Chris Tegho (they/he) is a creative technologist, and machine learning engineer from Lebanon and the UK.
Their work moves across movement, code, 3D modeling, and material, grounded in an ongoing interest in raw emotion and play. Chris explores how technology shapes identity and perception, and uses play as a method for connection, experimentation, and expanding perspectives. Their practice is driven by questions of queer belonging and the need to build ecosystems that hold multiplicity and difference.
They have collaborated on immersive installations with numerous artists, Jazmin Morris on TRex Dreams of Mangoes and Figs, exploring technological access, waiting in digital spaces, and consciousness; and Zach Blas on installations such as Cultus (Arebyte, Secession), Profundior (Berlin Biennale), and The Doors (Edith-Russ-Haus für Medienkunst, De Young Museum, Van Abbemuseum). These works examine consciousness expansion, human/machine relations, and AI religiosity, interrogating the extractive data practices underlying AI's rapidly advancing emotional intelligence.
Chris is co-founder of Disruptive Nostalgia, a collective which sets out to reimagine and challenge the narratives of architecture, landscape, and cultural memory informed by intersectional politics. The collective is currently resident at Spreepark in Berlin where they explore how memory, color, and play shape our understanding of place and connection to each other and nature.
Chris completed a Master's in Machine Learning at the University of Cambridge in August 2017.
ml 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
Infrastructures of AI — ongoing research and visual essay exploring Big Tech’s AI dominance through improvised Global South infrastructures, accepted for presentation at the Connective (t)Issues Workshop, with Data & Society
Scattered Minds — short film / coded animation exploring multiplicity of the mind
The Doors with Zach Blas (2020) — commissioned by Edith-Russ-Haus für Medienkunst, Oldenburg, de Young Museum, San Fransisco, and Van Abbemuseum, Eidhoven
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).
machine learning work
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
Commissioned by Berlin Biennale for Contemporary Art, exhibited at Hamburger Bahnhof
Profundior is an immersive multimedia installation that envisions an AI system as a deity consuming human emotional data. Responding to the quasi-religious veneration of AI in Silicon Valley, it presents an "AI god" in the form of a black box network that ritualistically ingests simulated human tears. Through this speculative work, Profundior interrogates the ethical implications and extractive data practices underlying AI's rapidly advancing emotional intelligence capabilities. In this work, I trained diffusion models on images of tears to generate videos for the installation. My work also involved training language models to generate text for the installation.
Video Credit: Chris Tegho
Low resolution protype video generated from a diffusion model for Profundior. Final videos only available through the installation.
