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Intranet

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PADS - Lehre

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    Kurse

    • Einführung in Data Science
    • Business Process Intelligence
    • Advanced Process Mining
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    Pro-Seminare

    • Proseminar on Process and Data Science
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    Seminare

    • Data-Driven Approaches to Sustainability & Resilience
    • Selected Topics in Process Mining
    • Machine Learning applications in Process Mining
    • Prediction and Simulation in Process Mining
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    Praktika

    • Process Conformance Checking using Python (MSc)
    • Process Conformance Checking using Python (BSc)
    • Process Discovery using Python - Master's
    • Introduction to Process Discovery using Python (Bachelor’s)
    • Process Mining in Celonis (MSc)
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    Abschlussarbeiten

    • Bachelor Thesis - A recommender system for process discovery
    • Bachelor Thesis - Integration of Sustainability Data into Object-centric Process Mining
    • Master Thesis – Object-Centric Process Mining in Lufthansa
    • Master Thesis - Protecting Event Data and Process Mining Results Using Generalization Techniques
    • Master Thesis - Process Mining Case Studies on SAP
    • Master Thesis - Fairness in Business Process Analysis
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    Abgeschlossene Abschlussarbeiten

    • 2023
    • 2022
    • 2021
    • 2020
    • 2019
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    Schwerpunktkolloquium

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      HiWi Stellen

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        New Process Mining Course by PADS and Celonis

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          Coursera Data Science in Action

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            PADS/Celonis Academic Center of Excellence

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              PADS - Forschung

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                Process Mining

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                  Publikationen

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                    Hardware

                    • HPC Cluster
                    • GPU Cluster
                    • Low-Power/IoT
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                    Software

                    • In-House Development
                    • External Data Mining
                    • External Information Systems
                    • XES and OCEL
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                    Event Logs

                    • Repository
                    • XES Certification
                    • Parquet for Process Mining
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                    Ressourcen

                    • Empfohlene Videos
                    • Folien und Videos
                    • Ausgewählte Publikationen
                    • Process-Mining-Manifest
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                    Willkommen

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                      Aktuelle Meldungen

                      • The new 2023 ranking of computer scientists by Research.com is out
                      • Video proceedings of the first Process Mining Summer School
                      • ICT Young Researcher Award 2022 for a PADS member, Mahsa Pourbafrani
                      • Connecting Process Mining and Sustainability
                      • Celonis Process Sphere provides easy access to the benefits of Object-Centric Process Mining
                      • Several awards for PADS members at ICPM 2022 in Bolzano
                      • PADS Excellence Initiative Started
                      • The Process Mining Handbook
                      • First Process Mining Summer School was a Big Success!
                      • RWTH und Celonis verstärken ihre Zusammenarbeit durch die Gründung des neuen Engineering and Innovation Lab auf dem RWTH Aachen Campus
                      • Six Levels of Autonomous Process Execution Management (APEM)
                      • New talk series: the Artificial Intelligence Colloquium
                      • New Process Mining Course Created by PADS and Celonis
                      • Summer School on Process Mining
                      • RWTH awarded 'Celonis Process Mining Centre of Excellence' status
                      • Celonis Appoints ‘Godfather of Process Mining’ Professor Wil van der Aalst as Chief Scientist
                      • New process mining website is now live!
                      • PADS Involved in Two New Projects Combining Process Mining, AI, and Learning Analytics: AIStudyBuddy and BridgingAI
                      • Julian Schnitzler wins the prize for the best Bachelor CS thesis award at RWTH
                      • The Changing Process Mining Landscape
                      • Global Process Mining Survey Identifies Success Factors and Increasing Adoption of Process Mining
                      • Process mining scholarships sponsored by the Deloitte Foundation
                      • RWTH Center for Artificial Intelligence
                      • Interview mit ACM Mitglied Prof. Wil van der Aalst
                      • OCEL Standard for Object-Centric Process Mining Released!
                      • Professor Wil van der Aalst wurde zum Fellow der Association for Computing Machinery (ACM) ernannt, der weltweit führenden Gesellschaft für Computertechnik
                      • First Audio Course on Process Mining
                      • PhD Positions on Machine Learning for Process Mining (ML4ProM) at RWTH Aachen University
                      • Prof. Dr. Wil van der Aalst benannt 2021 IEEE Fellow
                      • Do you want to apply cutting-edge process-mining techniques to your SAP data? Contact us!
                      • Tag der Informatik 2020 - Promo Video
                      • Wil van der Aalst in die Nordrhein-Westfälische Akademie der Wissenschaften und der Künste aufgenommen
                      • Professor Wil van der Aalst zum IFIP Fellow gewählt
                      • New Membership Structure and Website for the IEEE Task Force on Process Mining
                      • PADS Teaching in the Coming Semester (Summer 2020)
                      • A Side of Data: Podcast On Process Mining
                      • WITS Keynote: Process Mining In Today’s Platforms Economy - Opportunities and Challenges
                      • Recognition for Process Mining: Celonis Wins the "Deutscher Zukunftspreis 2019"
                      • PM4Py: State-of-the-art-process mining in Python
                      • Business Process Hygiene: No Business Case Needed
                      • Process Mining: Bridging Not Only Data and Processes, But Also Industry and Academia
                      • Centeris/ProjMAN/HCist Keynote on Process Mining and the Limitations of the Directly-Follows Graphs (DFGs)
                      • PADS Teaching in the Coming Semester (Winter 2019-2020)
                      • First Japanese Process Mining Conference
                      • SEFM Keynote on Object-Centric Process Mining
                      • Process Mining Book Translated in Japanese
                      • Reflections on 40 years of Petri Net Conferences
                      • First International Conference on Process Mining was a Huge Success
                      • ICPM Keynote on 20 Years of Process Mining Research
                      • New Gartner Market Guide for Process Mining
                      • 1. Internationale Konferenz über Process Mining (ICPM) im Juni 2019 in Aachen
                      • 39. International Conference on Applications and Theory of Petri Nets and Concurrency 24.6 bis 29.6.2018 in Bratislava
                      • PM4Py 1.0 Release Announcement
                      • Tag der Informatik 2018
                      • PADS startet neuen Blog
                      • Vorlesung "Introduction to Data Science" nun auch Wahlpflichtfach für Master Informatik, Master Software Systems Engineering, Master Media Informatics
                      • PADS – Neue Themen für Masterarbeiten
                      • Neues Kursangebot im Wintersemester 2018/2019
                      • Fraunhofer FIT feiert Jubiläum: 35 Jahre angewandte Forschung
                      • Alexander von Humboldt Preisverleihung
                      • Keynote on "Responsible Data Science in a Dynamic World" at the IFIP World Computer Congress in Poznan, Poland on September 18th 2018
                      • Keynote Summer Simulation Multi-Conference 2018
                      • Gartner Publishes Market Guide
                      • Alexander von Humboldt Professur
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                      Team

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                        Stellenangebote

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                          Fakultäten und Einrichtungen

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                          Fakultäten und Institute

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                          Lehrstuhl für Process and Data Science

                          2019

                           

                          Abgeschlossene Abschlussarbeiten 2019

                          Name Studiengang Thema
                          Ding, Kefang Master Model Repair by Incorporating Negative Instances In Process Enhancement
                          Schuster, Daniel Master History-Aware Process Monitoring
                          Lee, Gyumin Master MMI Distinguishing Undesired and Desired Infrequent Behavior in Process Mining
                          Hülsmann, Tom Bachelor Integration of MongoDB in PM4Pyfor Preprocessing Event Data and Discover
                          Yang, Jihoon Bachelor Big Data Process Mining in Python: Integra Tion of Spark in PM4PY for Preprocessing Event Data
                          Lyu, Zheqi Master Improved Alignment Repair
                          Kourani, Humam Bachelor Implementation of a Scalable lnteractive Event Data Visualization in Python
                          Bauerle, Tim Bachelor Complex Event Processing on MongoDB
                          Pohl, Timo Bachelor An Inductive Miner Implementation for the PM4Py Framework
                          Epstein, Yannick Master Improving State-Space Traversal of the eST-Miner by Exploiting Underlying
                          Tacke genannt Unterberg, Daniel Bachelor Localized Conformance and Performance Analysis based on Event Data: Diagnosing Individual Places

                           

                          Letzte Aktualisierung : 14.05.2023

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                          Abgeschlossene Abschlussarbeiten
                          • 2023
                          • 2022
                          • 2021
                          • 2020
                          • Sie sind hier:2019
                            • Model Repair by Incorporating Negative Instances In Process Enhancement
                            • History-Aware Process Monitoring
                            • Distinguishing Undesired and Desired Infrequent Behavior in Process Mining
                            • Integration of MongoDB in PM4Py for Preprocessing Event Data and Discover Process Models
                            • Big Data Process Mining in Python - Integration of Spark in PM4Py for Preprocessing Event Data and Discover Process Models
                            • Improved Alignment Repair
                            • Implementation of a Scalable Interactive Event Data Visualization in Python
                            • Complex Event Processing on MongoDB
                            • An Inductive Miner Implementation for the PM4Py Framework
                            • Improving State-Space Traversal of the eST-Miner by Exploiting Underlying Log Structures
                            • Localized Conformance and Performance Analysis based on Event Data: Diagnosing Individual Places
                           
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