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Black-and-white portrait of David Vega, cropped in a circle with an olive-green ring: he looks at the camera and smiles, with dark curly hair, a mustache and a dark V-neck T-shirt.

David Vega

Visual artist and Electronic Arts professor. I build bespoke systems for interactive art and for small and medium-sized businesses. Bogotá, Colombia.

Write to me
hola@davidvega.org
Profiles

For art

I’m a visual artist working with virtual reality, 360 video, installations and interactive systems. Through technology I’m interested in naming environmental, social and political situations: the floods in Pakistan in Pafloodstan, the memory of the Amazonian world in Audiovisiones Amazónicas, the knowledge of Indigenous communities of the Amazon for forest recovery in Armonías Ancestrales. I’ve worked with Indigenous communities, with RecLab, with Línea ACT at the Planetarium as Dome Master and teaching artist, and with Idartes, the Banco de la República and the Pontificia Universidad Javeriana, where I’ve taught Electronic Arts and Physical Computing since 2023. My work has been shown at COP26, at the Ars Electronica Festival University and in The World Around’s Young Climate Prize cohort of 25.

For business

I build bespoke artificial intelligence systems: agents, automations, knowledge bases and websites that integrate with the tools you already use. I work in a hands-on, close way, side by side, on projects designed to grow over one or two years, iterating toward new methods together with business leaders. I always start with a short, honest assessment: what’s worth automating and what isn’t. I’ve worked with organizations in Colombia, Spain and Italy, and my own lab runs on a server I manage myself.

Short bio (press and festivals)

David Vega (Bogotá) is a visual artist, Electronic Arts professor at the Pontificia Universidad Javeriana and technologist. He works with interactive systems alongside communities, and develops artificial intelligence systems for organizations.

Erythrophleum sp., 17.5 m, measured with a terrestrial laser scanner. Data from Hackenberg et al. (2021), CC BY 4.0. 9,000 of its 215,186 points are shown here. Credits