Lata (Byron) D.
AI Data Annotation Lead
Experience
AI Data Annotation Lead
Tech Innovations AI Lab
- Managed teams in annotating large-scale datasets for computer vision and NLP models, ensuring 99% consistency through rigorous QA processes and guideline adherence.
- Specialized in image labeling for object detection and segmentation, using tools like LabelStudio and CVAT to train AI models for physics-based simulations.
- Developed voice AI training protocols, annotating audio datasets for speech recognition systems, improving model accuracy by 25% in noisy environments.
- Acted as an AI tutor, mentoring junior annotators and conducting shadowing sessions to operationalize best practices and feedback from product teams.
- Collaborated on multi-project flexing, adapting to new guidelines weekly and contributing to efficiency improvements that boosted throughput by 40%.
Research Scientist in AI and Physics
Duke University Quantum AI Center
- Led data annotation efforts for quantum machine learning projects, labeling complex physical datasets to refine AI models for predictive simulations.
- Trained voice AI systems for scientific dictation tools, annotating thousands of hours of audio from physics lectures and experiments.
- Served as an AI tutor for graduate students, teaching data labeling techniques and AI training fundamentals integrated with physics concepts.
- Performed audits on labeled datasets, validating accuracy and identifying process enhancements to drive high-quality outputs.
- Supported additional tasks like dataset curation and model fine-tuning, contributing to publications on AI-enhanced physical modeling.
Physics and AI Intern
IBM Research AI Division
- Annotated image and video data for AI training in materials science applications, focusing on physical property identification.
- Assisted in voice AI development by labeling speech data for domain-specific models in scientific computing.
- Contributed to QA processes, reviewing datasets for consistency and providing feedback to improve annotation guidelines.
- Gained hands-on experience in multi-project environments, learning to adapt quickly to evolving AI training needs.
Summary
As a passionate physicist turned AI enthusiast, I've always been fascinated by how the laws of the universe can inform intelligent systems.
With a solid foundation in Physics from Duke University, I've pivoted my analytical skills to excel in AI training, data annotation, and model refinement. My journey began with quantum simulations and evolved into hands-on work labeling vast datasets for machine learning models, tutoring AI systems, and training voice recognition algorithms. I thrive in dynamic environments where precision meets creativity, ensuring AI models are accurate, unbiased, and ready for real-world applications. I'm eager to bring my interdisciplinary expertise to innovative AI teams, contributing to breakthroughs that push technological boundaries.
Languages
Education
Duke University
Ph.D., Computational Physics and AI Integration · Physics · Durham, United States · 3.9/4.0
Duke University
Master of Science, Applied Physics with AI Electives · Physics · Durham, United States · 3.8/4.0
Duke University
Bachelor of Science · Physics · Durham, United States · 3.7/4.0
Certifications & licenses
Certified AI Data Specialist
Coursera
Advanced Machine Learning Certification
edX, Duke University
IBM AI Internship Completion Certificate
IBM
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