He is working on implementing a Text-to-SQL generation system using Schema Items Classifier and Encoder-Decoder Architecture. The objective of the text-to-SQL task is to convert natural language queries into SQL queries. However, the presence of extensive text-to-SQL datasets across multiple domains, such as Spider, introduces the challenge of effectively generalizing to unseen data. He proposed an approach to evaluate and use the Seq2Seq model by giving the most relevant schema items as the input to the encoder and to generate accurate and valid cross-domain SQL queries using the decoder by understanding the skeleton of the target SQL query.
Aadhil Rushdy
Aadhil is a postgraduate student at the University of Moratuwa. He earned his undergraduate degree in Information Technology from the same university in 2018. He also has five and a half years of industry experience as a Data Engineer and he is an AWS Certified Data Analytics Specialist. Currently he is working as a Technical Lead – Data Engineering in Sri Lanka.
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