Git Product home page Git Product logo

Hi there, I'm Justin Boylan-Toomey 👋

🏢 Work

Currently I lead the Machine Learning team at the Wellcome Trust, where we develop machine learning models and metrics to support Wellcome fund new discoveries in life, health, and wellbeing. We also support the Wellcome Collection, a museum that explores the connections between medicine, life and art.

Areas I have worked on at Wellcome (working with many fantastic colleagues, teams and external collaborators) include:

Leadership: Since joining Wellcome in 2022 I've implemented development standards, a robust prioritisation process and a technical road map, increasing the delivery of high impact machine learning products and the status of data science within the organisation. Improving our data and MLOps infrastructure alongside setting the direction of the teams technical work. The teams work includes the automatic topic modelling of research publications using BERTopic and the Llama large language model, development of WellcomeBertMesh a transformer model for tagging texts with MeSH terms, using text content and network dynamics to predict translational potential, and the development of network and citation based metrics. You can follow our team's work on the Wellcome Data blog here.

Wellcome Academic Graph: Designed, modelled and developed the Wellcome Academic Graph, a heterogeneous academic graph stored in Neo4j. Capturing over 2 billion relationships between 200 million academic entities, enabling our work to apply and development network based metrics and geometric machine learning.

Vector Database: Created a vector store, a foundational part of our new data infrastructure. Building a large-scale data pipeline with multi-GPU parallelisation with SciBERT and Nvidia RAPIDS for efficient inference and embedding of millions of publication and grant texts for storage in our Milvus vector database.

☕ Get in Touch

I am always interested in discussing the use of data and machine learning in research funding and data science for public good.

Justin Boylan-Toomey's Projects

akin icon akin

Python library for detecting near duplicate texts in a corpus at scale using Locality Sensitive Hashing, as described in chapter three of Mining Massive Datasets.

multimodal-document-classification icon multimodal-document-classification

MSc project investigating multi-modal fusion approaches to combining textual and visual features for multi-page classification of documents within the OGA National Data Repository (NDR).

mystic-bit icon mystic-bit

Learning whilst drilling through real-time, near-bit prediction ahead of the drill-bit, using offset well log data.

simple-genetic-algorithm icon simple-genetic-algorithm

Simple genetic algorithm to evolve a population of binary strings to create a child string composed entirely of ones.

wame-optimiser icon wame-optimiser

Implementation of the WAME (Weight-wise Adaptive learning rates with Moving average Estimator) optimization algorithm for TensorFlow version 2.0 or higher.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.