Callum Blair


Creative Technologist working in a multitude of areas within the digital era from coding animation, web development,  and game design.

Studied at the Glasgow School of Art between 2015 to 2020 at the Interaction Design course.


Patterns of Play

2019/2020 - Year 4 Project

Made with Processing(Java), Runway, RiTa and AxiDraw

Built on my love of sport and my love of coding. This piece takes elements from machine learning and data from radio tennis matches to allow the machine to generate its own points. These points are then interpreted by myself and drawn with code into an AxiDraw onto A3 card to create these fascinating patterns that depict the essence of the sport.

Video of full documentation here:

Along with the machine learning versions, I used radio coverage and interpreted it to create real life drawings of the matches. I used the radio coverage as spoken data that could be used to create interpretations of the match, most of the matches are classes as classic matches through the years, most are grand slam finals but there are some that show some of the great moments in our sport such as the 2010 Wimbledon match between John Isner and Nicolas Mahut (The longest match ever).
April 15th 2020

AR Tennis

2019/2020 - Year 4 Project

Made with Unity, C# and Vuforuia

(Work in Progress)

Inspired by new ways that TV broadcasters are showing tennis with freeD cameras I wanted to explore how tennis could be viewed in 3D spaces.

AR Tennis was a side project from ‘Patterns of Play’ In an effort to give a better understanding of how the points where drawn from start to finish I was facinated by the drawings of the lines and started to animate them. Wanting then in a 3D environment made me look into Unity and AR. This would become a series using the sound from live tennis linking it with the AR to create a virtual experiance of the sport.

The full documentation can be found here:
April 14 2020

‘Untitled Tennis Project’

2019/2020 - Year 4 Project

Made with Processing, AfterEffects, AxiDraw.

Another link into my 4th year project had me look at anotating the movements of players from around the world. I had this idea when doing research for projects.

Robert Rauschenberg was a large influence on my 4th year with his project called ‘Open Score’ 1966. He said for this piece “Tennis is a movement, put in the context of theatre it is a formal dance improvisation” The idea of tennis being a kind of dance made me think of the movements, especially in the hands looking at them I saw this signature form for each player and started to analyse these movements.

This lead back to the AxiDraw and using After Effects to capture the motion to form these signature like hits.

Below the slide show was another example made through the same process rather than an individual shot I analyse a full point between Nadal and Del Potro at Wimbledon 2019. Aswell as the image a video was made of it as well found below.

The full documentation can be found here:
April 15th 2020

String Sports AD


Made with Adobe Photoshop and illustrator.

When working at String Sports I was commissioned to make an advertisement to go in the Tennis West of Scotland Handbook for 2018. This continued over the few years up to 2020 and they have all featured in the handbook for the last 3 years.

April 16th 2020

Poems by RiTa

2019 - Year 3 Project

Made with Processing (Java), Runway and RiTa.

Created with Processing and Runway a Machine Learning tool for Artist/designers. Poems by RiTa was created for the Sense and Sensibility project in 3rd Year. The project based on how we can use Machine learning to create a body of work. I was fascinated by how Runway’s Image GAN worked and how a machine see’s the world based on the word provided. This lead me using the RiTa processing sketch used in pass projects to generate sentences based on text files provided. In my case the text files were based on different poets and the RiTa sketch would produce its own Stanzas.

These stanzas would be put into the Runway Image GAN to create images based on the stanza. The images are what the machine believes to be the best way to describe the sentence provided.

This was later put into miniture show for the Interaction Design at the end of the year