جستجوی استاد راهنمای دانشگاهی

Jan-Willem van Groenigenمشاهده پروفایل

استاد

• Soil Biogeochemistry
• Nitrogen Cycle
• Phosphorus Cycle
• +۵ مورد دیگر

Prof. Jan-Willem van Groenigen is a full professor in the Department of Soil Biology at Wageningen University. He serves as Chair of the Editors-in-Chief of Geoderma and Subject Chair for Agriculture & Biological Sciences on Scopus's Content Selection and Advisory Board. His research focuses on soil biogeochemistry, emphasizing nitrogen and phosphorus cycles, and the role of soil fauna like earthworms in agricultural systems. He advocates for integrating natural processes with agricultural practices to enhance sustainability and mitigate climate change. Education: Not explicitly detailed in provided text, but holds a PhD in Soil Science or related field. Affiliations: Wageningen University, Geoderma leadership, Scopus CSAB. His research interests include understanding how soil organisms influence nutrient cycles in managed ecosystems, with a focus on carbon sequestration, greenhouse gas emissions, and sustainable agriculture. He has supervised 19 PhD students and over 100 MSc/BSc students, contributing to projects like phosphorus availability in manure and peat soil management. Prof. van Groenigen has received prestigious awards, including the Philippe Duchaufour Medal (2024) for integrating agricultural management with environmental science. He actively communicates research through media outlets and popular science platforms, emphasizing soil's role in global challenges.

Gonzalo Nápolesمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Cognitive Science
• +۵ مورد دیگر

Gonzalo Nápoles is an Assistant Professor at Tilburg University's School of Humanities and Digital Sciences, Department of Cognitive Science and AI. He holds a Doctoral Degree in Computer Science from Rough Cognitive Networks (2014–2017). His research focuses on AI applications in cognitive modeling, pattern classification, and neural networks with interdisciplinary applications in healthcare, finance, and social sciences. Key research areas include Fuzzy Cognitive Maps, data augmentation techniques for neuroimaging, and interpretable machine learning systems. He actively contributes to UN Sustainable Development Goals related to education and innovation. Recent work explores AI ethics, financial risk assessment using dynamic networks, and sensory processing disorder analysis through neural networks. Education: Doctoral Degree in Computer Science, 2017 (Thesis: Rough Cognitive Networks) Prize-winning research includes Best Paper Awards at CIARP 2021 and IWAIPR 2023. He collaborates internationally, hosting academic visitors and serving on multiple PhD committees. Current projects involve stock prediction using graph neural networks and fMRI data augmentation methodologies. Awards: Best Paper Award - CIARP 2021 Best Paper Award - IWAIPR 2023 Nápoles advises on PhD theses in cognitive science and AI applications. His work bridges theoretical advancements with practical implementations in healthcare, finance, and urban systems.

Rianne Conijnمشاهده پروفایل

استادیار

• Learning Analytics
• Human-Technology Interaction
• Artificial Intelligence
• +۶ مورد دیگر

Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), Netherlands. Her research bridges data-driven methodologies (machine learning, statistical modeling) with human-centered design to enhance learning analytics, explainable AI, and writing process analysis. She holds a joint PhD (cum laude) from Antwerp University and Tilburg University, and an MSc (cum laude) in Human-Technology Interaction from TU/e. Academic Background: MSc (2015, TU/e, cum laude), PhD (2020, Antwerp University & Tilburg University, cum laude). Research Focus: Learning analytics, keystroke logging, explainable AI for education, data dashboards, and self-regulated learning dynamics. Teaching: Courses in Advanced Research Methods, Human-AI Interaction, Behavioral Research Methods, and AI ethics in education. Her recent publications explore parallel language planning in writing, longitudinal self-regulated learning strategies, and generalizability of academic performance prediction models. She leads an NWO Veni project on Human-Centered AI in education, emphasizing tailored explanations for student-AI collaboration. Scientific awards include cum laude distinctions for her MSc and PhD, and the NWO Veni grant. Collaborative work spans institutions in the Netherlands, Norway, and the U.S., with applications in intelligent tutoring systems and ethical AI deployment in exams. Key trends across her work: integration of machine learning with educational theory, leveraging keystroke data for cognitive process insights, and prioritizing actionable, explainable AI systems for student support. Publications span journals like the Journal of Experimental Psychology: General , Computers and Education , and IEEE Transactions on Learning Technologies . Scientific Awards: NWO Veni grant for Human-Centered AI in education Cum laude for MSc and PhD Grants & Collaborations: National Science Foundation grants (2016868, 2302644) for biometric feedback in writing UK Research and Innovation grant (ES/W011832/1) for real-time AI scaffolding TU/e Boost! Program grant for self-regulated learning analysis Labs & Teams: EAISI Foundational (Eindhoven AI Systems Institute) Human Technology Interaction group at TU/e Collaboration with Norwegian Reading National Center (University of Stavanger) Project teams for Waterproof ITS and ProWrite grants

Antoni Forner Cuencaمشاهده پروفایل

دانشیار

• Electrochemical Engineering
• Energy Storage
• Fuel Cells
• +۴ مورد دیگر

Antoni Forner-Cuenca is an Associate Professor at Eindhoven University of Technology's Department of Chemical Engineering and Chemistry, leading the Electrochemical Materials and Systems group. He holds a PhD from ETH Zurich (2016) and conducted postdoctoral research at MIT (2017-2018). His research focuses on advancing energy storage and conversion technologies, including redox flow batteries, fuel cells, and CO₂ reduction systems. He has received prestigious awards such as the NWO Veni Grant (2019), ERC Starting Grant (2022), and the ETH Zurich Medal (2017). Research interests include designing porous electrodes, optimizing electrochemical systems, and developing sustainable materials for large-scale energy storage. His group collaborates on projects like the Next-generation gas diffusion electrodes for CO₂ reduction and low-cost iron-air flow batteries. Key contributions involve non-solvent induced phase separation techniques and computational modeling for electrode optimization. Grants & Projects: Next-generation gas diffusion electrodes for electrochemical reduction of CO₂ to ethylene (2021-2025) CuGDEs - Copper-based gas diffusion electrodes for CO₂ reduction (2020-2027) Media Highlights: Featured in press coverage on eco-friendly redox flow batteries and lung-inspired electrode designs Invited expert commentary on energy storage innovations Labs/Teams: Leads the Electrochemical Materials and Systems group, focusing on interdisciplinary research at the interface of materials science and energy engineering.

Nicola Calabrettaمشاهده پروفایل

استاد

• Optical Communication Systems
• Photonics
• Telecommunications Engineering
• +۶ مورد دیگر

Nicola Calabretta is a Full Professor in Electro-Optical Communication Systems and Senior Research Fellow at Eindhoven University of Technology (TU/e). His work focuses on smart optical networks, high-speed electronics, FPGA implementations for scheduling algorithms, and photonic integrated circuits. He holds a PhD from TU/e (2004) and previously conducted research at DTU Fotonik and the Sant'Anna School of Advanced Studies. His expertise spans optical signal processing, multi-level modulation formats, and applications in data center and metro networks. Key research areas include optical switching architectures (e.g., SOA-based switches), WDM systems, and low-latency interconnect networks. He has led projects like ADAPTOR (resource optimization), SmartTWO (future telecom technologies), and 5G-MOBIX (cross-border mobility). His courses include 'Optical Fibre Communication Technology' and 'Optical Interconnection Networks.' Collaborations involve institutions globally, with recent work emphasizing photonic integration for neural networks, ultra-fast switching, and edge computing. His contributions align with UN SDGs through sustainable telecom infrastructure advancements.

Laura Toniمشاهده پروفایل

دانشیار

• Machine Learning
• Signal Processing
• Immersive Communications
• +۵ مورد دیگر

Laura Toni is an Associate Professor in the Department of Electronic & Electrical Engineering at University College London (UCL). She serves as Director of the MSc in Telecommunications and Internet Engineering and the MRes in Telecommunications. Additionally, she is a Turing Fellow at the Alan Turing Institute and a member of ELLIS (European Lab for Learning and Intelligent Systems). Her research focuses on coding, streaming technologies, machine learning for immersive communications, decision-making under uncertainty, and large-scale signal processing. She leads the LASP (Learning And Signal Processing) group at UCL. Education: MSc (2005) and PhD (2009) from the University of Bologna, followed by postdoctoral research at UC San Diego and EPFL under Professors L. Milstein, P. Cosman, and P. Frossard. Key roles include Technical Program Chair at ACM MM 2022, Keynote Co-Chair at ACM MMSys 2022, and leadership in organizing workshops on graph-based machine learning and emerging technologies in performing arts. She is a Senior IEEE Member and holds editorial roles in IEEE Multimedia Magazine and EURASIP Journal on Signal Processing. Her work bridges communication systems and machine learning, with contributions to adaptive streaming, network optimization, and graph signal processing. She actively promotes diversity and inclusion in technical conferences, including roles as Diversity Chair at MMSys 2021 and PIMRC 2020.

Carlo Cavicchiaمشاهده پروفایل

استادیار

• Statistics
• Data Science
• Machine Learning
• +۶ مورد دیگر

Dr. Carlo Cavicchia is an Assistant Professor of Statistics at the Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam. He holds a PhD in Methodological Statistics from La Sapienza University of Rome and has held roles such as Research Fellow at UnitelmaSapienza University and Consultant for NGOs in Zanzibar. His research focuses on latent variable models, composite indicators, and unsupervised classification, with applications in environmental policy, sports analytics, and teacher job satisfaction. Cavicchia teaches statistics and data science courses at undergraduate and graduate levels and actively contributes to academic communities through journal reviewing, conference organizing, and editorial roles. Education: PhD in Methodological Statistics (La Sapienza University of Rome, 2020) MSc in Statistics and Decision Sciences (La Sapienza University of Rome, 2016) BSc in Statistics (La Sapienza University of Rome, 2013) Dutch University Teaching Qualification (BKO, 2022) Research Interests: Cavicchia’s work emphasizes hierarchical models, non-parametric statistics, and data science applications. He develops methodologies for composite indicators, including ultrametric Gaussian mixture models and disjoint principal component analysis. His research bridges theoretical advancements with real-world problems, such as waste management in Italian municipalities and ranking European football teams using composite metrics. Grants & Awards: 2024: IFCS Chikio Hayashi Award 2023: ESE Starter Grant (€300,000) 2017: Research Grant for Junior Researchers (€1,270) 2016: PhD Scholarship, La Sapienza University Academic Engagement: Cavicchia serves as IASC Data Analysis Competition Officer (2023–2025), co-edits the ISI Magazine , and organizes conferences like DSSV 2020 and DSSV-ECDA 2021. He is an elected member of the International Statistical Institute and contributes to SVQS’s Sustainability initiatives. Labs & Teams: He co-organizes the Econometrics internal seminars at Erasmus University and collaborates with researchers at University of Naples Federico II on hierarchical models and convex clustering.

Arno Siebesمشاهده پروفایل

استاد

• Data Mining
• Pattern Mining
• Minimum Description Length Principle
• +۲ مورد دیگر

Arno Siebes is Professor of Algorithmic Data Analysis in the Department of Information and Computing Sciences at Utrecht University's Faculty of Science. His research focuses on data mining methodologies, particularly pattern mining and Minimum Description Length (MDL) principles. Key research areas include: Developing efficient algorithms for pattern discovery Applying MDL to data characterization Creating interpretable models for complex datasets Addressing challenges in data science education Recent publications demonstrate applications in diverse domains including mobility analysis, genomic screening, and pandemic response. His work combines theoretical foundations with practical implementations for knowledge discovery.

Rianne de Heideمشاهده پروفایل

استادیار

• Machine Learning
• Statistics
• Hypothesis Testing
• +۷ مورد دیگر

Rianne de Heide is an Assistant Professor in the Statistics group (STAT) within the Department of Applied Mathematics at the University of Twente's Faculty of Electrical Engineering, Mathematics and Computer Science. She maintains collaborative arrangements with LUXs Data Science in Leiden, CWI, and VU Mathematics in Amsterdam as a guest researcher while working partly remotely during her family's relocation. Her academic journey includes a previous position as Assistant Professor at Vrije Universiteit Amsterdam. PhD Dissertation: 'Bayesian Learning: Challenges, Limitations and Pragmatics' (2020) MSc Thesis: 'The Safe-Bayesian Lasso' (2016) De Heide's research spans multiple interconnected domains within statistics and machine learning, with particular emphasis on developing mathematically rigorous frameworks that remain accessible to diverse audiences. Her work bridges theoretical foundations with practical applications, focusing on hypothesis testing with e-values, Bayesian learning methodologies, and best-arm identification problems in multi-armed bandit settings. She demonstrates exceptional interdisciplinary range, connecting statistical theory with philosophical inquiry and even theological discussions as evidenced by her publications on biblical authorship verification and mathematical beauty. Analysis of her publication trajectory reveals a clear evolution toward developing anytime-valid statistical methods, particularly through e-values and e-processes for multiple testing scenarios. Her recent work shows increasing focus on foundational questions in statistical inference while maintaining strong connections to practical machine learning applications. The 2024 'Safe Testing' paper in the Journal of the Royal Statistical Society represents a significant contribution that generated a formal discussion meeting. VENI project 'E-values for Multiple Testing' NWO M2 grant of €742,708 with Jelle Goeman (funding 2 PhD students and a scientific programmer) 2025 Bernoulli Society New Researcher Award De Heide actively supervises research through her VENI project and the NWO M2 grant, while also contributing to broader academic service through the 'Kindness and Excellence in Academia' initiative she co-founded. This initiative addresses critical cultural issues in academic environments through opinion pieces, resources, and community building around compassionate academic practices. She has organized specialized events like the E-Day meet-up for e-value researchers at CWI in Amsterdam, demonstrating leadership in her niche research community. Her research activities are centered around the Statistics group at the University of Twente, with significant external collaborations through the E-mailing list for e-value researchers and partnerships with institutions including CWI, VU Amsterdam, and Leiden's LUXs Data Science. The interdisciplinary nature of her work creates connections across mathematics, computer science, philosophy, and even religious studies.

• Integrated Care Governance
• Health Care Management
• Strategic Innovation
• +۵ مورد دیگر

Prof. dr. Mirella M.N. Minkman serves as the Vilans Chair in Innovation of Organization and Governance of Integrated Care at Tilburg University's TIAS School for Business and Society. Concurrently, she is CEO of Vilans (National Knowledge Organization for care and support), bridging science, practice, policy, and education through national innovation programs. Her leadership extends to Chair of the National Governance Innovation Advisory Committee (BoZ), Chair of the NVTZ Scientific Advisory Board, Supervisory Board roles at RIBW Brabant and Rivierenland Hospital, and membership in the VGN Committee of Experts. Minkman's research pioneers person-oriented integrated care governance within multi-organizational networks, focusing on leadership, accountability systems, and strategic innovation. She examines how governance modes enable collaborative care models while addressing implementation barriers in healthcare transformation. Her work emphasizes change management frameworks for large-scale system integration, with particular attention to supervision mechanisms and value-based accountability structures across care continua. Analysis of her 15 recent publications (2021-2023) reveals consistent exploration of integrated care governance across Dutch and international contexts. Key thematic clusters include leadership in nursing home care, decision-making dilemmas in service networks, and emerging AI applications in long-term care. Methodologically, her work spans systematic reviews, policy analyses, and implementation studies, predominantly published in the International Journal of Integrated Care and specialized healthcare management outlets. Through Vilans, Minkman directs national knowledge platforms and large-scale implementation programs that connect academic research with practical healthcare innovation. Her international engagement includes board membership with the International Foundation for Integrated Care, editorial roles for the International Journal for Integrated Care, advisory positions with WHO's Integrating the Health and Care Workforce group, and participation in the UK Center for Evidence IMPACT's Critical Friends Group.

Tanya Bondaroukمشاهده پروفایل

استاد

• Human Resource Management
• Electronic HRM
• Technology Impact on Workplaces
• +۳ مورد دیگر

Prof. Tanya Bondarouk is a distinguished academic affiliated with the Digital Society Institute and Faculty of Behavioural, Management and Social Sciences at the University of Twente. Her research focuses on Human Resource Management (HRM), electronic HRM systems, and the impact of disruptive technologies on work environments. She holds leadership roles including Board Member of the National Network of Female Professors (Landelijk Netwerk Vrouwelijke Hoogleraren). Her academic contributions span over 250 publications, including influential works on AI in HRM, open innovation, and gig economy challenges. Notable awards include the Best HRM Scientist in The Netherlands (2018) and the Inspiration Award (2019). Research interests: Technology-human interaction in workplaces, HRM strategies for innovation, and digital transformation in organizations. Recent articles analyze AI-driven recruitment, generational differences in tech engagement, and algorithmic management dilemmas. Prof. Bondarouk actively engages in academic networks, organizing conferences like the 38th EGOS Colloquium (2022), and provides expert commentary on digital labor platforms and employer branding strategies. Her work bridges theoretical HRM frameworks with real-world organizational challenges.

• 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.

Maurice van Keulenمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Data Mining
• Process Mining
• +۷ مورد دیگر

Maurice van Keulen is an Associate Professor affiliated with the University of Twente's research institutes including Datamanagement & Biometrics, Digital Society Institute, and TechMed Centre. His multidisciplinary work bridges computer science, healthcare, and social systems. Research Focus: Van Keulen specializes in artificial intelligence applications with emphasis on: Data management (quality, integration, probabilistic databases) Explainable AI and interpretable machine learning models Healthcare informatics (cancer prediction, medical imaging, outcome analysis) Natural language processing and social media analytics His recent work explores dynamic sparse training, meta-learning for data imputation, and ethical AI frameworks. Publication Trends: Recent articles (2023-2025) show strong focus on: Interpretable AI methods in healthcare diagnostics Robust machine learning under data corruption Meta-learning approaches for data preprocessing 3D medical imaging and reconstruction techniques Awards: Beste paper award (2018) for work on probabilistic data conditioning Supervision & Activities: Has supervised 14 research projects and serves on executive boards including EDBT (Extending DataBase Technology) and IFIP WG 2.6. Leads research on ethical dimensions of AI systems.

• Media Effects
• Communication Science
• Philosophical Foundations of Research
• +۳ مورد دیگر

Dr. Lennert Coenen is an Assistant Professor at the Department of Communication and Cognition within the Tilburg School of Humanities and Digital Sciences at Tilburg University. His research focuses on media effects, statistical methodology in communication science, and the philosophical foundations of research design. He has held a visiting professor position at KU Leuven (Feb–Sept 2021). His work critically examines issues like moderation analysis, omitted variable bias in mediation studies, and the implications of algorithmic platforms on media exposure. Research Interests include: Media effects and epistemological challenges in communication research Statistical methodologies such as strong-form frequentist testing and mediation analysis Philosophical issues in hypothesis testing and theoretical interpretation Family technoference and digital media's societal impacts Recent publications highlight critical examinations of research methodology and the theoretical implications of statistical findings in communication science. Collaborations include work with Tim Smits on frequentist testing frameworks and interdisciplinary projects on algorithmic governance. Teaching responsibilities include courses on statistics, data visualization, and media effects analysis.

• Distributed Systems
• Cloud Computing
• Data-Intensive Workflow Management
• +۵ مورد دیگر

Dr. Zhiming Zhao is an Associate Professor and Chair of the Multiscale Networked Systems (MNS) research group at the Informatics Institute (IvI), University of Amsterdam (UvA). He serves as the technical manager of the Virtual Lab and Innovation Center (VLIC) of LifeWatch ERIC, a European research infrastructure for ecology and biodiversity science. Zhao holds an IEEE Senior Member designation and is the Managing Editor of the Journal of Cloud Computing . He earned his Ph.D. in Computer Science from UvA in 2004. His research focuses on quality-critical distributed computing, data-intensive workflows, virtual research environments, and digital twins. He leads projects such as LTER-LIFE (Dutch research infrastructure for digital twins) and coordinates UvA contributions to EU initiatives like ENVRI-HUB Next , EVERSE , and BlueCloud-2026 . Zhao’s work spans technical development in EU projects (e.g., ENVRI-FAIR , ARTICONF , CLARIFY ) and leadership roles in international workshops and conferences. His team develops frameworks like NaaVRE (Jupyter-based collaborative environments) and CloudsStorm (dynamic infrastructure planning). Current research emphasizes trustworthy AI in cloud systems, federated learning, and edge-cloud resource optimization. Key achievements include over 150 peer-reviewed publications, supervision of numerous PhD students, and contributions to open science initiatives. His lab actively explores interdisciplinary applications in environmental science, medical imaging, and blockchain-based decentralized systems.