Chaim Elchik

I am a computational ecologist and data scientist pursuing a PhD in Ecology at Lancaster University. My research sits at the intersection of AI, computer vision, and conservation, leveraging machine learning to monitor and protect biodiversity.

I hold a BSc in Information Science and an MSc in Data Science from the University of Amsterdam. My master’s thesis adapted YOLOv8 with stereo inputs to create a novel multi-view framework for underwater fish tracking.

Currently, my doctoral research investigates the evolutionary role of biological colouration. Using AI-driven image analysis and unsupervised clustering, I examine whether habitat degradation disrupts adaptive colour-environment matching. I aim to build scalable tools capable of detecting early environmental disruption from natural optical signals before they are visible to the naked eye.

Professionally, I serve as a Data Scientist for Conservation AI, training object detection models to track animals in aerial drone videos, and for Vastgoeddata Nederland, developing predictive vision and NLP models. I also support students as a university module Demonstrator at Lancaster University.

I have authored papers on computer vision in ecology, including a framework for tracking elephants in Drone Systems and Applications, with additional manuscripts on 3D stereo-matching, lemur thermal detection, and visual ecology in progress. Beyond academia, I am fluent in Dutch, English, Hebrew, and Spanish, and I enjoy solo travel, competitive kickboxing, and remote wildlife rescue volunteering.

July 2026