جستجوی استاد راهنمای دانشگاهی

• Photovoltaics
• Solar Cells
• Silicon Solar Cells
• +۵ مورد دیگر

Olindo Isabella serves as a Full Professor within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. She heads the Photovoltaic Materials and Devices (PVMD) research group, driving innovation in solar energy conversion technologies. Her academic role encompasses teaching, research leadership, and extensive collaboration with industry and international institutions to advance photovoltaic science and engineering. Professor Isabella's research spans multiple domains of photovoltaics, including silicon and perovskite solar cells, thin-film technologies, offshore floating systems, and agrivoltaics. She investigates material properties, device physics, and system performance to enhance efficiency, reliability, and environmental sustainability of solar energy solutions. Her work integrates experimental and computational approaches for comprehensive analysis. Analysis of her recent publications indicates a strategic focus on machine learning for PV-climate classification, impedance spectroscopy of silicon solar cells, offshore floating platform engineering, and perovskite crystallization processes. These studies collectively address key barriers to large-scale solar deployment, such as performance prediction, structural integrity in marine environments, and novel material synthesis. Scientific Awards: The available information does not mention any specific awards or honors for Professor Isabella. She has guided the research of 20 students and secured competitive funding for impactful projects. Currently, she leads SYMBIOSYST (2023-2026), which explores symbiotic relationships between solar PV and agriculture, and recently completed TRUST-PV (2020-2024), aimed at improving PV plant integration across market segments through machine learning and monitoring technologies. The PVMD group under her direction operates state-of-the-art laboratories for solar cell fabrication and characterization. The team collaborates with global partners on field trials, data analysis, and technology development, contributing to both fundamental knowledge and practical applications in renewable energy.

• Process Mining
• Healthcare Informatics
• Data Security
• +۳ مورد دیگر

Dr. Jeewanie Jayasinghe Arachchige is a Lecturer in the Department of Computer Science at Vrije Universiteit Amsterdam, Faculty of Science. She teaches undergraduate courses including Bachelor Project Computer Science, Professional Development, and Software Engineering Processes for the academic year 2024–2025. Her research focuses on process mining , healthcare informatics , and data security . She applies process mining to analyze healthcare pathways and subpopulation treatment variations, develops explainable AI frameworks for predictive analytics, and examines data governance in emerging architectures like Data Lakehouses. Her work intersects legal informatics, particularly formalizing Sri Lankan civil court processes using ontology engineering. Recent publications highlight trends in balancing simplicity and complexity in process modeling, Industry 4.0 healthcare applications, and cybersecurity in model-driven web development. She has contributed to over 20 peer-reviewed articles since 2006, spanning topics from service-oriented architectures to value network analysis. Her teaching and research emphasize practical applications of IT in healthcare, legal systems, and enterprise environments. No ancillary activities are currently recorded.

• AgriFood Supply Chain Logistics
• Supply Chain Management
• Logistics Network Design
• +۴ مورد دیگر

Prof. Jack van der Vorst is the Personal Professor of AgriFood Supply Chain Logistics at Wageningen University's Operations Research and Logistics Group. Previously serving as a member of the Board of Directors of Wageningen University & Research (until 2024) and General Director of the Social Sciences Group, he leads over 1000 personnel across three institutes. His advisory roles include the Topteam AgriFood (Science Captain), Top consortium for Knowledge and Innovation (TKI), The Sustainability Consortium (TSC), and Florensis BV's Supervisory Board. With 20+ PhD supervisions and 200+ publications, his research focuses on innovative logistics concepts in AgriFood systems, including supply chain resilience, sustainability, and system innovation. His work integrates modeling frameworks with practical industry applications, emphasizing perishable products, horizontal collaboration, and environmental efficiency. Research interests span AgriFood System Design, Supply Chain Strategy, and Performance Management. His recent studies address challenges like postharvest loss reduction in developing countries, CO2 emission minimization in cold chains, and circular economy implementation in mushroom supply chains. Methodologically, he employs multi-criteria decision models, optimization techniques, and simulation to address complex logistics problems. Publications highlight themes such as horizontal collaboration success factors, vulnerability assessment frameworks, and green supply chain design. His work bridges academic rigor with industry needs, often collaborating with policymakers and international organizations to promote sustainable agri-food systems.

Ioannis Athanasiadisمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Agricultural Modeling
• +۷ مورد دیگر

Ioannis Athanasiadis is a Full Professor and Chair of Artificial Intelligence at Wageningen University & Research (The Netherlands). He leads the Artificial Intelligence (AIN) group, focusing on advancing AI methods for global challenges in agriculture, ecology, and sustainability. Previously, he was faculty at the Dalle Molle Institute for Artificial Intelligence (IDSIA, Switzerland) and the Democritus University of Thrace (Greece). He holds a PhD (2005, cum laude) in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research integrates machine learning, knowledge engineering, and environmental modeling to address food security, climate adaptation, and ecosystem services. He leads initiatives like AgML (AgMIP's machine learning benchmarking effort) and coordinates European grants such as LTER-LIFE and CYBELE . Prof. Athanasiadis has supervised over 40 PhD/postdoc researchers and serves as Editor of Environmental Modelling and Software . He collaborates internationally on projects involving AI for crop modeling, digital twins, and sustainable agriculture. His team develops frameworks like Crop2ML and PyCrop2ML to enhance interoperability between process-based models and machine learning systems.

• Sports Analytics
• Predictive Analytics
• Complex Networks
• +۳ مورد دیگر

Dr. Otto Koppius is an Assistant Professor at the Rotterdam School of Management , Department of Technology and Operations Management. His research focuses on sports analytics , predictive analytics , and complex networks , emphasizing data-driven decision-making in organizations. He explores applications ranging from talent identification in sports using sensor data to sustainability in supply chains. Key research interests include: Methodological advances in predictive analytics, including feature engineering and algorithmic bias detection. Integration of predictive analytics into organizational practices. Smart cargo sensor data for optimizing supply chain networks. Past work includes studies on social influence in networks, closed-loop supply chains, and knowledge transfer within firms. His articles analyze topics like network interventions, innovation dynamics, and digital ecosystem orchestration. No scientific awards were explicitly mentioned in the provided text. He has supervised 6 academic works, though specific student names are not listed. Research extends to themes like sustainability, business strategy, and organizational behavior, with a focus on translating technical methods to real-world business challenges.

Sabine Waschullمشاهده پروفایل

استادیار

• Industry 4.0/5.0
• Work Design
• Digitalization
• +۳ مورد دیگر

Sabine Waschull is an Assistant Professor of Operations Management at the Faculty of Economics and Business, University of Groningen. She holds a MSc and PhD in Operations Management from the same institution. Her research focuses on human-centric design in Industry 4.0/5.0 contexts, including AI integration, digitalization, and work system evaluation. She is a member of the IFIP WG 5.7 working group on Production Management Systems. Her teaching includes courses such as Smart Industry Operations, Technology-Enabled Innovation, and Operations Strategy & Technology across bachelor and master programs. Her work emphasizes human-AI synergies and co-creation methodologies in manufacturing systems. Recent research trends highlight AI-driven enterprise interoperability, socio-technical evaluation of manufacturing systems, and human-centric design of augmented reality tools. Collaborations with co-authors like Christos Emmanouilidis and Joost Bokhorst explore AI ethics, digital twin integration, and assembly process optimization.

Mykola Pechenizkiyمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Predictive Analytics
• +۵ مورد دیگر

Mykola Pechenizkiy is a Full Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), holding the Data Mining Chair. He also serves as an Adjunct Professor in Data Mining for Industrial Applications at the University of Jyväskylä. His research focuses on predictive analytics, data mining, and responsible AI, addressing real-world challenges in industry, healthcare, and education. He leads the Customer Journey research program at the Data Science Center Eindhoven, emphasizing ethical and transparent analytics. Academically, he holds a PhD from the University of Jyväskylä (2005) and has held visiting researcher positions at institutions like Columbia University and NYU. He has co-authored over 300 peer-reviewed publications and serves on editorial boards and committees for leading conferences (e.g., AAAI, IJCAI). He is the President of the International Educational Data Mining Society (IEDMS). His research interests include concept drift adaptation, sparsity techniques in neural networks, and fairness-aware AI. He has led projects such as the TKI PPS KPN Smart Two initiative and collaborates with industries like ASML, Philips, and Rabobank. His work contributes to UN SDGs, particularly in sustainable development through AI-driven solutions. Awards: Best Demo Paper Award (IEEE ICDE 2023), Best Paper Awards (ALA 2022, LoG 2022), and SensorKDD 2009 recognition. Grants/Projects: Active projects include TKI PPS KPN Smart Two (2019–2025) and Smart One W&I TKI KPN Flagship (2018–2022). Labs/Teams: Affiliated with EAISI Health, SIKS Scientific Board, and the University of Waikato’s AI Institute.

Wiebe M. de Vosمشاهده پروفایل

استاد

• Membrane Science
• Polyelectrolyte Multilayers
• Nanofiltration
• +۷ مورد دیگر

Wiebe M. de Vos is a Full Professor at the MESA+ Institute, University of Twente, where he leads research in advanced membrane technologies. His work bridges fundamental polymer chemistry and practical applications in water treatment and sustainability. Full Professor, MESA+ Institute, University of Twente His research focuses on membrane science, particularly polyelectrolyte multilayer systems, nanofiltration, and sustainable material design. He investigates how surface chemistry, phase separation, and polymer interactions influence membrane performance in complex aqueous environments. His work addresses critical challenges such as nanoplastics removal, salinity management, and micropollutant degradation. The recent publications highlight a strong trend in developing next-generation membranes with enhanced stability, selectivity, and environmental compatibility. His team explores pH-responsive systems, biocatalytic membranes, and scalable fabrication methods, contributing significantly to both academic knowledge and industrial applications in water purification. No scientific awards were mentioned in the provided text. Dr. de Vos has supervised 22 academic works, indicating active mentorship of Master’s and PhD students. While specific grants are not detailed, his extensive research output and dataset publications suggest sustained funding and collaborative projects. His research integrates experimental design, material characterization, and process engineering. His work is conducted within the MESA+ Institute, a leading nanotechnology research center, fostering interdisciplinary collaboration in materials science and engineering.

Paul Boersmaمشاهده پروفایل

استاد

• Phonetics
• Phonology
• Computational Linguistics
• +۷ مورد دیگر

Paul Boersma is a Professor of Phonetic Sciences at the University of Amsterdam within the Faculty of Humanities. His research explores how phonetic, phonological, and morphological phenomena emerge through computational modeling using artificial neural networks and Optimality Theory, with a focus on multi-level constraint interactions and distributional learning. University of Amsterdam Faculty of Humanities Phonetic Sciences Key research areas include: Computational Modeling : Simulations of phonological category emergence from phonetic data Optimality Theory : Gradual Learning Algorithm applications BiPhon Framework : Parallel bidirectional phonology/phonetics models Statistical Learning : Cross-situational and distributional learning mechanisms Recent publications emphasize: 2025: Inclusive speech recognition systems using Whisper model 2025: F0 ratio analysis for creaky voice diagnostics 2024: Prosodic clitics in child speech and checked tones in Shanghai Chinese 2023: Distributional learning in developmental language disorder contexts 2022: Substance-free phonological features and ghost segment phenomena He has also contributed extensively to the Praat software for phonetic analysis, with continuous updates since 1993.

Nezihe Merve Gürelمشاهده پروفایل

استادیار

• Machine Learning
• Computer Science
• Pattern Recognition
• +۴ مورد دیگر

Nezihe Merve Gürel is an Assistant Professor in Computer Science at Delft University of Technology (TU Delft), affiliated with the Pattern Recognition & Bioinformatics Group within the Intelligent Systems Department of the Faculty of Electrical Engineering, Mathematics and Computer Science. Her research focuses on developing robust, reliable, and efficient machine learning methods with enhanced reasoning capabilities, bridging theoretical rigor and practical applications. She emphasizes data-centric approaches to improve ML systems. Education: PhD in Computer Science from ETH Zurich, MSc from EPFL (Switzerland). Research Interests: ML robustness, reliability, reasoning, data-centric ML, federated learning, and explainable AI. Her recent work includes certified robustness for retrieval-augmented models and time-efficient learning algorithms. She has contributed to the Journal of Data-centric Machine Learning Research as an executive editor and served as a reviewer for top ML conferences (NeurIPS, ICML, ICLR). She previously held roles at IBM Research, Stanford University's Human-Centered AI Lab, and Westlake Institute for Advanced Study. Her awards include the Generation Google Scholarship and Cisco Research Funding . Scientific Awards : Generation Google Scholarship (2021) Cisco Research Center University Funding Labs & Teams : She leads research in the Pattern Recognition Laboratory at TU Delft and collaborates with international institutions like Stanford and Westlake Institute for Advanced Study.

A.A.J.F. van den Dobbelsteenمشاهده پروفایل

استاد

• Sustainable Architecture
• Climate-Resilient Design
• Urban Climate Adaptation
• +۵ مورد دیگر

Prof. Dr. Ir. Andy van den Dobbelsteen is a Professor of Climate Design & Sustainability at Delft University of Technology's Faculty of Architecture and the Built Environment . His work focuses on integrating sustainable energy systems , climate adaptation strategies , and urban development through innovative design solutions. Department: Architectural Engineering + Technology Expertise: Energy systems, climate-responsive architecture, urban sustainability He actively translates research findings into actionable concepts for heritage building retrofitting , data center energy alternatives , and vertical urban farming , emphasizing interdisciplinary collaboration and knowledge transfer. His recent publications explore parametric modeling for energy efficiency, renewable backup systems , and synergetic urban design . He received prestigious awards including the edX Prize and Knight of the Netherlands Lion . 2020 edX Prize for Zero-Energy Design MOOC 2020 Golden Heron for educational film 'Energy Slaves' 2019 Solar Decathlon Europe 2nd prize As a dedicated educator, he supervises students in user-centred sustainability projects while maintaining active industry partnerships through secondary roles as speaker and columnist.

Maarten Renkemaمشاهده پروفایل

استادیار

• Artificial Intelligence
• Human Resource Management
• Digitalization
• +۵ مورد دیگر

Maarten Renkema is an Assistant Professor at the University of Twente, specializing in Artificial Intelligence (AI) and its intersection with Human Resource Management (HRM) , Healthcare , and Organizational Innovation . His research explores how AI transforms work design, employee autonomy, and HRM practices in formalized contexts. Key Research Themes: Algorithmic HRM and Digitalization Human-AI Collaboration in Healthcare Self-Managing Teams and Organizational Structures AI Literacy in Education Scientific Awards: Best Dissertation Award (2019) from the Dutch HRM Network Research Trends: His recent work focuses on AI adoption in HRM, ethical implications of algorithmic management, and redefining professional roles in AI-integrated environments. Articles from 2024-2025 highlight practical applications of AI in healthcare workflows, employee-driven innovation, and the evolving responsibilities of HR professionals. Collaborations: Active in cross-sector partnerships, including projects on AI literacy frameworks and talent management in sports. Regularly contributes to professional discourse through invited talks and media commentary on AI's societal impact.

• Robotics
• Control Systems
• Multi-Agent Systems
• +۶ مورد دیگر

Herman Bruyninckx is a Part-Time Full Professor at Eindhoven University of Technology (TU/e) in the Mechanical Engineering department, specifically within the Control Systems Technology group and EAISI High Tech Systems initiative. He also serves as a professor (Hoogleraar) at KU Leuven in Belgium. Academic focus on robotics, control systems, and multi-agent coordination Active research in model predictive control , semantic mapping , and dynamic constraint algorithms Recent publications address industrial automation , agro-food robotics , and haptic technology Research Highlights : Developed hybrid decision-making frameworks for multi-agent navigation Innovated swing-free control methods for robotic pick-and-place operations Formulated constrained dynamics algorithms with LQR-Gauss principle integration Created ExoTen-Glove for haptic feedback in virtual environments Collaborative Projects : Coordinated with researchers like René van de Molengraft , Elena Torta , and Koen de Vos Contributed to NWO/TTW FlexCRAFT project for cognitive robotics in agro-food technology

Laura Marusterمشاهده پروفایل

استادیار

• Process Mining
• Process Modelling
• Healthcare Networks
• +۵ مورد دیگر

Laura Maruster is an Assistant Professor at the Faculty of Economics and Business, University of Groningen, Netherlands. She holds an MSc from the West University of Timisoara, Romania, and a PhD in Technology Management from Eindhoven University of Technology, Netherlands. Her research focuses on process mining, process modelling, and healthcare networks, with applications in operations research and data science. She collaborates extensively with industry and public sector partners on projects like the Casimir initiative (RuG and Gasunie). Teaching areas include business processes, data mining, and research methodology. Recent work includes studies on healthcare logistics optimization and process mining beyond traditional workflows. Her publications appear in leading journals such as BMJ Open , IEEE Transactions on Engineering Management , and Computers in Industry . Research interests span healthcare networks, emergency medical services analytics, and enterprise process optimization. Notable recent contributions include analyzing interhospital patient transfers and redesigning engineering design processes using data-driven methods.

Pieter van Oelمشاهده پروفایل

دانشیار

• Water Resources Management
• Sociohydrology
• Drought Management
• +۹ مورد دیگر

Dr. Pieter van Oel is an Associate Professor in the Water Resources Management group at Wageningen University & Research, focusing on sociohydrology and addressing water crises in South America and Africa. His expertise spans civil/hydraulic engineering, environmental management, hydrology, irrigation systems, and drought diagnosis. He teaches courses like Design in Land and Water Management and supervises PhD students such as Louise Cavalcante and Daniel Wiegant. His research emphasizes societal dimensions of water challenges, including drought impacts, agent-based modeling, and serious gaming for community engagement. Projects include analyzing drought policies in Brazil, improving water governance in Kenya, and evaluating groundwater vulnerability in Ethiopia. He collaborates on initiatives like the Diagnosing Drought project and Socio-hydrological Simulation tool development. Key contributions include critiques of drought monitoring systems' alignment with local realities and frameworks for sustainable agroforestry management. His work bridges science and policy, advocating for interdisciplinary solutions to water scarcity and climate resilience.