Charles Geyer is a Professor at the School of Statistics, University of Minnesota . His work spans computational statistics, spatial statistics, and statistical genetics, with applications to endangered species conservation and stochastic process modeling. Research Interests: Spatial statistics, Markov chain Monte Carlo methods, likelihood inference in exponential families, constrained optimization, and statistical software development. Software Contributions: Developed R packages mcmc , aster , rcdd , and trust for Monte Carlo methods, life history analysis, computational geometry, and optimization. Teaching: Instructs graduate and undergraduate courses including Stat 5101, Stat 5102, Stat 5421, Stat 5601, and advanced seminars on computational statistics. Publications: Notable works include research on maximum likelihood estimation in exponential families, fuzzy P-values, geometric ergodicity in MCMC, and computational methods for conservation genetics.
Serge Provost is a Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario. His office is located in WSC 280, and he can be contacted via phone (519-661-2111 x83624) or email (provost@uwo.ca). Research Focus: Professor Provost specializes in multivariate statistical analysis, distribution theory, and probabilistic modeling with applications in environmental sciences and actuarial science. His work emphasizes: Development of approximation methods for complex distributions Innovations in density estimation techniques Statistical inference for incomplete data Serial correlation analysis Functional linear modeling frameworks Publication Trends: His recent articles (2011-2016) predominantly focus on theoretical and computational statistics, with recurring themes in distribution theory, orthogonal polynomial approximations, and specialized probability models. Research frequently intersects with actuarial mathematics, time series diagnostics, and nonparametric estimation methods. Graduate Supervision: Currently advises three PhD students: Cong Nie Zhaoqi Yang Yishan Zang
Fedor Fomin is a Professor at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Bergen. He is renowned for his contributions to theoretical computer science, particularly in parameterized complexity and exact exponential algorithms, earning him the ACM Fellow 2023 distinction. University: University of Bergen School: Faculty of Mathematics and Natural Sciences Department: Department of Informatics Academic Rank: Professor Research Interests: Fomin's work focuses on designing efficient algorithms for computationally hard problems, with a specialization in parameterized and exact exponential algorithms. His research spans graph theory, combinatorial optimization, and computational complexity, addressing foundational challenges in sparse graphs, planar graphs, and treewidth-based techniques. Key Contributions: His research includes kernelization methods, subexponential algorithms for planar graphs, and novel approaches to edge domination and satisfiability problems. He has published extensively in top venues like STOC, FOCS, and SODA. Awards: ACM Fellow 2023 EATCS Award 2019 ERC Advanced Grant 2016 Nordic Researcher Award in Theoretical Computer Science 2010 Publications: His work covers parameterized algorithms for cluster editing, feedback vertex sets, and induced subgraph problems, with applications in computational biology and network science. Collaborations: Fomin collaborates with leading researchers in theoretical computer science, including Petr Golovach and Saket Saurabh, mentoring numerous PhD students and shaping the field's future.
Prof. Dr. Hans Bodlaender is a Full Professor of Algorithms and Complexity at Utrecht University's Faculty of Science, Department of Information and Computing Sciences. He holds a Ph.D. in Mathematics from Utrecht University (1985) and has held academic positions since 1983, including roles at Eindhoven University of Technology. His research focuses on algorithms, computational complexity, graph theory, and parameterized complexity, with a particular emphasis on treewidth and network algorithms. He has been recognized with the EATCS-IPEC Nerode Prize (2014) and has contributed to over 500 publications. His work includes developing algorithms for graph decomposition, scheduling, and NP-hard problem analysis. He has organized international workshops and served on editorial boards, including the Journal of Discrete Algorithms. Education: B.Sc. Mathematics, Utrecht University (1981) M.Sc. Mathematics, Utrecht University (1983) Ph.D. in Distributed Computing (1985), supervised by Jan van Leeuwen Research Interests: Algorithms, complexity theory, parameterized complexity, treewidth, graph algorithms, network optimization, and computational problem-solving. His work bridges theoretical foundations with practical algorithm design, emphasizing efficient algorithms for NP-hard problems. Recent Article Trends: Focus on parameterized complexity, treewidth applications, scheduling algorithms, and algorithmic lower bounds. Recent work explores fixed-parameter tractability, graph decompositions, and hardness results for problems on structured graphs. Awards: EATCS-IPEC Nerode Prize (2014) for contributions to parameterized complexity. Grants/Advising: Extensive involvement in grant-funded research projects and academic leadership roles. Supervised numerous PhD and Master's students (details not fully listed here). Labs/Teams: Active in the Algorithms and Complexity research group at Utrecht University, collaborating on theoretical computer science and algorithmic challenges.
Fedor Fomin is a Professor in Algorithms at the Department of Informatics, University of Bergen, Norway, since 2002. His research focuses on fundamental problems in computer science and mathematics, particularly in algorithm design and graph theory. Research Interests: His work spans advanced algorithmic techniques such as Matroid algorithms Algorithmic graph minors Treewidth and its applications Exact and exponential time algorithms Pursuit-evasion games and graph searching Parameterized algorithms and kernelization Graph coloring Publications: He has authored over 150 peer-reviewed journal articles in venues like J. ACM, SIAM J. Computing, and Combinatorica, alongside 160 conference papers in top-tier events including FOCS, STOC, and AAAI. His research demonstrates expertise in bridging theoretical computer science and discrete mathematics. Scientific Awards: EATCS Fellow (2019) ERC Advanced Investigator Grant (2010) EATCS-IPEC Nerode Prize 2017 (with F. Grandoni and D. Kratsch) EATCS-IPEC Nerode Prize 2015 (with E. D. Demaine, M. T. Hajiaghayi, and D. M. Thilikos) Norway's Outstanding Young Investigator Award (2005) Grants: He has secured major grants from The Research Council of Norway (NFR), the Russian Ministry of Education and Science (mega-grant), and the European Research Council (ERC) as Principal Investigator.
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.
Charles J Geyer is a Professor in the Department of Statistics at the University of Minnesota, Twin Cities, within the College of Science and Engineering. He has been an active researcher since at least 1988, with a sustained record of scholarly output in statistical theory and methodology. His research focuses on advanced statistical methods including maximum likelihood estimation, exponential families, Markov Chain Monte Carlo (MCMC), likelihood-free inference, and aster models. These methods are applied in interdisciplinary contexts such as evolutionary biology, genetics, and ecological modeling, particularly in life history analysis and phenotypic selection. His work bridges theoretical statistics with practical computational tools for complex data. The recent publications highlight a strong trend toward computationally efficient inference, especially in models where traditional maximum likelihood fails. He has contributed to the development of the R package glmm for generalized linear mixed models and has worked extensively on envelope methods and variance reduction techniques. His research outputs include numerous peer-reviewed articles, book chapters, and publicly shared datasets, reflecting a commitment to open science. Scientific contributions include: Development of MCMC methods for dependent data Foundational work on likelihood inference when MLE does not exist Integration of aster models with envelope methodology Applications in evolutionary and ecological statistics He has collaborated with researchers such as D. J. Eck, R. G. Shaw, and R. D. Cook. While formal advisee relationships are not listed, his collaborative work suggests mentorship and academic leadership. He has not received any explicitly mentioned awards in the provided text, but his sustained impact is evident through citations and methodological influence. His datasets are archived in the University of Minnesota Data Repository, supporting reproducible research.
Sorin Micu is a Professor in the Department of Mathematics at the Faculty of Mathematics and Natural Sciences, University of Craiova, Romania. He is actively involved in research and teaching, with a strong focus on partial differential equations and their control. University: University of Craiova School: Faculty of Mathematics and Natural Sciences Department: Department of Mathematics Email: sd_micu@yahoo.com Office: Room 309, Central Building, AI Cuza 13, 200585 Craiova, Romania Research Interests: His primary research areas include the control of partial differential equations (PDEs), numerical analysis of PDEs, and mathematical modeling. He investigates controllability properties of various PDEs such as the heat, wave, Schrödinger, and Korteweg-de Vries equations, often using tools like Carleman estimates, duality methods, and finite element approximations. His work bridges theoretical analysis with numerical simulation, particularly in the context of semidiscretized and discrete systems. Publication Trends: The articles span from 1995 to 2017, showing sustained contributions in control theory for PDEs. The research evolves from classical equations (heat, wave) to more complex models (nonlocal, degenerate, nonlinear), with increasing focus on numerical approximation and discrete controllability. Keywords consistently revolve around controllability , stabilization , numerical methods , and nonlinear dynamics . Scientific Projects: Bilateral Contract Romania-France (2009–2010), Capacities Program, Module III Bilateral Project Romania-France (English version) Project PN-II-ID-PCE-2011-3-0257 Teaching and Advising: Professor Micu teaches courses such as Numerical Analysis, Algorithmics and Numerical Simulation in C++, Modeling and Simulation, and Finite Element Methods at both undergraduate and master’s levels. While formal advisees are not listed, his teaching and research supervision likely involve mentoring graduate students. He offers consultations every Thursday from 15:00 to 16:00 in Room 309. Laboratories and Teams: He is affiliated with research groups working on PDE control and numerical analysis at the University of Craiova. His collaboration with French institutions indicates participation in international research networks focused on applied mathematics and control theory.
Iliopoulos Georgios is a Professor and Department Chair at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus. He has held this position since 2015, following his progression from Assistant Professor (2003-2010) to Associate Professor (2010-2015) at the same institution. Education: 1993: B.A. in Mathematics, Department of Mathematics, University of Patras 1999: PhD in Statistics, Department of Mathematics, University of Patras Iliopoulos specializes in statistical theory and methodology, with particular expertise in Markov chain Monte Carlo methods, Statistical Decision Theory, and Scale parameter estimation. His research focuses on accurate inference under censorship and constrained inference arrangement, addressing fundamental challenges in statistical analysis of complex data structures. His work bridges theoretical statistics with practical applications in reliability analysis and survival analysis. His publication record shows consistent contributions to exact statistical inference methods, particularly for censored data and complex distributions like Laplace and Gamma. His research demonstrates expertise in both parametric and semiparametric approaches, with significant work on variance reduction techniques in computational statistics and solutions to the label switching problem in Bayesian mixture models. Iliopoulos teaches undergraduate courses including Linear Algebra, Statistics II: Hypothesis Testing, and Special Topics in Statistics (Bayesian Statistics), as well as the postgraduate course Computational Statistical Techniques for the Master of Science in Applied Statistics.
Professor Georgios Iliopoulos is a distinguished academic serving as Professor and Department Chair of the Department of Statistics and Actuarial Science at the University of Piraeus. With an extensive academic career spanning over two decades, Professor Iliopoulos has established himself as a leading expert in statistical theory and methodology. His leadership as Department Chair demonstrates his significant contribution to the academic community and his commitment to advancing statistical education and research. Professor Iliopoulos completed his educational journey at the University of Patras, earning his B.A. in Mathematics in 1993 followed by a PhD in Statistics in 1999. His academic career progressed through various institutions before he settled at the University of Piraeus, where he has held positions from Assistant Professor (2003-2010) to Associate Professor (2010-2015) and ultimately to Professor (2015-present). Professor Iliopoulos's research focuses on several key areas of statistical theory, with particular emphasis on Markov chain Monte Carlo methods, Statistical Decision Theory, Scale parameter estimation, Accurate inference under censorship, and Constrained inference arrangement. His work bridges theoretical statistics with practical applications, demonstrating how sophisticated statistical methods can solve real-world problems across various domains. His research has consistently addressed challenging theoretical questions while maintaining relevance to practical statistical challenges faced by researchers and practitioners. Analysis of Professor Iliopoulos's publication record reveals a strong focus on theoretical statistics with applications in reliability analysis, Bayesian inference, and censoring methodologies. His work demonstrates a consistent pattern of advancing statistical theory while maintaining practical relevance, particularly in the areas of parameter estimation, confidence interval construction, and inference with censored data. The interdisciplinary nature of his research is evident in publications spanning journals in statistics, biostatistics, and computational statistics. Professor Iliopoulos is actively involved in teaching both undergraduate and postgraduate courses. At the undergraduate level, he teaches Linear Algebra, Statistics II: Hypothesis Testing, and Special Topics in Statistics (Bayesian Statistics). For postgraduate students, he offers Computational Statistical Techniques as part of the Master of Science in Applied Statistics program. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications of advanced statistical methods.
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).
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).
