جست‌وجوی استاد و پژوهشگر

Manfred Reichertمشاهده پروفایل

استاد

• Business Process Management (BPM)
• Service-Oriented Architectures
• E-health
• +۷ مورد دیگر

Prof. Manfred Reichert is a full professor at the University of Ulm, serving as Director of the Institute of Databases and Information Systems and Dean of Studies at the Faculty of Engineering and Computer Science. He holds dual expertise in Computer Science and Mathematics, with academic leadership roles including chairing examination boards and strategic research initiatives. His interdisciplinary affiliations include co-opted membership in the Faculty of Mathematics and Economic Sciences. Reichert's research focuses on Business Process Management (BPM), IoT-driven processes, service-oriented architectures, and e-health applications. Notable contributions include co-developing the ADEPT process management system and pioneering object-centric process modeling. He has led over 20 international research projects (EU FP7, DFG, Industry) and authored >200 peer-reviewed papers, earning an h-index of 60+ and prestigious awards like the Merckle Forschungspreis. Education: PhD in Computer Science & Mathematics Diploma Leadership: Former associate professor at University of Twente, former director of CTIT research center Service: Conference chair for BPM, CoopIS, EDOC; steering committee member for GI SIG Databases Recent work explores IoT integration in BPM, generative AI for process models, and neuroscience-informed usability studies. His research bridges technical innovation with human-centric design, addressing challenges in process lifecycle management, federated learning, and mobile health interventions. Awards: IFIP TC2 Manfred Paul Award, doIT Software Award Key Projects: BPMN extensions for IoT, data-driven healthcare solutions

Wolfgang Echelmeyerمشاهده پروفایل

استاد

• Logistics and Supply Chain Management
• Material Handling
• Operations Research
• +۳ مورد دیگر

Professor Wolfgang Echelmeyer is a faculty member at Reutlingen University’s Faculty of Sustainability and Technology, specializing in Technical Logistics. His research focuses on logistics automation, human-robot interaction, and sustainable supply chain systems. Position: Professor Department: Technical Logistics Email: wolfgang.echelmeyer@reutlingen-university.de Research interests include robotic container unloading, lean logistics, and ergonomics in automated systems. Recent projects involve EU-funded initiatives like RobLog (EU# 270350) for cognitive robotics in freight handling. His work spans applications in city logistics, milk-run transportation systems, and decision support tools for automation investments. Key article trends explore robotics in logistics, sustainability in freight systems, and ergonomic resource planning. Publications from 2018–2024 emphasize innovative solutions for intermodal terminals, deformable cargo handling, and smart transportation networks. Administrative roles include Dean of Studies for the BSc in Sustainable Production and Business and Pro-Dean for Teaching at the Faculty of Sustainability and Technology. Collaborators include Marco Bonini, Tuan Nguyen, and Augusto Urru. Labs and teams: Active in projects like LogFabr (Logistics Fabrication) and partnerships with industry leaders such as Merck AG, Proctor & Gamble, and STIHL. His work addresses real-world challenges in logistics planning and automation deployment.

• Process Mining
• Data Privacy
• Event Log Analysis
• +۳ مورد دیگر

Martin Kabierski serves as a Researcher at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin, specializing in process mining and data privacy. His work bridges theoretical frameworks and practical applications in event log analysis and privacy preservation. Education: Master of Science (M.Sc.) Kabierski's research centers on advancing process mining methodologies through species estimation techniques for data quality assessment, privacy-preserving mechanisms, and conformance checking. He has pioneered approaches for log representativeness evaluation, control-flow anonymization, and stream processing optimization. His work consistently addresses critical challenges in balancing analytical utility with data privacy requirements in business process analysis. Analysis of his 15 most recent publications (2021-2025) reveals three dominant research trajectories: (1) Species estimation applications for quantifying process representation completeness and diversity in event logs; (2) Privacy-preserving frameworks for process performance indicators and control-flow anonymization; (3) Stream mining innovations for window sizing and real-time conformance checking. These themes demonstrate his systematic approach to solving data quality and privacy challenges in process mining. No scientific awards are documented in the available information. Kabierski has not publicly listed any doctoral or master's students under his supervision. His research appears to be conducted collaboratively within institutional frameworks without mention of specific grant funding in the provided materials. He operates within the Databases and Information Systems research group at Humboldt University, contributing to the institute's focus on foundational data management and analysis techniques with applications in process mining.

Jan Mendlingمشاهده پروفایل

استاد

• Business Process Management
• Process Mining
• Information Systems
• +۳ مورد دیگر

Jan Mendling is a Professor of Process Science at the Department of Computer Science, Humboldt University of Berlin, Germany. He also holds adjunct professorships at Vienna University of Economics and Business, Austria, and serves as a Principle Investigator at the Weizenbaum Institute, Berlin. Additionally, he co-founded Noreja Intelligence GmbH. University: Humboldt University of Berlin Department: Department of Computer Science Other Affiliations: Weizenbaum Institute, Vienna University of Economics and Business His research spans business process management, process mining, information systems, and sustainability compliance. He has authored over 500 publications and co-authored textbooks including Fundamentals of Business Process Management and Wirtschaftsinformatik . Recent research trends focus on timeline-based process discovery, event sequence analysis, and leveraging large language models (LLMs) for business process sustainability. His work integrates temporal analytics, resource analysis, and contextual frameworks for process mining. Scientific Awards: Runner-Up for Best Paper at ICPM 2024 Winner of Best Paper at EdbA 2024 Best Paper at ER 2021 Best Forum Paper at PoEM 2020 Excellence in Teaching Awards (2016, 2017) He leads projects funded by the Einstein Foundation Berlin, BMBF, EU FP7, Horizon 2020, Erasmus+, and FFG. His editorial roles include founding co-Editor-in-Chief of Process Science and memberships on boards like Software and Systems Modeling and Business Process Management Journal .

• Materials Science
• Machine Learning
• Atom Probe Tomography
• +۳ مورد دیگر

Alaukik Saxena is a Researcher at the Department of Computational Materials Design, Max Planck Institute for Sustainable Materials. Their work focuses on applying machine learning techniques to analyze atom probe tomography (APT) datasets for advanced material design. Saxena holds a B.Eng. in Mechanical Engineering from Panjab University (2016), an M.Sc. in Material Science and Simulation from Ruhr University Bochum (2020), and is a PhD candidate at the Max-Planck Institut für Eisenforschung GmbH (2020–2023). Research interests include defect chemistry, microstructure analysis, and data-driven materials science. Saxena’s work bridges experimental techniques like APT and scanning transmission electron tomography (STEM) with machine learning to quantify chemical segregation, grain boundary roles in corrosion, and optimize permanent magnet performance. They also develop open-source tools for high-throughput material data analysis. Publications emphasize APT data workflows, microstructural feature quantification, and roadmap strategies for data-centric materials science. Their contributions highlight theoretical advancements in nanoporous materials and θ′ precipitation in Al-Cu alloys. Saxena collaborates within the Defect Chemistry and Spectroscopy group, advancing computational phase studies and material defect engineering. Awards and grants are not explicitly listed, but their research aligns with sustainable materials innovation. Advising and team leadership are inferred through collaborative projects in computational materials design and defect chemistry.

• Edge Computing
• Mobile Computing
• Wireless Networking
• +۹ مورد دیگر

Sanglu Lu is a Professor in the Department of Computer Science at Nanjing University's School of Computer Science and Engineering. With over 400 publications spanning from 1998 to 2025, Professor Lu has established a significant research presence in mobile computing, edge computing, and wireless sensing technologies. Their work frequently appears in top-tier conferences including INFOCOM, IEEE Transactions journals, and AAAI. Professor Lu's research focuses on cutting-edge areas in computer science, particularly in edge AI systems, millimeter-wave and RFID-based sensing, graph neural networks, and time series analysis. Their work bridges theoretical advances with practical applications, often addressing resource-constrained environments and real-world deployment challenges. Recent publications show a strong emphasis on privacy-preserving sensing techniques, efficient model deployment at the edge, and multimodal approaches to human activity understanding. Analysis of publication trends reveals Professor Lu's work has evolved from traditional mobile networking topics toward more AI-centric research, particularly in the last five years. The research demonstrates strong interdisciplinary connections between networking, sensing, and machine learning, with increasing focus on practical applications in healthcare, accessibility technology, and industrial IoT systems. Publications consistently show collaboration with researchers across China and internationally, indicating an active research group and extensive professional network. Professor Lu has mentored numerous researchers as evidenced by the extensive publication record with various co-authors, though specific student names aren't detailed in the provided information. Their work has received significant attention in the research community, as reflected by the substantial number of publications in high-impact venues. Current research directions include innovative approaches to edge AI, advanced wireless sensing techniques using commercial hardware, and novel neural network architectures for time series and graph data. Professor Lu's laboratory appears to be actively working on real-world applications of these technologies, particularly in health monitoring, accessibility solutions, and industrial automation contexts.

• Computer Science
• Multimodal Learning
• 3D Vision
• +۴ مورد دیگر

Junjie Fei is an active researcher in Computer Science with a focus on Multimodal Learning , Vision-Language Understanding , and Retrieval-Augmented Generation . They have collaborated with prominent researchers like Mohamed Elhoseiny , Sanjoy Chowdhury , and Jun Chen on various projects. Key research contributions include: Part-Aware 3D Vision-Language Understanding (2024) with novel tasks like Part-Aware Point Grounding MAGNET (2025) - a multi-agent framework for audio-visual retrieval WikiAutoGen (2025) - automated Wikipedia-style multimodal article generation V-RAG (2024) - vision-centric retrieval-augmented generation for document haystacks While no explicit academic affiliation or awards are stated in the provided text, their work spans 3D object segmentation , multi-video temporal grounding , multimodal knowledge integration , and large document reasoning , indicating significant contributions to AI research.

• Radar Technology
• Microwave Engineering
• Wireless Sensor Systems
• +۳ مورد دیگر

Patrick Kwiatkowski is a researcher at the Ruhr University Bochum , affiliated with the Faculty of Electrical Engineering and Information Technology and the Integrated Systems department. His work focuses on advanced radar technologies, particularly in the development of FMCW and MIMO radar systems for automotive, biomedical, and environmental applications. Role: Researcher Institution: Ruhr University Bochum Department: Integrated Systems His research spans Radar Technology , Microwave Engineering , and Wireless Sensor Systems , with a strong emphasis on 3D target localization , frequency-steered antennas , and harmonic RFID tag integration . Recent work highlights radar-based navigation aids for visually impaired individuals and high-frequency sensor systems for biomedical monitoring. The publications demonstrate expertise in Microwave Sensors , Millimeter-Wave Technology , and Signal Processing , with applications in Automotive Safety , Medical Engineering , and Environmental Imaging . Key trends include the integration of MIMO architectures and ISM band systems for enhanced spatial resolution and functional diversity. Dr. Kwiatkowski works within the Integrated Systems team, collaborating with colleagues like Nils Pohl and Andreas Orth on cutting-edge radar solutions. His research is documented in peer-reviewed journals and conferences including IEEE transactions and European Radar Conference proceedings.

Maximilian Röglingerمشاهده پروفایل

استاد

• Business Process Management
• Process Mining
• Digital Transformation
• +۱۵ مورد دیگر

Prof. Dr. Maximilian Röglinger is Chair of Business Informatics and Value-Oriented Process Management at the University of Bayreuth and Managing Director of the FIM Research Institute for Information Management. He is also Deputy Director of the Business Informatics branch at Fraunhofer FIT and previously served as an Adjunct Professor at Queensland University of Technology. He co-directs the Finance & Information Management program with TUM and co-moderates the Master's program in Digitalization & Entrepreneurship. His research spans digital transformation , process mining , AI in business processes , strategic IT management , and digital innovation . He investigates how data-driven methods can enhance process decisions, how digital technologies reshape customer interactions, and how organizations can structure digital transformation initiatives. His work combines theoretical rigor with practical application across industries. His recent publications (2023–2025) reveal a strong focus on generative AI integration in process mining and chatbots, human-AI collaboration in healthcare and logistics, process improvement systems , and digital ecosystems . He explores emerging topics like triadic delegation, explainable AI, and object-centric process mining from text. Scientific recognitions include: Paper of the Year 2019, Electronic Markets Best Associate Editor Award, ECIS 2021 Top 1.5% in BWL-Forschungsranking 2024 Certificate of Outstanding Contribution in Reviewing, European Journal of Information Systems 2023 Röglinger leads numerous publicly funded and industry-applied research projects with partners such as BMW, Siemens, Deutsche Bahn, Allianz, and Celonis. His work is supported by BMBF, ERDF, ERASMUS+, and Bavarian Research Foundation. He has co-founded the Digital Innovation Workshop, Digital Leadership Academy, and Fraunhofer Center for Process Intelligence. He is active in the international research community as Associate Editor of Business & Information Systems Engineering and editorial board member of Electronic Markets and Journal of Strategic Information Systems , and regularly organizes tracks at ECIS and BPM conferences.

Edith Tretschkمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Computer Vision
• Machine Learning
• +۵ مورد دیگر

Edith Tretschk is a Research Scientist at Meta Reality Labs Research in the San Francisco Bay Area. She completed her Ph.D. in Computer Science at Saarland University and Max Planck Institute for Informatics (2018-2023), advised by Christian Theobalt . Her work bridges computer graphics , computer vision , and machine learning , with a focus on 3D reconstruction and quantum computing applications. Education Ph.D. in Computer Science (2018-2023), Max Planck Institute for Informatics & Saarland University M.Sc. in Computer Science (2017-2023), Graduate School of Computer Science, Saarland University B.Sc. in Computer Science (2014-2017), Saarland University Research Focus Her research explores 3D reconstruction of dynamic scenes, neural rendering , and quantum computing for vision tasks. Recent work includes time-consistent scene flow (SceNeRFlow), quantum auto-encoders (3D-QAE), and physics-driven template matching (φ-SfT). Article Trends Her publications span 3D vision , quantum algorithms , and neural scene modeling . Key themes include non-rigid deformation, quantum-hybrid approaches, and physics-based reconstruction. Scientific Recognition Bachelor Award (2017) for top CS graduates Deutschlandstipendium scholarship (2015-2017) NeurIPS Top Reviewer (2022) Additional Contributions She has delivered invited talks at World Labs, Meta, Nvidia, and Epic Games. Active as a reviewer for CVPR, ECCV, ICCV, and NeurIPS, she has also contributed to open-source projects and datasets.

Dominic Petrakمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Conversational AI
• Machine Learning
• +۴ مورد دیگر

Dominic Petrak is a Doctoral Researcher at the UKP Lab, Technical University of Darmstadt. His research focuses on conversational AI, particularly improving dialogue systems through implicit user feedback analysis and error prevention in open-world scenarios. He holds an M.Sc. in Computer Science from RheinMain University of Applied Sciences and has professional experience in software engineering with firms like Sopra Steria and DXC Technology, specializing in NLP, enterprise applications, and Jakarta EE. Research Interests: Natural Language Processing, Machine Learning, Conversational AI, Numeracy in Language Models, Dialogue Systems Design, Software Architecture, and Enterprise Application Development. Publications: His work spans dialogue systems (e.g., FEDI dataset), numeracy enhancement in LMs (Arithmetic-Based Pretraining), and citizen science for NLP. Recent contributions include analyzing social acceptance requirements for service robots and exploring free-text human feedback integration. Advisors & Labs: Supervised by Prof. Nafise Sadat Moosavi (University of Sheffield) and Prof. Iryna Gurevych. Affiliated with the UKP Lab, TU Darmstadt.

Tobias Brogtمشاهده پروفایل

پژوهشگر

• Service Systems
• Service Systems Engineering
• Process Models
• +۵ مورد دیگر

Tobias Brogt is an External Ph.D. Student and Research Assistant at the Chair of Business Information Systems and Software Engineering within the Faculty of Business and Economics at the University of Duisburg-Essen. He combines academic work with practical experience as a Software Engineer at IT-Objects GmbH since 2015. Ph.D. research in Service Systems Engineering and Smart Connected Products Active lecturer in DBIT (Digital Business Innovation and Transformation) and VAWi (Virtual Continuing Education Program) since 2019 and 2016 Published extensively in ECIS , HICSS , and Springer Gabler publications Research Focus includes digital transformation , smart product architectures , and quality management in sociotechnical systems . His work applies service-dominant logic to analyze value creation through resource integration, particularly in IoT-enabled environments. Key Publications Trends reveal expertise in: Smart service system taxonomies Quality factors for self-tracking solutions Hybrid process models combining agile and plan-driven approaches Industry 4.0 transformation strategies Academic Contributions include: Supervision of 54+ Bachelor’s and Master’s theses since 2016 Design of courses like Advanced Programming Concepts and Software Development Paradigms Collaboration on the WIWI-chairT3 web content management solution

Conny Junghansمشاهده پروفایل

پژوهشگر

• Data mining in data streams
• Resource-adaptive data mining
• Spatio-temporal data analysis
• +۳ مورد دیگر

Dr. Conny Junghans is a researcher in computer science with expertise in data mining, spatio-temporal analysis, and information security. She completed her diploma at Ilmenau University of Technology (2005) and earned her PhD at the University of California, Davis (2009). From 2009-2011, she worked at Ruprecht-Karls-University of Heidelberg in the Database Systems Research group under Prof. Dr. Michael Gertz. Education: Diploma in Computer Science, Ilmenau University of Technology (2005) PhD in Computer Science, University of California at Davis (2009) Her research focuses on data stream mining with adaptive resource management, spatial/sensor network anomaly detection, and data quality assurance. She has contributed to multilingual document similarity models and burst detection in stream engines. Recent publications highlight trends in quality-aware systems, obstacle handling in sensor networks, and adaptive spatio-temporal prediction. She has served on program committees for SSDBM and CIKM conferences and acted as an external reviewer for multiple journals and conferences.

Pierre Maierمشاهده پروفایل

پژوهشگر

• Multi-Level Software Languages
• Software Language Engineering
• Conceptual Modeling
• +۴ مورد دیگر

Pierre Maier is a Researcher at the University of Duisburg-Essen , affiliated with the Faculty of Computer Science and the Information Systems and Integrated Information Systems department. His research explores the intersection of information systems and software languages, with a focus on multi-level modeling (MLM), natural language generation (NLG), and the application of large language models (LLMs) in organizational problem-solving. Maier's work investigates automation techniques to enhance the usability of multi-level software languages and addresses challenges in transitioning from traditional two-level languages. He supervises theses on topics like Machine Learning-Assisted Domain Modeling , LLM-Driven Semantic Matching , and Flexible Modeling , reflecting his interest in bridging conceptual modeling with AI advancements. His recent publications analyze the integration of generative language models with UML, the evolution of low-code platforms, and the role of multi-level modeling in improving software artifacts. Maier teaches courses in Object-Oriented Modeling , Robotic Process Automation , and Data Integration , combining technical rigor with practical applications for enterprise environments.

• Process Mining
• Privacy-Preserving Data Analysis
• Business Process Management
• +۳ مورد دیگر

Dr. Stephan Fahrenkrog-Petersen is a Researcher at the Institute of Computer Science , Humboldt University of Berlin , affiliated with the Faculty of Mathematics and Natural Sciences . He works on privacy-preserving process mining and business process management at the Weizenbaum Institute, Berlin. Email: stephan.fahrkrog-petersen@hu-berlin.de Address: Hardenbergstr. 32, 10623 Berlin His research focuses on data privacy , event log anonymization , and control-flow reconstruction in process mining. Recent work explores EU taxonomy compliance , human-centric BPM , and multi-perspective privacy mechanisms. Key article trends include privacy-preserving frameworks for process discovery, semantic anonymization techniques, and sustainable BPM . Publications span 2018–2025, with collaborative efforts in privacy-aware analysis and data generalization .