CV

linkedin · sam DOT j DOT coope AT gmail DOT com

DigitalGenius - Deep Learning Researcher

London: 2017 - Present

  • Researching state of the art NLP - extractive question answering, word embeddings etc.
  • Moving successful models from research to production systems.
  • Developing fast thresholding algorithms to ensure highly accurate automations.
  • Working with customers to improve model performance on their data.
  • Teaching sales representatives on the AI platform, workshopping effective pitches.
  • Interviewing and supervising new machine learning employees/interns.
  • Refactoring the production codebase to a more functional/compositional structure.

Imperial College London - Computing MEng

London: 2013 — 2017

  • Lead a group project to create a heartbeat sensor which uses video of the face and deep learning techniques. This was hosted on a server in a similar way to google deep dream.
  • Created a back end service which authenticates users based on the way they type as part of a team web app project. Used PostgreSQL for managing the databases which stored users keystroke information.
  • Worked in a team to create a compiler using ANTLR and java for a simple imperative language. Created an extension which used graph colouring to allocate registers.
  • Completed PINTOS - a series of coursework aimed at improving the understanding of operating systems.
  • Created an assembler and emulator for ARM architecture in a group project, then used the assembler to compile ARM assembly code into object code which activates lights on a raspberry pi when run.
  • Completed weekly programming projects in Haskell, Java and C.
  • Awarded a Computing Entrance Scholarship for outstanding A-level grades.
  • Achieved a 1st honours for the second year of study including 91% in coursework and 92% in Compilers.
  • Achieved a 1st honours for the third year of study.

AliveCor

San Fransisco/Mountain View: April — September 2016

Worked as a machine learning intern for 6 months.

  • Developed my own 'medium-sized data' pipeline for use in machine learning.
  • Used Go, react-redux for creating an internal tool.
  • Used keras, scikit-learn and AWS for machine learning.
  • Work was very independent, enjoyed the pragmatic culture of a startup trying to change the world.

Bloomberg LP.

London: July — September 2015

Worked in Core Monitors, a team creating realtime customisable spreadsheets for viewing market data. Developed in a proprietary Node.js like technology with Angular like front-end.

  • Created the foundation for the mobile version of the new monitors app, moving a large client side application to a backend service, refactoring the codebase to allow for a UI-less version of the app to run on a server.
  • Worked in a team following agile principles, and took part in formal code reviews for pull requests.

Autodesk.

Birmingham: July — September 2014

Worked in ArtCAM, a small team developing artistic CADCAM software. Developed backend in c++ and used Javascript for UI.

  • Created a tool which takes incremental slices of a 3D model, outputting the slices as models in the program, PNG files or SVG graphics.
  • Wrote an API which, given a list of vector objects(beziers/shapes/straight lines), created a to-scale SVG file. This was then used for exporting vector graphics as part of a client’s request.

Bromsgrove School

Bromsgrove: 2003 — 2013

* Achieved A level results of A*AAA in Further Maths A2, Additional Further Maths AS, Physics A2 and Chemistry A2 respectively.

Hackathons

  • Created a Google Chrome extension at HackKings ’14, ‘Baker’s Revenge’, which visualises cookies in your browser and allows you to delete them in a gamified fashion.
  • Used Leap Motion and Tobii Rex at ICHack ’14 to create a unity game concept which used hand tracking on the Leap Motion and eye tracking of the Tobii Rex to navigate the user around a 3D space.
  • Attended Nvidia deep learning hackathon where my team tried to create a network which could reverse engineer the latex from an image of a latex equation.