جستجوی استاد راهنمای دانشگاهی

Jan Draismaمشاهده پروفایل

استاد

• Algebraic Geometry
• Combinatorics
• Algebraic Statistics
• +۸ مورد دیگر

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.

Rudi A. Pendavinghمشاهده پروفایل

استادیار

• Combinatorics
• Matroid Theory
• Graph Theory
• +۳ مورد دیگر

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.

• Lattice Algorithms and Geometry of Numbers
• Linear and Integer Programming
• Extended Formulations
• +۳ مورد دیگر

Daniel Dadush is a part-time Professor of Geometry of Optimization at Utrecht University and leads the Networks & Optimization group at Centrum Wiskunde & Informatica (CWI). He has held previous positions as a Simons Postdoctoral Fellow at the Courant Institute of Mathematical Sciences (New York University) and a PhD in the ACO program (Algorithms, Combinatorics, and Optimization) at Georgia Tech. Research Interests: Lattice Algorithms, Geometry of Numbers, Linear/Integer Programming, Extended Formulations, Discrepancy Theory, Convex Optimization, Asymptotic Convex Geometry. Awards: Van Dantzig Prize (2020), Best Paper Award at CCC'20 (2020), Tucker Prize (2015). Advising: Supervised PhD/MSc students including Ben Bals, Samarth Tiwari, Sander Borst, Sophie Huiberts, Huck Bennett, and Yilin Li. Recent Publications: His 15 most recent articles focus on strongly polynomial algorithms, exact integer programming, convex optimization in the oracle model, matrix discrepancy, circuit diameter bounds, and integrality gaps, spanning journals and conferences like STOC, SODA, FOCS, and Mathematical Programming. Professional Activities: Organizer of the Dutch Day on Optimization (2022), co-organizer of workshops on Discrepancy Theory, Lattices, and Discrete Optimization at institutions like HIM Bonn and the Simons Institute. Served on program committees for STOC 2025, SODA 2024, and other major conferences. Teaching: Lectured on Interior Point Methods, Straight-Line Complexity, and courses in Continuous Optimization at Utrecht University and Mastermath.

• Artificial Intelligence
• Smart and Service Industry
• Mobility and Transport
• +۵ مورد دیگر

Marco Schutten is an Associate Professor at the Digital Society Institute of the University of Twente, affiliated with the Industrial Engineering & Business Information Systems department. His work bridges Artificial Intelligence , Transportation , and Operations Research , focusing on optimizing complex systems. Expert in Urban Logistics and Freight Transport Specializes in Mathematical Programming and Optimization Research interests include Vehicle Routing , Machine Scheduling , and Agent-Based Simulation . Key trends in his 15 most recent articles (2015–2025) involve: Dynamic scheduling under time constraints Urban logistics and smart city applications Heuristics for combinatorial optimization Integration of MILP and Simulation models No scientific awards, formal supervisory roles, or part-time appointments are explicitly mentioned.

Wan Fokkinkمشاهده پروفایل

استاد

• Distributed Systems
• Formal Analysis of Protocols
• Concurrency Theory
• +۳ مورد دیگر

Prof. Wan Fokkink is a Full Professor in Theoretical Computer Science at Vrije Universiteit Amsterdam (VU) and holds a part-time position as Professor of Model-Based System Engineering at Eindhoven University of Technology (TU/e). His research focuses on distributed systems, formal analysis of protocols, and supervisory control synthesis. He leads the Theoretical Computer Science group at VU and has authored three influential textbooks: Introduction to Process Algebra , Modelling Distributed Systems , and Distributed Algorithms: An Intuitive Approach . Education: MSc in Mathematics (University of Amsterdam, 1990) and PhD in Computer Science (University of Amsterdam, 1994). Postdoctoral work at Utrecht University and lectureship at Swansea University preceded his leadership roles at CWI (2001–2004) and VU (since 2004). Teaching includes courses on logic, concurrency, and distributed algorithms. He is editor of Logical Methods in Computer Science and co-founder of the Electronic Proceedings in Theoretical Computer Science . Active in professional organizations: co-founder of IFIP WG 1.8 (Concurrency Theory) and steering committee member of the CONCUR conference. Research interests span formal verification, concurrency theory, and practical applications of supervisory control in engineering systems (e.g., traffic management, ship locks). His work aligns with sustainable development goals through contributions to reliable system design and optimization. Recent articles explore model-based specification, distributed control under communication delays, and tools like Eclipse ESCET for supervisory control synthesis. Collaborations span international teams in Europe and beyond.

Christopher Hojnyمشاهده پروفایل

استادیار

• Mixed-Integer Programming
• Symmetry Handling in Optimization
• Combinatorial Optimization
• +۳ مورد دیگر

Christopher Hojny is an Assistant Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology , specializing in combinatorial optimization. He contributes to the EAISI Foundational group and co-develops the academic solver SCIP . His research focuses on symmetry handling in mixed-integer programming , theoretical properties of integer programs, and algorithm development for combinatorial optimization. Recent work explores applications in graph neural network verification , clustering problems, and network coding through mixed-integer programming frameworks. Key publication trends show expertise in Symmetry detection and mitigation techniques Relaxation complexity theory Applications to machine learning robustness Decision diagram-based scheduling Scientific contributions include Proof systems for symmetry certification Topological bounds tightening in GNNs Stable set problem symmetry handling SCIP solver extensions He supervises PhD students Cédric Roy (NWO project on Local Symmetries) and Sten Wessel (co-supervised with Frits Spieksma), while Jasper van Doornmalen (2019-2023) investigated symmetry propagation algorithms.

• Operations Research
• Scheduling Algorithms
• Integer Linear Programming
• +۳ مورد دیگر

Gerhard F. Post is an Assistant Professor specializing in Mathematics of Operations Research. His work focuses on algorithmic solutions for scheduling and optimization problems, particularly in healthcare and educational contexts. He contributes to the UN Sustainable Development Goals through research addressing complex operational challenges. Research interests include personnel scheduling, integer linear programming, and timetabling systems. His work bridges theoretical models with real-world applications, such as nurse rostering and compliance with labor regulations. Recent studies involve service planning processes and shift design optimization using advanced mathematical frameworks. Key contributions include a unified nurse rostering model and analyses of Dutch labor law inconsistencies. His research has been disseminated through peer-reviewed journals like Annals of Operations Research and conference proceedings such as PATAT. Active in academic discourse, he has presented on topics ranging from sports tournament scheduling to harmonious personnel scheduling strategies.

Ilker Birbilمشاهده پروفایل

استاد

• Optimization Methods
• Data Science
• Decision Making
• +۳ مورد دیگر

Prof. Dr. Ilker Birbil is a Professor of AI & Optimization Techniques for Business & Society at the University of Amsterdam (UvA), affiliated with the Amsterdam Business School's Business Analytics section. He previously held professorships at Erasmus University and Sabancı University, focusing on optimization and data science. His research interests include interpretable machine learning, data privacy, and optimization methods in decision-making. Education: PhD in Operations Research from North Carolina State University Postdoc at Erasmus Research Institute of Management (ERIM), Netherlands Research Interests: Optimization in data science, interpretable AI, privacy-preserving algorithms, and decision-making systems. Recent work focuses on differentially private optimization and meta-learning techniques like LESS. Key Achievements: Recipient of multiple teaching awards at Sabancı University Affiliated researcher at OPTIMAL (Optimization for and with Machine Learning) Organized workshops on ML for optimization and mathematics of ML Grants & Teams: Leads the UvA group on Optimization and Machine Learning at LNMB. Collaborates on projects blending OR and ML, including privacy-aware algorithms and revenue management systems. Labs/Teams: OPTIMAL, UvA Optimization Group, and interdisciplinary teams in data analytics.

• Chemical Engineering
• Sustainable Chemistry
• Process Technology
• +۵ مورد دیگر

Aloysius G.J. van der Ham is a Lecturer in Sustainable Process Technology, focusing on chemical engineering and sustainable chemistry. His research bridges fundamental thermodynamics with industrial applications, particularly in renewable energy integration and resource-efficient processes. Research Focus: Dr. van der Ham investigates sustainable chemical transformations, including electrified hydrocarbon production, hydrogen storage via liquid organic carriers, ionic liquid-based metal extraction, and carbon capture optimization. His work emphasizes: Electrification of industrial processes (ethylene/propylene production) Advanced membrane reactor designs Economic feasibility of renewable technologies Thermodynamic modeling of separation systems Publication Trends: Recent articles (2023-2025) demonstrate a consistent focus on decarbonizing chemical manufacturing through electrification, membrane-assisted reactions, and circular resource recovery. Key themes include techno-economic analysis of sustainable processes and thermodynamic optimization for energy systems. Supervision: He has guided 5 research projects, though specific student names or grant details are unavailable in this profile.

• Electric Power Distribution
• Load Profile Analysis
• Distribution Systems
• +۵ مورد دیگر

Mauricio Salazar Duque serves as a University Researcher in the Department of Electrical Energy Systems within the School of Electrical Engineering at Eindhoven University of Technology (TU/e). His work focuses on modernizing power distribution infrastructure through advanced computational techniques. His research expertise spans critical domains in electrical grid modernization: Electric Power Distribution & Load Profile Analysis Distribution System Optimization & Photovoltaics Integration Community Energy Storage & Reinforcement Learning Applications His publications consistently address UN Sustainable Development Goals related to affordable clean energy and climate action. Recent work demonstrates strong emphasis on data-driven modeling for grid resilience. Analysis of his 2023-2025 publications reveals a strategic shift toward generative AI for load profile synthesis and tensor-based mathematical formulations for multidimensional grid analysis. Key themes include handling PV integration challenges in low-voltage networks and developing visualization techniques for medium-voltage load anomalies. No scientific awards are documented in available records. He contributed to the 2018-2022 project 'Decentrale Optimalisatie en Sturing van Elektriciteitsdistributienetten' as a research member and supervised at least one Master's thesis on transfer learning for medium-voltage network measurements. His research collaborations extend through TU/e's press engagements including National Growth Fund initiatives and mobility systems workshops. Salazar Duque operates within TU/e's Electrical Energy Systems research group, collaborating with Prof. J.G. Slootweg and international partners on smart grid innovation projects.

Eric Verbeekمشاهده پروفایل

پژوهشگر

• Process Mining
• Process Models
• Process Discovery
• +۳ مورد دیگر

H.M.W. (Eric) Verbeek is an ICT Developer in the Department of Mathematics and Computer Science at Eindhoven University of Technology, specializing in Process Analytics. His work focuses on advancing process mining techniques, standardization of event data (e.g., IEEE XES), and the development of tools like ProM and CPN IDE. He has contributed to over 160 publications since 1986, with recent research emphasizing process discovery algorithms, workflow net synthesis, and context-rich process modeling. Research Interests include Process Mining, Process Models, Process Discovery, Petri Net Analysis, and Workflow Management. He has actively participated in projects like the GDPR compliance toolkit and has been involved in defining standards for event data interoperability. Notable contributions include the IEEE XES standard for process mining, tools for event log generation and analysis, and methods for decomposed conformance checking. His work bridges theoretical advancements in process modeling with practical tool development, supporting both academia and industry applications. Collaborations span international academia, focusing on process mining workflows and compliance monitoring. His research trends highlight a balance between algorithmic innovation and real-world applicability in areas like healthcare, logistics, and service management.

• Mathematical Programming
• Correspondence Analysis
• Hierarchical Clustering
• +۷ مورد دیگر

Rick Willemsen is a Lecturer in the Department of Econometrics at the Erasmus School of Economics, Erasmus University Rotterdam. His academic work lies at the intersection of mathematical programming, statistical data analysis, and computational optimization. Research Interests: His primary research focuses on correspondence analysis, hierarchical clustering, and dimension reduction techniques. He employs mathematical and mixed integer programming to develop exact and inverse solutions for statistical problems involving categorical data and contingency tables. His methodological contributions aim to improve the accuracy and interpretability of clustering and dimensionality reduction methods in econometric and data science applications. Publication Trends: Over recent years, Rick has published on exact algorithms for hierarchical clustering, uniqueness conditions in correspondence analysis, and novel optimization approaches for inverse problems. His research consistently integrates theoretical rigor with practical computational implementation, as evidenced by both journal articles and software outputs. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: There is no public information available on students advised or grants received. However, his recent completion of a doctoral thesis suggests he is in the early stage of his independent academic career. Labs and Research Teams: Rick Willemsen collaborates closely with researchers such as Michel van de Velden and Willem van den Heuvel, likely within the Data Science or Quantitative Methods group at Erasmus School of Economics. His work appears to be part of a broader effort in developing optimization-based tools for statistical data analysis.

• Operations Research
• Stochastic Programming
• Mixed-Integer Optimization
• +۷ مورد دیگر

Ruben van Beesten is an Assistant Professor in the Department of Econometrics at the Erasmus School of Economics, Erasmus University Rotterdam. He also holds an adjunct professorship at the Norwegian University of Science and Technology since September 2023, reflecting his international academic engagement and collaborative research. His research lies at the intersection of operations research, mathematical optimization, and applied economics. His primary interests include distributionally robust optimization, stochastic programming with integer recourse, error bounds in convex approximations, and energy system modeling. His work combines theoretical rigor with practical applications, particularly in energy markets and decision-making under uncertainty. The recent publications of Ruben van Beesten demonstrate a consistent focus on improving the tractability and accuracy of two-stage mixed-integer recourse models. His work spans theoretical developments in error bounds and parametric analysis, algorithmic improvements for energy system design, and market-level applications such as interconnector capacity incentives. The research trends highlight a strong emphasis on computational optimization, risk-averse decision frameworks, and the integration of robust methods in real-world systems. His scientific contributions are recognized through publications in top-tier journals such as SIAM Journal on Optimization , Computational Optimization and Applications , and Energy . While no formal awards are listed in the provided text, his active publication record and external collaborations indicate a growing academic impact. Ruben van Beesten collaborates with prominent researchers such as Ward Romeijnders, Kees Jan Roodbergen, and Asgeir Tomasgard. His research involves both theoretical grants in optimization methodology and applied projects in energy systems, suggesting involvement in funded interdisciplinary initiatives, though specific grants are not detailed. He has co-authored multiple peer-reviewed articles and a doctoral thesis, indicating a strong research trajectory. He is actively involved in a research network focused on optimization under uncertainty, with strong ties to institutions in Norway and the Netherlands. His work contributes to both academic and practical advancements in energy modeling and stochastic programming, positioning him within a dynamic and impactful research community.

Rob van der Meiمشاهده پروفایل

استاد

• Stochastic Operations Research
• Queueing Theory
• Emergency Response Systems
• +۱۷ مورد دیگر

Rob van der Mei is a Distinguished Full Professor (part-time) at Vrije Universiteit Amsterdam and a Principal Researcher and Manager R&D at Centrum Wiskunde & Informatica (CWI), where he leads research at the intersection of theory and application in Stochastic Operations Research. His work spans emergency response systems, logistics, healthcare, telecommunications, and cybersecurity. He is the chair of the European COST Action ACROSS and co-founder of the spin-off Stokhos Emergency Mathematics. PhD in Stochastic Operations Research – Vrije Universiteit Amsterdam Senior Researcher – AT&T Labs, USA (1995–1999) Senior Researcher – KPN Research (1999–2002) Senior Researcher – TNO ICT (2002–2004) His research focuses on applying mathematical modeling, queueing theory, and data analytics to optimize complex systems. Key areas include emergency response, service logistics, healthcare optimization, and machine learning in telecommunications. He has led numerous projects on data-driven decision-making in healthcare, such as suicide prevention helplines and elderly care systems, and in maritime design under energy transition uncertainty. The most recent publications reflect a strong trend toward interdisciplinary and socially impactful research, combining optimization, machine learning, and real-time decision systems. Topics include mobile stroke unit deployment, AI-assisted counseling, cyber anomaly detection, and energy-efficient ship design. These works highlight his expertise in translating theoretical models into practical tools. Harald W. Kuhn Award 2020 (2021) Huibregtsen Award 2021 First prize for logistic innovation in Covid-19 vaccination strategy (2021) Best-paper award, 8th International Conference on Data Analytics (2019) Runner-up Huibregtsen-prijs 2014 Rob van der Mei has secured extensive external funding from NWO, EU COST, and industry partners for projects in healthcare logistics, emergency systems, and digital infrastructure. He advises PhD students and collaborates widely across academia and industry. He leads major initiatives such as DOLCE VITA, COCONUT, and ACROSS, and is an active keynote speaker and invited lecturer on data science and optimization. He is affiliated with the Stochastics group at CWI, where he supervises researchers and contributes to national and international research strategy.

Berry Schoenmakersمشاهده پروفایل

دانشیار

• Cryptography
• Secure Computation
• Algorithms
• +۳ مورد دیگر

Berry Schoenmakers is an Associate Professor at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). He specializes in Cryptography and Secure Computation, with a focus on cryptographic protocols, secure multiparty computation, and algorithm design. His research integrates theoretical foundations with practical implementations, particularly in secure arithmetic operations and numerical methods. He teaches courses including Set theory and algebra , Programming and modelling , Basic linear algebra , and Cryptographic Protocols . His recent work emphasizes advancements in threshold cryptography, fixed-point arithmetic for secure computation, and efficient GCD algorithms. Collaborations include co-authorship with researchers like Stan Korzilius and Toon Segers on topics ranging from secure group protocols to trigonometric function implementations in cryptographic contexts. No ancillary activities or scientific awards are listed in the provided information.