جستجوی استاد راهنمای دانشگاهی

Frits C.R. Spieksmaمشاهده پروفایل

استاد

• Combinatorial Optimization
• Operations Research
• Scheduling
• +۷ مورد دیگر

Prof. Frits C.R. Spieksma is a full professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e) , where he leads research within the Combinatorial Optimization Group. He has held academic positions at Maastricht University, KU Leuven, and the University of British Columbia, and has been at TU/e since 2018. Education: M.Sc. in Econometrics, University of Groningen (1987) Ph.D. in Operations Research, Maastricht University (1992) Research Focus: His work lies at the intersection of combinatorial optimization and real-world applications . Key themes include: Scheduling and clustering problems, especially in sports tournaments Organ allocation optimization for Eurotransplant Assignment and transportation problems Approximation algorithms and graph-theoretic optimization Scientific Service & Leadership: Founder and ex-Chair, EURO Working Group OR in Sports Member, Steering Committees of MAPSP and MathSports International President, EURO (Association of European Operational Research Societies) Former Vice-President, IFORS Former President, Belgian Society of Operations Research (ORBEL) Editorial Boards: Associate Editor, 4OR (2015–present) Associate Editor, Journal of Quantitative Analysis in Sports (2014–present) Associate Editor, Operations Research Letters (2008–2024) Former Associate Editor, INFORMS Transactions on Education , OMEGA , Computers & Operations Research , IIE Transactions , Naval Research Logistics PhD Supervision & Mentoring: He has supervised more than 25 PhD theses at KU Leuven and TU/e, many of whom now hold academic positions worldwide. Conference & Workshop Organisation: Recent leadership roles include General Chair of IPCO 2022 (Eindhoven), organiser of Benders Day 2024 , and co-organiser of the Dagstuhl Seminar on Fairness in Scheduling and Resource Allocation (March 2025).

Daniel Buncicمشاهده پروفایل

استاد

• Empirical Finance
• Macroeconomics
• Asset Pricing
• +۴ مورد دیگر

Daniel Buncic is Professor of Finance at Stockholm Business School, Stockholm University, specializing in empirical finance, macroeconomics, and econometrics. He holds a Ph.D. in Economics from the University of New South Wales and has held positions at Sveriges Riksbank and the University of St. Gallen. His research integrates machine learning with traditional econometric methods for financial forecasting and policy analysis. Research Focus: Buncic's work spans asset pricing, volatility forecasting, exchange rate dynamics, and macroprudential policy. He employs advanced techniques like Bayesian econometrics, nonlinear time-series models, and high-dimensional data analysis to address questions in financial stability and market predictability. His recent work critiques methodological approaches in natural rate estimation and equity return prediction. Publication Trends: His articles frequently address econometric methodology, financial market volatility, and monetary policy transmission, with a growing emphasis on machine learning applications in finance. Common themes include forecasting under structural breaks, model robustness, and cross-market interdependencies. Grants & Advising: He secured a 1.74M SEK grant (2020-2023) from the Jan Wallander & Tom Hedelius Foundation. Currently advising PhD student Qinglin Ouyang, he previously directed Stockholm University's Master’s in Banking and Finance program (2019-2022).

Momoko Hayamizuمشاهده پروفایل

دانشیار

• Computational Biology
• Theoretical Biology
• Discrete Mathematics
• +۴ مورد دیگر

Momoko Hayamizu is an Associate Professor at Waseda University's Faculty of Science and Engineering, Department of Applied Mathematics . Her work bridges discrete mathematics with computational biology , focusing on phylogenetic tree/network analysis, single-cell RNA-seq trajectory inference, and algorithm development. She holds a Ph.D. in Mathematical Sciences from The University of Tokyo and an M.D. from SOKENDAI. Research Interests : She specializes in combinatorics, graph theory, and discrete algorithms for modeling biological processes like cell differentiation and viral evolution. Her research emphasizes phylogenetic network theory , tree-based models , and software development (e.g., Treefit). Academic Contributions : Her work includes structure theorems for phylogenetic networks , algorithms for network orientation , and quantitative trajectory analysis methods . Publications span journals like SIAM Journal on Discrete Mathematics and IEEE/ACM Transactions on Computational Biology . Awards & Recognition : Recipient of MEXT's Young Scientists’ Prize , multiple WASEDA e-Teaching Awards , and international scholarships like the Anita Borg APAC . She actively contributes to educational outreach via YouTube lectures and high school collaborations. Leadership & Collaboration : Organized ICIAM 2023 Mini-symposium on phylogenetics, collaborated with institutions like IMI Kyushu University and RIKEN , and developed open-source tools like Treefit for single-cell data analysis.

• Theoretical Computer Science
• Algorithm Design and Analysis
• Approximation Algorithms
• +۳ مورد دیگر

Michael Lampis is a Maître de conférences HDR (Assistant Professor) at LAMSADE , Universite Paris Dauphine. His research focuses on theoretical computer science , particularly in approximation algorithms , parameterized complexity , and graph algorithm design . He has held post-doctoral positions at Kyoto University and KTH, Stockholm, and earned his PhD from the Graduate Center of CUNY under Amotz Bar-Noy. Research Interests include: Structural Graph Parameters (treewidth, pathwidth, clique-width) Algorithmic Meta-Theorems Approximation Schemes Combinatorial Optimization Computational Complexity Recent Research Trends highlight his work on parameterized approximation algorithms for graph problems (e.g., feedback vertex set, matching) and complexity analysis of games/puzzles. His projects S-EX-AP-PE-AL (ANR JCJC), COAL-GAS (CNRS-PSL), and collaborations with Japanese institutions (PARAGA, GRAPA) emphasize cross-border innovation. Scientific Awards include: Best Student Paper Award at WG 2025 Best Paper Award at SOFSEM 2024 Advising involves PhD students Ioannis Katsikarelis, Louis Dublois, and Manolis Vasilakis, alongside Master's advisees like Edouard Nemery and Alban Guerbois. He actively participates in peer review for conferences (ICALP, ESA, STACS) and journals (Algorithmica, JCSS, DAM).

• Computational Complexity
• Algorithmic Game Theory
• Mechanism Design
• +۳ مورد دیگر

Argyrios Deligkas is a Senior Lecturer (equivalent to Associate Professor) at the Royal Holloway University of London. He obtained his PhD from the University of Liverpool under the supervision of Rahul Savani and held postdoctoral positions at the University of Liverpool and the Technion (Industrial Engineering and Management department). His research focuses on computational aspects of game theory, optimization, and complexity. Key interests include: Algorithmic Game Theory and Mechanism Design Computational Complexity (PPAD/PPA-hardness) Fixed-parameter algorithms and combinatorial optimization Fair division and resource allocation Equilibrium computation in multi-agent systems Recent publications (2023-2025) demonstrate a strong emphasis on computational hardness in fair division (e.g., PPA-hardness proofs), mechanism design with real-world constraints, and parameterized algorithms for pathfinding/graph problems. Collaborative work with European researchers dominates his output, with frequent appearances at AAAI, IJCAI, and AAMAS. He actively presents at conferences (e.g., ALGA2025, WINE 2024) and collaborates internationally, including visits to universities in Vienna, Prague, Glasgow, and Edinburgh.

Sean Kauffmanمشاهده پروفایل

استادیار

• Formal Methods
• Real-time Systems
• Software Engineering
• +۴ مورد دیگر

Sean Kauffman is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen's University, Faculty of Engineering and Applied Science. He holds his office in Walter Light Hall, Room 611, and can be reached at sean.k@queensu.ca or by phone at 613-533-6000 ext. 77360. Dr. Kauffman earned his Ph.D. in Electrical and Computer Engineering from the University of Waterloo before completing a two-year postdoctoral position at Aalborg University in Denmark. Notably, he returned to academia after accumulating over a decade of industry experience as a software engineer, with his final industry role being Principal Software Engineer at Oracle. His research expertise spans several critical areas in computer science and software engineering, with a particular focus on safety-critical software systems. His work significantly contributes to the fields of Formal Methods, Runtime Verification, Anomaly Detection, and Explainable AI. Dr. Kauffman has established productive research collaborations with prestigious organizations including NASA's Jet Propulsion Laboratory, the Embedded Systems Institute, QNX, and Pratt and Whitney Canada. Dr. Kauffman's research output demonstrates a consistent focus on event stream analysis, formal verification techniques, and the development of practical tools for system monitoring. His most notable contribution is the nfer language and toolset, which has become influential in the runtime verification community for its ability to abstract event streams into meaningful temporal hierarchies. His publications reveal a progression from theoretical foundations to practical implementations, with applications spanning spacecraft telemetry, autonomous vehicles, and embedded systems. Among his scientific contributions, Dr. Kauffman has received recognition for his work on the complexity analysis of nfer evaluation, developing methods for annotating control-flow graphs for formalized test coverage criteria, and creating frameworks for anomaly detection in embedded systems. His research has been published in top-tier venues including Science of Computer Programming, International Journal on Software Tools for Technology Transfer, and proceedings of major conferences like Runtime Verification and NASA Formal Methods. As an educator, Dr. Kauffman employs active learning techniques, productive failure approaches, and peer instruction to foster student engagement. His industry background informs his teaching approach, providing students with practical insights into real-world software engineering challenges, particularly in safety-critical domains. Dr. Kauffman leads the CritLab research group at Queen's University, which focuses on critical systems research. The lab develops tools and techniques for analyzing and verifying systems where failures could have severe consequences, with applications in aerospace, automotive, and other safety-critical domains. His work on the nfer language has spawned related projects including nvis for visualizing temporal interval hierarchies.

Stéphane Bessyمشاهده پروفایل

استاد

• Graph theory
• Directed graphs
• Algorithms
• +۱ مورد دیگر

Stéphane Bessy is a Professor of Computer Science at the University of Montpellier , serving as Director of the Computer Science Department within the Faculty of Sciences . He is a member of the Graph Algorithms and Combinatorics (AlGCo) team at LIRMM (Laboratory of Informatics, Robotics, and Microelectronics of Montpellier). His research focuses on graph theory, directed graphs, algorithms, and combinatorial optimization. Current teachings include Algorithmic 3, System, Algebra and Geometry, Probability and Statistics, Graphs and Structures, Graphs, Algorithms, Complexity, and Oral Preparation courses. His publications explore topics such as cycle packing in tournaments , exponential domination in graphs , Wiener index optimization , and degree-constrained graph partitions . His work often intersects algorithmic complexity and structural graph theory. Contact: Stephane.Bessy@lirmm.fr

• Robotics
• Control Systems
• Nonholonomic Mobile Robots
• +۷ مورد دیگر

Professor Maciej Michałek is a distinguished academic at Poznań University of Technology, where he serves in the Faculty of Automatic Control, Robotics and Electrical Engineering within the Institute of Automation and Robotics. His research spans robotics, control systems, and automation with particular focus on nonholonomic mobile robots and advanced control methodologies. Professor Michałek's research interests center on Vector Field Orientation (VFO) control methodology, mobile robot motion planning, and Active Disturbance Rejection Control (ADRC). He has made significant contributions to fixed-time and predefined-time control systems, kinematic modeling of multi-trailer vehicles, and precision docking systems for electric buses. His work bridges theoretical control concepts with practical applications in automotive, aerospace, and robotics domains. His recent publications demonstrate a clear trajectory toward time-constrained control systems with guaranteed convergence properties, multi-agent coordination, and practical implementations in electric vehicle infrastructure. Professor Michałek has published extensively in top-tier journals including IEEE Transactions on Cybernetics, Nonlinear Dynamics, and IEEE Transactions on Vehicular Technology. As a supervisor, Professor Michałek has guided doctoral students through research on cascaded control systems for mobile robots and motion algorithmization within the VFO framework. His mentorship focuses on rigorous theoretical development combined with practical implementation of advanced control systems. Professor Michałek maintains active research in both theoretical control methodologies and their practical applications, particularly in electric vehicle charging systems, automotive control mechanisms, and aerospace stabilization. His laboratory work focuses on experimental validation of control algorithms using robotic platforms and vehicle simulation systems.

Tomasz Falborskiمشاهده پروفایل

استادیار

• Structural Engineering
• Seismic Analysis
• Earthquake Engineering
• +۵ مورد دیگر

Tomasz Falborski is an Assistant Professor at the Department of Building Engineering within the Faculty of Civil and Environmental Engineering at Gdańsk University of Technology. He maintains his office in Building A of the Faculty (Żelbet section) at room 220, and can be contacted at tomfalbo@pg.edu.pl. Dr. Falborski's research focuses on structural engineering with emphasis on seismic analysis and mitigation techniques for buildings. His work primarily addresses: Structural dynamics and damping systems for steel frame buildings Base isolation systems and tuned mass dampers for earthquake protection Soil-structure interaction effects on building safety Optimization of structural control systems for multi-storey buildings Seismic performance evaluation of steel moment frames Development of fractional-order controllers for structural protection His 2025 publications reveal a strong research trajectory focused on practical seismic protection solutions. The work spans from fundamental structural dynamics to advanced control systems, with particular attention to optimization algorithms for determining optimal parameters of damping and control mechanisms. His research has significant practical implications for building design in earthquake-prone regions. Dr. Falborski serves as project manager for the MINIATURA-funded research project investigating rotational stiffness of column bases and soil flexibility effects on seismic response of structural steel buildings. His collaborative work with international researchers indicates active participation in the global structural engineering research community.

Daniel Kráľمشاهده پروفایل

استاد

• Discrete Mathematics
• Graph Theory
• Combinatorics
• +۷ مورد دیگر

Daniel Kráľ is an Alexander von Humboldt Professor for Discrete Mathematics at Leipzig University and an affiliated member of the Max Planck Institute for Mathematics in the Sciences (MPI MiS). Previously, he held the Donald Ervin Knuth Professorship at Masaryk University in Brno and is also an honorary professor at the University of Warwick, where he was a professor of mathematics and computer science and a member of the Centre for Discrete Mathematics and its Applications (DIMAP). His research addresses various topics at the interface of mathematics and computer science, with primary focus on structural and extremal graph theory, discrete algorithms, and combinatorial limits. The theory of combinatorial limits is an emerging area that provides analytic methods to study large graphs such as social networks, establishing new links between analysis, combinatorics, ergodic theory, group theory and probability theory. His work has been supported by prestigious ERC grants including the CCOSA Starting grant and LADIST Consolidator grant. Dr. Kráľ's scholarly output includes over 150 journal research papers and numerous conference contributions. His recent publications demonstrate continued leadership in extremal combinatorics, graph limits, and structural graph theory, with significant contributions to understanding quasirandomness, Turán densities, and the coloring of complex graph structures. Scientific Recognition: SIAM Fellow (2024) Fellow of the American Mathematical Society (2020) Philip Leverhulme Prize in Mathematics and Statistics (2014) European Prize in Combinatorics (2011) ERC Consolidator grant LADIST (2015-21) ERC Starting grant CCOSA (2010-15) Professor Kráľ has supervised numerous PhD students and postdoctoral fellows throughout his career. His editorial service includes Editor-in-Chief of SIAM Journal on Discrete Mathematics (2017-2022), Co-Editor-in-Chief of Journal of Combinatorial Theory (since 2025), and Managing editor of Advances in Combinatorics (since 2018). He has organized multiple international workshops and conferences including Oberwolfach workshops on Graph Theory and the European Conference on Combinatorics, Graph Theory and Applications (EUROCOMB'23).

Slim TNANIمشاهده پروفایل

دانشیار

• Electrical Engineering
• Control Systems
• Power Electronics
• +۴ مورد دیگر

Slim TNANI is an Associate Professor with HDR (Habilitation à Diriger des Recherches) in Automatic Control and Systems at the University of Poitiers' Institute of Technology (IUT). He maintains dual affiliations with the Laboratory of Engineering Applications of Dynamics and Systems (LIAS) at both the ENSIP (École Nationale Supérieure d'Ingénieurs de Poitiers) and ISAE-ENSMA (Institut Supérieur de l'Aéronautique et de l'Espace) campuses in France. His research spans electrical engineering with particular focus on control systems, power electronics, and renewable energy integration. Key interests include fault diagnosis in electrical machines, synchronous generator control, energy storage systems, and power network stability. His work demonstrates strong theoretical foundations combined with practical industrial applications, particularly in wind energy systems and hybrid power generation. Analysis of his publication record shows consistent research trajectory with increasing focus on renewable energy integration since 2015. His work bridges traditional power systems engineering with modern control theory, showing particular expertise in parameter estimation techniques for fault detection and advanced control strategies for energy storage integration. Recent publications emphasize optimization of hybrid renewable systems and stability analysis for power networks with high renewable penetration. As an HDR-qualified researcher, TNANI supervises doctoral candidates and leads research projects within the LIAS laboratory. His work has resulted in significant industrial collaborations, particularly in power electronics applications for renewable energy systems. The laboratory environment supports both theoretical research and practical implementation through specialized teams in automatic control, data engineering, and real-time systems. His research group maintains strong connections with international partners, evidenced by collaborations with Tunisian researchers on grid interconnection studies and renewable energy projects. The LIAS laboratory provides infrastructure for experimental validation of control systems in power electronics and renewable energy applications.

• Forensic Statistics
• Medical Statistics
• Machine Learning
• +۲ مورد دیگر

Giulia Cereda serves as Associate Professor in the Department of Statistics, Computer Science, and Applications 'G. Parenti' (DiSIA) at the University of Florence since 2025. Her academic journey includes prior roles as Fixed-term Researcher (RTD-b, 2022-2024), Research Fellow (2021-2022), and Swiss National Science Foundation Postdoc Mobility Fellow (2019-2021) at Leiden University and University of Florence. She holds a Joint PhD in Statistics from Leiden University and University of Lausanne (2011-2016), complemented by Master's and Bachelor's degrees in Mathematics from the University of Milan. Her research spans forensic statistics with focus on rare type match problems in DNA evidence evaluation, medical statistics applied to SARS-CoV-2 pandemic modeling, and machine learning implementations for biogeographical ancestry prediction. Recent publications demonstrate methodological innovations in Bayesian approaches for forensic evidence, compartmental modeling of epidemic dynamics, and supervised learning applications in population genetics. Analysis of her 14 most recent publications (2020-2025) reveals dual research thrusts: (1) forensic statistics addressing DNA mixture interpretation and rare haplotype matching through Bayesian frameworks, and (2) epidemiological modeling of smoking dynamics and SARS-CoV-2 transmission using compartmental models with uncertainty quantification. Her work bridges theoretical statistics with practical public health and forensic applications, frequently employing machine learning for complex prediction tasks. Supported by the Swiss National Science Foundation for postdoctoral research (2019-2021), she has contributed to pandemic response through Tuscan regional modeling and school-based screening strategies. Current office hours are Thursdays 3:00-4:00 PM by appointment, with ongoing research in forensic identification systems and epidemic forecasting methodologies.