TOM SHANNON
I'm Tom — a mutli-disciplinary technologist and artist. I currently work as a software developer and consultant at ThoughtWorks, based in Chicago. I specialize in machine learning, cloud computing, mobile development, and technology driven art installations.
I attended Carthage College for my undergraduate degree and received my B.A. in physics and computer science. During my studies, I helped lead several NASA funded research projects, involving building suborbital rocketry payloads, high powered rockets, and a small earth observing satellite.
Since then, I have collaborated with artists to create unique technology driven art installations that push boundaries of what art can do. Some of this software includes emotion driven film, eye gaze tracking on mobile devices, and re-creating lost ancestry records using generative adversial networks. Some of these pieces have gone on to exhibit at places such as the Cooper Hewitt Smithsonian Museum, ARS Electronica, BOZAR, and Science Gallery Dublin. For future projects, I am interested in continuing to create generative artwork that addresses social, economic, and cultural issues in our society.
Exhibitions
COOPER HEWITT SMITHSONIAN MUSEUM
Face Values: Exploring Artificial Intelligence
New York City, New York
September 2019 - March 2020
ARS ELECTRONICA 2020
STARTS Prize — Honorary Mention
Linz, Austria
September 9th - 13th, 2020
BOZAR 2020
Speculating on the Future Through Art And Science
Brussels, Belgium
September 26th - October 25th, 2020
SCIENCE GALLERY DUBLIN
Speculating on the Future Through Art And Science
Brussels, Belgium
September 26th - October 25th, 2020
SXSW 2020 (Cancelled due to COVID)
Immersive Futures Lab
Austin, Texas
March 17th - 18th, 2020
Project Credits
Director & Producer: Karen Palmer
Commissioned by: Ellen Lupton Senior Curator, Contemporary Design, The Cooper Hewitt Smithsonian Design Museum
Software Development Coordination: ThoughtWorks Arts Program Director Andrew McWilliams, Julien Deswaef & The ThoughtWorks Arts Team
Development Team: Tom Shannon, Emilio Escobedo, Lauren O’Neal, Dan Lewis-Toakley, J.C. Holder, Stephanie Weber, Peter Graves, Lee Faria, Diana Gámez Díaz, Emily Sachs, Whelan Workmaster, Andrew Zou, Ling Tran, Margaret Plumley, Megan Andrea Louw
R&D: Emily Balcetis, Associate Professor of Psychology NYU, Lab Director The SPAM (Social Perception Action & Motivation) Lab
Film Production Team: She Shot Me Films
Sound Design: Mike Wyeld
Actors: Police Officer Michael Mirlas, Black Male Hassan Farrow, White Male Jeremie Egiazarian, Background female Christin Johnson
Perception iO is an immersive storytelling experience that reveals how your emotions can influence your perception of reality. Perception iO puts you in the point of view of a police officer who is wearing a body camera. The footage from the body camera will be used to train an artificial intelligence system for the future of law enforcement. In this film you are put into two volatile sitations with characters of different races. Based on your emotional response, the interactive film narrative changes, which ultimately has an effect on the characters you see in the film. Through this experience, participants become aware of their own subconscious bias, spefically towards race, and how it can have an effect training articicial intelligence of the future. Through this, Perception iO calls for regulation and democratization in the artificial intelligence sector today.
Personal Accomplishments
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Exhibitions
NEURIPS
Machine Learning for Creativity and Design
September 2019 - March 2020
COMPUTER VISION ART GALLERY
Winning Entry
September 9th - 13th, 2020
Project Credits
ThoughtWorks Artist in Residence: Nouf Aljowaysir
Thoughtworks Arts Residency Director: Andy McWilliams
Development Team: Austin Garrard, Vini Macedo, Nikola Savic, Tom Shannon, Rohit Naidu, Alwina Oyewoleturner, Ellen Pearlman, Shraddha Surana
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Salaf [سلف], a piece envisioned by Nouf Aljowaysir and created through the ThoughtWorks Arts Resicency Program, is an ongoing exploration of using generative adversarial networks (GANs) to investigate cultural transmission across generations and to help construct a story of the artist's heritage. Over the course of the exploratory research period, it was evident that many of the open source datasets we initially were using were biased and white-washed. With the limited availability of images of non-western Arab people, it was difficult to generate high resolution models to generate scenes that would help convey the artist's vision. While experimenting, we found it easier to generate interesting images when training on images that cut out the individuals out of the image using person segmentation; what remained was a silouhette of past records of her ancestral lineage. This additionally helped depict the eradication of the artist's ancestral collective memory.
Personal Accomplishments
Inquisitive Introspection is an installation that forces participants to ask difficult questions about their lives posed by their future self. The installation consists of a double sided mirror that the participant approaches. When they approach, an image is taken of them. Using a generative adversarial model, an image of their future self is generated and is projected through the double sided mirror with an interior display. This image is animated with a first order motion model to ask questions such as: Are you happy with what you are doing in your life? If not, what could you do to change it? After the line of conversation, the projection of the particpiant's future self vanishes. The participant is left looking at themself in the mirror to think about these questions.
Personal Accomplishments
A link to my undergraduate thesis for physics and computer science
For my undergraduate thesis, I created software to conduct 3D structural topology optimization problems using the bi-directional evolutionary structure optimization (BESO) method. This code was written based on work done for the 2D case by Xie and Huang in the book, Evolutionary Topology Optimization of Continuum Structures: Methods and Applications. This work included building a finite element analysis suite for hexahedral elements and optimization methods. Future work is planned to be done to improve performace using cloud computing GPUs and to explore the usage of generative models to create similar structures in exceedly less time.
Personal Accomplishments
A link with description of RockSat-X program on NASA page
Personal Accomplishments
This was a project conducted in my first year of undergraduate, where I helped build an experimental payload that flew aboard a NASA Malemute Sounding Rocket. The experiment my team and I built was a receiver that collected very low frequency electromagnetic waves from lightning signals in the upper atmosphere.
A link to the poster I presented at the 33rd Annual American Society for Gravitational and Space Research Conference, Seattle, WA (2017)
Personal Accomplishments
The CaNOP CubeSat mission is a student lead project to build a small satellite that takes multispectral images of the Earth with similiar resolution to large scale satellites such as LandSat. The system is composed of off the shelf units brought together. During this project, I played many roles, but created thermal simulations of the CubeSat and electronic parts. I also helped create software for operational modes that the multispectral camera will use to determine behavior in orbit.