Chris Tegho is a creative technologist, and machine learning engineer from Lebanon and the UK.
They experiment with and integrate computer vision, new technologies, movement, coding, 3D modeling and materials to embrace emotional plurality, more-than-human perspectives, and ethical dimensions of technology.
Chris’ work explores multiplicity, how we connect with ourselves, our inner complexity, questions of belonging, and the ecological systems we are part of through technology, movement and play.
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
Ecological Dialogues — ongoing research, workshop and work on movement, play and technology
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 UP Projects for “This is Public Space” series
576 Tears is an online experiential work that speculates on how an AI system imbued with godlike qualities might perceive and learn from the ritual of human emotional crying. Through an interactive website, audiences offer their own tears to train an imagined "AI god" on the symbolism and expressions embedded in weeping across religious, scientific, and cultural contexts.
For this work, I trained StyleGANs on images of tears to produce videos for the interactive experience; and language models on writings on crying in religious, philosophical, scientific, cultural, and technical contexts to produce text and poetry communicated through the digital experience.
