جست‌وجوی استاد و پژوهشگر

Petteri Kaskiمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Algorithm Design
• Exact and Parameterized Algorithms
• +۵ مورد دیگر

Petteri Kaski is an Associate Professor at the Department of Computer Science, School of Science, Aalto University , and a member of the Helsinki Institute for Information Technology (HIIT) . His research focuses on theoretical computer science, particularly in algorithm design, exact and parameterized algorithms, algebraic algorithms, and combinatorics. Doctoral Degree in Engineering and Technology, Helsinki University of Technology (2005) Licentiate Degree in Engineering and Technology, Helsinki University of Technology (2002) Master's Degree in Engineering and Technology, Helsinki University of Technology (2001) His recent work explores tensor scaling, Johnson-Lindenstrauss transforms, Hamiltonian cycles, and computational complexity, with contributions to polynomial-time algorithms, finite field computations, and combinatorial optimization. Notable awards include the Best Paper Award at ICALP 2017 , an ERC Starting Grant (2014) , and the Kirkman Medal (2007) . He has served on scientific committees for conferences like STACS 2025 and ICALP 2024 , and collaborated with institutions such as the IT University of Copenhagen and Universität Regensburg . Key Research Areas : Theoretical Computer Science, Algorithm Design, Exact Algorithms, Algebraic Computation, Graph Theory, Combinatorics

Pauli Miettinenمشاهده پروفایل

استاد

• Data Science
• Data Mining
• Matrix and Tensor Decompositions
• +۴ مورد دیگر

Pauli Miettinen is a Professor of Data Science at the University of Eastern Finland, affiliated with the School of Computing within the Faculty of Science, Forestry and Technology. His research focuses on data science methodologies, including matrix and tensor decompositions, redescription mining, and social network analysis. Key applications span ecological niche modeling, health data analysis, and parliamentary candidate opinion analysis. He leads the Algorithmic Data Analysis research group and contributed to the Neuro-Innovation project (2021–2026). Recent work includes advancements in differentially private redescription mining and hyperbolic community graph generation. His publications emphasize efficient algorithms for data mining tasks like biclustering and non-negative matrix factorization. Selected achievements include developing the HyGen graph generator and pioneering techniques for interpretable data representation. His research bridges theoretical method development with practical applications in diverse domains.

• Boolean Optimization
• Constraint Reasoning
• Satisfiability (SAT) Solving
• +۳ مورد دیگر

Matti Järvisalo is a Professor in the Department of Computer Science at the University of Helsinki, Finland, holding the title of Docent and serving as Supervisor for the Doctoral Programme in Computer Science. He is affiliated with the Helsinki Institute for Information Technology (HIIT), a leading collaborative research institute between the University of Helsinki and Aalto University. His research centers on computational logic and constraint-based reasoning, with core expertise in Boolean optimization, SAT/MaxSAT solving, and argumentation frameworks. He develops declarative approaches for combinatorial problems in computational social choice, judgment aggregation, and fair division, emphasizing certified algorithms and preprocessing techniques. His work bridges theoretical computer science with practical implementations in optimization and AI. Recent publications (2024-2025) reveal a strong focus on multi-objective optimization, certified reasoning, and argumentation under incomplete information. Key trends include symmetry-aware core learning for Pseudo-Boolean optimization, Pareto-optimality certification in MaxSAT, and novel algorithms for manipulation analysis in judgment aggregation, demonstrating his leadership in advancing SAT-based AI methods. Professor Järvisalo's significant contributions have been recognized by prestigious awards: IJCAI-JAIR Best Paper Prize (2019) Best Researcher Award from University of Helsinki Department of Computer Science (2011) CP 2017 Distinguished Paper Award ECAI 2016 Runner-Up Best Student Paper Award Honorary Mention at ICCMA 2015 He actively mentors the next generation of researchers and secures major research funding: Supervision: 6 doctoral theses and 6 Master's/Licentiate theses Active Grant: Academy of Finland project 'Next-generation Unsatisfiability-based Declarative Optimization' (2023-2027) Past Projects: 'Symbolic Techniques for Formally Verified and Explainable AI' (2020-2022), 'Declarative Boolean Optimization: Pushing the Envelope' (2019-2023) As a core member of HIIT, he collaborates within Finland's premier information technology research ecosystem, contributing to the institute's mission of advancing fundamental and applied IT research through interdisciplinary teamwork and international partnerships.

Juha Kontinenمشاهده پروفایل

استاد

• Mathematical Logic
• Theoretical Computer Science
• Computational Complexity
• +۳ مورد دیگر

Juha Kontinen is a Professor and Docent in the Department of Mathematics and Statistics at the University of Helsinki. He serves as a Supervisor for the Doctoral Programme in Mathematics and Statistics. His research focuses on mathematical logic, theoretical computer science, computational complexity, and formal methods. Key areas include dependence logic, team semantics, and their applications in areas like database theory and artificial intelligence. He has been actively involved in numerous research projects funded by organizations such as the Magnus Ehrnrooth Foundation and the Academy of Finland. His work spans foundational studies of computational complexity, formal logics for team semantics, and interdisciplinary applications. Recent projects include exploring discrete differential equations for circuit complexity and probabilistic team semantics with Boolean negation. Kontinen has authored/co-authored over 90 publications, including articles in prestigious journals and conference proceedings. His work bridges theoretical foundations with practical computational challenges, addressing topics like neural network training complexity and hyperproperties in temporal logics. He has also contributed to conference organization, peer review, and doctoral supervision, highlighting his role as a leader in the academic community.

• Distributed Computing
• Quantum Computing
• Cellular Automata
• +۳ مورد دیگر

Augusto Modanese is a Postdoctoral Researcher in the Department of Computer Science at Aalto University. His research focuses on distributed computing, quantum computing, and computational models like cellular automata and fungal automata. He investigates local problems in tree networks, quantum advantage limitations, and sublinear-time algorithms. Research Trends: Recent publications emphasize distributed quantum computing, algorithmic equivalence between quantum and classical models, and computational complexity in constrained topologies. Key themes include probabilistic cellular automata, graph coloring, and bio-inspired computing frameworks.

• Formal Methods
• Model Checking
• Satisfiability (SAT) Solving
• +۴ مورد دیگر

Tommi Junttila serves as a Senior University Lecturer in the Department of Computer Science at Aalto University, Finland, where he conducts cutting-edge research at the intersection of formal methods and computational logic. His academic profile demonstrates sustained contributions to theoretical computer science with practical applications in system verification and blockchain technology. His research program centers on advancing formal verification techniques, with core expertise in: Symmetry reduction algorithms for state space explosion SAT/SMT solving with specialized parity and XOR reasoning Bounded model checking of timed and asynchronous systems Blockchain protocol verification (notably DeFi lending pools) Canonical labeling tools for graph automorphism detection Recent work shows increasing focus on decentralized finance applications while maintaining foundational contributions to solver technology. Analysis of his publication trajectory (2011-2022) reveals consistent innovation in SAT solving methodologies, with symmetry reduction and parity reasoning forming persistent research threads. His 2022 work on DeFi lending pools represents a strategic expansion into blockchain verification, leveraging established formal methods expertise for emerging financial technologies. Tool development (bliss, PySMT) demonstrates commitment to practical research impact. No scientific awards were documented in the source materials. Similarly, no information regarding student supervision, grant funding, or laboratory affiliations was present in the provided text. His independent tool development (including bliss for graph canonical labeling and PySMT for SMT solver interfaces) indicates significant technical leadership within the formal methods community.

• Mathematical Logic
• Theoretical Computer Science
• Computational Logic
• +۵ مورد دیگر

Antti Kuusisto is an Associate Professor of Discrete Mathematics at the Faculty of Information Technology and Communication Sciences, Tampere University. He previously held roles as Academy Research Fellow (2019-2024) and Senior Research Fellow at Tampere Institute for Advanced Study. His research focuses on mathematical logic, theoretical computer science, and their applications in distributed computing, descriptive complexity, and explainable AI. He leads the consortium and serves as Principal Investigator (PI) for the Academy of Finland-funded projects: “Explaining AI via Logic” and “Theory of Computational Logics.” His work bridges foundational logic with practical computational challenges, including neural network interpretability and distributed automata theory. Key research interests include modal logic, game-theoretic semantics, and computational complexity classifications. Notable contributions span logical frameworks for distributed systems, entropy-based complexity analysis, and formal methods for AI explainability. His recent publications address topics like graded modal logics, boolean formula-based classifiers, and optimal strategies in repeated coordination games. Kuusisto’s research also explores connections between algebraic logic and complexity theory, with applications to neural networks and graph algorithms.

Tomi Janhunenمشاهده پروفایل

استاد

• Knowledge Representation and Reasoning
• Answer Set Programming
• Satisfiability Checking
• +۶ مورد دیگر

Tomi Janhunen is a Professor in Computing Sciences at Tampere University, specializing in knowledge representation, automated reasoning, and logic programming. He previously served as Adjunct Professor at Aalto University (2019–2024) and maintains a Doctor of Science (Tech.) degree. His research spans answer set programming, satisfiability checking, optimization, and distributed computation. PhD, Aalto University (Doctor of Science (Tech.)) Adjunct Professor of Computer Science (Aalto University, 2019–2024) His research focuses on Answer Set Programming (modularity, verification, optimization), Satisfiability Modulo Theories , Nonmonotonic Logics , and Computational Complexity . He integrates logic programming into real-world applications like preventive maintenance scheduling and AI security systems. Recent work includes translating logic programs into integer programming, developing probabilistic reasoning systems (Plingo), and creating interpretable classifiers for tabular data. His publications emphasize stable model semantics , optimization techniques , and constraint networks . He supervises M.Sc., Lic.Sc., and Ph.D. theses and has completed pedagogical studies. Janhunen actively reviews for journals like Artificial Intelligence Journal and ACM Transactions on Computational Logic .