جستجوی استاد راهنمای دانشگاهی

Martijn C. Willemsenمشاهده پروفایل

دانشیار

• Human-Technology Interaction
• Decision Making in Online Environments
• Recommender Systems
• +۷ مورد دیگر

Martijn C. Willemsen is an Associate Professor at Eindhoven University of Technology (TU/e) and Jheronimus Academy of Data Science (JADS), specializing in human decision making within interactive systems. His roles include EAISI Foundational Associate Professor and Human Technology Interaction Associate Professor. He holds an MSc in Electrical Engineering and Technology & Society from TU/e, followed by a PhD in decision-making psychology and a Veni grant from NWO. His research focuses on cognitive aspects of Human-Technology Interaction, particularly judgment and decision-making in online environments, with applications in recommender systems, explainable AI, and health behavior change. Education: MSc in Electrical Engineering (TU/e), MSc in Technology & Society (TU/e), PhD in Psychology of Decision Making. Academic Background includes postdoc work at Columbia University developing mouselabWEB for studying decision processes, and collaborations with institutions like Clemson University on IoT privacy research. Research interests span interactive AI, decision-support systems (e.g., health, energy-saving), and process tracing methods. He leads projects like TEPAIV (2018–2024) on explainable AI and visualization. Over 114 publications in venues like CHI, IUI, RecSys, and journals such as User Modeling and Psychological Review. Scientific Awards: Veni Grant (NWO), AlignAI Prize (ERC, 2024). Active in grants including NWO/NSF-funded IoT privacy projects. Teaches courses on Cognitive Science, AI, and data science at JADS and TU/e. Labs/Teams: Part of Human Technology Interaction group at TU/e. Collaborates with industry on health coaching technologies and AI-assisted decision tools. Recent work emphasizes interactive systems that foster behavioral change rather than reinforcing existing habits.

Iris Huijbenمشاهده پروفایل

پژوهشگر

• Representation Learning
• Sleep Medicine
• Medical Signal Processing
• +۳ مورد دیگر

Iris Huijben is a Researcher and Doctoral Candidate in the Signal Processing Systems group at Eindhoven University of Technology (TU/e). Her work bridges signal processing and deep learning in sleep medicine and fetal health monitoring. She holds an MSc in Electrical Engineering (cum laude, 2019) from TU/e and is pursuing a PhD under Prof. Ruud van Sloun, focusing on discrete representation learning for sleep recordings. Research Interests: Representation learning for biomedical signals, fetal health assessment using cardiotocograms, sleep stage analysis, and machine learning-driven data compression. Key Projects: Developed attention mechanisms for sleep stage classification, improved fetal health anomaly detection with contrastive predictive coding, and analyzed temporal dynamics of parasomnia awakenings. Collaborations: Research internship at Qualcomm AI Research (Amsterdam) on data compression. Publications highlight advancements in medical AI, including real-time fetal monitoring systems and sleep dynamics analysis. Awards include TU/e’s MSc Thesis Award 2020 for work on sub-Nyquist sampling in medical ultrasound.

• Functional Magnetic Resonance Imaging
• Visual Cortex
• Decision-Making
• +۵ مورد دیگر

Tomas Knapen is an Assistant Professor at the Faculty of Behavioural and Movement Sciences and the IBBA at Vrije Universiteit Amsterdam. His research focuses on Functional Magnetic Resonance Imaging (fMRI) , Visual Cortex dynamics, Decision-Making , and Neuroimaging Methodologies . He leads the PERISCOPE project exploring peripheral vision in visual search and has contributed to advanced 7-Tesla MRI techniques for studying brain disorders like major depressive disorder. He teaches courses on Brain Imaging and Neural Models of Cognitive Processes . Research Interests: Visual perception, neuroimaging, attention mechanisms, and computational modeling of sensory systems Supervised 6 PhD theses, with ongoing research into cortical plasticity and psychedelic effects on visual processing Active in developing open-source neuroimaging tools like Porcupine and Connective Field Modeling His work bridges cognitive neuroscience with cutting-edge neuroimaging techniques, advancing our understanding of brain function and disorders.

• Computer Security
• Operating Systems
• Hardware Security
• +۳ مورد دیگر

C Giuffrida is an Associate Professor at the Faculty of Science, Vrije Universiteit Amsterdam, with affiliations to the Network Institute and the Systems and Network Security group. His research focuses on computer systems security, hardware vulnerabilities, and software reliability. Giuffrida holds a PhD in Computer Systems from Vrije Universiteit Amsterdam (2014). His academic contributions span multiple areas including transient execution attacks, fuzzing techniques, and hardware-software co-design for security. Research Interests: Hardware Security: Investigating vulnerabilities like Spectre, Rowhammer, and speculative execution risks. Software Security: Focusing on memory safety, compiler optimizations, and exploit mitigation strategies. Systems Research: Developing tools like BinRec for binary analysis and VPS for C++ vulnerability protection. His work has been recognized with awards such as the Distinguished Paper Award in 2021. Giuffrida supervises advanced courses in operating systems and hardware security, and has guided 16 PhD theses to completion.

Fabio Massacciمشاهده پروفایل

استاد

• Cybersecurity
• Software Security
• Security Economics
• +۵ مورد دیگر

Prof. Fabio Massacci is a Full Professor at the Faculty of Science (Computer Systems Department) and Network Institute of Vrije Universiteit Amsterdam. He concurrently holds a part-time professorship in Computer Science at Università degli studi di Trento. His research focuses on cybersecurity, software supply chain risks, security economics, and experimental methods for vulnerability analysis. He earned a PhD in Computer Science from La Sapienza University of Rome (1998). Research interests include software ecosystem security, malware analysis, security policy design, and risk assessment frameworks. Notable contributions include the 2015 IEEE RE Ten Years Most Influential Paper Award for work on socio-technical security systems. Recent studies explore AI in vulnerability detection, cloud configuration security, and GDPR compliance in educational institutions. Teaching responsibilities include courses on Security and Safety Engineering, Security Experiments, and Data Structures for AI. Key projects include the HEWSTI initiative (Hybrid Explainable Workflows for Threat Intelligence) and studies on cybersecurity training in European education programs. Collaborations span global institutions, with datasets published on Zenodo and IEEE DataPort.

Jiahuan Peiمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing
• Dialogue Systems
• +۳ مورد دیگر

Dr. Jiahuan Pei is an Assistant Professor at the Vrije Universiteit Amsterdam, affiliated with the Faculty of Science's Department of Artificial Intelligence, the Network Institute, and Social AI. His research focuses on advanced AI applications in dialogue systems, natural language processing (NLP), and large language models (LLMs), with particular emphasis on clinical and therapeutic contexts. Recent work includes improving conversational recommendation systems, enhancing psychotherapy dialogue generation through motivational interviewing strategies, and developing multilingual dialogue management techniques. Key research topics include information retrieval robustness in LLMs, parameter-efficient fine-tuning methods (e.g., MELoRA), and the ethical integration of AI in healthcare. He has contributed to seminal studies on dialogue alignment, faithfulness metrics for citations, and perceptual quality in 3D point clouds. His work often bridges theoretical NLP advancements with practical applications in healthcare, education, and mixed reality environments. Pei's articles reflect a strong focus on innovation in dialogue systems, with over 15 peer-reviewed publications since 2020. He teaches the Project Conversational Agents course, emphasizing hands-on AI development. Collaborations span academic and industry partners, addressing challenges in cross-lingual communication, therapeutic AI, and multimodal training systems.

• Consumer Neuroscience
• Marketing
• Neuroscience
• +۳ مورد دیگر

Letizia Alvino is an Assistant Professor at Delft University of Technology, specializing in Consumer Neuroscience, Marketing, and Entrepreneurship. Her research focuses on applying neuroscience tools to study consumer behavior, particularly in the domains of wine, advertising, and sustainable consumption. She contributes to the UN Sustainable Development Goals through studies on circular economies and sustainable healthcare strategies. Her work bridges neuroscience and marketing, using methods like electroencephalography (EEG) and eye-tracking to analyze how consumers perceive products and brands. Key collaborations include studies on circular healthcare economies and neuromarketing applications in advertising effectiveness. Alvino has authored influential books and datasets, including Creating a Circular Healthcare Economy and coded neuromarketing literature reviews. Alvino’s research also addresses sustainable consumption patterns, exploring how consumers respond to product attributes and sustainability claims. Her articles frequently analyze the interplay between rational and emotional decision-making processes. Awards and recognitions include an h-index of 23 and over 230 citations. She actively disseminates findings through peer-reviewed journals and media engagements like the Circular Economy Knowledge Agenda project.

• Software Engineering
• Machine Learning
• Software Testing
• +۵ مورد دیگر

Dr. Kwabena Bennin is an Assistant Professor in the Information Technology Group at Wageningen University & Research. His expertise spans software engineering, machine learning, and software quality assurance. He holds a PhD in Computer Science from City University of Hong Kong and a BA (Hons) in Computer Science and Statistics from the University of Ghana. His research focuses on applying AI to software engineering tasks, including defect prediction, automated testing, and software analytics. He has conducted extensive studies on machine learning applications in agriculture, such as plant disease detection using deep learning. Bennin also explores recommender systems for sustainable online food choices and has experience in distributed software development methodologies. He has over 40 international publications and has worked as a Postdoctoral researcher at Blekinge Institute of Technology and a Data Science Consultant at Ericsson. His current projects include developing socio-technical decision support systems for healthy and sustainable food choices in online shopping platforms. Key Skills: Software Architecture, Empirical Software Engineering, Precision Agriculture Analytics Education: PhD in Computer Science, City University of Hong Kong BA (Hons) in Computer Science and Statistics, University of Ghana His work integrates technical innovation with real-world applications, addressing challenges in both software systems and agricultural technology domains.

Federico de Martinoمشاهده پروفایل

استاد

• Neuroimaging
• Auditory Perception
• Machine Learning
• +۳ مورد دیگر

Federico de Martino is a Full Professor at Maastricht University's Faculty of Psychology and Neuroscience (FPN), specializing in Sensory Circuits and Neuroimaging. He holds an honorary researcher position at the Center for Magnetic Resonance Research (CMRR) in Minneapolis, USA. His research integrates computational models with high-resolution neuroimaging techniques to study auditory perception and predictive coding in the brain. Education: Graduated in Electronic Engineering (cum laude) from Sapienza University of Rome (2003), earned a PhD in Cognitive Neuroscience from Maastricht University (2008). Career milestones include roles as Post-Doctoral Fellow (2008-2011), Research Associate at CMRR (2009-2012), Assistant Professor (2011-2017), and Associate Professor (2017-2022) at FPN. Research interests focus on ultra-high field MRI (7T+), mesoscopic neural computations, and the functional organization of auditory pathways. Key projects include mapping auditory circuits at sub-millimeter resolution and investigating vascular underpinnings of fMRI signals. Collaborations span institutions like CMRR, University of Glasgow, and Max Planck Institute. Teaching roles include coordinating fMRI data analysis courses at FPN and the Maastricht Science Program. He co-chairs the Maastricht Brain Imaging Center (MBIC) Graduate School and leads FPN's MRI user support group. Active in science outreach as a founding member of the Maastricht Young Academy (MYA) and co-chair of the Growing Up in Science (GUS) initiative. Grants include an NWO VIDI grant (auditory pathway mapping), NIH Brain Initiative funding (laminar fMRI), and an ERC Consolidator grant (predictive listening). Recent publications emphasize high-resolution auditory imaging, predictive coding, and methodological advancements in neuroimaging.

• Software Engineering
• Machine Learning
• Precision Agriculture
• +۷ مورد دیگر

Önder Babur is an Assistant Professor in the Department of Information Technology at Eindhoven University of Technology. His research focuses on software engineering, machine learning applications, precision agriculture, and digital twin technologies. He has contributed to projects involving business process modeling, drone analytics, and energy market methodologies. Babur collaborates with institutions like Wageningen University & Research and has supervised PhD candidates in generative AI approaches and digital twin systems. His research interests span model analytics, clone detection, API usage analysis, and low-code platforms. Notable projects include an empirical study of business process models on GitHub and foundational work in digital twins for energy markets. Babur has co-developed datasets for drone imagery analysis and systematic reviews of food recommender systems. His work bridges theoretical software engineering advancements with practical applications in agriculture and energy systems. Advising PhD candidates include Gürkan Soykan (digital twins in energy markets) and Jeroen Doornbos (generative AI in drone analytics). Projects emphasize collaborative frameworks like SAMOS for model management and Apache Spark-based distributed analytics. Babur’s contributions span 45+ peer-reviewed publications and two active PhD supervisions.

Eddy Cardinaelsمشاهده پروفایل

استاد

• Experimental Accounting Research
• Management Accounting Systems
• Artificial Intelligence in Accounting
• +۷ مورد دیگر

Prof. Dr. Eddy Cardinaels is a Full Professor of Accounting at Tilburg University and part-time professor at KU Leuven. He holds positions in the Tilburg School of Economics and Management (TiSEM) within the Department of Accountancy. His research focuses on experimental and archival studies in accounting, including AI applications in performance evaluations, management control systems, and audit quality. He has authored over 50 publications in leading journals like The Accounting Review and serves as editor for multiple journals. Education and Career: Prof. Cardinaels earned his PhD and has held academic roles since 1997. He has supervised numerous PhD students, including Huaxiang Yin, Victor van Pelt, and Qinnan Ruan. His editorial roles include editorships at Accounting Horizons , Journal of Management Accounting Research , and others. Research Interests: His work explores decision-making under social motives, audit office dynamics, and corporate governance. Key areas include AI integration in auditing, social capital effects on audit quality, and compensation design for innovation adoption. Recent studies address AI’s role in audit efficiency and ethical reporting under conflicting incentives. Publications: His recent work includes studies on audit 2.0 with AI, social capital in Big 4 auditors, and CSR disclosures in buyer-seller markets. These articles highlight his focus on modernizing accounting practices through technology and ethical frameworks. Awards: He has received prestigious awards such as the AAA’s Greatest Impact on Practice Award and the Jim Bulloch Award for contributions to management accounting research. Advising & Grants: Prof. Cardinaels has advised over 20 PhD students and led research projects on auditor allocation and decision-making. His grants examine topics like partner risk reduction and multi-agent budgeting systems. Labs/Teams: His research group collaborates internationally, focusing on experimental accounting, healthcare management, and audit behavior. He also leads initiatives on ESG contracting and tax avoidance strategies.

Mohsen Ghanbariمشاهده پروفایل

دانشیار

• Molecular Epidemiology
• Genetics
• Multi-Omics
• +۱۲ مورد دیگر

Mohsen Ghanbari is an Associate Professor in the Department of Epidemiology at Erasmus MC, Rotterdam. He leads the 'Molecular & Systems Epidemiology' research line as Principal Investigator, overseeing a multidisciplinary team of MSc students, PhD candidates, postdoctoral researchers, and lab technicians. His work is deeply embedded in large-scale population studies, including the Rotterdam Study and the Erasmus Rucphen Family (ERF) study. Research Interests: Dr. Ghanbari’s research focuses on uncovering genetic determinants and identifying novel biomarkers for complex age-related diseases such as Alzheimer’s disease, cardiometabolic disorders, and fatty liver disease. He integrates multi-omics data—genomics, epigenomics, metabolomics, and transcriptomics—using advanced analytical and molecular techniques. His work aims to elucidate disease mechanisms and improve early diagnosis and risk stratification. Recent Research Trends: His most recent publications (2025) highlight a strong focus on aging, biomarker discovery, and population genomics. Articles span diverse areas including metabolomics of adipose tissue, plasma microRNA signatures in aging, Y-chromosome variation in forensics, environmental-genetic interactions in mortality, and non-coding RNA in eye disorders. These reflect a cohesive trajectory toward systems-level understanding of aging and complex diseases. Scientific Recognition: His work has been published in high-impact journals such as Nature Medicine , Genome Medicine , and Human Genetics . His research has been widely disseminated, with mentions in 325 news outlets, over 1,000 posts on X (formerly Twitter), and engagement across Facebook, Bluesky, and Reddit, indicating significant academic and public impact. Teaching and Supervision: Dr. Ghanbari is actively involved in academic education, coordinating multiple courses through the Netherlands Institute for Health Sciences (NIHES) at Erasmus MC Graduate School. He supervises MSc and PhD students, though specific names are not listed in the provided text. He also manages omics data for the Rotterdam Study and leads the ERF study. Collaborations and Infrastructure: He participates in numerous international multicenter consortia focused on population omics and age-related diseases, reflecting a strong collaborative network. His lab functions as a hub for molecular and systems epidemiology, integrating bioinformatics with experimental validation.

• Genome-Wide Association Study
• Cohort Analysis
• Genetic Divergence
• +۴ مورد دیگر

FJA van Rooij is an active researcher in the Department of Epidemiology at Erasmus University Medical Center, specifically affiliated with the Erasmus School of Health Policy & Management. Their work centers on large-scale genetic and cohort studies, leveraging data from initiatives like the Rotterdam Study, VA Million Veteran Program, and NHLBI Trans-Omics for Precision Medicine Consortium. Research interests focus on genome-wide association methodologies, cardiovascular disease mechanisms, and pharmacological epidemiology. Key areas include genetic regulation of coagulation factors (fibrinogen, factor VIII), microRNA biomarkers for aging populations, and validation of data-driven approaches in antihypertensive prescription analysis. This work bridges molecular genetics with population health through multi-ethnic cohort analyses. Recent publications demonstrate expertise in cohort study design and genetic epidemiology, with trends emphasizing translational applications of genomic data for cardiovascular risk prediction and drug utilization research. Collaborations span major international consortia including TOPMed and INVENT, highlighting integration of omics data with clinical outcomes. No scientific awards are documented in the provided profile. Van Rooij participates in collaborative research networks without explicit mention of independent grant leadership or student supervision in the scraped content. Their work is embedded within institutional cohort studies like the Rotterdam Study, which serves as a primary data source for cardiovascular and genetic epidemiology research at Erasmus MC.

• Genetics
• Brain Development
• Regulatory Elements
• +۶ مورد دیگر

Eva Medico Salsench is a Researcher in the Clinical Genetics department at Erasmus MC, focusing on the molecular mechanisms of genetic brain disorders. Her work bridges fundamental genetic research with clinical applications, particularly in understanding regulatory elements and enhancer regions in neurodevelopment. Her research interests center on the non-coding genome's role in brain disorders, with specific expertise in enhancer regions, regulatory elements, and zebra fish models for studying neurological conditions. She investigates how mutations in genes like AMFR and YIF1B lead to disorders such as hereditary spastic paraplegia and other neurodevelopmental conditions, with recent work exploring potential statin treatments for genetic neurological disorders. Her publications from 2021-2023 demonstrate a strong focus on integrating multi-omics approaches to understand brain development and genetic disorders. The research spans from basic mechanisms of gene regulation to clinical applications, with particular attention to autosomal recessive inheritance patterns and potential therapeutic interventions. Dr. Medico Salsench collaborates extensively with international research teams across Europe and beyond, as evidenced by her multi-author publications with researchers from various institutions worldwide. Her work has gained attention in academic circles with significant citation counts and social media engagement.

Anja Ernstمشاهده پروفایل

استادیار

• Statistics & Probability
• Intensive Longitudinal Data Analysis
• Statistical Modeling
• +۴ مورد دیگر

Dr. Anja Ernst is an Assistant Professor at the University of Groningen's Faculty of Behavioural and Social Sciences, affiliated with the Psychometrics & Statistics Department. She holds a PhD in Dynamic Clustering (2022) and focuses on statistical modeling for intensive longitudinal data, clustering methods, and software implementation. Her research includes developing latent class vector-autoregressive models and promoting open-source tools via GitHub and the Open Science Framework. Education: BSc Psychology (cum laude), Honours College Research Master in Psychometrics & Statistics (cum laude) PhD on Dynamic Clustering (supervised by Albers & Timmerman) Research Interests: Ernst's work centers on between-individual differences in longitudinal data, statistical software development, and improving statistical methodology adoption in empirical research. She emphasizes practical applications through freely available code and collaboration with researchers globally. Grants & Awards: Recipient of the NWO Research Talent grant supporting her PhD research. Active in promoting research transparency and open science practices. Teaching & Mentorship: Teaches Advanced Statistics and supervises multiple PhD students focusing on psychometrics and statistical techniques. Leads the Methodology shop supporting students and researchers in methodology design.