A.I. for biodiversity monitoring

Study Nature


Our solution in computer vision and information retrieval algorithms provide an algorithmic chain capable of: (i) analysing shapes in sequential video-frames, (ii) extracting vision based features used to detect movements.

augmenting tool

Once the shape has been described and analysed, the surroundings and context can be augmented, for archival, labelling, sharing with others for further study.

learning tool

We integrate latest ideas and algorithms from the Machine Learning field, applied to problems of monitoring the biodiversity in a particular setting.

what we do

Computer science innovation for biodiversity understanding
Solutions in shape & movement recognition & description

We develop novel techniques able to recognise different lifeforms, characterise their shape, movements, sequential gestures, to the level where they will describe and compute articulated movements in real time. The research outcomes would change the paradigm of monitoring biodiversity, by giving feedback on behaviours after analysing, in real time, the streaming videos.


We are international experts based in London, UK.

Prof. Frederic Fol Leymarie

Founder, Director
Frederic (PhD, Brown, 2003), a professor of Computing, is developing a mathematical language for shape representation with potential for applications in various domains and industries, from the Arts and Performance areas to Biology, Medicine, CAD, and more.


Founder, Director
Stefan (PhD, Technische Universität Berlin, 1996) is a Professor of Knowledge Media with expertise in visual processing with a view to automated multimedia understanding and has worked as a consultant for data mining and information management projects.


Prashant Aparajeya (PhD Uni. of London, 2016) is a researcher in computer vision, with a focus on shape understanding, pose and movement computing, information retrieval, machine learning.


Vesna (PhD, FRSA) is a transdisciplinary artist and thinker. She composes and performs with sound, light, rhythm, space, movement, text and code. She explores embodiment, transformation, manipulation of time and movement.

Ryan Rueger

IT support & Research Assistant
Ryan Rueger is a mathematics student at ETH Zürich with particular interest in applications of algebra in cryptography. Ryan is a part time research assistant at Dynaikon for the Cos4Cloud Project.

Kai Waddington

Software developer & Researcher (Deep Learning)
Kai has a BSc in Computer Science from Goldsmiths, University of London, and is currently a Ph.D. student at the Open University where he is researching the area of automatic species detection in camera-trap images for the purpose of bio-diversity monitoring.

Miklas Riechmann

Software developer & Research Assistant (Camera Traps)
Miklas has an MEng in Electronic and Software Engineering from the University of Glasgow. He is currently working at DynAIkon as a Visiting Junior Software Developer & Research Assistant focussing on AI in camera traps.

Ross Gardiner

Software developer and Research assistant (Deep Learning for low-powered devices)
Ross Gardiner is an Electronic and Software Engineering student at the University of Glasgow. Ross is completing his MEng final-year project with DynAIkon as a Research Assistant and Software Developer for DynAIkon camera trap software.

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