جست‌وجوی استاد و پژوهشگر

Alessandro Zoccaمشاهده پروفایل

استادیار

• Applied Probability
• Stochastic Dynamics on Networks
• Power Systems Resilience
• +۳ مورد دیگر

Alessandro Zocca is an Assistant Professor in the Department of Mathematics at the Vrije Universiteit Amsterdam , where he has been since 2019. His research sits at the intersection of applied probability , reinforcement learning , and network optimization , with primary applications in power systems resilience against climate-driven uncertainties. Education: PhD in Mathematics (2015, Eindhoven University of Technology), Postdoctoral work at Caltech (2017-2019) and CWI Amsterdam (2016-2017) Key Research Themes: Stochastic dynamics on networks, climate crisis impact on infrastructure, optimization under uncertainty Awards: Applied Probability Trust award (2015), NWO Rubicon grant (2017) His recent work focuses on reinforcement learning for grid topology control, two-stage stochastic programming for exponential constraint handling, and Markov Chain Monte Carlo methods for rare-event analysis. He actively supervises five PhD students on topics ranging from weather-driven grid failures to stochastic frequency reserve optimization . Co-author of the textbook Hands-On Mathematical Optimization with Python (Cambridge University Press, 2025), he also organizes the IFIP Performance 2025 conference in Amsterdam.

Joost Hulshofمشاهده پروفایل

استاد

• Nonlinear Partial Differential Equations
• Mathematical Physics
• Fluid Dynamics
• +۴ مورد دیگر

Joost Hulshof is a Professor in the Department of Mathematics at the Faculty of Sciences, VU University Amsterdam. He maintains an office in room 9A-29 on the 9th floor of the NU building and is an active member of the Dynamical Systems and Analysis research group, where he serves as a project supervisor for students. His research spans a wide range of topics in applied mathematics with significant contributions to Nonlinear Partial Differential Equations , Mathematical Physics , and Fluid Dynamics . Specific research areas include flows in porous media, nonlinear diffusion, coronal loops of the sun, thin film viscous flows, turbulence models, combustion modeling, flame dynamics, free boundary problems, stability analysis of traveling waves, singularity formation, geometric flows, and mathematical modeling in physiology. More recently, his work has expanded into systems biology including glycolysis, optimization in metabolic pathways, and machine learning applications. His research demonstrates strong interdisciplinary connections between pure mathematical analysis and practical applications across physics, engineering, and biological sciences. Dr. Hulshof is an active participant in the academic community, having served as a local organizer for the "Problems in Operator Theory" conference held in October 2022 at VU University Amsterdam, which honored Professor André Ran on the occasion of his becoming Professor Emeritus. He is also a supporter of Bio Bob and Franks' lab, indicating strong collaborative relationships with biological research groups. While specific scientific awards are not detailed in the available information, Dr. Hulshof's extensive research portfolio, conference organization activities, and supervisory role suggest significant recognition within his fields of expertise. His work bridges theoretical mathematical concepts with real-world applications, particularly in industrial and medical contexts as noted in his research interests covering mathematics and industry, medical applications, and virus control.

Bram De Moorمشاهده پروفایل

استادیار

• Transportation Management
• Inventory Management
• Multi-Modal Supply Chains
• +۳ مورد دیگر

Bram De Moor is an Assistant Professor in the Operations, Planning, Accounting & Control group at Eindhoven University of Technology (TU/e), Department of Industrial Engineering & Innovation Sciences. His research focuses on transportation and inventory management, particularly in multi-modal, collaborative, and closed-loop supply chains. Education: B.Sc. (2018) and M.Sc. (2020) in Business Engineering from KU Leuven, Belgium; Ph.D. in Business Economics (2024) from KU Leuven's Research Center of Operations Management. His research applies advanced computational methods like deep reinforcement learning (DRL) to solve complex inventory control problems with multi-dimensional state and action spaces. He explores scalable solutions for practical implementation in sustainable logistics systems. Recent publications demonstrate novel approaches using continuous action representations in DRL, enabling faster training and handling of larger problem instances compared to discrete action methods. These studies bridge theoretical advancements with real-world supply chain applications. Bram is affiliated with the Operations Planning Acc. & Control group at TU/e, contributing to education through courses in Stochastic operations management and Circular service supply chain .

Marit Schoonhovenمشاهده پروفایل

دانشیار

• Statistical Process Control
• Lean Six Sigma
• Quality Management
• +۴ مورد دیگر

Dr. Marit Schoonhoven is an Associate Professor at the University of Amsterdam , affiliated with the Faculty of Economics and Business and the Business Analytics department. Since 2007, she has been instrumental at IBIS UvA, delivering Lean Six Sigma Green Belt and Black Belt training while guiding process improvement projects for organizations including Zwitserleven, AEGON, Deventer Hospital, and the University Medical Center Utrecht. Research Focus : Her work centers on control charts and statistical process control, extending to applications in healthcare efficiency, educational analytics, and Bayesian modeling. She frequently publishes in journals like the Journal of Quality Technology and Technometrics . Key research areas: Statistical Process Control, Lean Six Sigma, Healthcare Operations, Bayesian Modeling Recent article trends: Bayesian graphical models for Alzheimer’s disease, multilevel monitoring in education, nonparametric control in dynamic systems

Antoinette van Laarhovenمشاهده پروفایل

دانشیار

• Psychophysiology
• Chronic Itch
• Chronic Pain
• +۵ مورد دیگر

Antoinette van Laarhoven is an Associate Professor at the Health, Medical and Neuropsychology Unit of Leiden University , Netherlands. Her research focuses on psychophysiological mechanisms in chronic itch and pain , with emphasis on attentional processes , expectancies , and placebo/nocebo effects . She employs quantitative sensory testing (QST) , EEG , behavioral tasks , and virtual reality to explore biomarkers for chronic disease prevention and personalized treatment . Education: MSc in Biomedical Sciences, Radboud University (2006) PhD in Medical Science, Radboudumc (2012) Research Interests: Psychophysiology of Itch and Pain : Investigating common and distinct mechanisms in inflammatory (e.g., atopic dermatitis) and non-inflammatory conditions (e.g., fibromyalgia). Expectancy-Driven Sensory Modulation : How expectations influence symptom aggravation or relief through placebo/nocebo effects . Attentional Biases : Using tasks like dot-probe and Flanker to study attention allocation toward somatic cues. Virtual Reality Applications : Testing immersive environments for sensory perception research. Article Trends: Recent work synthesizes placebo/nocebo generalization , biopsychosocial factors in chronic skin conditions , and neurophysiological correlates of learned aversion . Keywords span psychology , neuroscience , dermatology , and pain research , with sub-fields like expectancy theory , attentional bias modification , somatosensory integration , and clinical intervention design . Scientific Awards: John de Korte Travel Grant (2019) IFSI Travel Grants (2013, 2015, 2024) ARPH PhD Thesis Award (2013) Herman Musaph Article Prize (2012) Advising and Grants: She supervises PhD candidates in projects like "Expect to Avoid" and "Placebo-Itch Interactions ". Her grants include NWO Gravitation Grant (2019), Veni Grant (2015), and Netherlands Organisation for Scientific Research funding.

Cindy Shuan Ju Tehمشاهده پروفایل

دانشیار

• Antimicrobial Resistance (AMR)
• Microbiology
• Molecular Epidemiology
• +۳ مورد دیگر

Dr. Cindy Shuan Ju Teh is an Associate Professor at the Faculty of Medicine, Universiti Malaya, Malaysia. Her work spans antimicrobial resistance (AMR), molecular microbiology, and hospital/community epidemiology, with a focus on multidrug-resistant organisms (MDRO) and their impact on public health. Teaching : Educates students in AMR and infectious disease transmission across MBBS, Biomedical Science, Nursing, and Dentistry programs. Leadership : Serves as Chairperson of the Institutional Biosafety and Biosecurity Committee (IBBC) and former Quality Manager (2018-2022) at the Faculty of Medicine. Research Interests center on AMR mechanisms, MDRO transmission dynamics, gut microbiome analysis, and behavioral psychology in healthcare compliance. She integrates molecular approaches with clinical and environmental studies to address AMR. Publications include over 100 peer-reviewed papers on topics like Carbapenem-Resistant Enterobacteriaceae , Flomoxef Efficacy , and Impact of Diet on Microbiome . Her work also explores AI-driven models for infectious disease trends. Scientific Awards L’Oréal-UNESCO Women in Science Fellowship (2021) MSIDC-Institut Mérieux Young Researcher Award (2018) Multiple medals at national and international innovation exhibitions Grants : Secured over 40 national and international research grants totaling RM10 million. Outreach : Develops educational initiatives to combat AMR in schools and authored the public awareness book AMR Diary (2023).

• Applied Data Science
• Human-centered Artificial Intelligence
• Privacy in Collaborative Systems
• +۴ مورد دیگر

Dr. Onuralp Ulusoy is a Researcher at Utrecht University's Faculty of Science, specifically within the Software Technology for Learning and Teaching department. Based at the Buys Ballot Building in Utrecht, he focuses on the intersection of privacy, artificial intelligence, and collaborative systems. His research spans Applied Data Science and Human-centered Artificial Intelligence, with particular emphasis on privacy mechanisms in online environments. Ulusoy's work explores how privacy norms emerge and can be managed in collaborative settings, especially within social networks. His publication record shows a clear trajectory in privacy research, evolving from foundational work on privacy auctioning mechanisms to more recent applications in learning analytics. His most cited work, 'PANOLA: A Personal Assistant for Supporting Users in Preserving Privacy' (2022), demonstrates practical applications of his theoretical frameworks. Recent publications indicate an expansion into educational technology with tools like 'mAIchart' for primary school educators. As a researcher at Utrecht University, Ulusoy has established himself as a specialist in privacy-preserving collaborative systems, with publications spanning top conferences in multi-agent systems, access control, and social network analysis.

• Traffic Engineering
• Transportation Systems
• Pedestrian Flow Modeling
• +۴ مورد دیگر

Serge Hoogendoorn is a Professor in Traffic Systems Engineering within the Faculty of Civil Engineering & Geosciences at Delft University of Technology. With over 1,000 research outputs to his name, including 360 articles and 541 conference contributions, he stands as a leading figure in transportation research. His work spans theoretical foundations and practical applications in traffic engineering, with a particular focus on innovative modeling approaches. His educational background, though not explicitly detailed in the provided text, reflects the 'dr.ir.' designation in his title, indicating both a doctorate and engineering degree from the Dutch academic system. His research interests center around traffic flow theory , pedestrian dynamics , intelligent transportation systems , and mobility as a service , with recent work increasingly incorporating artificial intelligence and machine learning techniques. Analysis of his recent publications (2023-2025) reveals a strong trend toward applying advanced computational methods to transportation challenges. His work bridges theoretical traffic flow models with practical applications, particularly in pedestrian flow prediction, driving behavior analysis, and active transportation mode forecasting. The research demonstrates increasing integration of spatiotemporal modeling , graph neural networks , and synthetic data generation techniques to address complex mobility challenges. ERC Advanced Grant 2015 D. Grant Mickle Award 2016 Greenshields Prize 2016 Recognition for Dynamic speed limit control to resolve shock waves on freeways Professor Hoogendoorn has supervised 59 students throughout his career and has been actively involved in numerous research projects, most notably the CriticalMaaS project (2019-2023) focused on Mobility as a Service. His research group appears to collaborate extensively with colleagues like S. Hoogendoorn-Lanser, O. Cats, and N. van Oort. Beyond traditional academic work, he maintains strong engagement with public discourse on mobility topics, as evidenced by 27 press/media appearances discussing AI in mobility, intelligent bike paths, and post-pandemic traffic patterns. His work has practical applications in traffic management systems, pedestrian infrastructure design, and future mobility planning.

• Neuroscience
• Clinical Neuropsychology
• Emotion Processing
• +۴ مورد دیگر

Katharina Görlich is a researcher affiliated with the Faculty of Behavioural and Social Sciences and the Faculty of Medical Sciences at the University of Groningen. Her work focuses on neuroscience, clinical neuropsychology, and emotion processing, with a particular emphasis on alexithymia and its intersections with social hierarchy, hormonal abnormalities, and cutaneous disease morbidity. Schools : Faculty of Behavioural and Social Sciences, Faculty of Medical Sciences Department : Department of Clinical & Developmental Neuropsychology Email : k.s.gorlich@umcg.nl Research Interests include: Social hierarchy and emotion perception Neurocomputational mechanisms in fear-biased learning Hormonal and physiological correlates of alexithymia Impact of alexithymia on dermatological and psychiatric conditions Neuroimaging (fMRI) studies on cognitive-emotional interactions Behavioral neuroscience in social contexts Recent Publications highlight her work on: Dynamic interplay of social hierarchy and fairness perception (2025) Neural sensitivity to hierarchy in competitive settings (2024) Hormonal dysregulation in alexithymia (2023) Computational models of fear adaptation (2023) Alexithymia's role in dermatological morbidity (2022) Neuroimaging of inhibitory control in Parkinson's patients (2022)

Q.A. Stokkinkمشاهده پروفایل

پژوهشگر

• Blockchain
• Web3
• Identity Management Systems
• +۳ مورد دیگر

Q.A. Stokkink is a researcher at Delft University of Technology's Faculty of Electrical Engineering, Mathematics and Computer Science, specializing in the Data-Intensive Systems group. Their work bridges theoretical computer science and practical decentralized system design. Research focuses on critical challenges in Web3 infrastructure, including: Sybil attack prevention through network latency analysis Energy-efficient smart contract implementations Digital self-sovereignty frameworks Decentralized reputation systems Recent publications demonstrate innovative approaches to transformer-based ranking in peer networks and green computing for blockchain applications. Notable recognition includes the prestigious LCN Best Paper Award 2021 for foundational work in reputation-based data carrying. Research outputs include 10 peer-reviewed publications, 3 curated datasets, and active contributions to open-access academic resources through TU Delft's 4TU.ResearchData repository. Stokkink's work shows strong industry relevance with prototype implementations referenced in 2 Wikipedia pages and engagement across academic platforms (25+ Mendeley readers). Current projects emphasize practical Web3 solutions balancing security, efficiency, and user control in decentralized environments.

• Scaphoid Fracture
• Patient-Reported Outcome
• Nonunion
• +۵ مورد دیگر

Abi Cohen is a Researcher at Erasmus MC, specializing in the Department of Orthopedics and Sports Medicine. Their work focuses on scaphoid fractures, nonunion conditions, and patient-centered outcomes in orthopedic trauma care. Research Interests: Active in domains such as Scaphoid Fracture, Patient-Reported Outcome, Nonunion, and Wrist Injury. Recent studies also address the impact of the COVID-19 pandemic on orthopedic patient recovery and the role of morphological analysis in fracture risk assessment. Research Trends: Abi Cohen's recent publications include Multicenter randomized controlled trials on conservative treatment strategies for suspected scaphoid fractures Evaluations of surgical indications for nonunion in minimally symptomatic patients Case-control studies on anatomical risk factors for scaphoid fractures Population-level analyses of pandemic-related disruptions in arthroplasty outcomes Machine learning models to improve diagnostic accuracy in wrist trauma Collaborations: Collaborated with the SUSPECT study group and the Machine Learning Consortium, contributing to clinical guidelines and diagnostic technologies in orthopedic surgery.

Zaharah Bukhshمشاهده پروفایل

استادیار

• Data-driven decision support technologies
• Deep reinforcement learning
• Learning-based optimization methods
• +۵ مورد دیگر

Zaharah Bukhsh is an Assistant Professor in the Information Systems group at Eindhoven University of Technology (TU/e), specializing in data-driven decision support technologies with a focus on deep reinforcement learning applications for operational optimization challenges including resource utilization, cost optimization, planning, and scheduling. Her academic background includes: MSc in Information Systems Engineering (2015) from the University of Twente PhD in Operations Research (2019) from the University of Twente, with research focused on data-driven decision support methods for transport infrastructure maintenance planning Dr. Bukhsh's research extends to process mining for monitoring and improving operational processes. She has established strong industry collaborations with organizations including Rijkswaterstaat and IrishRail, as well as academic partnerships with ETH Zurich, Trinity College Dublin, and TU Delft. Her PhD research was funded by the H2020 projects DESTination RAIL and COST ACTION TU1406. Her recent publication portfolio shows a clear trend toward developing hybrid approaches that combine simulation with deep reinforcement learning to address real-world operational challenges. The research demonstrates significant improvements in cycle time reduction (up to 307%) and resource allocation efficiency across various business process and scheduling contexts. Her work bridges theoretical AI advancements with practical applications in infrastructure management and business process optimization. Before joining TU/e in 2021, Dr. Bukhsh contributed to the PrimaVera (NWO) project as a post-doc researcher at Radboud University. She teaches courses on Business Analytics & Decision Support and Data-Driven Artificial Intelligence, reflecting her commitment to translating cutting-edge research into educational content.

Remco Dijkmanمشاهده پروفایل

استاد

• Business Process Management
• Data-driven Optimization
• Quantitative Business Process Analysis
• +۴ مورد دیگر

Remco Dijkman is a Full Professor in Information Systems and chair of the Information Systems group at Eindhoven University of Technology (TU/e) within the Industrial Engineering and Innovation Sciences school. He leads research in Business Process Management with a focus on data-driven optimization of business processes. His work bridges theoretical advancements with practical applications in transportation and high-tech supply chains. Dr. Dijkman received his PhD and Master's degrees in computer science from the University of Twente. His academic journey includes visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. PhD in Computer Science - University of Twente Master's in Computer Science - University of Twente Professor Dijkman's research focuses on the detection, diagnosis and prediction of optimal execution scenarios, mathematical models for quantitative analysis of business processes, and resource assignment optimization. His work integrates advanced techniques including queueing models, stochastic programming, and deep reinforcement learning to solve complex business process challenges. He has particular expertise in applying these methods to transportation logistics and high-tech supply chain planning, where he investigates how data-driven predictions can improve transport order assignment and supply chain planning. His recent publications demonstrate a strong trend toward integrating artificial intelligence techniques with traditional operations research methods. The research shows increasing sophistication in handling uncertainty in business processes, with a growing emphasis on real-time decision making and optimization. His work spans theoretical advancements in process modeling and practical applications in logistics and supply chain management, reflecting his commitment to bridging academic research with industry needs. Professor Dijkman serves on the editorial board of Information Systems journal and has published over 100 papers in prestigious venues including Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology. He currently leads or participates in several major research projects including DynaPlex, CERTIF-AI, SLEM, and FENIX. Additionally, he serves as research director for high-tech supply chain at the European Supply Chain Forum, a networking organization with over 50 multinational companies. His adjunct professorship at Queensland University of Technology demonstrates his international academic engagement. Professor Dijkman's research group focuses on developing advanced methods for business process analysis and optimization, with particular emphasis on handling uncertainty and making real-time decisions in complex business environments. The team works closely with industry partners to ensure practical relevance of their research, particularly in transportation and high-tech manufacturing sectors.

Nieske Vergunstمشاهده پروفایل

پژوهشگر

• Science Communication
• Sustainability Education
• Climate Change Communication
• +۴ مورد دیگر

Dr. Nieske Vergunst is a Science Communication Researcher at the Center for Science and Culture , Utrecht University. As part of the Faculty Open Science Team and Freudenthal Institute, she focuses on improving public engagement with science through innovative methods like serious games and dilemma-based educational tools. PhD in Artificial Intelligence (2011, Utrecht University) Research Themes: Bridges climate science communication with youth engagement via games like the Sea Level Game , targeting accessibility for diverse audiences. Her work spans: Sustainability Education Science Communication Strategies Board Game Design for Learning Public Engagement Metrics AI-Driven Dialogue Systems Robotics Social Reasoning Recent Scientific Outputs demonstrate expertise in climate gamification and AI communication frameworks. She has also authored two popular-scientific books: Oorlogsbrieven (2016) and Hallo Robot (2017), with international translations.

Clara Maathuisمشاهده پروفایل

استادیار

• AI (Technical/Responsible/Trustworthy)
• Cyber Security
• Military Technologies
• +۵ مورد دیگر

Clara Maathuis is an Assistant Professor in AI and Cyber Security at Open University, with a PhD in Military Cyber Operations and AI from TU Delft. Her research focuses on designing intelligent systems that respect ethical, social, and legal norms, particularly in military, security, and societal contexts. She develops courses in Machine Learning and Responsible AI while contributing to interdisciplinary research in cyber security, autonomous weapon systems, and digital twins. Primary Affiliation: Open University (Assistant Professor) Research Domains: AI, Cyber Security, Military Technologies, Social Media Manipulation, XR/AR/VR Teaching Focus: Responsible AI, Machine Learning, Cyber Security Key Collaborations: 4TU.Ethics and Technology Her recent publications emphasize hybrid AI models for military operations, safety protocols in autonomous systems, and ethical integration of AI in extended reality environments. She also explores applications in police conflict training, sensor data analysis, and open-source software evolution. Clara's work bridges technical AI advancements with critical societal issues, including disinformation awareness, digital sovereignty frameworks, and inclusive software engineering practices.