Christopher Grainger - Co-Founder at Amplified

Christopher Grainger

Co-Founder at Amplified

Melbourne, Victoria, Australia

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Summary

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Rockstar

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Top School

Christopher Grainger is an innovation economist, data scientist, and entrepreneur with 11 years’ experience building deep learning and NLP solutions to quantify technological change and streamline invention workflows. As Co-Founder of Amplified he applies cutting-edge ML to reduce low-value, labour-intensive tasks in the IP and innovation process, translating research-grade methods into product-ready tooling. His academic background (PhD and MSc from UCL) and research roles at institutions like the Grantham Research Institute inform novel econometric approaches and patent novelty scoring that avoid citation reliance. A practical engineer as well as a theorist, he contributes to open-source Elixir data tooling—enhancing dataframe functionality and Parquet/NDJSON I/O—bridging empirical research and production-grade software.

11 years of coding experience

3 years of employment as a software developer

MA Honours, History, First Class, MA Honours, History, First Class at The University of Edinburgh

Master of Science (MSc), Sustainability (Transport), Merit, Master of Science (MSc), Sustainability (Transport), Merit at University of Leeds

University College London

English, French

Stackoverflow

Stats

2,176reputation

160kreached

1answer

7questions

Github Skills (14)

data-manipulation10

dataframes10

back-end-development10

elixir10

dataframe10

parquet7

ndjson7

vector6

lme46

heatmap6

neural-network6

mixed-models6

python6

Programming languages (18)

JavaC++RustSchemeCScalaHTMLJupyter Notebook

Github contributions (5)

elixir-explorer/explorer

Jul 2021 - Dec 2022

Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir

Role in this project:

Back-end Developer

Contributions:3 releases, 194 reviews, 230 commits in 1 year 5 months

Contributions summary:Christopher primarily contributed to refactoring and extending the `Explorer.DataFrame` module, focusing on data manipulation capabilities within the Elixir ecosystem. They implemented new features for column renaming, including support for lists, maps, and functions. Further, the user improved the `select/3`, `filter`, `mutate/2`, `arrange/2`, `distinct/2`, `pivot_longer/3` functions and added functionality like `concat_rows`, `to_binary`, and `from_rows` and implemented the ability to read and write Parquet and NDJSON files. These changes enhanced the dataframe's usability and feature set.

dataframesdata-explorationdata-sciencerusttwo-dimensional

elixir-nx/tokenizers

Feb 2022 - Dec 2022

Contributions:1 release, 15 reviews, 42 commits in 9 months

rusttext-processingelixirmachine-learningtokenizers

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