جست‌وجوی استاد و پژوهشگر

• Process Mining
• Process Modelling
• Conceptual Modelling
• +۵ مورد دیگر

Jan Martijn van der Werf serves as Associate Professor in Process Science at Utrecht University's Faculty of Science, Department of Information and Computer Science. Since September 2022, he has held the position of Programme Director for the Bachelor Information Sciences, overseeing curriculum development and academic operations for both Business Informatics and Information Sciences programs. Education: Dual PhD in Computer Science from Eindhoven University of Technology and Humboldt Universität zu Berlin (Thesis: 'Compositional Design and Verification of Component-based Information Systems') Research Focus: Van der Werf's work centers on process mining and behavioral modeling in software architectures, with emphasis on the interplay between data and processes. His expertise spans Conceptual Modelling of Information Systems , Enterprise Architecture , and Service-Oriented Architecture , addressing challenges in process discovery, verification, and practical implementation within complex organizational contexts. Current research explores the human dimensions of process mining adoption and AI-driven event log extraction. Publication Trends: Recent work (2023-2024) reveals increasing focus on methodological rigor in process discovery, human factors in process mining initiatives, and formal verification techniques for Petri nets. His publications bridge theoretical foundations with practical applications, particularly in event log extraction using large language models and visualization of complex process chronologies from heterogeneous data sources. Academic Contributions: Van der Werf teaches core courses in Process Modelling and Software Architecture , actively participates in academic workshops (including the 2020 'Information System Modeling' workshop), and supervises graduate research. His Scopus profile indicates 77 research outputs and supervision of 3 students, reflecting sustained scholarly engagement in process science and information systems.

• Computer Science
• Electrical Engineering
• Data Systems
• +۵ مورد دیگر

Kubilay Atasu is an Associate Professor at Delft University of Technology, affiliated with the School of Electrical Engineering, Mathematics and Computer Science and the Data-Intensive Systems department. His research focuses on core areas of computer science and electrical engineering, particularly in data systems and high-performance computing.

Aleida Braaksmaمشاهده پروفایل

مدرس

• Artificial Intelligence
• Health and Well-being
• Reinforcement Learning
• +۷ مورد دیگر

Aleida Braaksma is a Lecturer at the University of Twente, affiliated with the TechMed Centre and Mathematics of Operations Research department. Her work bridges Artificial Intelligence with Health and Well-being , focusing on optimizing healthcare systems through Operations Research methodologies. Key Affiliations: Digital Society Institute, TechMed Centre, Mathematics of Operations Research department Research Themes: Reinforcement Learning, Data Mining, Process Mining, and Queueing Theory applications in healthcare logistics Her recent publications highlight advancements in medical diagnostic scheduling , bed allocation , and adaptive clinical trial designs . She has pioneered dynamic robust optimization frameworks for time-sensitive pharmaceutical workflows and developed sampling-based methods for Gittins index approximation in stochastic environments. Scientific contributions include: Optimization of rheumatology outpatient clinics via patient classification algorithms Response-adaptive procedures in clinical trials using constrained Markov decision processes Real-time forecasting systems for pandemic-related hospital capacity planning Computerized decision support for nurse-to-patient assignment

• Artificial Intelligence
• Systems Engineering
• Cyber-Physical Production Systems
• +۵ مورد دیگر

Dr. Saber Darmoul is an Associate Professor specializing in Systems Engineering and Multidisciplinary Design. His research bridges artificial intelligence with industrial applications, focusing on cyber-physical production systems, operational resilience, and smart transportation. He actively explores knowledge representation, reinforcement learning, and agent-based modeling to address complex system challenges. Key Research Interests: Operational resilience, AI in manufacturing, multi-agent systems, smart mobility Technical Expertise: Ontology modeling, simulation platforms, immune-inspired control architectures His recent publications (2025-2019) demonstrate a consistent focus on integrating artificial immune systems into control architectures for transportation and manufacturing. Notable trends include: Development of knowledge-based systems for dynamic reconfiguration Application of multi-criteria decision frameworks in production environments Advancing predictive maintenance strategies through distributed systems Exploring 6G system-of-systems engineering While no explicit awards or student advisement information appears in available records, his 15 most recent publications reflect sustained academic productivity and evolving focus from foundational control systems (2017-2019) to advanced applications in Industry 4.0 (2020-2025).

Dannis Brouwerمشاهده پروفایل

استاد

• Precision Engineering
• Flexure Mechanisms
• Mechatronic Systems
• +۶ مورد دیگر

Prof. Dr. Ir. Dannis Brouwer is a professor at the Faculty of Engineering Technology, University of Twente, leading the Precision Engineering group. His work focuses on flexure mechanisms with applications in ultra-precision machinery, robotics, orthoses, and flexible implants. He lectures Design Principles for Precision Mechanisms in Mechanical Engineering programs and has pioneered advancements in large-motion flexure joints. Education: MSc in Mechanical Engineering and Mechatronic Design (Eindhoven University of Technology, 1998-2001); PhD (University of Twente, 2007) Past Roles: Mechatronics System Designer at Philips (2001-2004); Senior Applied Research Engineer at Demcon (2007-2009) Brouwer’s research addresses the limitations of traditional bearings by optimizing flexure joints for high load capacity, large motion, and stiffness. His group developed topology synthesis methods and leverages additive manufacturing to enable geometric complexity at low cost. Applications span space mechanisms, cryogenic systems, and medical devices. His 15 most recent publications focus on flexure modeling, optimization, and applications in robotics and precision engineering. Key subfields include torsion reinforcement, underactuated grippers, and superelement formulations. Scientific Leadership: Associate Editor of Precision Engineering; Director-at-Large, American Society for Precision Engineering (2015-2017) Grants: 14 projects (total 5.5M€), supervising 11 PhD students, 7 PostDocs, and 2 EngD candidates Brouwer integrates education with industry through intensive Master’s courses and lectures at industrial academies. His work bridges theoretical advancements with practical implementations in mechatronic systems.

Gang Meiمشاهده پروفایل

دانشیار

• Numerical Simulation and Computational Modeling
• GPU Computing
• Machine Learning
• +۵ مورد دیگر

Dr. Gang Mei is an Associate Professor in Scientific Computing within the School of Engineering and Technology at China University of Geosciences (Beijing), where he has held academic positions since 2014. His career progression includes Postdoctoral Researcher (2014-2016), Lecturer (Oct-Dec 2016), and current Associate Professor (since Jan 2017). His research bridges computational science and engineering applications with significant editorial contributions to computer science literature. Education: Ph.D. in Computer Science, University of Freiburg, Germany (2014) Research Interests: Dr. Mei specializes in Numerical Simulation and Computational Modeling, GPU Computing, Machine Learning, and Data Mining, with strong applications in Network Science and Spatial Information Systems. His work integrates Distributed and Parallel Computing techniques for large-scale scientific simulations, particularly in geospatial modeling and network analysis. The research demonstrates consistent focus on computational efficiency through hardware acceleration and algorithmic optimization across diverse domains including satellite imagery processing, financial event detection, and medical image classification. Publication Trends: His editorial portfolio reveals strong interdisciplinary patterns connecting computer science fundamentals with domain-specific applications. Recent works emphasize GPU-accelerated methods for data-intensive problems (2020-2022), spatial-temporal modeling (2019-2020), and network science applications (2021). The publications consistently address computational scalability challenges while maintaining practical relevance across geospatial, financial, medical, and engineering contexts. Professional Recognition: As an IEEE Member, Dr. Mei serves on editorial boards for IEEE Access and PeerJ Computer Science, reflecting peer recognition in computational fields. His editorial contributions span 15+ publications demonstrating expertise in evaluating cutting-edge computer science research. Academic Service: Beyond editorial work, Dr. Mei's service includes advising on computational methodology across multiple disciplines. His role as Academic Editor demonstrates commitment to scholarly communication, particularly in bridging theoretical computer science with practical engineering applications. No grant funding details were specified in available materials.

Ignacio M. Llorenteمشاهده پروفایل

استاد

• Cloud Computing
• Distributed Computing
• Computer Architecture
• +۲ مورد دیگر

Ignacio M. Llorente is a Full Professor at Complutense University of Madrid in the School of Computer Science and co-founder/Director of OpenNebula Systems. Dr. Llorente is a leading researcher in cloud technologies with expertise spanning multiple computer science domains: Cloud Computing Distributed Computing Computer Architecture Computer Networks & Communications Distributed & Parallel Computing Recognized as one of the pioneers and world's leading authorities on Cloud Computing, he has managed numerous international projects and initiatives in this field. His scholarly contributions include many publications in leading journals and proceedings. Professional service includes: Editorial Board Member of PeerJ Computer Science Through his dual roles in academia and industry (OpenNebula Systems), Dr. Llorente bridges theoretical research with practical implementation in cloud computing infrastructure.