Aditya Nanda
Researcher and Data-scientist at Vanderbilt
Nashville, Tennessee, United States
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Aditya is currently Research Assistant Professor at Biomedical engineering department at Vanderbilt university. He has authored 7 peer-reviewed journal articles and many conference proceedings. He obtained his PhD from University at Buffalo in Mechanical Engineering and his Bachelors and Masters degrees from IIT Kharagpur (India). Outside of work, he likes to play soccer (centennial park), bike around nashville and read books on popular science, neuroscience and ancient indian history.
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Synthetic tabular data: Applications, methods and comparision
In the healthcare industry, Anonymizing data ("data-masking") can often render it useless for analytics and machine learning. Synthetic data is a promising solution. Synthetic data is artificiality generated data that is statistically similar to real data. It preserves data utility without sacrificing privacy.
The main applications of synthetic tabular data are enabling data-sharing and data-analytics on sensitive data.
In this session, I will describe some use-cases for synthetic data. I will introduce the latest methods for generating tabular synthetic data (and do a simple demo using a excel spreadsheet) and compare the methods against each other in detail.
Aditya Nanda
Researcher and Data-scientist at Vanderbilt
Nashville, Tennessee, United States
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