جست‌وجوی استاد و پژوهشگر

James Townsendمشاهده پروفایل

پژوهشگر

• deep generative models
• lossless compression
• unsupervised learning
• +۴ مورد دیگر

James Townsend, also known as Jamie, is a machine learning researcher at the Amsterdam Machine Learning Lab (AMLab) within the Informatics Institute at the University of Amsterdam. He completed his PhD in 2020 at the UCL AI Centre in London under the supervision of Professor David Barber. His educational background includes a PhD in lossless compression with latent variable models from University College London, with prior research contributions to the Autograd library and early development of JAX during a Google Brain internship in 2018. Townsend's research centers on deep generative models and lossless compression, extending to unsupervised learning, approximate inference, Monte Carlo methods, optimization, and machine learning software systems. His work bridges theoretical information theory with practical implementation, particularly in neural compression techniques. He has significantly contributed to open-source tools including Autograd and JAX, demonstrating expertise in automatic differentiation systems. His publication record spans high-impact venues like NeurIPS, ICLR, and ICML, with recent work focusing on innovative compression paradigms for complex data structures including graphs and multisets. Key contributions include shuffle coding, reversible programming for compression verification, and multiset compression techniques that challenge conventional approaches. Scientific recognition includes: Best Paper Award at Deep Generative Models and Downstream Applications Workshop (2021) Townsend actively participates in the research community through invited talks at Stanford's Information Theory Forum and the Languages for Inference workshop. His collaborations span academic institutions and industry partners like Google Brain, with current work centered on advancing lossless compression through deep learning at the AMLab. He maintains an active open-source presence via GitHub (@j-towns) and technical discourse on Twitter (@_j_towns), while publishing through Google Scholar under his formal name James Townsend.

Jorn van der Polمشاهده پروفایل

مدرس

• Matroid Theory
• Combinatorics
• Discrete Mathematics
• +۳ مورد دیگر

Jorn van der Pol is a Lecturer in the Department of Mathematics of Operations Research. His research focuses on matroid theory, combinatorics, and discrete mathematics, with notable contributions to the study of matroid enumeration, properties of matroids, and their applications in graph theory and optimization. His work often intersects with extremal combinatorics, hypergraph structures, and algorithmic enumeration techniques. Key research interests include Turán densities in hypergraphs, binary geometries, and the analysis of matroid minors. Recent collaborations explore the interplay between matroid theory and stochastic simulation methods. His publications span prestigious journals such as SIAM Journal on Discrete Mathematics and the Electronic Journal of Combinatorics, with an emphasis on open-access research. Van der Pol’s research trends highlight advancements in enumerative combinatorics, symmetry analysis in matroids, and probabilistic approaches to matroid structures. His work contributes to foundational questions in discrete mathematics and operations research, with applications in graph theory and algorithm design. No scientific awards are explicitly mentioned. His advising and grant activities remain unspecified in the provided texts. Research collaborations include studies on Earth and Planetary Sciences, though the primary focus remains matroid theory and combinatorial structures.

Anton J. Wijsمشاهده پروفایل

دانشیار

• Parallel Software Development
• Formal Verification
• Model Checking
• +۴ مورد دیگر

Anton J. Wijs is an Associate Professor at the Eindhoven University of Technology (TU/e) , affiliated with the Model-Driven Software Engineering group within the Department of Software Engineering and Technology . His research focuses on parallel software development and leveraging parallelism to enhance formal verification techniques. He holds leadership roles as a Board Member of the European Association for Programming Languages and Systems (EAPLS) and a member of the Steering Committee of ETAPS. Academic Background: Wijs earned his PhD in Computer Science from VU Amsterdam (2007), followed by postdoc positions at INRIA (France), TU/e, and RWTH Aachen University (Germany). He transitioned to an Assistant Professor role at TU/e in 2015 and became an Associate Professor in 2023. Research Interests: His work emphasizes scalable verification methodologies using GPUs, formal analysis of concurrent systems, and tools like mCRL2 . He collaborates with industry partners such as ASML and Codeplay Software to bridge academic research with practical applications. Awards & Grants: Notable achievements include the Best Student Paper Award (FACS 2017) , the Amazon Research Award (2022) , and an NWO grant for GPU-accelerated state space analysis. He co-led the GEARS project (2017–2022) , focusing on efficient parallel model checking. Teaching: Wijs teaches courses on Programming , Program Verification Techniques , and Digital Twins of Medical Devices . He actively supervises students and contributes to international conferences as a program chair and reviewer.

• Plant Ecology
• Pest Management
• Agricultural Biology
• +۳ مورد دیگر

Bob Douma is an External employee at PE&RC (Plant Research International) within the Crop and Weed Ecology department at Wageningen University & Research. His work focuses on agricultural and ecological systems, particularly plant defense mechanisms, pest management strategies, and biodiversity conservation. He has contributed to over 60 research outputs and actively supervises PhD candidates in projects like intercropping disease suppression and forest pest invasion predictions. Research interests include plant-pest interactions, forest biodiversity dynamics, and innovative technologies for agricultural monitoring (e.g., THz spectroscopy). He collaborates internationally on topics such as pest outbreak delimitation and agroecological pest control. Notable projects involve probabilistic modeling for pest invasion risk assessment and legacy effects of crop diversity. Education: Holds a dr.ir. (Dutch academic title) in agricultural sciences. Grants/Projects: Led projects on forest pest invasions and co-led PhD programs on pest management and disease suppression. Labs/Teams: Affiliated with Wageningen’s PE&RC group, contributing to datasets on plant defense and cover crop legacies.

Isaac Corro Ramosمشاهده پروفایل

پژوهشگر ارشد

• Health Economics
• Cost-Effectiveness Analysis
• Health Technology Assessment
• +۳ مورد دیگر

Isaac Corro Ramos is a Research Fellow at the Institute for Medical Technology Assessment (iMTA) within the Erasmus School of Health Policy & Management at Erasmus University Rotterdam. His research focuses on health economics, with an emphasis on cost-effectiveness analysis, probabilistic modeling, and value of information analysis. He has held this position since August 2009 after completing his PhD in Mathematics at Eindhoven University of Technology (2009), preceded by a Master’s in Mathematics from the University of Sevilla (2001). His work spans diverse areas including healthcare technology assessment, discrete event simulation, and systematic reviews of validation methodologies in health economic models. Notable contributions include the EPISODE study evaluating seizure dogs for refractory epilepsy and research on AI-driven glaucoma screening programs. He has authored over 40 peer-reviewed articles and contributed to datasets on topics like COPD management and continence nurse specialization. Collaborations include projects on immune-oncology therapies, cardiac risk prediction tools, and capacity-building initiatives in Malta’s healthcare system. His research consistently integrates quantitative rigor with real-world healthcare policy implications, emphasizing transparency and methodological innovation in economic modeling.

Matthias Volkمشاهده پروفایل

استادیار

• Formal Methods
• Probabilistic Model Checking
• Safety-Critical Systems
• +۳ مورد دیگر

Matthias Volk is an Assistant Professor in the Formal System Analysis group at Eindhoven University of Technology (TU/e). His research focuses on improving the safety and reliability of complex systems through formal methods, particularly probabilistic model checking. He develops automated techniques for system modeling and analysis, with a focus on industrial applications. He is a core developer of the Storm model checker. Academic Background: B.Sc. and M.Sc. in Computer Science from RWTH Aachen University Ph.D. from RWTH Aachen University, supervised by Joost-Pieter Katoen Postdoctoral researcher at the University of Twente Joined TU/e as an Assistant Professor in 2023 Research Interests: Probabilistic model checking Safety-critical systems Automated verification tools Industrial collaborations for formal methods Grants and Funding: NWO grant NWA.1160.18.238 (PrimaVera) ERC Consolidator Grant 864075 (CAESAR) EU Horizon 2020 project MISSION (101008233) Labs/Teams: Part of the Formal System Analysis group and Algorithms and Logics for Verification group at TU/e.

Thijs van de Laarمشاهده پروفایل

استادیار

• Bayesian Machine Learning
• Active Inference
• Probabilistic Programming
• +۳ مورد دیگر

Thijs van de Laar is an Assistant Professor at the BIASlab (Bayesian Intelligence and Autonomous Systems Laboratory) within the Department of Electrical Engineering at Eindhoven University of Technology. His research bridges advanced computational principles with real-world applications in uncertainty modeling. Education: PhD in Machine Learning (2019), Eindhoven University of Technology MSc in Natural Sciences (2010), Radboud University Nijmegen Research Focus: Bayesian machine learning, active inference, and probabilistic programming, with applications in autonomous agent control, hearing loss compensation, and efficient real-time decision-making systems. His work integrates insights from physics and neuroscience to develop novel computational frameworks. Software Contributions: Key contributor to ForneyLab.jl, a Julia toolbox for automated Bayesian inference through message passing on factor graphs. Also developed Herring.jl, a Poisson node extension for probabilistic modeling. Publications: His 15 most recent articles focus on variational message passing, active inference agents, epistemic value in graphical models, and factor graph-based algorithm design. These works span disciplines including artificial intelligence, control theory, and biomedical engineering.

Yannis Velegrakisمشاهده پروفایل

استاد

• Big Data Management & Analytics
• Knowledge Discovery
• Graph Management
• +۱۵ مورد دیگر

Yannis Velegrakis is a Professor in the Department of Information and Computing Sciences at Utrecht University, where he holds the chair of Very Large Data Management. He leads the Data Intensive Systems research group and is the program leader for the Master’s in Data Science . He is also a part-time faculty member at the University of Trento and a Principal Investigator at the Archimedes AI and Data Science hub, Athena Research Center . Education: PhD in Computer Science, University of Toronto MSc in Computer Science, University of Crete BSc in Computer Science, University of Crete His research focuses on Big Data Management & Analytics , Knowledge Discovery , Graph Management , Data Integration , and Data Quality . His work combines theoretical rigor with practical system development, emphasizing human-centered approaches to data exploration and analysis. He has pioneered methods in example-based search, entity resolution, and dynamic graph analysis. His recent publications reflect a strong trend in knowledge graph exploration , data quality assessment , and dynamic network mining . These works often integrate machine learning with database systems to support interactive and intelligent data discovery. His research bridges foundational data management with applied AI, particularly in the context of real-world data challenges. Scientific Leadership and Awards: PC Chair, ICDE 2024 General Chair, VLDB 2013 PC Chair, EDBT 2021 He has advised numerous researchers and contributed to major projects in data integration and semantic search. His secondary activities include visiting positions at IBM Almaden , AT&T Research Labs , UC Santa Cruz , and University of Paris-Saclay . He has secured funding through collaborative research initiatives and has served on program committees of top international conferences. He leads the Data Intensive Systems group, which develops innovative tools for managing and exploring large-scale, heterogeneous datasets. The group emphasizes systems that support intuitive, example-driven interaction with complex data, aligning with the principles of human-centered AI.

• Logic
• Philosophical Logic
• Formal Epistemology
• +۵ مورد دیگر

Francesco Berto is Professor of Philosophy at both the University of St Andrews (Department of Philosophy) and the University of Amsterdam (Institute for Logic, Language and Computation - ILLC). At the ILLC, he holds primary affiliation with the Formal Semantics & Philosophical Logic research group and secondary affiliation with Epistemology & Philosophy of Science. His work bridges formal logic, ontology, and epistemology with significant contributions to contemporary philosophical debates. Berto specializes in logic, ontology, and formal epistemology with particular focus on hyperintensionality, topic-sensitive semantics, belief revision, counterfactual reasoning, and the logic of imagination. His research develops what he terms 'thick content' theories where propositions have both truth-conditional and topical components. This approach addresses limitations in traditional possible worlds semantics by incorporating subject matter as a fundamental aspect of meaning and knowledge representation. His recent publications (2019-2025) reveal a coherent research trajectory examining how topicality affects logical reasoning across multiple domains. Berto's work demonstrates increasing integration of formal logic with cognitive science, particularly in modeling realistic human reasoning rather than idealized logical competence. Key contributions include formal models of framing effects, the logic of imagination as reality-oriented mental simulation, and solutions to the problem of logical omniscience through topic-sensitive approaches. Berto's scholarly influence extends through his extensive publication record in top philosophy and logic journals including Mind, Journal of Philosophical Logic, Synthese, and Noûs. His work has been cited over 2,400 times according to academic metrics, indicating substantial impact on contemporary philosophical logic and formal epistemology. As an active researcher, Berto supervises PhD candidates and participates in collaborative projects at the intersection of logic, language, and computation. His current work continues to develop formal frameworks that better capture the nuances of human cognition while maintaining rigorous logical standards. His research program represents a significant contribution to bridging the gap between idealized logical systems and the messy reality of human thought processes.

Burcu Kulahcioglu Ozkanمشاهده پروفایل

استادیار

• Formal Methods
• Software Testing
• Concurrent Systems
• +۷ مورد دیگر

Burcu Kulahcioglu Ozkan is an Assistant Professor and Delft Technology Fellow at the Delft University of Technology (TU Delft) Software Engineering Research Group (SERG). Her research bridges formal methods with software engineering to enhance the reliability of concurrent and distributed systems , with applications in blockchain systems and graph databases . Recipient of Amazon Research Award (2022) and Stellar Academic Research Grant (2023) Founder of the FORSE Lab , focusing on lightweight formal methods for software engineering Co-PI of Ripple’s UBRI program at TU Delft, targeting blockchain testing Co-leader of the TU Delft-JetBrains AI4SE collaboration track Her research spans model checking , debugging , and fuzz testing , addressing challenges in event interleavings and network faults in distributed systems. She has received multiple best paper awards , including OOPSLA’23 Distinguished Paper and ICGT’25 Best Software Science Paper . She serves on program committees for major conferences like ICSE’26 , CAV’25 , and ECOOP’25 , and has delivered invited talks at VLDB Summer School (2025), Sabanci University (2024), and Dagstuhl Seminars (2023).

• Automated Software Testing
• Artificial Intelligence
• Program Verification
• +۵ مورد دیگر

Dr. Wishnu Prasetya is an Assistant Professor at Utrecht University's Faculty of Science, Department of Software Technology. His research focuses on automated software testing, artificial intelligence applications in testing, program verification, and game technology. He leads projects including iv4XR (AI-enhanced automated testing) and IMPRESS (gamification in software engineering education), with demonstrated applications in computer game testing and extended reality systems. Research Interests: Prasetya's work spans automated testing methodologies enhanced by AI, formal verification techniques, and gamification. Key domains include: Agent-based testing frameworks for complex systems Model-based verification under uncertainty Player experience modeling in games Automated test generation for Java and XR systems Gamification of software engineering education Publication Trends: His recent articles (2020-2025) show strong focus on AI-driven testing approaches for games and extended reality, with innovations in agent-based test automation, formal verification of player experiences, and industrial applications of testing frameworks. Over 80% of recent publications involve multi-agent architectures or model-based validation techniques. Educational Contributions: Teaches courses on Program semantics and verification and Software testing and verification Developed gamification tools to improve student engagement in software engineering courses Tools & Frameworks: iv4XR/Aplib: Agent-programming testing framework T3: Automated testing tool for Java APSL: Protocol testing tool for complex systems

Robert C. Lanzafameمشاهده پروفایل

مدرس ارشد

• Flood Risk Management
• Structural Reliability
• Geotechnical Engineering
• +۳ مورد دیگر

Robert C. Lanzafame is a Senior Lecturer at Delft University of Technology's Faculty of Civil Engineering and Geosciences, specializing in Hydraulic Structures and Flood Risk. Holding a PhD from UC Berkeley and licensed as a California Civil Engineer, he teaches foundational engineering methods, programming, probability theory, and applied levee design while supervising bachelor's and master's students. His educational background includes BSc and MSc degrees in Civil Engineering from UC Berkeley, with doctoral research on vegetation effects on dike stability using probabilistic design methods. Professional experience encompasses geotechnical consulting on California levees, dams, and pipeline projects, informed by firsthand work in the Sacramento-San Joaquin Delta. Lanzafame's research integrates flood risk management with educational innovation, focusing on structural reliability, probabilistic design, and computational thinking. Recent work examines animal burrow impacts on levees and human stability during wave overtopping, while his educational research develops interactive Jupyter Book tools for engineering curricula. Since 2023, he leads the MUDE module for all first-year MSc engineering students. His teaching excellence is recognized through multiple awards: 1st Place, Best Teacher, Hydraulic Engineering (2020) 1st Place, Best Teacher, Hydraulic Engineering (2021) 2nd Place, Best Teacher, Hydraulic Engineering (2021) 2nd Place, Best Teacher, Program Core and MUDE Modules (2022) 2nd Place, Best Teaching Team (MUDE), Structural Engineering Track (2022) Lanzafame directs the faculty-wide TeachBooks project to create interactive educational materials using open-source tools, collaborating with university initiatives to transform engineering pedagogy through computational thinking integration. He actively presents workshops on Python programming in education and interactive book development across TU Delft.

Pascal Wissinkمشاهده پروفایل

استادیار

• Disruption Risk Management
• Stochastic Optimization
• Supply Chain Resilience
• +۳ مورد دیگر

Pascal Wissink is an Assistant Professor in the Department of Operations Analytics at the School of Business and Economics, Vrije Universiteit Amsterdam. His research focuses on optimizing networks under disruption risks, particularly in financial, supply, and transportation systems. He emphasizes sustainability challenges in logistics and employs stochastic processes, copulas, and multi-stage optimization techniques. Education: Bachelor's (2011) and Master's (2013) in Econometrics & Operational Research from Erasmus University Rotterdam PhD in Management Science & Business Economics from the University of Edinburgh (2019) Research Interests: Resilience of optimal decisions in percolation-prone networks Liquidity in ridesharing economies and sustainable investments in aluminum Stochastic optimization methods including copula-based modeling and robust frameworks His work bridges theoretical optimization with real-world applications in sustainability and network stability. Teaching: Coordinates courses like Business Processes (BSc) and Process Analytics (PGDip), and oversees MSc thesis programs in Transport & Supply Chain Management. Teaches Supply Chain Management and Computing for Business. Projects: Led research on Dutch pharmaceutical supply chains (funded by TKI Dinalog) and European aluminum circularity. Collaborated with TNO (2015–2019) as scientist/project manager.

Martin Roa-Villescasمشاهده پروفایل

پژوهشگر

• Probabilistic graphical models
• Bayesian Machine Learning
• Tensor Networks
• +۵ مورد دیگر

Martin Roa-Villescas is a Doctoral Candidate and Teaching Assistant in the Department of Electronic Systems within the Electrical Engineering school at Eindhoven University of Technology (TU/e). He also holds an external position as a Docent (Lecturer) at Fontys University of Applied Sciences since August 2023. His educational background includes a B.Sc. in Electronic Engineering from the National University of Colombia (2010) and an M.Sc. in Embedded Systems from TU/e (2013). Between 2013 and 2018, he worked as an embedded software designer at Philips Research in Eindhoven. Roa-Villescas' research focuses on probabilistic graphical models, Bayesian machine learning, and tensor network applications. His work spans both theoretical advancements in probabilistic inference algorithms and practical implementations in open-source software. He has made significant contributions to optimizing message passing algorithms and developing efficient execution schedules for Bayesian inference. His recent publications demonstrate a clear trajectory toward improving the scalability and efficiency of probabilistic inference methods, with applications spanning audio signal processing, robotics, and hearing aid technology. The development of TensorInference, a Julia package for tensor-based probabilistic inference, represents his commitment to open-source tools that advance the field. As a researcher involved in the STW Zero Autonomous Acoustic Systems project (2017-2024), he has contributed to advancing acoustic sensing technologies through probabilistic modeling approaches. His work aligns with UN Sustainable Development Goals related to technology innovation and accessibility.

Oliver Tseمشاهده پروفایل

دانشیار

• Partial Differential Equations
• Optimal Control
• Mathematical Modeling
• +۵ مورد دیگر

Oliver Tse is an Associate Professor in the Applied Analysis group of the Centre for Analysis, Scientific computing and Applications (CASA) at Eindhoven University of Technology (TU/e). He leads the Calculus of Variations and Optimal Control group within CASA and is affiliated with both the Center for Quantum Materials and Technology Eindhoven and the Applied Analysis group. His office is located at MetaForum 5.059, and he can be contacted at o.t.c.tse@tue.nl or +31 40 247 4356. Oliver Tse earned his master's degree in Applied Mathematics at the University of Kaiserlautern (sponsored by the Fraunhofer Institute for Industrial Mathematics), followed by his doctorate (Dr. rer. nat.) in 2011 under the supervision of Prof. René Pinnau. He worked at the University of Kaiserlautern for five years, including two years as an Assistant Professor in the Industrial Mathematics group. Tse's research centers on nonlinear and nonlocal Partial Differential Equations (PDEs), with expertise spanning modeling and simulation, numerical methods, optimization, and stability analysis. His current interests focus on the connections between optimal transport, generalized gradient flows, and large deviations, as well as probabilistic methods for studying PDEs. He aims to develop new analytical tools by establishing these connections. His recent work demonstrates a strong interdisciplinary approach, bridging pure mathematical analysis with quantum computing applications, particularly in variational quantum optimal control and neutral atom quantum systems. His publication record from 2024-2025 shows a clear trend toward applying mathematical analysis to quantum computing challenges, with three 2025 papers focusing on quantum optimal control and qubit configuration optimization, while maintaining strong connections to his foundational work in PDE theory as evidenced by his 2024 Numerische Mathematik paper. This demonstrates his ability to translate abstract mathematical concepts into practical solutions for emerging quantum technologies. Tse is actively involved in the academic community, organizing and participating in workshops such as the Finite Volumes and Optimal Transport workshop in Paris (November 2024), the Oberwolfach mini-workshop on High-Dimensional Control Problems (December 2024), and the IPAM long program on Non-commutative Optimal Transport in Los Angeles (March-June 2025). He hosts academic visitors including Urbain Vaes from École des Ponts ParisTech and Riccarda Rossi from the University of Brescia in early 2025. In addition to research, Tse teaches several mathematics courses including Measure, Integration and Probability Theory, Calculus Variant 2, and Partial Differential Equations. His research has received funding from the Dutch Ministry of Economic Affairs and Climate Policy as part of the Quantum Delta NL program, the Horizon Europe program HORIZON-CL4-2021-DIGITAL-EMERGING-01-30 via Project No. 101070144 (EuRyQa), and the Netherlands Organization for Scientific Research (NWO) under Grants No. 680.92.18.05 and No. NGF.1582.22.009.