Chris
Tegho
Chris is a machine learning engineer with a focus on computer vision, language modeling, and generative models, and is interested in the intersection of art and machine learning, with a focus on multiplicity, relations to others, queerness, and movement.
Recent artistic collaborations include work with artist Zach Blas on Cultus, an installation commissioned by Arebyte Gallery and Secession, and developing a few-shot gas canister detector for Forensic Architecture.
Chris executed challenging tasks throughout entire pipelines, from dealing with small amounts of data (as little as 10 training data points) all the way to deploying ML models that serve thousands of requests per second.
Chris completed a Master's in Machine Learning at the University of Cambridge in August 2017.
research interests
video language models — few shot learning — generative models — Bayesian modeling — computer vision: video understanding, video generation, object and movement detection
other interests
contemporary dance — internal family systems psychotherapy —compassion therapy
residencies
2025
Spreepark International Art Residency, Berlin, Germany
2024
Immersive Assembly Volume 4, Dreams and Echoes, Mediale, Oxford and York, UK
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contributions, artwork and commissions
2024
When T-Rex Dreams of Mangoes and Figs with Jazmin Morris —showcase as part of the Immersive Assembly Vol. 4 and Adventures in Consciousness Season at the University of Oxford
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2023
CULTUS with Zach Blas — commissioned by Arebyte Gallery, London, UK, and Secession, Vienna, Austria
— text generation
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Profundior with Zach Blas — commissioned by Berlin Biennale for Contemporary Art, exhibited at Hamburger Bahnhof
— diffusion video generation
— text generation
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2022
576 Tears with Zach Blas — commissioned by UP Projects for “This is Public Space” series
— live GANs video generation
— live sentiment camera based detection
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2021
Triple Chaser, with Forensic Architecture —exhibited at Uncanny Valley: Being human in the age of AI, at the de Young Museum in San Fransisco
research work in collaboration with Forensic Architecture.
developped a few shot detector for detecting tear-gas canisters in videos, for assisting human rights investigations.
— object detection
— video understanding
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Machines of Loving Grace, with DJ and producer Sonikku music video for single release Lifestyle with Boilerroom TV
— audio reactive StyleGANs video generation
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2020
The Doors with Zach Blas — commissioned by Edith-Russ-Haus für Medienkunst, Oldenburg, de Young Museum, San Fransisco, and Van Abbemuseum, Eidhoven
— GANs video generation
— text generation
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2019
MELTS INTO LOVE with Xin — album cover
— neural style transfer
CAD Conspiracy: Pattern Recognition in Contemporary Art with Mahan Moalemi and Bahar Noorizadeh — commissioned by the Mosaic Rooms, London
— GANs image generation
publications
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D’Cruz, A.∗, Tegho, C.∗, Greaves, S.∗, & Kermode L. (2022). Detecting Tear Gas Canisters With Limited Training Data. IEEE/CVF
Winter Conference on Applications of Computer Vision (WACV).
∗equal contribution - Tegho, C., Budzianowski, P., & Gašić, M. (2018). Benchmarking Uncertainty Estimates With Deep Reinforcement Learning for Dialogue
Policy Optimisation. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
- Tegho, C., Budzianowski, P., & Gašić, M. (2017). Uncertainty Estimates for Efficient Neural Network-based Dialogue Policy Optimisation. Accepted at the Bayesian Deep Learning Workshop, 31st Conference on Neural Information Processing Systems (NeurIPS).
2022 - 2024
Unitary, London, UK
— Develop and deploy multimodal machine learning models and pipelines for detecting harmful content in videos, images and text
2017 - 2022
Calipsa, London, UK
— Design, implement and evaluate models and software prototypes for object detection and motion detection in videos
Chris Tegho —
CULTUS with Zach Blas
Photo Credits: Zach Blascommissioned by Arebyte Gallery, London, UK, and Secession, Vienna, Austria
CULTUS explores a burgeoning "AI religiosity" in the tech industry, where artificial intelligence is imbued with god-like powers centered around themes like desire, judgment, extraction, and immortality.
In this work, I trained language models to generate sermons and prayers for the AI gods featured in the installation.