University of Freiburg
Doctor of Philosophy, Microsystems Engineering
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I have experience working with structured and semi-structured technical datasets in an engineering context, where precise annotation, classification, and consistency are critical. In my work, I regularly handle measurement data, defect inspection results, and process-related datasets, ensuring data quality, standardization, and traceability. This includes labeling patterns, categorizing anomalies, and validating data against defined criteria, which aligns closely with the requirements of AI training data preparation. What sets me apart is my strong attention to detail and domain-specific understanding, particularly in handling complex technical data. I focus on maintaining labeling consistency, reducing ambiguity, and improving data reliability for downstream analysis or model training. Additionally, my background enables me to quickly understand labeling guidelines and adapt to new data schemas, ensuring both accuracy and efficiency.
Zhiqiu L. hasn’t added any AI Training or Data Labeling experience to their OpenTrain profile yet.
Doctor of Philosophy, Microsystems Engineering
Master of Science, Solid State Electronics and Microelectronics
Scientific Researcher
Test Engineer