Lightning Talks
summary
A rapid sequence of concrete outcomes and tools: a Haskell dataframe called dataf frame using types to catch nulls at compile time, a Python validation/generation pipeline built on paguro and polars that outputs validated tables, a Presidio stack for PII/PHI detection and anonymization, table-format work around parquet/iceberg/hoodie and an Xtable converter, plus PI CINDy code for learning ODEs and public‑health data tooling — each demoed with implementation details and working prototypes.
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chapters (8)
- 0:00Future of coding with AI
- 4:46Python data validation with Paguro
- 10:05File formats in data lakes
- 15:24Open-source research challenges
- 21:08Anonymizing text with Presidio
- 26:54AI for preterm birth prediction
- 29:26Networking for students and pros
- 31:34Data architecture maturity
