جست‌وجوی استاد و پژوهشگر

Irfan Ahmadمشاهده پروفایل

دانشیار

• Pattern Recognition
• Document Image Analysis
• Handwriting Recognition
• +۷ مورد دیگر

Dr. Irfan Ahmad serves as an Associate Professor in the Department of Information and Computer Science at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, where he teaches undergraduate and graduate courses in Computer Science and Software Engineering while conducting research and advising graduate students. His academic service includes committee roles on graduate studies, program development, and competitions. His research expertise centers on Pattern Recognition with specialized focus on Document Image Analysis , Handwriting Recognition , and Machine-Printed Text Recognition . He actively explores Machine Learning applications including Deep Learning and Natural Language Processing , with significant contributions across Artificial Intelligence, Computer Vision, Data Mining, Neural Networks, and Computational Linguistics as evidenced by his PeerJ subject area specializations. Recent publications reveal a strategic emphasis on adaptive deep learning architectures for document analysis, particularly generative methods for handwritten text recognition and knowledge distillation techniques. His editorial work on feature extraction and multilingual fake news detection further demonstrates applied research bridging theoretical machine learning with real-world language processing challenges. As an active Academic Editor for PeerJ Computer Science with 1,205 contribution points, Dr. Ahmad provides substantial service to the scholarly community through manuscript evaluation and editorial oversight across emerging technologies in data science and artificial intelligence.

Remco M. Dijkmanمشاهده پروفایل

استاد

• Business Process Management
• Data-Driven Process Optimization
• Supply Chain Management
• +۳ مورد دیگر

Remco M. Dijkman serves as Full Professor in Information Systems at Eindhoven University of Technology (TU/e), chairing the Information Systems group within the Industrial Engineering and Innovation Sciences school. He additionally holds a Full Professor position at EAISI High Tech Systems and acts as research director for high-tech supply chains at the European Supply Chain Forum—a network of over 50 multinational companies. His research centers on Business Process Management with emphasis on data-driven optimization of business processes. His academic background includes both PhD and Master's degrees in Computer Science from the University of Twente. Publications span Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology, with over 100 papers and service on the editorial board of Information Systems. He has held visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. Dijkman's research interests focus on detecting, diagnosing, and predicting optimal execution scenarios in business processes, developing mathematical models for quantitative process analysis , and resource assignment optimization . These are primarily applied in transportation logistics and high-tech supply chains, where he investigates data-driven predictions for transport order assignment and supply chain planning. His work bridges artificial intelligence with practical business applications. Recent publications (2024-2025) reveal concentrated efforts in deep reinforcement learning for resource allocation, process pattern discovery, and software library development (GymPN, SimPN). Key trends include predictive process monitoring for healthcare applications, event data enrichment frameworks, and uncertainty handling in logistics planning—demonstrating strong interdisciplinary integration. Scientific recognition includes: Best Demo Award (2019) Best Reviewer Award (2016) Test of Time Award (2019) He has supervised 150 students, including Lotte Vugs who received the Dow Chemical Best OML Master Thesis Award in 2020. Grant leadership spans eight projects: NXTGEN Smart Industry (2023-2030), CollChain (2023-2029), CERTIF-AI (2020-2025), FENIX (2019-2023), and DynaPlex (2021-2024), focusing on digital twins, federated networks, and AI-driven supply chain solutions. Dijkman directs the Information Systems group at TU/e and leads the European Supply Chain Forum's high-tech supply chain research. His work integrates with semiconductor manufacturing and transportation logistics through collaborations with industry partners, while his 2023 invited talks at Technical University of Munich and Humboldt University Berlin highlight his international engagement.

• Haptics
• Human-Computer Interaction
• Social Touch
• +۴ مورد دیگر

Angelika H. Mader is an Associate Professor at the University of Twente, holding dual appointments at the Digital Society Institute and within the Human Media Interaction research group. Her work bridges computer science, design, and human factors with a focus on embodied interaction technologies and educational innovation. Her research centers on Haptics and Human-Computer Interaction , specializing in Social Touch systems, textile-based actuators, and pressure perception thresholds. She investigates emotional and sensory qualities of mediated touch while contributing to programming education through automated assessment tools. Her interdisciplinary approach integrates computer science, psychology, and design to develop novel user experiences for social and educational contexts. Recent publications (2023-2025) reveal a concentrated focus on haptic interfaces for social interaction, including textile actuators for pressure feedback, spatiotemporal touch illusions, and systems for social breath awareness. Her programming education work addresses automated assessment for learning-by-doing, demonstrating a clear trend toward embodied interaction in health, education, and collaborative environments. Professional recognition includes: Best Practices in Education Award (2018) She has supervised 3 students and maintains active research through dataset contributions on psychophysics and social touch. Her work shows consistent funding through collaborative projects evidenced by 6 public datasets and high-impact publications. As a core member of the Human Media Interaction group, she contributes to multimodal interaction research while advancing the Digital Society Institute's mission of addressing societal challenges through digital innovation. Her cross-disciplinary collaborations span engineering, psychology, and design teams focused on tactile communication systems.

Iwan de Eschمشاهده پروفایل

استاد

• Drug Design
• Fragment-Based Drug Design (FBDD)
• Computer-Aided Drug Design (CADD)
• +۵ مورد دیگر

Prof. Iwan de Esch is a Full Professor in the Department of Chemistry and Pharmaceutical Sciences at VU University Amsterdam, leading the Drug Design & Synthesis division and serving as Head of Department. He holds dual appointments in the Faculty of Science and AIMMS (Amsterdam Institute for Molecular and Life Sciences). His research focuses on understanding molecular interactions for drug discovery, employing CADD and FBDD approaches. He co-founded three biotech companies (De Novo Pharmaceuticals, IOTA Pharmaceuticals, Griffin Discoveries) and coordinates the EU-funded FRAGNET network. PhD from VU University (1998) Postdoc at University of Cambridge (Drug Design Group) Recipient of the 2011 Galenus Research Prize Received grants from EU-FP7, IMI, and Dutch STW Research interests span fragment-based drug design, receptor-ligand interactions, and pre-clinical drug candidate development. His work impacts GPCRs, PDEs, kinases, and protein-protein interactions. He teaches courses on drug discovery methodologies and computational tools. Over 200 peer-reviewed publications and 8 datasets/software contributions highlight his impactful career.

• Food Safety
• Cumulative Risk Assessment
• Pesticide Residues
• +۳ مورد دیگر

Johannes Kruisselbrink is a Researcher at Biometris , a department within Wageningen University & Research , specializing in food safety and cumulative risk assessment. His work focuses on pesticide residues, dietary exposure, and computational modeling for regulatory compliance. Key Collaborations: European Food Safety Authority, EFSA Projects: Active in pesticide exposure analysis (2024-2028), cumulative risk assessment tools (2019-2023), and regulatory frameworks (2018-2019). His research integrates data modeling and statistical software to enhance risk assessment methodologies. Recent projects emphasize interoperability and accessibility of platforms like MCRA and PARC. Scientific Contributions: Developed AMIGA Power Analysis tool for equivalence testing Authored reports on pesticide risk surveillance in fruits and vegetables Advancing EFSA standards for acute reference dose calculations

Anuj Pathaniaمشاهده پروفایل

استادیار

• Low Power Design
• Sustainable Systems
• Electronic Design Automation
• +۴ مورد دیگر

Anuj Pathania serves as an Assistant Professor in the Parallel Computing Systems (PCS) group within the Informatics Institute at the University of Amsterdam's Faculty of Science. His research pioneers sustainable computing systems operating under severe power, thermal, and reliability constraints, with significant contributions to energy-efficient hardware design and embedded systems. Education: PhD in Computer Science (2018), Karlsruhe Institute of Technology MSc in Computer Science (2012), National University of Singapore B.Tech in Computer Science (2009), Maharaja Agrasen Institute of Technology Pathania's research centers on low-power design and sustainable systems for constrained environments, with particular expertise in thermal management of 3D-stacked architectures and energy-efficient machine learning inference . His work bridges electronic design automation with real-world reliability challenges, developing novel power budgeting techniques like T-TSP that incorporate transient temperature effects ignored by conventional methods. Current projects include EU-funded initiatives on energy labeling for digital services, addressing ecological impacts through technological, behavioral, and legal frameworks. His publication trajectory reveals a strategic evolution toward zero-waste computing , with recent work (2023-2025) focusing on hardware-software co-design for edge AI, energy modeling across computing continua, and parameter-efficient neural adaptation. Key themes include thermal-aware scheduling for S-NUCA many-cores, cooperative processor utilization in heterogeneous systems, and sustainability metrics for digital services. Scientific Recognition: Best Paper Award Nomination at IEEE Computer Society Annual Symposium on VLSI 2023 for 3D-TTP power budgeting technique Pathania actively mentors 4 PhD students (Ehsan Aghapour, Saeedeh Baneshi, Sudam Wasala, Yixian Shen) and has successfully supervised 5 Master's theses (including Cum Laude defenses by Joris op ten Berg and Jurre Wolff). His research is supported by major grants including Energy Labels for Ecologically Sustainable Digital Services (2023-2024) and Towards Zero-Waste Computing (2021-2025), developing simulation frameworks like HotSniper and CoMeT for thermal analysis. The PCS group maintains strong industry collaborations with ARM and NVIDIA, particularly through tools like ARM-CO-UP for heterogeneous processor utilization.

Maya Danevaمشاهده پروفایل

دانشیار

• Requirements Engineering
• Cybersecurity
• Software Engineering
• +۳ مورد دیگر

Maya Daneva is an Associate Professor at the University of Twente's Digital Society Institute and part of the Semantics, Cybersecurity & Services research group. With over 200 research outputs, her work focuses on Requirements Engineering , Cybersecurity , and Agile Methodologies , particularly in digital transformation and enterprise systems. Academic Role: Associate Professor in Computer Science Institution: University of Twente Her research spans Model-Driven Engineering , security risk mitigation, and quality requirements prioritization, often employing empirical studies and systematic reviews. Recent articles explore phishing detection ontologies (2025), secure data storage architectures (2024), and digital consulting service modeling (2024). Scientific Awards: CBI 2021 Best Paper Award for work on digital IT consulting platforms EMMSAD 2025 Best Paper Award for phishing attack modeling She actively organizes academic events, serves on editorial boards (e.g., Empirical Software Engineering ), and contributes to conference peer-review, reflecting her leadership in the field.

Jaco van de Polمشاهده پروفایل

استاد

• Model Checking
• Formal Methods
• Computer Science
• +۳ مورد دیگر

Jaco van de Pol is a Full Professor of Computer Science at Aarhus University, holding dual roles in the Digital Society Institute and Formal Methods and Tools. He earned his PhD from Utrecht University in 1996, specializing in Termination of Higher-order Rewrite Systems, and a Master's in Computer Science (Term Rewriting) in 1992. His research focuses on model checking, formal methods, algorithms, and automated verification, contributing to UN Sustainable Development Goals related to innovation and education. Education: PhD, Termination of Higher-order Rewrite Systems, Utrecht University (1996) Master's in Computer Science (Term Rewriting), Utrecht University (1992) Research Interests: His work spans model checking, formal verification, parallel algorithms, and their applications in software engineering and bioengineering. He emphasizes practical formal methods, such as SCC algorithms and timed automata analysis, to solve complex computational challenges. Awards: Best Paper Award SPIN 2017 (2017) Best Student Paper Award (2018) Advising & Grants: Supervised 12 students and contributed to collaborative projects in formal methods and computational biology. His research has been applied to areas like cartilage phenotype modeling and parallel algorithm design. Labs/Teams: Engages with interdisciplinary teams, including computational biology and distributed systems groups, to advance formal methods in practical contexts.

• Environmental Chemistry
• Mass Spectrometry
• Non-Targeted Analysis
• +۵ مورد دیگر

Dr. Saer Samanipour is a Visiting Professor at the Van 't Hoff Institute for Molecular Sciences, part of the Faculty of Science at the University of Amsterdam. His research focuses on advanced analytical techniques for environmental and biomedical applications, with a strong emphasis on non-targeted analysis, mass spectrometry, and machine learning integration. He leads efforts in developing open-source tools like GcDUO and jHRMSToolBox to enhance data interpretation in complex chemical datasets. Key areas include environmental contaminant detection, chemical exposure assessment via wastewater-based epidemiology, and proteomic analysis of snake venoms. His work bridges computational methods with experimental chemistry to address global challenges in environmental health and toxicology. Primary affiliation: Van 't Hoff Institute for Molecular Sciences Research themes: Non-targeted LC-HRMS workflows, machine learning applications in analytical chemistry, PFAS analysis, and exposome research Software contributions: GcDUO (GC×GC-MS), jHRMSToolBox (HRMS data processing) His publications highlight innovations in data-driven approaches for compound prioritization, toxicity prediction, and method optimization. Recent work explores chemical space exploration and chemometric strategies for complex mixture analysis, with applications to environmental monitoring and forensic science.

• Software Engineering
• Machine Learning
• Software Architecture
• +۴ مورد دیگر

Cagatay Catal is a Lecturer at the Information Technology Department of Wageningen University & Research in the Netherlands. Previously, he served as Associate Professor at Istanbul Kultur University's Department of Computer Engineering (2012–2017), including three years as Department Head (2014–2017). Prior to academia, he worked for 8 years at TÜBİTAK's Information Technologies Institute as Senior Researcher & Project Manager (2002–2012), contributing to large-scale software systems. He holds a BSc/MSc from Istanbul Technical University and a PhD from Yildiz Technical University, all in Computer Engineering. His research focuses on machine learning applications in software engineering, software quality assurance, testing methodologies, and architecture design. He actively reviews for funding bodies like the European Union's EUROSTARS program, Canada's Research Council, and Turkey's Research Council. Catal leads projects such as INREF Smart-In-Ag (SMART farming in Indonesia), VIRAL (ICT in agricultural education), and malware detection in software systems. His work bridges academic research with practical software development challenges in diverse sectors like healthcare and education.

Oktay Türetkenمشاهده پروفایل

استاد

• Business Process Management
• Digital Business Models
• Smart Mobility Solutions
• +۳ مورد دیگر

Oktay Türetken is a Full Professor at Eindhoven University of Technology (TU/e) in the Industrial Engineering and Innovation Sciences school, specializing in Information Systems . He chairs the Industrial Engineering Bachelor Program and contributes to the European Research Center for Information Systems (ERCIS) in Münster, Germany. PhD in Information Systems Research Fellow at European Research Institute in Service Science (2008-2012) Adjunct Lecturer at METU’s Software Management program (pre-2008) His research focuses on digital innovation and collaborative business models , particularly in urban mobility. He develops methods for operational design , business process management , and data analytics maturity models . Key projects include MobilitEU and EU-funded initiatives in smart mobility. Recent publications address KPI frameworks for business models, platform design for shared mobility, and maturity models for organizational capabilities. He leads multi-disciplinary teams and has co-authored over 129 research outputs, including 2025 articles in Production Planning & Control and Business & Information Systems Engineering . 2021 : 1st Prize at DESRIST for paper prototype 2022 : 1st Prize for MaaS Platform Features research He supervises PhD candidates Ginger Korsten , Yasmin Rettab , and Stella Lo Giudice , and teaches courses like Digitalization and Enterprise Systems and Green and Digital Transformation . His work bridges academic research with industry consultancy via Cogniton Business Engineering Consultancy.

• Model-Based Design
• Design Automation
• Optimization
• +۴ مورد دیگر

Marc C.W. Geilen is an Associate Professor at the Electronic Systems group , Eindhoven University of Technology. He leads the Model-Based Design Lab and contributes to the CompSOC Lab and High Tech Systems Center . His work focuses on model-based design methods, design automation, and optimization for real-time and embedded systems. Research Keywords: Cyber-Physical Systems, Real-Time Systems, Embedded Systems, Performance Analysis, Design Automation Key Collaborations: EU ECSEL TRANSACT project, SAM-FMS project, Arrowhead Tools initiative His recent publications address weakly-hard timing constraints in server-based systems, hybrid performance modeling for cyber-physical systems, and neural network optimization for communication. Article trends span Real-Time Scheduling , Trustworthy Modeling , Neural Network Efficiency , and Resource Allocation in distributed environments. Scientific Awards : Partial-Order Reduction for Performance Analysis (2018) Teaching activities include courses in Computational Modeling , Embedded Signal Processing , and Discrete Mathematics . He collaborates across projects like TRANSACT, SAM-FMS, and Arrowhead Tools, focusing on flexible manufacturing and cloud-to-edge transitions.

Didier Meuwlyمشاهده پروفایل

استاد

• Forensic Science
• Biometrics
• Probabilistic Evaluation
• +۳ مورد دیگر

Didier Meuwly is a Full Professor of Forensic Biometrics at the University of Twente (since 2013) and Principal Scientist at the Netherlands Forensic Institute (NFI). His work focuses on automating and validating probabilistic evaluation of forensic evidence, particularly biometric traces. He has contributed to international standards via ISO Technical Committee 272 and served as Associate Editor for Forensic Science International . PhD in Forensic Speaker Recognition (University of Lausanne, 2000) Research spans forensic biometrics, likelihood ratios, AI validation, and gait/body analysis from surveillance footage. Recent work addresses ISO standards (21043), forensic AI explainability, and multimodal evidence evaluation. His publications emphasize empirical validation and statistical rigor. Key awards include: ENFSI Distinguished Forensic Scientist Award (2022) University of Lausanne Law Faculty Prize (2002) Active in global forensic networks, he chairs the ENFSI R&D Committee and collaborates across disciplines on digital evidence, biometric security, and forensic methodology.

Tom Verhoeffمشاهده پروفایل

استادیار

• Software Engineering
• Model-Driven Engineering
• Domain-Specific Languages
• +۷ مورد دیگر

Tom Verhoeff is an Assistant Professor at the Faculty of Mathematics and Computing Science of Eindhoven University of Technology (TU/e) , working within the Software Engineering & Technology group. His research focuses on Model-Driven Engineering (MDE) , Domain-Specific Languages (DSLs) , and the intersection of mathematics, computing, and the arts . He teaches courses in data analytics, programming, algorithms, theoretical computer science , and logic . Verhoeff earned both his MSc and PhD in Technical Science (Mathematics and Computer Science) from TU/e. He is actively involved in promoting mathematics and informatics through initiatives like the annual Bridges conference , and serves as board member and treasurer of the Dutch Mathematics Olympiad , as well as chair of the Koos Verhoeff MathArt foundation . He has also held roles as guest lecturer in Lithuania and Finals Director for the ACM International Collegiate Programming Contest . Research Interests: Verhoeff’s work spans Model-Driven Engineering , domain-specific language development , and 3D geometric modeling . His scholarship often explores symmetry, recursion, and mathematical visualization , particularly through computational art and algorithmic puzzles . Recent publications highlight 3D rotation methods , knot theory , and mathematical art using lattice paths and geometric transformations . Scientific Awards: ACM ICPC European Founders Award (2004) IOI Distinguished Service Award (2007) Second Place in the 2022 Wolfram Computational Art Contest Notable Collaborations and Affiliations: He is affiliated with the Esprit Working Group on Asynchronous Circuit Design (ACiD-WG) , WIRE (TUE Mathematics Alumni) , ACM (Senior Member) , CSTA , IEEE Computer Society , and Royal Dutch Mathematical Society (KWG) .

• Software Architecture
• Technical Debt Management
• Self-Adaptive Systems
• +۴ مورد دیگر

Prof. P. (Paris) Avgeriou is a full professor of Software Engineering at the Faculty of Science and Engineering , University of Groningen (RUG). His research focuses on software architecture , technical debt management , and self-adaptive systems through empirical studies and industrial collaborations. His work explores architectural decision-making using financial investment models, machine learning for debt detection, and dependency analysis in software systems. Recent projects include SDK4ED for energy-efficient embedded systems and DebtViz for debt visualization. Key article trends include technical debt lifecycle analysis (2023-2025), self-adaptive systems (2025), and modular architecture challenges (2024). Keywords span Computer Science , Machine Learning , and Software Systems . As an ancillary academic activity , he serves as editor for the Journal of Systems and Software (Elsevier). His collaborations extend to institutions in the Netherlands, Brazil, and Italy, with research outputs appearing in IEEE and ACM venues.