جست‌وجوی استاد و پژوهشگر

Karl Bringmannمشاهده پروفایل

استاد

• Theoretical Computer Science
• Fine-Grained Complexity
• Algorithm Design
• +۵ مورد دیگر

Karl Bringmann is a Professor at Saarland University since November 2019 and is affiliated with the Max Planck Institute for Informatics, where he works in the Department of Algorithms and Complexity. He has established himself as a leading researcher in theoretical computer science, particularly in fine-grained complexity and algorithm design. His work bridges theoretical insights with practical applications in optimization problems. Bringmann's research focuses on conditional lower bounds (often based on the Strong Exponential Time Hypothesis) and algorithm design, with particular emphasis on optimization problems, string algorithms, and computational geometry. His work has significant implications for fundamental problems like Subset Sum, Knapsack, and Integer Programming, with applications ranging from scheduling to post-quantum cryptography. He develops innovative approaches combining modern algorithmic techniques, mathematical structure theory, and fine-grained complexity to design faster algorithms and establish optimality. His publication record shows a consistent trend toward developing near-optimal algorithms for fundamental problems, with significant contributions to fine-grained complexity theory. His work often establishes tight conditional lower bounds while simultaneously providing matching upper bounds, creating a comprehensive understanding of problem complexity. He has made notable advances in string algorithms (particularly edit distance), geometric problems, and optimization. ERC Starting Grant 2019: Technology Transfer between Integer Programming and Efficient Algorithms (TIPEA) EATCS Presburger Award for Young Scientists 2019 Heinz Maier-Leibnitz-Prize 2019 EATCS Distinguished Dissertation Award 2015 Google European Doctoral Fellowship 2012-2014 Bringmann leads the ERC-funded TIPEA project (2019-2024), which investigates fundamental optimization problems with the goal of developing next-generation industrial solvers. He advises several PhD students including Nick Fischer, Alejandro Cassis, and Vasileios Nakos, and has served on numerous program committees for top theoretical computer science conferences including STOC, FOCS, SODA, and ICALP. His teaching includes advanced courses on Fine-Grained Complexity Theory and Competitive Programming.

Laure Daviaudمشاهده پروفایل

دانشیار

• Formal Verification
• Automata Theory
• Models of Computation
• +۴ مورد دیگر

Laure Daviaud is an Associate Professor in the School of Computing Sciences at the University of East Anglia (UEA). She holds associate membership in the Algebra, Number Theory, Logic, and Representations (ANTLR) group and the Computational Biology team, and is a member of UEA's Data Science and AI initiatives. Her academic background includes a Doctor of Philosophy from IRIF - CNRS/Université de Paris, focusing on the asymptotic behavior of min-plus and max-plus automata (2014). Her research interests center on Formal Verification, Automata Theory, Logic, Automata Learning, and Decidability. Recent work explores decidability questions in max-plus automata, probabilistic automata containment, and neural network analysis. She has contributed to quasi-polynomial lower bounds for parity games and the study of counting mechanisms in ReLU RNNs. Current projects include the Engineering and Physical Sciences Research Council-funded 'Learning, Approximating and Minimising Streaming Automata for Large-scale Optimisation' (2023–2024). She collaborates internationally, including as a Visiting Research Fellow at City, University of London since 2023. Her publications span over 25 peer-reviewed articles, with recent focus on weighted automata, max-plus algebra, and formal methods. She actively participates in program committees for conferences like ICALP and FoSSaCS, and delivers invited talks at events such as Highlights of Logic, Games and Automata.

Peter Szabóمشاهده پروفایل

دانشیار

• Mathematics
• Linear Algebra
• Computer Algebra
• +۵ مورد دیگر

Peter Szabó is an Associate Professor at the Department of Aviation Technical Training , Faculty of Aeronautics , Technical University of Košice , Slovakia. He is actively involved in research at the intersection of mathematics, computer algebra, and aerospace engineering. Academic Affiliation: Technical University of Košice, Faculty of Aeronautics, Department of Aviation Technical Training Research Interests include: Mathematical modeling in aviation (Free Route Airspace, complex networks) Linear algebra and numerical methods with MATLAB/SageMath Calculus education and computational techniques Graph theory applications to air traffic systems Recent Article Trends highlight: Integration of calculus and numerical analysis for educational tools (2025) Mathematical axioms for airspace modeling (2022) Cloud computing in aviation research (2022) Linear algebra textbooks and computational exercises (2019) Advising : Mentored students on topics ranging from satellite stabilization to air traffic optimization.

• Stochastic Optimization
• Optimal Control
• Decomposition Methods
• +۵ مورد دیگر

Jean-Philippe Chancelier is a researcher at Cermics (École des Ponts ParisTech) , focusing on stochastic optimization , optimal control , and decomposition methods . His work bridges mathematical theory and computational tools, with applications in energy systems, supply chain management, and sparse optimization. Key Research Themes : Stochastic and multistage optimization Capra-convexity and sparsity-inducing norms Decomposition-coordination algorithms Tropical numerical methods for control Recent Article Trends : Unified frameworks for sparsity-inducing norms Coq-assisted formalization of conditional separation Two-time-scale models for storage and energy systems Complexity bounds for POMDP and deterministic systems Applications in hydrogen infrastructure and reservoir management Software Contributions : NSP (Numerical Scientific Programming) package Integration with ScicosLab and ScilabGtk His research often involves collaboration with colleagues like Michel De Lara, Pierre Carpentier, and Benoît Heymann, and is published in journals such as Transportation Science , JMLR , and Computers & Chemical Engineering .

Monika Molnárováمشاهده پروفایل

استادیار

• Discrete dynamical systems
• Max-plus algebra
• Production line modeling
• +۳ مورد دیگر

RNDr. Monika Molnárová, PhD. is faculty at Technical University of Košice, teaching in the Department of Production Modeling. She holds consultations on Thursdays from 11:00-12:30 and can be reached at room N32 604 or by telephone at +421 55 602 3245. Her research interests focus on discrete dynamical systems and their applications in production modeling. Key areas include max-plus algebra, digraph applications, production line management, and matrix periodicity. Her work bridges theoretical mathematics with industrial applications, particularly in production systems optimization and steady-state analysis of dynamical systems. Dr. Molnárová teaches Discrete Dynamical Systems, Mathematics I-HI, and Mathematics II-HI courses. For the 2024/2025 academic year, she's teaching Mathematics 1 for Economic Informatics students in a combined format (online lectures via Webex, in-person exercises) and Discrete Dynamical Systems for Computer Modeling students in full-time format. First-year engineering students in the PM department select projects from her offerings by October 11, 2024. Her course materials demonstrate expertise in stability analysis of discrete dynamical systems, eigenspace calculations for reducible matrices, and robustness considerations in production systems. She provides specialized resources for students including credit sheets and exam letterheads in both A3 and A4 formats.

Laure Daviaudمشاهده پروفایل

مدرس

• Verification
• Logic
• Game Theory
• +۷ مورد دیگر

Dr Laure Daviaud is a Lecturer in Computer Science at City, University of London, affiliated with the CitAI research center specializing in artificial intelligence. Her research focuses on verification, logic, game and automata theory, quantitative models, and algebraic/topological approaches to rational languages. She leads the EPSRC-funded project on streaming automata optimization (EP/T018313/1, 2020-2023). Dr Daviaud has supervised PhD student Alex Dean and postdoc Andrew Ryzhikov. She actively participates in program committees for conferences like ICLA, FSTTCS, and LICS, and serves as an editor for AEJM. Her work spans theoretical computer science, with contributions to probabilistic automata, max-plus automata, and tropical algebra. Qualifications include a PhD from University Paris VII (2011-2014) supervised by Thomas Colcombet and Jean-Eric Pin. Postdoctoral roles included the University of Warwick (2017-2019), University of Warsaw (2016-2017), and ENS Lyon (2015-2016).

• Model Predictive Control
• Water Resources Systems
• Intelligent Transportation Systems
• +۵ مورد دیگر

Pau Segovia Castillo is a Research Fellow in the Department of Automatic Control at Universitat Politècnica de Catalunya (UPC) since September 2023, holding the prestigious Beatriz Galindo Fellowship. His research focuses on large-scale systems management using non-centralized predictive control approaches, with applications in water resources, transportation, and energy systems. He holds a joint PhD in Automatic Control from UPC and IMT Lille Douai (France), completed in 2019. Previously, he held postdoctoral positions at IMT Lille Douai (2019–2020), TU Delft (2020–2023), and UPC (2023). His educational background includes a BS/MS in Industrial Engineering from UPC (2015). He is a member of the Advanced Control Systrems (SAC) group within the CS2AC research center. His work emphasizes model predictive control (MPC), observer design for nonlinear systems, and digital twin technologies applied to waterway infrastructure. Notable contributions include multilayer control strategies for canals and coordinated scheduling for inland vessel navigation. Key research areas span fault diagnosis in hydraulic systems, optimization algorithms for transportation logistics, and sustainable energy production from waterways. His publications address topics like MPC-based digital twins, observer schemes for noisy nonlinear systems, and lock scheduling using max-plus linear systems. He currently supervises Javier Pedrosa Alias's PhD on job-shop scheduling with AI approaches. Awards: Beatriz Galindo Fellowship Labs/Teams: Advanced Control Systrems (SAC) group, CS2AC Research Center

Nathan Lhoteمشاهده پروفایل

مدرس

• Automata Theory
• Semigroup Theory
• Logics
• +۲ مورد دیگر

Nathan Lhote is a Lecturer (Maître de Conférences) at Aix-Marseille University , affiliated with the Laboratoire d'Informatique et Systèmes (LIS) and its MoVe research team. He is actively involved in two ANR research projects: Delta and Ticktac . Prior to this, he worked as a postdoctoral researcher at the University of Warsaw under the supervision of Mikołaj Bojańczyk (2018–2020). His PhD, completed jointly at University of Bordeaux and Université Libre de Bruxelles (2015–2018), was supervised by Emmanuel Filiot, Olivier Gauwin, and Anca Muscholl.

• Control Systems Engineering
• Marine Energy Systems
• Process Optimization
• +۵ مورد دیگر

Jari Böling is a University researcher at Åbo Akademi University, affiliated with the Faculty of Natural Sciences and Engineering in the Department of Process and Systems Engineering. His research focuses on developing technologies for a sustainable future, particularly in marine engineering and control systems with strong connections to UN Sustainable Development Goals. Böling's research expertise spans multiple engineering domains with specialized focus areas including: Distributed control and fault-tolerant control systems Marine energy systems and cruise ship optimization Process engineering applications for sustainability Machine learning integration in industrial control systems Complex system optimization techniques Analysis of Böling's publication trends reveals a strategic evolution from theoretical control systems toward applied sustainable technologies. His recent work demonstrates increasing integration of data analytics and machine learning with traditional control engineering to address environmental challenges in marine transportation. The research shows a clear progression toward practical implementations that reduce energy consumption and emissions in cruise ship operations and other marine applications. Böling actively supervises students, having guided 12 bachelor's theses in energy technology in 2020. His research portfolio includes significant projects funded by Business Finland: DAZE: Data Analytics for Zero Emission Marine (2023-2026) as Co-Principal Investigator INDECS: Integration of design and operation of cruise ship energy systems (2023-2025) as Responsible researcher CASEMATE: Computationally aided systems engineering for marine technology (2022-2025) as Principal researcher CPT: CLEAN PROPULSION TECHNOLOGIES (2021-2023) as Co-Investigator Energy technology development project in Vaasa (2011-2017) as Co-Investigator

• Mathematics
• Applied Mathematics
• Probability Theory
• +۵ مورد دیگر

Göran Högnäs is a Professor in the Faculty of Science and Engineering, specializing in Mathematics. His research spans probability theory, stochastic processes, and applied mathematics, with a focus on large deviations, random matrix theory, and stochastic orders. He has contributed to interdisciplinary topics like max-plus linear systems and batch manufacturing optimization. Research Themes: Central limit theorems, random walks, weakly interacting particles, β-ensembles, and topological abelian group stochastic orders. Activities: Active in evaluating funding applications and professorship assessments since 2022.

Bart De Schutterمشاهده پروفایل

استاد

• Model Predictive Control
• Hybrid Systems
• Multi-Agent Systems
• +۱۳ مورد دیگر

Bart De Schutter is a Full Professor and Head of the Delft Center for Systems and Control (DCSC) at Delft University of Technology , The Netherlands. He leads a research group focused on advanced control methodologies with applications in transportation, energy, and environmental systems. His research interests span model predictive control (MPC) , hybrid and piecewise-affine systems , multi-agent and distributed control , reinforcement learning , and discrete event systems with applications in intelligent transportation, smart grids, and underwater robotics. His work integrates model-based and data-driven approaches to enable robust, scalable, and intelligent control of large-scale networks. His recent publications reflect a strong trend toward integrating learning with formal control methods, ensuring safety and performance in complex hybrid systems. Research themes include learning-based MPC, scenario reduction for stochastic control, stability analysis of max-plus systems, and applications in railway scheduling and marine monitoring. Notable scientific awards include: ERC Advanced Grant (CLariNet, 2021–2026) Richard C. DiPrima Prize for PhD thesis Robert Stock Prize for PhD theses in Exact Sciences VIDI grant from STW IEEE Fellow IFAC Fellow Bart De Schutter has coordinated major EU projects such as HD-MPC , SeaClear , and SeaClear2.0 , demonstrating leadership in both theoretical innovation and real-world applications. He serves as a senior editor for IEEE Transactions on Intelligent Transportation Systems and associate editor for IEEE Transactions on Automatic Control . He leads a research team working on next-generation control solutions for autonomous systems and infrastructure, with ongoing projects in intelligent traffic control, smart energy systems, and underwater robotics. The group actively recruits PhD and postdoctoral researchers, indicating a vibrant and expanding lab environment.

Michael C. Mungerمشاهده پروفایل

استاد

• Political Economy
• Public Choice Theory
• Regulation and Government Institutions
• +۴ مورد دیگر

Michael C. Munger is the Pfizer,Inc./Edmund T. Pratt, Jr. University Distinguished Professor at Duke University, holding appointments in Political Science, Economics, and the Sanford School of Public Policy. He directs the Philosophy, Politics & Economics (PPE) Certificate Program and serves as a Bass Fellow in Trinity College. His research focuses on markets, government institutions, and the sharing economy, blending political economy with institutional analysis. Education : Ph.D. in Political Science, Washington University in St. Louis (1984) M.A. in Political Science, Washington University in St. Louis (1981) B.A. in Political Science, Davidson College (1980) Research Interests : Munger examines the intersections of public policy, market design, and institutional frameworks. He critiques government failures and explores how decentralized platforms (e.g., Airbnb, solar energy markets) challenge traditional economic theories. His work often bridges Adam Smith’s moral philosophy with Vernon Smith’s experimental economics, emphasizing normative social systems. Awards & Recognition : Pfizer,Inc./Edmund T. Pratt, Jr. University Distinguished Professor (2024–present) Bass Fellow in Political Science (2011–present) Recipient of the Otto 'Toby' Davis Lecture (2012) Advising & Teaching : Munger has advised numerous programs, including directing Duke’s PPE Certificate and undergraduate political science studies. He teaches courses on political economy, public choice, and ethics, emphasizing critical thinking in policy analysis. Labs & External Roles : Collaborates with international institutions such as the Cevro Institute (Prague), Friedrich Alexander University (Erlangen-Nuremberg), and Universidad del Desarrollo (Santiago de Chile) in research and teaching. Maintains a public-facing presence through podcasts (EconTalk), YouTube videos, and blogs.

• Optimal Control
• Tropical Mathematics
• Idempotent Analysis
• +۸ مورد دیگر

Marianne Akian is a Researcher at INRIA Saclay – Île-de-France , affiliated with the Tropical team (joint with CMAP, École Polytechnique, IP Paris, and CNRS). Her research spans deterministic and stochastic optimal control, tropical mathematics, idempotent analysis, and nonlinear Perron-Frobenius theory. She has contributed to numerical methods for Hamilton-Jacobi-Bellman equations and mean payoff games. Education: PhD in Mathematics (1990), Université Paris IX-Dauphine Habilitation (HDR) in Mathematics (2007), Université Pierre et Marie Curie Her work integrates max-plus/tropical algebra with applications in portfolio optimization, dynamic programming, and epidemiological modeling. Recent articles focus on accelerating value iteration algorithms, tropical convexity, and entropy games. Scientific awards are not explicitly mentioned in the provided texts. She collaborates extensively with researchers like Stéphane Gaubert, Marouen B for Stochastic Control, and others in applied mathematics. Lab/Team: Tropical team at INRIA, which bridges tropical mathematics with control theory and optimization.

Pieter J.L. Cuijpersمشاهده پروفایل

دانشیار

• Cyber-Physical Systems
• Real-Time Systems
• Formal Methods
• +۶ مورد دیگر

Pieter J.L. Cuijpers is an Associate Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), affiliated with the Interconnected Resource-aware Intelligent Systems (IRIS) group and EAISI Mobility. His research focuses on quantitative formal modeling of cyber-physical systems, real-time scheduling, and performance analysis of embedded systems, leveraging tools like max-plus algebra and the Lean proof assistant. He holds an MSc in Electrical Engineering (2000) and a PhD in Computer Science (2004), both from TU/e. Research interests include hybrid systems, energy-aware scheduling, Time-Sensitive Networking (TSN), and formal verification. He teaches courses such as Quantitative Evaluation of Embedded Systems and advocates for innovative educational methods like MOOCs and challenge-based learning (CBL). His work contributes to UN Sustainable Development Goals related to industry, innovation, and infrastructure. Notable recognition includes the Outstanding paper award RTNS 2016 . He coordinates the capstone project CBL Embedded Systems and has mentored 44 students, including master’s thesis advisor for M.P.J. Stevens. His lab, IRIS, explores interconnected systems and resource optimization.

Anthony Aidooمشاهده پروفایل

استاد

• Mathematical Biology
• Medical Imaging
• Epidemiological Modeling
• +۳ مورد دیگر

Anthony Aidoo is a Professor of Mathematical Sciences at Eastern Connecticut State University. He holds a Ph.D. in Mathematical Sciences from the University of Vermont, with research interests spanning Mathematical Biology, Epidemiological Modeling, Medical Imaging, and ACh-AChE analysis. His work integrates applied mathematics with real-world applications in biology and medicine. Education: Ph.D., Mathematical Sciences, University of Vermont M.S., Mathematical Sciences, University of Vermont Bachelor's Degree, Kwame Nkrumah University of Science and Technology (Ghana) Research Interests: Mathematical Biology/Physiology Medical Imaging Techniques (e.g., wavelet-based image enhancement) Modeling of diseases like Hepatitis B and campus drinking behavior Collaborations with institutions in Ghana, Canada, Germany, and others Teaching Philosophy: Emphasizes student engagement and the universality of mathematics, particularly through courses like Real Analysis I. Aims to create an enabling environment where students can explore and apply mathematical concepts beyond textbook theories. Professional Contributions: Frequent presenter at international conferences (Bulgaria, Germany, Spain, etc.), with a focus on interdisciplinary research at the intersection of mathematics and life sciences.