video annotation
Conducted a comprehensive data annotation project focusing on dynamic object localization within various visual environments. The primary goal was to ensure high-precision spatial accuracy for machine learning training sets.
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I’ve spent the last few years training my eye for detail, first through a rigorous medical degree and now through a deep dive into pathology. In my world, "labeling" isn't just a task—it’s a diagnosis. I’m used to looking at complex information, stripping away the noise, and categorizing it with extreme precision because I know exactly how much a small error can mess up the final result. When it comes to AI training and data labeling, I bring that same clinical mindset. I’ve worked on everything from basic image annotation and sentiment analysis to high-level RLHF (Reinforcement Learning from Human Feedback). I’m great at following dense style guides, spotting those tiny edge cases that most people miss, and making sure the data going into the model is actually high-quality. I’m at that point where I’m not just clicking boxes; I’m auditing the logic of the responses to make sure they’re accurate, safe, and actually make sense in a real-world context.
Conducted a comprehensive data annotation project focusing on dynamic object localization within various visual environments. The primary goal was to ensure high-precision spatial accuracy for machine learning training sets.
Bachelor of Medicine, Bachelor of Surgery, Medicine
Biology Teacher
NGO Volunteer