Stanford University
Master of Science, Applied and Engineering Physics
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I have hands-on experience developing, evaluating, and refining AI training data, particularly in the context of large language models and scientific domains. During my AI internship, I created and analyzed domain-specific prompts to assess LLM performance, focusing on scientific accuracy, clarity, and depth. My work involved detailed annotation and expert review of model outputs, helping improve AI understanding of complex biological and technical topics. Additionally, my research experience in quantum information science required precise data analysis, coding in Python, and presenting findings, further strengthening my attention to detail and ability to generate high-quality, reliable training data. I am passionate about ensuring data accuracy and integrity to support robust AI systems.
Charles S. hasn’t added any AI Training or Data Labeling experience to their OpenTrain profile yet.
Master of Science, Applied and Engineering Physics
Bachelor of Science, Engineering Physics
Undergraduate Researcher
Robotics Coach