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 |