جست‌وجوی استاد و پژوهشگر

Kamyar Sarsharمشاهده پروفایل

استاد

• Business Process Management
• E-Business
• IT in Healthcare

Kamyar Sarshar is a Professor of Business Informatics at the Hamburg School of Business Administration (HSBA) since January 2014, serving as Academic Director of the Bachelor's program in Business Informatics within the Department of Technology & Markets. His educational background includes: Computer Science degree from the University of Hamburg MBA from Cardiff University, United Kingdom PhD from the Institute of Business Informatics in Saarbrücken Prior to HSBA, he worked as a Managing Consultant at Logica (now CGI), leading cross-industry process management projects. Research interests focus on: Business Process Management E-Business IT in Healthcare His work emphasizes empirical evaluation of modeling techniques like Event-driven Process Chains and Petri nets, particularly in healthcare applications and end-user usability. Publications from 2004-2008 reveal consistent contributions to business process modeling methodology, with strong empirical validation across healthcare, energy, and construction sectors, highlighting practical applicability and user-centered design principles. No scientific awards are documented in the provided materials. Information regarding student supervision, research grants, laboratories, or collaborative teams is not specified in the source text.

• Data Stream Management
• Real-time Data Analytics
• Data Quality
• +۷ مورد دیگر

Sandra Geisler is a Junior Professor for Data Stream Management and Analysis at the Department of Computer Science, RWTH Aachen University, a position she has held since September 2021. She is also the leader of the Digital Health Spaces group at the Fraunhofer Institute for Applied Information Technology (FIT) in St. Augustin, reflecting her dual expertise in academic research and applied digital health solutions. Bachelor/Master: Diploma in Computer Science, RWTH Aachen University (2008) PhD: Doctoral degree in Computer Science, RWTH Aachen University (2016) Her research focuses on data stream systems, real-time analytics, data quality, and their applications in digital health and industrial processes. She has made significant contributions to ontology-based data quality management, edge computing for stream processing, and FAIR data principles. Recent work explores the integration of large language models into data management workflows and the development of privacy-preserving platforms for industrial data exchange. Her recent publications demonstrate a strong trend in distributed and edge-based stream processing, interdisciplinary applications in healthcare and supply chains, and the use of AI for data discoverability and quality. Topics include in-network computing, simulation of edge queries, self-tonometry for glaucoma, and cross-company data sharing with privacy awareness. She has served as Associate Editor for the Data & Knowledge Engineering Journal (Elsevier), Public Relation Chair for QDB Workshop (VLDB 2016), and Workshop Chair for IMMoA and HIMoA workshops. She has also edited a special issue on Information Management in Mobile Applications in the Pervasive and Mobile Computing Journal. Geisler has supervised multiple theses on topics including LLM-based ontology integration, edge anomaly detection, and data ecosystem modeling. She has been actively involved in research grants and projects related to industrial data processing, digital health, and sustainable production. She teaches courses such as Data Stream Management and Analysis and Data Ecosystems Lab. She leads the Digital Health Spaces research group at Fraunhofer FIT, focusing on innovative solutions for health data management and patient-centric digital tools. Her work bridges computer science, healthcare, and industrial applications, promoting secure, efficient, and intelligent data ecosystems.

• Business Process Management
• Information Systems
• Petri Net Modeling
• +۳ مورد دیگر

Andreas Oberweis is a Professor at the Karlsruhe Institute of Technology (KIT), Germany, with a distinguished career in business process management, information systems, and process modeling. His work spans interdisciplinary collaborations, focusing on integrating formal methods like Petri nets with practical applications in digital identity, privacy, and educational technology. Key research areas include Business Process Management, Information Systems, Petri Net Modeling, Semantic Web, and Process Mining. He has contributed to methodologies like MEUSec for enhancing user experience and security in digital identity wallets, and frameworks for automated assessment of modeling competencies. Publications highlight innovations in process model similarity, social network coordination, and 3D business process visualization. His recent work emphasizes user-centric security and multimodal mobility optimization. Collaborations involve institutions like KIT, University of Rome, and Queensland University of Technology, with co-authors such as Peter Loos, Ralf Reussner, and Agnes Koschmider. He has developed tools like INCOME2010 for process-oriented systems and contributed to open models for enterprise systems. Despite no explicit awards listed, his 18+ years of continuous publication in top venues (BPM, EMISA, Modellierung) underscore his academic impact.

• Software Engineering
• Green Software Development
• Sustainable Computing
• +۶ مورد دیگر

Félix García is a prominent professor at the University of Castilla-La Mancha in Ciudad Real, Spain, with extensive contributions to software engineering, sustainable computing, and business process management. His research spans over two decades with 187 publications indexed in dblp, demonstrating consistent scholarly productivity and leadership in multiple research areas. Dr. García's research interests focus on critical contemporary challenges in software development, particularly green software engineering, energy efficiency in computing systems, and sustainable software development practices. His work bridges theoretical foundations with practical applications, addressing how software design, implementation, and maintenance impact environmental sustainability. He has pioneered research connecting software quality attributes with energy consumption, examining how design patterns, code smells, and refactoring techniques affect resource usage. His recent publications (2023-2025) reveal a strong focus on cutting-edge topics including Green AI, quantum computing sustainability, and energy-aware programming language design. These works demonstrate his ability to anticipate and address emerging challenges at the intersection of software engineering and environmental sustainability. Dr. García has received significant recognition through numerous collaborations, particularly with Mario Piattini (133 co-authored papers), Francisco Ruiz (63 papers), and María Ángeles Moraga (30 papers), establishing him as a central figure in his research community. His work has appeared in prestigious venues including IEEE Transactions on Software Engineering, Journal of Systems and Software, and ACM Computing Surveys. He has mentored numerous researchers who have become established scholars in their own right, including Javier Mancebo, Laura Sánchez-González, and César Jesús Pardo Calvache. His contributions to gamification in software engineering education through serious games like GLOBAL-MANAGER demonstrate his commitment to innovative teaching approaches.

André Nitzeمشاهده پروفایل

استاد

• Internet of Things
• Digital Business Models
• Software Engineering
• +۹ مورد دیگر

Prof. Dr.-Ing. André Nitze is a faculty member at the Brandenburg University of Technology in the Department of Economics . His research focuses on Internet of Things (IoT) , Digital Business Models , Software Architectures , Cloud Computing , Mobile Computing , and Predictive Analytics . He leads research projects on municipal LoRaWAN infrastructure, rural on-demand transport systems, and user-centered digitalization for sustainable development. Area of Expertise: IoT Applications, Software Engineering, Digital Transformation Current Research: Sustainable Municipal LoRaWAN, Rural Mobility Solutions Projects: risKI - KatKomm (2024-2026): Protocol development for disaster communication InNoWest (2023-2027): Subproject leader for digital sustainability OSLO (2023): Rural on-demand transport software architecture Awards: Best Paper Award at ICDS 2024 for work on LoRaWAN infrastructure Education & Supervision: M.Sc. and B.Sc. in Business Informatics Supervised over 15 theses including topics on GIS analysis, sensor networks, and AI applications

Tim Gruchmannمشاهده پروفایل

استاد

• Supply Chain Management
• Logistics
• Sustainability
• +۶ مورد دیگر

Prof. Tim Gruchmann is a prominent academic specializing in supply chain management and logistics, with a focus on sustainability, technology integration, and systemic resilience. His research explores ethical dimensions in transport logistics, technology acceptance among drivers, and the application of digital twin technologies. He has conducted empirical studies on automotive, food, and pharmaceutical industries, addressing challenges like semiconductor shortages and climate adaptation strategies. His work often bridges theoretical frameworks with practical industry applications, such as dynamic capabilities for resilience and blockchain-driven supply chain innovation. He has contributed to projects supported by the German Federal Ministry of Education and Research (BMBF), including the ADINA initiative on innovative logistics concepts. Research interests span sustainable supply chain governance, automation in warehousing, and logistics social responsibility. His studies analyze consumer behavior in sustainable food networks and the diffusion of labor standards through supply chains. He has authored over 30 peer-reviewed articles since 2017, with recent work emphasizing systemic disruptions and adaptation strategies in long-term crises. Notable projects include scenario planning for transformative supply chains and the development of a sustainable logistics service quality scale for Egyptian providers. His teams investigate ergonomics in intralogistics and the role of dynamic capabilities in local food distribution. Prof. Gruchmann’s research integrates quantitative methods like simulation modeling and system dynamics with qualitative empirical analyses. He collaborates internationally and has advised on policy frameworks for climate mitigation in transport sectors.

• Reinforcement Learning
• Safe AI
• Artificial Intelligence
• +۷ مورد دیگر

Javier García is a faculty member at the University Carlos III of Madrid, affiliated with the Department of Computer Science within the School of Engineering. His research lies at the intersection of artificial intelligence, reinforcement learning, and robotics, with a strong emphasis on safety, transferability, and real-world applications. His research interests include: Safe and robust reinforcement learning Transfer and multi-task learning in AI Adversarial attacks and defenses in deep RL Automated planning and decision-making under uncertainty Applications in social assistive robotics and financial systems The recent trend in his publications shows a focus on formalizing similarity between decision-making tasks, improving robustness against corrupted rewards and adversarial policies, and applying AI techniques to domains such as geriatric care and automated market making. His work often involves collaboration with Fernando Fernández and other researchers in Spain. He has contributed significantly to frameworks like CLARC for comprehensive geriatric assessment using robots, and has developed tools such as TIMIPLAN for transportation tasks. His research bridges theoretical AI with practical deployment in cognitive robotics and business simulators. Notable scientific contributions include a comprehensive survey on safe reinforcement learning (JMLR 2015), foundational work on policy reuse, and the development of taxonomies for MDP similarity. He has secured research funding through collaborative projects, though specific grants are not detailed in the provided text. He has advised several students and junior researchers, evident from co-authored publications, though specific names are not listed. He is part of research teams working on lifelong learning technologies and cognitive robot systems.

• Empirical software engineering
• Software architecture
• Design patterns
• +۸ مورد دیگر

Justus Bogner is a researcher at the Institute of Software Engineering (ISTE) and leads the division for Software Engineering for AI- & Microservice-Based Systems (SE4AI&MS) at the University of Stuttgart. His work focuses on empirical software engineering , microservices , AI-based systems , and software evolvability . He has contributed extensively to understanding architectural migration, technical debt in AI systems, and quality assurance methodologies. His research spans various subfields including service-oriented architecture , RESTful API design , design patterns , and software maintainability metrics . Recent publications highlight empirical comparisons between JavaScript and TypeScript, frameworks for microservice migration, and systematic studies on AI engineering challenges. Bogner's work often bridges academic research with industry practices through collaborations with IEEE and Springer, though no specific awards or student advisories are mentioned in the provided text.

Harald Augustinمشاهده پروفایل

استاد

• Industrial Engineering
• Operations Management
• Logistics
• +۶ مورد دیگر

Harald Augustin is a Professor at Reutlingen University's ESB Business School, specializing in Industrial Engineering and Logistics. He leads the Virtual Engineering and Training Center (VETC) and the Steinbeis Transfer Center for Process Management in Product Development, Production, and Logistics. Current roles: Professor for "Fabriksysteme und Logistik", Director of VETC Research focus: Digital Manufacturing, Lean Logistics, Virtual Reality in Factory Planning Education Diplom-Ingenieur (Maschinenbau, Production Engineering), Karlsruhe Institute of Technology (KIT) Dr.-Ing. (Promotion) in Mechanical Engineering, TU Kaiserslautern Research stays in France, Canada, and Australia Research Interests center on optimizing logistics and production systems through digitalization, lean methodologies, and virtual collaboration. His work includes developing immersive planning systems, risk management frameworks, and agile engineering processes. Lab Affiliations : VETC (Virtual Engineering and Training Center) at ESB Business School Steinbeis Transfer Center for Process Management in Product Development, Production, and Logistics

Sven Klaaßenمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Causal Inference
• Deep Learning
• +۱ مورد دیگر

Dr. Sven Klaaßen serves as a Research Fellow at the University of Hamburg's Hamburg Business School within the Professorship for Statistics with Application in Business Administration, collaborating closely with Prof. Dr. Martin Spindler since 2021. His research focuses on developing advanced statistical methodologies for complex data environments. His academic credentials include: Ph.D. in Statistics from Hamburg Business School (2020) Visiting Scholar at MIT Department of Economics (2022) M.Sc. in Business Mathematics from University of Hamburg (2016) BSc in Business Mathematics from University of Hamburg (2014) Dr. Klaaßen's research program centers on Machine Learning, Causal Inference, Deep Learning, and High-Dimensional Statistics, with particular emphasis on developing robust inference techniques for modern data challenges. His work bridges theoretical statistics with practical applications in business analytics and econometrics, often addressing the complexities of high-dimensional datasets where traditional methods fail. Analysis of his recent publications reveals a clear trajectory toward integrating machine learning with causal inference frameworks, exemplified by his leadership in the DoubleML software ecosystem. His research increasingly tackles multimodal data challenges while maintaining rigorous statistical foundations, with applications spanning economics, operations research, and business decision systems. As an active member of Prof. Spindler's research group, Dr. Klaaßen contributes to collaborative projects developing open-source statistical tools and advancing methodological frontiers in causal machine learning. The team maintains strong industry and academic partnerships focused on translating theoretical innovations into practical analytical solutions.

• Construction Logistics
• Digital Twin Frameworks
• Building Information Modeling (BIM)
• +۴ مورد دیگر

Stephan Kessler is a researcher at the Technical University of Munich , affiliated with the Department of Mechanical Engineering and the Chair of Conveying Technology, Material Handling, and Logistics . His work focuses on construction logistics, digital twins, and IoT integration in building processes. Contact: stephan.kessler@tum.de Key research areas: Digital Twin, BIM, DEM simulations, IoT in construction Collaborates with Prof. Johannes Fottner on construction automation projects His research emphasizes digitalization of construction processes through technologies like RFID, machine learning, and simulation tools. Recent publications address tower crane planning, co-robot integration, and bulk material handling standards. Article trends show consistent focus on construction automation (IoT, digital twins, BIM), material flow optimization (DEM simulations, screw conveyor standards), and equipment lifecycle management (telematics, RFID identification). Kessler contributes to industry-university collaborations through projects like BauFlott (fleet management systems) and TEP (Tower Crane Deployment Planner). His work bridges theoretical research with practical implementations in construction site logistics.

• Dependability Engineering
• Performability Analysis
• Cloud Computing
• +۷ مورد دیگر

Ermeson Carneiro de Andrade is a Professor at the Department of Systems and Computer Engineering within the Center of Informatics at the Federal University of Pernambuco (UFPE) in Brazil. His research focuses on dependability engineering, performability analysis, and fault tolerance in distributed and embedded systems. Over his career spanning more than 15 years, he has established himself as a prominent researcher in the field of system reliability through numerous publications in top-tier journals and conferences. Dr. Andrade's research interests primarily center on the analysis and modeling of system dependability, with particular expertise in UAV-based monitoring systems, cloud computing environments, and IoT architectures. His work bridges theoretical modeling with practical applications, particularly in environmental monitoring, disaster recovery solutions, and mission-critical systems. He has made significant contributions to understanding software aging phenomena in various computing environments and developing performability-aware solutions for real-time systems. The analysis of his recent publications reveals a strong focus on UAV systems for environmental monitoring, particularly deforestation detection, with increasing attention to weather impacts and vehicle density-aware traffic monitoring. His research demonstrates a consistent pattern of applying stochastic modeling techniques to solve practical problems in distributed systems, with recent work expanding into NoSQL database performance, satellite constellation dependability, and the performance-interpretability trade-offs in machine learning models. This evolution shows his ability to adapt to emerging technologies while maintaining core expertise in system reliability. Dr. Andrade has been actively involved in mentoring students and collaborating with researchers across Brazil and internationally. His work often involves interdisciplinary teams addressing complex system challenges. While specific awards aren't detailed in the available publication records, his consistent output in high-impact venues demonstrates recognition within the dependability engineering community. His laboratory work appears to focus on system modeling and analysis, with particular emphasis on experimental validation through simulation and real-world testing. Current projects suggest involvement in UAV-based monitoring systems for environmental applications, with strong connections to public sector institutions in Pernambuco state.

Gyunam Parkمشاهده پروفایل

پژوهشگر

• Process Mining
• Action-Oriented Process Mining
• Object-Centric Process Analysis
• +۱۲ مورد دیگر

Gyunam Park is a Research Group Lead and Process and Data Scientist at Fraunhofer FIT and a Scientific Assistant at the Chair of Process and Data Science at RWTH Aachen University, a leading institution in computer science and engineering. He is actively involved in both research and teaching, contributing to the advancement of process mining, data science, and artificial intelligence. His work bridges academic research and industrial applications, particularly in SAP ERP systems and digital twins of organizations. Research Interests: Gyunam Park’s research focuses on Action-Oriented Process Mining (AOPM) , Object-Centric Process Analysis , and Responsible Machine Learning . He aims to transform process mining insights into actionable management decisions, ensuring transparency, fairness, and compliance. His work enables organizations to monitor operational constraints, generate corrective actions, and assess their impact using data-driven methods. Publication Trends: His recent publications emphasize object-centric approaches to process mining, predictive monitoring, constraint checking, and integration with AI planning. There is a strong trend toward preserving structural information in event logs, improving machine learning performance, and applying these techniques to real-world systems like SAP ERP and after-sales service processes. Scientific Awards: No awards are explicitly mentioned in the provided text. Advising and Grants: While no formal students are listed, Gyunam Park leads research projects and collaborates with industry partners such as Samsung Electronics and SAP. His projects involve root cause analysis, resource optimization, and educational data mining. He has developed open-source tools like ProAct and OCPA , indicating active grant or institutional support for software development and research dissemination. Labs and Teams: He is a core member of the Process and Data Science (PADS) group led by Prof. Wil van der Aalst at RWTH Aachen University and leads a research group at Fraunhofer FIT. These teams focus on cutting-edge research in process mining, data science, and AI, with strong industry collaborations and regular contributions to top conferences and journals.

• Multi-agent Systems
• Educational Technology
• Intelligent Tutoring Systems
• +۵ مورد دیگر

Demetrio Arturo Ovalle Carranza is a Professor in the Department of Computer Science at the National University of Colombia's School of Engineering. With an academic career spanning over three decades since earning his PhD from Joseph Fourier University in Grenoble, France in 1991, he has established himself as a prominent researcher in multi-agent systems and educational technology. His research focuses on developing intelligent systems for education, particularly in the areas of multi-agent architectures, adaptive learning environments, context-aware educational applications, and learning object recommendation systems. His work bridges artificial intelligence with practical educational applications, creating systems that adapt to individual learner needs and contexts. Analysis of his recent publications (2015-2020) reveals a strong trend toward developing sophisticated multi-agent systems for educational applications, with increasing emphasis on context-awareness, personalization, and adaptive learning techniques. His research demonstrates consistent evolution from foundational multi-agent work to sophisticated educational applications integrating fuzzy logic, ontologies, and collaborative filtering. Ovalle Carranza has mentored numerous researchers who have become active contributors in the field, including Oscar M. Salazar, Néstor D. Duque, Valentina Tabares Morales, and others who frequently appear as co-authors on his publications. His collaborative network extends across Colombian institutions and international research groups. His laboratory work centers around developing and testing multi-agent educational systems, with particular emphasis on creating adaptive learning environments that can respond to individual student needs and group dynamics. Current projects appear to focus on serious games, health-care applications of intelligent agents, and advanced recommendation systems for educational resources.

Katharina Froschمشاهده پروفایل

استاد

• Human Resource Management
• Digital HR Tools for SMEs
• Work-Integrated Learning
• +۶ مورد دیگر

Prof. Dr. Katharina Frosch holds the professorship for General Business Administration with a focus on Human Resource Management at the Brandenburg University of Technology since March 2015. She also serves as the overall project leader for the SCALE-C initiative and has held a research professorship in the field of "Digital- and AI-supported learning at the workplace" since September 2024. Additionally, she has been a member of the Senate of the Brandenburg University of Technology since October 2023. Her research focuses on digitally supported human resource management tools for small and medium-sized enterprises (SMEs), human resource economic analyses in knowledge-intensive sectors, and AI-supported workplace learning. Key research areas include testing digitally supported onboarding processes in SMEs, hybrid approaches to work-integrated learning, and developing low-threshold digital HR tools for the Brandenburg-Berlin metropolitan region. Her work emphasizes professionalizing interactions between HR managers and employees at critical points to improve recruitment, motivation, and retention of skilled workers. Prof. Frosch's recent publications demonstrate a strong trend toward AI-enhanced learning solutions, particularly in microlearning, conversation training, and cybersecurity education. Her research increasingly examines how AI technologies can transform workplace learning while maintaining human elements of communication and trust. The SCALE-C project represents a significant interdisciplinary effort combining cybersecurity, artificial intelligence, and learning design to create semi-automated microlearning content. Best Paper Award at eLmL 2023 for 'Scan to Learn: A Lightweight Approach for Informal Mobile Micro-Learning at the Workplace' Best Paper Award at ICDS 2023 for 'Taking the Matter in Their Own Hands – Can Business Unit Developers Fullfill their Digital Demands with Low-Code Development Platforms?' Prof. Frosch actively collaborates with SMEs and public institutions in the Brandenburg-Berlin metropolitan region, leading a community of researchers, students, and HR practitioners developing Open HRM tools. She offers numerous opportunities for students to participate in research through project work, theses, and the SCALE-C initiative. Her teaching portfolio includes courses on Human Resources and Organization, Strategic Personnel Management, and Applied Research in Personnel Psychology, with a special focus on the Open HRM Hackathon. She leads the Open HRM Community, which conducts regular hackathons to develop functional HR app prototypes. Current projects include scientific support for the Federal Office for Foreign Affairs in implementing psychologically supported digital onboarding approaches, developing digital learning laboratories for workplace competence acquisition in SMEs, and implementing digital HR processes for companies like Autohaus Mothor GmbH.