRA First Prize (ISEM) & MCE Award Second Prize 2013-2015: Lagrange Fellowship 2011: European Commission Award for methodological innovation No information is available regarding student advising, grants, labs, or research teams in the provided materials.

Matiyasevich Yuriمشاهده پروفایل

استاد

• Diophantine equations
• Computability theory
• Algorithms
• +۱ مورد دیگر

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.

Andrei Asinowskiمشاهده پروفایل

پژوهشگر

• Discrete Mathematics
• Combinatorics
• Computational Geometry
• +۳ مورد دیگر

Andrei Asinowski is a Researcher at the Institute of Mathematics at Alpen-Adria-Universität Klagenfurt. He has held academic appointments at institutions including Bielefeld University (2005–2006), University of Haifa (2006–2008), Technion (2008–2011), Free University of Berlin (2012–2015), and TU Wien (2015–2018). Since 2020, he leads the FWF-funded project 'Generic Rectangulations: Enumerative and Structural Aspects' (P32731). His research focuses on combinatorics, discrete mathematics, computational geometry, and enumerative combinatorics. Key interests include rectangulations, permutation patterns, lattice paths, and guillotine partitions. Research Interests: Combinatorics of rectangulations, permutation classes, enumerative combinatorics, geometric permutations, and algorithmic applications of discrete structures. His work bridges combinatorial theory and computational geometry, with recent emphasis on bijections between rectangulations and permutations, generating functions, and analytic methods. Grants & Projects: Principal Investigator of FWF Grant P32731 (since 2020), exploring enumerative and structural aspects of rectangulations. Collaborative projects include EuroGIGA's ComPoSe (2012–2015) and SFB F50's Algorithmic and Enumerative Combinatorics (2015–2018). Publications Trends: Recent work emphasizes rectangulation enumeration, permutation patterns, and analytic combinatorics techniques. Earlier contributions addressed geometric permutations, computational geometry, and lattice path enumeration.

Markus Steinbergerمشاهده پروفایل

دانشیار

• GPU Computing
• Computer Graphics
• Parallel Processing
• +۳ مورد دیگر

Markus Steinberger is an Associate Professor at Graz University of Technology (Austria), leading the GPU Computing and Visualization Group at the Institute for Computer Graphics and Vision. He holds an MSc and PhD in Computer Science from TU Graz, with a postdoc and multiple leadership roles in academic and industry labs, including NVIDIA and the Max Planck Institute. His research focuses on GPU scheduling, parallel computing, and high-performance visualization techniques. He has led teams at TU Graz, Huawei Technologies (Cloud Rendering Lab), and the Max-Planck-Center for Visual Computing. Education 11/2020: Habilitation in Practical Computer Science at TU Graz 10/2013: PhD in Computer Science (Dynamic Resource Scheduling on Graphics Processors) 10/2010: MSc in Telematics 10/2005: BSc in Telematics Research Interests Steinberger’s work centers on optimizing GPU computing for real-time rendering and parallel processing. He explores efficient resource scheduling, dynamic graph management, and high-performance visualization techniques, with applications in cloud rendering, scientific visualization, and interactive graphics. His methods emphasize scalability and real-world applicability in both academic and industrial settings. Awards Heinz Zemanek Prize (2016) – First Austrian recipient GI Dissertation Prize (2014) – Best dissertation in German-speaking computer science Multiple Eurographics Best Paper Awards (2021, 2020, 2014) HPEC Best Student Paper (2017) ACM CHI Honorable Mention (2014) Advising & Grants Steinberger has advised numerous students and led projects funded by EU initiatives and industry partnerships. His research has been recognized through grants supporting GPU scheduling, cloud rendering, and parallel computing. Labs & Teams Leads the GPU Computing and Visualization Group at TU Graz and directed the Cloud Rendering Lab at Huawei, focusing on scalable rendering solutions for distributed systems.

Thomas Eiterمشاهده پروفایل

استاد

• Answer Set Programming
• Knowledge Representation
• Logic Programming
• +۷ مورد دیگر

Thomas Eiter is a Professor at TU Wien's Institute of Logic and Computation. His research focuses on declarative programming paradigms, knowledge representation, and artificial intelligence. He leads projects in neurosymbolic systems, answer set programming (ASP), and stream reasoning, with applications in visual question answering, scheduling optimization, and semantic scene generation. Eiter has contributed to foundational work in ASP semantics, computational complexity, and hybrid reasoning frameworks. His work bridges logical formalisms with practical AI challenges, emphasizing explainability and scalability. Projects like ALASPO and neurosymbolic integration showcase his focus on advancing both theoretical and applied aspects of AI. Projects: HumanE AI Network, WASP, REWERSE Research Themes: Neurosymbolic AI, Answer Set Programming, Stream Reasoning Notable achievements include pioneering work on semiring-based reasoning frameworks and developing efficient ASP solvers like Alpha. His contributions span over 471 publications, emphasizing interdisciplinary applications in computer vision, robotics, and automated planning.

Wolfgang Dürمشاهده پروفایل

استاد

• Quantum Information Theory
• Quantum Computing
• Quantum Cryptography
• +۴ مورد دیگر

Univ.-Prof. Wolfgang Dür is a Professor and Head of the Department at the Institute of Theoretical Physics, University of Innsbruck. His research focuses on quantum communication, quantum networks, and quantum education. He leads the Quantum Communication and Quantum Networks research group, developing noise-resilient quantum protocols, scalable quantum repeaters, and quantum sensor networks. He has pioneered educational approaches integrating quantum information theory into school curricula, including games like 'Entangle Me!' and 'Encrypt Me!' to teach quantum principles. Collaborations include the RECC Physics West consortium to enhance teacher training and competency-based learning in secondary schools. Key projects include optimizing quantum resource states for networks, analyzing quantum metrology under noise, and exploring macroscopic quantum states' fragility. He has advised numerous students on topics ranging from quantum cryptography to quantum entanglement pedagogy. His work bridges foundational quantum theory with practical applications, emphasizing scalable architectures and educational innovation.

• Machine Learning
• Data Mining
• Social Network Analysis
• +۴ مورد دیگر

Yllka Velaj is an Assistant Professor in the Faculty of Computer Science, affiliated with the Research Group on Data Mining and Machine Learning. Her research focuses on machine learning, data mining, and network analysis, with applications in social networks, recommendation systems, and AI-enhanced education. She actively contributes to advancing methodologies for uncertain graphs, game-based learning in IT project management, and educational technologies targeting non-computer science students. Her scholarly activities include organizing events such as the Austrian Computer Science Day 2024. Her work bridges theoretical computer science with practical applications, emphasizing learner-centered approaches in data science education and innovative solutions for complex network problems. Key research areas include node embedding, cluster analysis, and algorithm design for social influence maximization. She collaborates on projects addressing multi-relational graph clustering, semi-supervised learning, and optimizing communication in datacenters.