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Jan DraismaView profile

Professor

• Algebraic Geometry
• Combinatorics
• Algebraic Statistics
• +8 more

Jan Draisma is a full professor of Mathematics at the University of Bern and a part-time full professor of Applied Algebra and Geometry at Eindhoven University of Technology (TU/e), where he is affiliated with the Department of Mathematics and Computer Science, specifically in Discrete Algebra and Geometry and Coding Theory and Cryptology. He obtained his Master's and Ph.D. degrees from TU/e cum laude and held a postdoctoral position at the University of Basel (2002–2005). He returned to TU/e as an assistant professor, later advancing to associate professor (2011–2016), and served as a part-time full professor at VU Amsterdam (2015–2016). His research focuses on the interplay between combinatorics, statistics, and algebraic geometry. Key areas include tropical geometry, algebraic statistics, symmetric systems of polynomial equations in infinitely many variables, and representation stability. His work often explores the structure of infinite-dimensional algebraic objects and their finite approximations. The most recent publications highlight trends in polynomial functors, topological Noetherianity, amoebas of linear spaces, and the geometry of tensor representations. These works reflect a deep integration of algebraic geometry with combinatorics and category theory, emphasizing stabilization phenomena and symmetry in algebraic structures. NWO Vici Award: Stabilisation in Algebra and Geometry (2015) NWO Vidi Award: Finite thanks to symmetry (2010) Draisma has received significant research funding, including the NWO Vidi and Vici grants, and two NWO Free Competition grants (2008, 2012). He has supervised 16 students and is actively involved in the academic community as an associate editor for Experimental Mathematics, SIAM Journal on Applied Algebra and Geometry, and Linear and Multilinear Algebra. He has held leadership roles in major conferences such as MEGA 2015 and SIAM AG 19. He is affiliated with the research groups in Discrete Algebra and Geometry and Coding Theory and Cryptology at TU/e and leads research activities centered on algebraic methods in discrete mathematics and statistics.

Jop BriëtView profile

Researcher

• Theoretical Computer Science
• Quantum Information Theory
• Combinatorics
• +3 more

Jop Briët is a Researcher at the Department of Algorithms and Complexity at Centrum Wiskunde & Informatica (CWI) in the Netherlands. His work focuses on theoretical computer science, quantum information theory, combinatorics, and tensor analysis. He has held grants including the Veni Innovational Research Grant from NWO and a Rubicon fellowship. He has authored over 50 publications in leading venues, exploring topics such as Grothendieck inequalities, quantum computing, and additive combinatorics. His research interests span the interplay between combinatorics and computational complexity, with particular emphasis on tensor analysis, probabilistic methods, and algorithm design. Recent work includes studies on Szemerédi’s theorem with random differences and the application of quantum query algorithms to entanglement-based problems. Awards: Outstanding paper award TQC (2020), Andreas Bonn medal (2013), Stieltjesprijs (2011). Professional Activities: Editor for ERCIM News, Board Member of Koninklijk Wiskundig Genootschap, and frequent invited speaker at workshops on quantum computing and combinatorics. Grants: Veni Grant (2014), Rubicon Fellowship (2012). Current teaching includes courses on Additive Combinatorics and Quantum Information Processing, reflecting his commitment to bridging foundational theory with advanced applications in computing and mathematics.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Optimization
• +7 more

Nikhil Bansal holds the prestigious Patrick C. Fischer Professorship of Theoretical Computer Science in the Department of Computer Science & Engineering at the University of Michigan's College of Engineering. His research program has established him as a leading figure in theoretical computer science, with significant contributions to algorithm design and analysis, particularly in discrete optimization problems. Bansal's research focuses on theoretical computer science with emphasis on design and analysis of algorithms for discrete optimization problems. His work spans multiple areas including discrepancy theory, approximation algorithms, randomized algorithms, combinatorial optimization, complexity theory, machine learning theory, and probability. He has made significant contributions to understanding the limits of approximation algorithms and developing novel techniques for combinatorial optimization problems. Analysis of Bansal's recent publications reveals a strong focus on discrepancy theory, online algorithms, and combinatorial optimization. His work often bridges theoretical computer science with discrete mathematics and probability theory. A recurring theme across his publications is the development of novel algorithmic techniques for solving NP-hard problems with provable guarantees. His research has evolved from foundational work in approximation algorithms to more recent contributions in quantum computing complexity and stochastic optimization. Patrick C. Fischer Professor of Theoretical Computer Science Bansal has advised numerous PhD students including Marek Elias, Shashwat Garg, and Greg Koumoutsous, as well as mentoring several postdoctoral researchers. He has served on editorial boards for top journals including Journal of the ACM, Theory of Computing, and Stochastic Models, and has been active on program committees for major conferences such as STOC, FOCS, SODA, and ICALP, including serving as chair for ICALP 2021. Bansal has organized multiple academic workshops including the STOC 2020 Workshop on Recent Advances in Discrepancy and Applications, several SDP Days at CWI Amsterdam, and the Semester on Bridging Continuous and Discrete Optimization at UC Berkeley in Fall 2017.

Rudi A. PendavinghView profile

Assistant Professor

• Combinatorics
• Matroid Theory
• Graph Theory
• +3 more

Rudi A. Pendavingh is an Assistant Professor at Eindhoven University of Technology's Mathematics and Computer Science department, specializing in Combinatorial Optimization. He earned his PhD at the University of Amsterdam in topological graph theory and has since contributed to diverse areas of combinatorics and geometry, with recent focus on matroid theory. His teaching spans mathematical programming topics including linear, integer, and semidefinite optimization. Education: PhD in Topological Graph Theory (University of Amsterdam) His research integrates combinatorial structures with geometric and algebraic methods, particularly in matroid theory, graph embeddings, and tropical geometry. Key publication themes include optimization algorithms, excluded matroid minors, and geometric invariants. Collaborations extend to institutions in mathematics and applied sciences, with notable academic output (67 research items) and external partnerships. Recent research outputs (2022-2025) highlight his work on the Colin de Verdière parameter, Dressian bounds, and tropical amoebas. While no explicit awards are mentioned in the provided text, his contributions to combinatorial optimization and network collaborations underscore his academic impact. He has supervised 29 students and contributed to 7 courses, including Discrete Optimization Modeling and Mathematics II.

Monique LaurentView profile

Professor

• Combinatorial Optimization
• Semidefinite Programming
• Polynomial Optimization
• +2 more

Monique Laurent is Professor of Quantitative Microeconomics at Tilburg University and Senior Researcher at CWI Amsterdam. Her research combines discrete mathematics and optimization, focusing on algebraic, combinatorial and geometric methods for algorithm design. Research interests include: Semidefinite programming for combinatorial optimization Approximation algorithms for NP-hard problems Polynomial optimization techniques Matrix factorization ranks Graph theory applications Recent publications develop semidefinite programming approaches for matrix factorization and biclique problems. She leads European research networks including TENORS on tensor optimization. Awards: Khachiyan Prize (2023) EUROPT Fellow (2021) Member of Royal Netherlands Academy (KNAW) SIAM Fellow (2017)

Maris OzolsView profile

Assistant Professor

• Quantum Algorithms
• Quantum Information Theory
• Quantum Cryptography
• +3 more

Maris Ozols is an Assistant Professor at the University of Amsterdam and a researcher at QuSoft, affiliated with the Algorithms and Complexity department at Centrum Wiskunde & Informatica (CWI). His primary research focuses on quantum algorithms and quantum information theory, with significant contributions to quantum complexity, quantum cryptography, and quantum state discrimination. His research interests span quantum algorithms, quantum information theory, quantum cryptography, quantum complexity, and theoretical computer science. Ozols has developed fundamental techniques in quantum query complexity, quantum state discrimination, and quantum cryptographic security models. His work often bridges theoretical computer science with quantum information physics, demonstrating practical implications for quantum computing architectures. His publication record shows consistent output in top venues including Communications in Mathematical Physics, Leibniz International Proceedings in Informatics, and Quantum journal. Recent work (2022-2025) focuses on quantum state discrimination, quantum circuit optimization, quantum machine learning, and cryptographic applications of quantum algorithms. His research demonstrates strong theoretical foundations with practical implications for quantum computing development. Leverhulme Early Career Fellow (University of Cambridge) Ozols has secured research funding through multiple Netherlands Organisation for Scientific Research (NWO) grants including the Quantum Software Consortium (QSC) and Quantum Computation with Bounded Space projects. His collaborative work spans international institutions including the University of Waterloo (where he earned his PhD), University of Cambridge, IBM Research, and various European quantum computing groups. He maintains active research groups in quantum algorithms at both QuSoft and CWI, with recent focus on quantum machine learning applications and quantum cryptographic protocols.

Etienne de KlerkView profile

Professor

• Mathematical Programming
• Operations Research
• Optimization
• +3 more

Prof. Etienne de Klerk is a Full Professor in the Department of Econometrics and Operations Research at Tilburg University, Netherlands. He holds affiliations with the Tilburg School of Economics and Management (TISEM) and has held academic positions at Nanyang Technological University (Singapore), University of Waterloo (Canada), and Delft University of Technology (Netherlands). His research focuses on mathematical programming, optimization, and operations research, with notable contributions to semidefinite programming, polynomial optimization, and interior point methods. Education & Career: PhD (exact title not specified) Assistant Professorships at TU Delft (1998–2003) Associate Professor at University of Waterloo (2003–2005) Full Professor at Tilburg University since 2009 Part-time Professor at TU Delft (2015–2019) Research Interests: Semidefinite programming, polynomial optimization, convex optimization, interior point methods, approximation theory, and algorithmic convergence analysis. His work bridges theoretical foundations with practical applications in engineering and machine learning. Awards & Grants: VIDI Grant (NWO) ENW-GROOT Grant (NWO) 2017 Best Paper Prize (Optimization Letters) Co-recipient of Canadian Foundation for Innovation’s New Opportunities Fund Recent Research Trends: Recent articles emphasize optimizing algorithms (e.g., DCA convergence analysis, predictor-corrector methods) and theoretical advancements in polynomial approximation and positivstellensatze. Collaborations span global institutions in optimization and applied mathematics. Supervision & Projects: Lead researcher on grants like POEMA and MINOA, focusing on polynomial optimization and training early-stage researchers. Actively involved in editorial roles for SIAM Journal on Optimization and INFORMS Journal on Computing. Labs & Teams: Research group in Operations Research at Tilburg University, collaborating on projects like semidefinite programming applications and machine learning optimization.

Renata SotirovView profile

Professor

• Optimization
• Operations Research
• Mathematical Programming
• +3 more

Renata Sotirov is a Full Professor at Tilburg University's Department of Econometrics & Operations Research within the Tilburg School of Economics and Management. She holds a PhD in Mathematics and has held academic positions including Associate Professor (2009–2014) and Assistant Professor (2007–2009). Her research focuses on optimization, operations research, and semidefinite programming with applications in combinatorial optimization and discrete mathematics. She has supervised PhD students such as Dr. Ning Ma and Dr. Uwe Truetsch and collaborates internationally, including with institutions like the University of Melbourne and McMaster University. Her work includes pioneering contributions to semidefinite relaxation techniques, integer SDPs, and algorithmic optimization. Recent projects involve the Chvátal-Gomory procedure for integer SDPs and complex cut polytopes. She has served as a research coordinator, director of graduate studies, and treasurer for her department. Her expertise spans teaching operations research methods, combinatorial optimization, and quantitative business analytics.

• Convex Optimization
• Quantum Computing
• Quantum Information Theory
• +7 more

Sander Gribling is an Assistant Professor in the Department of Econometrics and Operations Research at Tilburg School of Economics and Management, Tilburg University. His research bridges convex optimization, quantum computing, and quantum information theory, with a focus on quantum algorithms for classical optimization problems, semidefinite and polynomial optimization, and quantum graph parameters. PhD in Optimization and Quantum Information, Tilburg University (2019) MSc and BSc in Applied Mathematics, TU Delft His research interests include: Quantum algorithms for linear programming, semidefinite programming, and matrix scaling Polynomial and sum-of-squares optimization Quantum query complexity and the polynomial method Applications of optimization to quantum information and noncommutative graphs His recent publications reveal a strong focus on quantum algorithms, theoretical foundations of optimization, and sampling methods. Key trends include the development of optimal quantum linear solvers, complexity analysis of the Lasserre hierarchy, and the interplay between Grothendieck inequalities and quantum query models. Notable scientific roles: Associate Editor, INFORMS Journal on Computing Sander Gribling has advised or collaborated with numerous researchers including Simon Apers, Joran van Apeldoorn, Monique Laurent, and Ronald de Wolf. He has received no explicitly listed awards in the provided text, but his publications in high-impact journals such as Nature Reviews Physics and Quantum indicate strong recognition. He is involved in the Operations Research research group and contributes to advancing theoretical and applied quantum optimization.

• Operations Research
• Discrete Mathematics
• Tropical Geometry
• +3 more

Georg Loho is an Assistant Professor in the department of Mathematics of Operations Research. His research focuses on the intersection of combinatorics, optimization, and geometry, with a particular emphasis on oriented matroids, tropical geometry, and algorithmic game theory. He explores applications in machine learning, neural network architecture, and stochastic games. Key research themes include the study of matroid theory, convex analysis, and the development of algorithms for optimization problems. His work bridges theoretical mathematics with practical applications in computational fields, such as analyzing the complexity of neural networks and solving problems in mean payoff games. Recent contributions include advancements in tropical geometry applied to neural networks and the reduction of stochastic games to semidefinite programming. He actively collaborates on interdisciplinary projects, as evidenced by his talks and publications in top-tier journals such as Selecta Mathematica and TheoretiCS . His research outputs span topics like polymatroids, lattice polytopes, and combinatorial optimization, reflecting a commitment to both foundational theory and computational methods.

Hadi AbbaszadehpeivastiView profile

Researcher

• Optimization Methods
• Machine Learning
• Convergence Rate Analysis
• +4 more

Hadi Abbaszadehpeivasti is a researcher at the Department of Econometrics and Operations Research within the Tilburg School of Economics and Management at Tilburg University. His work focuses on optimization methods, machine learning, and convergence rate analysis using semidefinite programming techniques. Education: Master’s Degree in Statistics (Normal and Generalized Gamma Estimation), Sabanci University (2019–2020) Master’s Degree in Stochastic Kriging Meta-Modeling for Simulation Optimization, Sharif University of Technology (2012–2014) His research interests include convergence rate analysis of first-order optimization algorithms, performance estimation in non-convex settings, and applications of semidefinite programming to machine learning. He explores conditions like the Polyak–Łojasiewicz inequality for linear convergence and works on saddle-point problems and ADMM variants. Recent publications span convex-concave optimization, gradient descent-ascent methods, and ADMM convergence analysis, with a focus on non-asymptotic guarantees and exact worst-case bounds. His studies often bridge theoretical insights with practical algorithm design. His work also involves collaborations with researchers like Etienne de Klerk and Moslem Zamani, contributing to operations research and computational optimization theory.

Juan Vera LizcanoView profile

Professor

• Optimization
• Combinatorial Optimization
• Machine Learning
• +4 more

Juan Vera Lizcano is a Professor at Tilburg University's Tilburg School of Economics and Management, Department of Econometrics and Operations Research. He holds a PhD in Industrial Engineering from the University of Florida and specializes in optimization, machine learning, and operations research. His research focuses on mathematical programming, probabilistic combinatorics, and their applications in operations research and computer science, particularly in polynomial optimization, sparse methods for machine learning, and the relationship between error bounds and algorithm convergence. Professor Vera Lizcano's recent publications demonstrate a consistent focus on optimization techniques across mathematical, financial, and machine learning domains. His work shows strong interdisciplinary connections between operations research, computer science, and applied mathematics. He supervises doctoral research and has contributed to projects like the PROMISe initiative recording clinical interventions by community pharmacists. His laboratory investigates advanced optimization methods and their practical implementations.

Sven PolakView profile

Assistant Professor

• Discrete Mathematics
• Optimization
• Convex Relaxations
• +4 more

Sven Polak is an Assistant Professor at Tilburg University in the Department of Econometrics and Operations Research, part of the Tilburg School of Economics and Management. He holds a PhD in Mathematics from the University of Amsterdam (2019) and a Master's in Dutch Law from the same institution (2017). Prior to his academic role, he worked as an operations research engineer at ORTEC and as a postdoctoral researcher at Centrum Wiskunde & Informatica (CWI) in Amsterdam. His research focuses on the intersection of discrete mathematics and optimization, particularly convex relaxations, algebraic techniques, and coding theory. Polak's educational background includes a Bachelor's in Mathematics from the University of Amsterdam (2012) and advanced studies in algebraic geometry and combinatorics. His research interests span semidefinite programming, combinatorial optimization, graph theory, and applications in coding and queueing systems. He has taught courses on linear algebra, operations research methods, and networks and semidefinite programming at the PhD level. His work has been published in leading journals such as Mathematical Programming , Quantum , and SIAM Journal on Applied Algebra and Geometry . He actively participates in academic conferences, presenting on topics like crossing numbers, mutually unbiased bases, and computational complexity. Polak also maintains an interest in running, with notable achievements recorded in his World Athletics profile.

Monique LaurentView profile

Professor

• Discrete Mathematics
• Optimization
• Polynomial Optimization
• +5 more

Monique Laurent is a Tilburg University professor and senior researcher at CWI (Centrum Wiskunde & Informatica), focusing on discrete mathematics and optimization . Her work bridges algebra, geometry, and computer science to solve complex combinatorial and polynomial optimization problems. Part-time full professor at Tilburg University (since 2009) Group leader of Networks and Optimization at CWI (2005-2016) Current member of CWI Management Team Research Focus: Semidefinite programming hierarchies, noncommutative polynomial optimization, quantum information theory, and matrix factorization. Her recent work explores applications in quantum entanglement , graph parameters , and combinatorial data analysis . Key Publications: 15+ articles from 2017-2024 address topics like copositive matrices , sum-of-squares convergence , and hypergraph optimization . Collaborations span institutions in the Netherlands, France, Germany, and the U.S. Awards: 2023 Khachiyan Prize SIAM Fellow (2017) KNAW member (2018) EUROPT Fellow (2021) Grants & Projects: Leads EU-funded initiatives TENORS (2024) and POEMA (2019), with prior NWO and Marie Curie grants. Organizes international workshops on polynomial optimization and quantum information.

Lex SchrijverView profile

Professor

• Discrete Mathematics
• Optimization
• Algorithms
• +3 more

Lex Schrijver is a Professor of Mathematics at the University of Amsterdam since 1990 and a CWI-Fellow at Centrum voor Wiskunde en Informatica (CWI) since 1989. His research focuses on discrete mathematics, optimization, and algorithms, with significant contributions to graph theory, combinatorics, and coding theory. Research Interests: Discrete Mathematics, Optimization, Algorithms, Graph Theory, Combinatorics, Coding Theory. Awards: EURO Gold Medal (2015) Honorary Doctorate from Eotvos Lorand University (2011) Franz Edelman Award (2008) SIGMA Prize (2008) John von Neumann Theory Prize (2006) Spinoza Prijs (2005) Ridder in de orde van de Nederlandse Leeuw (2005) Lanchester Prize (2004, 1986) Fulkerson Prize (2003, 1982) Van Dantzig Prize - SIAM / MPS (2003) Eredoctoraat from University of Waterloo (2002) Projects: Involved in the Networks project, funded by the Netherlands Organisation for Scientific Research (NWO). Professional Activities: Fellow of the American Mathematical Society (AMS) and SIAM.