جست‌وجوی استاد و پژوهشگر

Ashish Cherukuriمشاهده پروفایل

دانشیار

• Optimization
• Control Systems
• Multi-agent Systems
• +۷ مورد دیگر

Ashish Cherukuri is an Associate Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Optimization and Decision Systems group. His research focuses on optimization-based control, game theory, and multi-agent systems applied to energy, transportation, and robotics. He holds a Ph.D. from UC San Diego and postdoctoral experience at ETH Zurich. Education: Ph.D., University of California, San Diego (2012–2017) M.Sc., ETH Zurich (2008–2010) B.Tech, Indian Institute of Technology Delhi (2004–2008) Research Interests: Data-driven optimization, distributed algorithms, networked cyber-physical systems, and uncertainty handling in energy and transportation systems. Recent work emphasizes stochastic optimization, game-theoretic routing, and risk-aware control. Awards: Robert E. Skelton Dissertation Award (2017) Outstanding Graduate Student Award (2016) Focht-Powell Fellowship (2012–2015) Grants & Service: Editor for the IEEE Control Systems Society, organizer of Energy-Open 2019, and member of professional societies (IEEE, INFORMS, SIAM). Active in conference organization and academic leadership roles. Labs/Teams: Part of the Jan C. Willems Center for Systems and Control and the Engineering and Technology Institute Groningen (ENTEG). Research integrates theoretical advancements with practical applications in energy networks and smart systems.

Rob Goverdeمشاهده پروفایل

استاد

• Railway Traffic Management
• Operations Research
• Transportation Systems Optimization
• +۴ مورد دیگر

Prof. Rob Goverde is a Professor of Railway Traffic Management & Operations at the Department of Transport & Planning, TU Delft, and Director of the Digital Rail Traffic Lab. He holds a PhD in Railway Operations (2005) from TU Delft and an MSc in Mathematics from Utrecht University (1993). His research focuses on resilient railway timetabling, disruption management, energy-efficient train control, and railway safety. He teaches MSc courses like 'Railway Operations and Control' and coordinates the MSc Annotation Railway Systems and a collaborative BSc program with Beijing Jiaotong University. Research interests include railway operations optimization using operations research, max-plus algebra, and data analytics. Projects funded by Shift2Rail, NSFC, and NWO address topics like high-speed rail network capacity and resilient railway systems. He leads the Railway Systems theme at TU Delft Transport Institute and serves as Editor-in-Chief of the Journal of Rail Transport Planning & Management. His work bridges mathematical methodologies with railway domain knowledge to enhance system performance and sustainability.

Anna Wilbikمشاهده پروفایل

استاد

• Data Fusion
• Intelligent Interaction
• Fuzzy Logic
• +۴ مورد دیگر

Anna Wilbik is a Professor in Data Fusion and Intelligent Interaction at the Department of Advanced Computing Sciences, Faculty of Science and Engineering, Maastricht University (The Netherlands). Her research bridges data understanding and human-machine synergy in complex systems, focusing on multi-criteria decision making, explainable AI, and data fusion techniques. PhD in Computer Science (with honors), Systems Research Institute, Polish Academy of Science (2010) Postdoctoral Fellow, University of Missouri (2011) Stanford University TOP500 Innovators Program Alumnus Research Pillars: Intelligent human-machine interaction for joint decision making Data fusion methods for heterogeneous data integration Contextualized multi-criteria decision frameworks Fuzzy logic and linguistic summaries for explainability Federated learning systems Article Trends: Recent work focuses on intuitionistic fuzzy sets for knowledge-intensive processes, federated learning with uncertainty handling, and linguistic summarization techniques for interpretable AI. She actively explores explainability , collaborative business models , and driver behavior analysis through attention-based models. Professional Leadership: Vice-chair of IEEE Fuzzy Systems Technical Committee Organizer of IEEE World Congress on Computational Intelligence (2024)

Jun Huمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Social Computing
• Design Research
• +۸ مورد دیگر

Dr. Jun Hu is an Associate Professor in Design Research on Social Computing at the Department of Industrial Design, Eindhoven University of Technology (TU/e). He serves as the Scientific Director for the Engineering Doctorate program in Designing Human-System Interaction and is the chair of the working group "Aesthetics and empowerment" of IFIP TC14. Additionally, he holds positions as a Distinguished Adjunct Professor at Jiangnan University and a Guest Professor at Zhejiang University. Dr. Hu earned his Ph.D. degree in Interaction Design and an Engineering Doctorate degree in User-system Interaction, both from TU/e. He also holds a B.Sc degree in Mathematics and an M.Eng degree in Computer Science. He is a System Analyst and a Senior Programmer with qualifications from the Ministry of Human Resources and Social Security, and the Ministry of Industry and Information Technology of China. His research focuses on the intersection of Human-Computer Interaction, Social Computing, and Design Research, with particular interests in data physicalization, empowering systems, and health informatics. Dr. Hu's work explores how technology can be designed to support human needs in social contexts, with applications in health, stress management, and physical activity motivation. His approach often combines aesthetic considerations with functional design to create systems that empower users. Analysis of Dr. Hu's recent publications reveals a strong focus on data physicalization, social aspects of personal informatics, and health applications of interactive systems. His work spans from theoretical frameworks for understanding user interaction with physicalized data to practical applications in stress management for children and motivation for physical activity. There's a clear trend toward integrating AI capabilities into human-centered design approaches while maintaining a focus on user empowerment. Senior Member of ACM Distinguished Adjunct Professor at Jiangnan University Guest Professor at Zhejiang University Editor-in-chief for EAI Endorsed Transactions on Pervasive Health and Technology Associate editor for Behaviour & Information Technology and Entertainment Computing Editor for the International Journal of Arts and Technology Dr. Hu has supervised numerous students through the Engineering Doctorate program and has been involved in various research grants, particularly in the areas of health technology and human-system interaction. He has served in leadership roles including head of the Designed Intelligence group at ID TU/e from 2015-2017 and currently chairs the working group "Aesthetics and empowerment" of IFIP TC14. He coordinates the TU/e DESIS Lab in the DESIS Network and serves on multiple editorial boards. Dr. Hu is actively involved with the Design Of Empowering Systems research group and the EAISI Health initiative at TU/e. His work often involves interdisciplinary collaboration across computer science, design, and healthcare domains, focusing on creating systems that empower users through thoughtful integration of technology into everyday contexts. He also serves as Chairman of the Foundation for Design Promotion in Europe and China and is a board member of the International Chinese Association of Computer Human Interaction (ICACHI).

Daniel Fruminمشاهده پروفایل

استادیار

• Logic
• Type Theory
• Program Verification
• +۵ مورد دیگر

Daniel Frumin is an Assistant Professor in the Department of Fundamental Computing Science at the University of Groningen, affiliated with the Bernoulli Institute. His research focuses on Logic, Type Theory, and Program Verification, with a particular emphasis on formal methods for concurrency, type systems, and homotopy type theory. He has contributed to foundational work in denotational semantics, modular programming language design, and mechanized verification of concurrent systems. His expertise includes the application of logical frameworks to concurrency models, such as ReLoC (Relational Logic for Concurrent Programming) and the integration of type theories with operational semantics. Recent work explores guarded interaction trees, interval domains in homotopy type theory, and compositional security properties for fine-grained systems. Frumin has published extensively in top-tier venues like ESOP, CONCUR, and ACM POPL, with peer-reviewed contributions on topics ranging from bunched implications in session-based concurrency to formal verification of data structures like concurrent queues. His research often bridges theoretical computer science and practical formal verification, leveraging tools like Coq for mechanized proofs. Collaborations include projects with institutions such as Aarhus University (Denmark) and the University of Bologna, focusing on univalent foundations, categorical semantics, and security verification. His work is supported by grants from the Dutch Research Council (NWO) and industry partnerships like Meta's Folly Library verification efforts. Labs/Teams: Active contributor to the Bernoulli Institute's Formal Methods Group and the Univalent Foundations initiative. His research group specializes in applying type-theoretic and categorical methods to concurrency and verification challenges.

Emilia Barakovaمشاهده پروفایل

دانشیار

• Social Robotics
• Cognitive Robotics
• Artificial Intelligence
• +۳ مورد دیگر

Emilia Barakova is an Associate Professor at the Industrial Design Department of Eindhoven University of Technology. She leads the Social Robotics Lab and Transdisciplinary Research & Design cluster, focusing on robotics for autism intervention and cognitive assistance. PhD in Mathematics & Natural Sciences (University of Groningen, 1999) MSc in Electronics & Automation Engineering (Technical University of Sofia, Bulgaria) Her research merges robotics, cognitive science, and AI to develop embodied agents for social skills training in autistic children and well-being enhancement for people with disabilities. She co-developed the TiViPE programming environment for customizable robot therapy scenarios. Key publication trends show emphasis on: Human-robot interaction for autism therapy Emotion recognition via movement analysis Visual programming frameworks for robot customization Multi-agent systems in social training She serves as Associate Editor for journals including International Journal of Social Robotics and Transactions of Human-Machine Systems , and has held academic positions at RIKEN Brain Science Institute and German-Japanese Robotics Research Lab.

Bert de Vriesمشاهده پروفایل

استاد

• Bayesian Machine Learning
• Signal Processing
• Biomedical Applications
• +۳ مورد دیگر

Bert de Vries is a Professor at the Signal Processing Systems Group at Eindhoven University of Technology (TU/e), where he has been employed since January 2012. He maintains a dual career, also working at GN Hearing in the hearing aids industry since April 1999, where he holds both research and managerial roles. His academic journey began at TU/e, where he earned his MSc in Electrical Engineering in 1986, followed by a PhD from the University of Florida in 1991. Between 1992 and 1999, he worked at Sarnoff Research Center in Princeton, NJ, contributing to diverse signal and image processing projects. Professor de Vries's research centers on Bayesian Machine Learning, with particular focus on the Free Energy Principle and its applications to engineering problems. His work bridges theoretical neuroscience with practical signal processing systems, especially in biomedical applications. He directs the BIASlab research team at TU/e, which develops probabilistic programming tools including RxInfer.jl, ForneyLab.jl, GraphPPL.jl, ReactiveMP.jl, and Rocket.jl. His research spans active inference, variational message passing, probabilistic programming, and Bayesian neural networks, with applications ranging from hearing aids to multi-agent systems. Analysis of his recent publications reveals a strong trend toward practical implementations of Bayesian inference frameworks, particularly through Julia-based probabilistic programming tools. His work shows increasing focus on active inference applications, message passing algorithms, and the intersection of Riemannian geometry with probabilistic modeling. The research demonstrates consistent progression from theoretical foundations toward real-world engineering applications, particularly in biomedical signal processing and autonomous systems. Professor de Vries teaches a graduate-level course on Bayesian Machine Learning at TU/e and actively contributes to open-source software development through his GitHub profile (bertdv), with recent activity as recent as August 2025. His research team has developed several influential probabilistic programming libraries that have gained significant attention in the machine learning community. The BIASlab research group continues to advance the state of the art in Bayesian inference methods with applications in hearing technology, robotics, and signal processing.

Thijs van Edeمشاهده پروفایل

استادیار

• Cybersecurity
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Thijs van Ede serves as an Assistant Professor in the Semantics, Cybersecurity and Services research group at the University of Twente's Faculty of Electrical Engineering, Mathematics and Computer Science. His academic work centers on security automation through machine learning and AI integration, with specialized expertise in large language models for intrusion detection systems and anomaly analysis in rapidly evolving network environments. His research program bridges theoretical AI advancements with practical cybersecurity applications, focusing on contextual security analysis using deep neural networks and Natural Language Processing techniques for cyber threat intelligence sharing. This work manifests in open-source tool development emphasizing collaborative science, including frameworks for encrypted traffic analysis and security event log interpretation. Recent publications demonstrate consistent innovation in applying deep learning to network security challenges, particularly through the DeepCASE (2022) and FlowPrint (2020) frameworks that address anomaly detection in security logs and mobile application fingerprinting respectively. These works establish patterns in leveraging sequential data analysis for real-time threat identification. Through active mentorship of the Twente Hacking Squad student team, he cultivates next-generation cybersecurity talent via Capture The Flag competitions while maintaining research infrastructure through open-source security tools. His academic service includes developing accessible research implementations that bridge theoretical concepts and operational security solutions. As a core member of the Semantics, Cybersecurity and Services research group, he contributes to the University of Twente's Digital Society Institute initiatives, focusing on deployable AI security systems that operate effectively in dynamic enterprise environments. His work maintains strong connections between academic research and practical security operations through toolchain development and student engagement.

Jacquelien Scherpenمشاهده پروفایل

استاد

• Automation & Control Systems
• Nonlinear Control Systems
• Smart Energy Systems
• +۳ مورد دیگر

Jacquelien Scherpen is a Professor at the University of Groningen, currently serving as Rector Magnificus. She holds a position in the Engineering and Technology institute Groningen (ENTEG) within the Faculty of Science and Engineering. Her academic journey includes a PhD in Applied Mathematics from the University of Twente (1994) and post-doctoral roles at Delft University of Technology before joining Groningen in 2006. She has been a leader in systems and control research, with roles as Scientific Director of ENTEG (2013–2019) and Director of the Groningen Engineering Center (2016–2023). Her research focuses on model reduction, nonlinear control, smart energy systems, and distributed control applications in smart grids. Key achievements include the Automatica Best Paper Prize (2020), Knight of the Order of the Netherlands Lion (2019), and the Prince Friso Engineer of the Year Award (2023). She has held leadership roles in organizations like the European Control Association (EUCA) and is a Fellow of IEEE. Her professional activities include editorial roles in journals like the IEEE Transactions on Automatic Control and the International Journal of Robust and Nonlinear Control. She has organized major conferences, including the European Control Conference (ECC) 2021 and 2023. Her work bridges theoretical advancements with practical applications, emphasizing sustainability and engineering innovation.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Optimization
• +۷ مورد دیگر

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. 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.

Roel Blooمشاهده پروفایل

مدرس

• Computer Science
• Theoretical Computer Science
• Formal Methods
• +۲ مورد دیگر

Roel Bloo is a University Lecturer in the Department of Mathematics and Computer Science at Eindhoven University of Technology. His research group focuses on Algorithms and Logics for Verification. His research spans theoretical computer science with emphasis on: Formal methods and verification techniques Lambda calculus and type systems Computational logic and term rewriting Explicit substitution models Publications (2001-2012) demonstrate consistent specialization in foundational aspects of computer science, particularly formal semantics of programming languages, type theory implementations, and equivalence proofs in computational systems. Teaching responsibilities include courses in Discrete Mathematics, Logic and Set Theory, and Automata Theory.

G. Caltaisمشاهده پروفایل

استادیار

• Concurrency Theory
• Causal Models
• Knowledge Models
• +۴ مورد دیگر

G. Caltais is an Assistant Professor in the Formal Methods and Tools (FMT) group at the University of Twente's Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). Previously, they worked as an independent junior scientist at the University of Konstanz (Chair for Software and Systems Engineering) and as a post-doctoral researcher at ETH Zürich (Chair of Software Engineering). They hold a PhD from Reykjavík University and Radboud University. Research Focus: Formal modeling of computer systems, emphasizing automata theory, concurrency, causal/knowledge models, and software-defined networks (SDNs). Current projects include DyNetKAT (formal SDN analysis), Zorro (zero downtime knowledge models), and exploring cyclic structures in software correctness. Committees: Served on program committees for CALCO 2023, ESOP 2023, FORTE 2022-2023, FSEN 2023-2025, IEEE NFV-SDN 2020-2022, SPIN 2022-2024, and others. Organized events like CREST@ETAPS 2019/2023 and EXPRESS/SOS 2023. Student Projects: Offers B.Sc./thesis proposals on DyNetKAT visualization, causal analysis of SDN safety violations, and learning formal network models from real datasets. Contact for custom project ideas.

• 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.

• Hydrogeology
• Groundwater
• Stochastic Modelling
• +۱۶ مورد دیگر

Dr. Alraune Zech is an Assistant Professor for Computational Environmental Hydrogeology at Utrecht University, Faculty of Geosciences, Department of Earth Sciences, Hydrogeology group. Her research focuses on groundwater flow and transport processes in heterogeneous environments, with emphasis on practical applications in contaminated aquifers, PFAS remediation, and construction-related groundwater issues. She is affiliated with the Helmholtz-Centre for Environmental Research and serves as convener for EGU sessions on contaminant transport. Dr. Zech's educational background includes: PhD in Computational Hydrosystems from Friedrich-Schiller-University Jena and Helmholtz-Centre for Environmental Research (2010-2013) Prediploma Degree in Business Mathematics from University Leipzig (2011) Diploma in Mathematics with minor in Chemistry from University Leipzig (2003-2009) Her research interests span hydrogeology, groundwater modeling, and environmental remediation. She specializes in stochastic and computational modeling of subsurface processes, with focus on contaminated aquifers, PFAS removal strategies, biodegradation, bioremediation, and heat transport in the subsurface. Her work bridges theoretical approaches with practical applications in construction engineering and environmental protection. Analysis of Dr. Zech's recent publications (2021-2025) reveals strong focus on advancing hydrogeological modeling techniques, particularly in aquifer heterogeneity characterization, machine learning applications in hydrogeology, and practical remediation strategies. Her work spans fundamental research on pore-scale processes to field-scale applications, with increasing integration of artificial intelligence methods for solving complex groundwater problems. Dr. Zech leads several significant research projects: Living Lab PFAS Remediation (2024-2028): Developing strategies for PFAS contamination SilPit (2024-2028): Studying erosion of silicate grouting in construction pits MIBIREM (2022-2027): Creating innovative technological toolbox for bioremediation She actively supervises multiple PhD students including Alexandra Hockin, Kim Bartsch, Mahammad Valibeknejad, Sona Aseyednezad, Hannah Gebhardt, and Martijn van Leer. Her research is supported by funding from the Ministry of Infrastructure and Water Management, NWO, and EU Horizon programs.