Researcher Time in DFKI

From 2014 to 2018, I conducted research on Big Data Anomaly Detection at a German research center for artificial intelligence (DFKI). This period was crucial for broadening my knowledge in artificial intelligence and big data analysis.

Pursuing a PhD in computer science proved to be challenging, as my background was primarily in mathematics, and I lacked foundational knowledge in computer science. Additionally, I faced language barriers, as the primary language of my team and all research activities was English, and my proficiency in the language was limited. Nonetheless, this experience was immensely rewarding; I successfully learned English and acquired essential knowledge in artificial intelligence independently while continuing with my research.

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During this time, I gained significant confidence in myself and my decisions. I feel fortunate to have had the opportunity to work at the DFKI.

Here are my published works:

  1. The Added Value of Advanced Feature Engineering and Selection for Machine Learning Models in Spacecraft Behavior Prediction (Best Paper)
    • The 15th International Conference on Space Operations (SpaceOps 2018)
    • Collected by Springer in “Space Operations: Inspiring Humankind’s Future” Link
  2. Book Chapter: Data Analytics: Industrial Perspective & Solutions – Data Mining in Agriculture
    • In “Data Mining in Time Series and Streaming Databases”
    • 2017, Publisher: World Scientific, Singapore
  3. The Multiple Views of Grid Based Outlier Detection for Combine Harvester
    • ML4CPS 2017 – 3rd Conference on Machine Learning for Cyber-Physical Systems
  4. Grid Based Outlier Detection in Large Data Sets for Combine Harvester
    • IEEE-INDIN 2017 (IEEE 15th International Conference on Industrial Informatics)
  5. Anomaly Detection in Sensor Data Provided by Combine Harvesters
    • IEEE-INDIN 2016 (IEEE 14th International Conference on Industrial Informatics)
  6. Analyse großer Datenmengen in Verarbeitungsprozessen
    • 2016, AUTOMATION 2016
  7. Anomaly Detection and Performance Evaluation of Mobile Agricultural Machines by Analysis of Big Data
    • 2015, VDI Conference on Agricultural Engineering (AgEng)
  8. Big Data Analysis of Manufacturing Processes
    • 2015, Journal of Physics Conference
  9. Datenströme intelligent lenken
    • 2015, Agrarzeitung – Trendbuch (2015 Edition)