Dr. Ekaterina Nepovinnykh, a rising expert in digital image processing and machine learning applications for wildlife conservation, is spending the week at The Ohio State University as part of her role as an Imageomics NextGen researcher.
Nepovinnykh kicked off her visit with a presentation on Monday morning, detailing her innovative work on automatic animal re-identification, a technology she developed to aid in the conservation of endangered species. On Tuesday, she discussed computer vision applications for animal and plankton identification.
Her talk, held at Pomerene Hall, explored a species-agnostic framework for animal re-identification. Her method, which evolved from work on Saimaa ringed seals, uses advanced computer vision techniques to automatically detect and identify individual animals across species.
Nepovinnykh said the approach has already been applied to zebras, giraffes, and tigers, providing critical tools for biologists and conservationists.
A doctoral graduate in computational engineering, Nepovinnykh has spent the last six years developing machine learning-based methods to streamline wildlife monitoring. Her research has focused on creating scalable solutions to tackle the challenge of re-identifying animals based on unique patterns, offering a breakthrough in species conservation efforts.
As part of her visit, Nepovinnykh is engaging with students and researchers to discuss her work and potential collaborations.
Nepovinnykh currently works at LUT and RPI Universities, continuing to refine the applications of her research for various species, with the aim of empowering biologists with innovative tools for global conservation efforts.

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