Mikko Impiö

I am a researcher and PhD candidate at the Finnish Environment Institute (Syke), working on deep learning and computer vision for environmental monitoring.

My work focuses on topics like fine-grained classification, out-of-distribution detection and multimodal learning from images, videos and DNA data, with applications in biodiversity monitoring and remote sensing.

I hold a MSc in Electrical Engineering from Tampere University, with a major in Signal Processing. During my studies I interned at Intel, where I worked with 3A algorithms, and at Vaisala, focusing on deep learning methods for predictive maintenance.

I am a member in several expert groups, including:

• EIONET Data and Digitalization (European Environment Agency).
• Lukki, Finland’s national coordination group for nature information.
• GEO AI4EO, a GEO subgroup focused on geospatial AI for Earth Observation.

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LinkedIn Github Google Scholar Bluesky

Selected publications

Google scholar: [Link]

Computer vision-based estimation of invertebrate biomass
Mikko Impiö, Philipp M. Rehsen, Jarrett Blair, Cecilie Mielec, Arne J. Beermann, Florian Leese, Toke T. Høye, Jenni Raitoharju
arXiv preprint arXiv:2603.06362, 2026
[paper] [dataset]

AquaMonitor: A multimodal multi-view image sequence dataset for real-life aquatic invertebrate biodiversity monitoring
Mikko Impiö, Philipp M. Rehsen, Tiina Laamanen, Arne J. Beermann, Florian Leese, Jenni Raitoharju
arXiv preprint arXiv:2505.22065, 2025
[paper] [code] [dataset]

Improving taxonomic image-based out-of-distribution detection with DNA barcodes
Mikko Impiö, Jenni Raitoharju
2024 32nd European Signal Processing Conference (EUSIPCO), 2024
[paper]

Remote sensing the habitats of Northern Lapland – Final project report, parts 1 and 2
Ylä-Lapin luonnon kaukokartoitus – Projektin loppuraportti, osat 1 ja 2
Anna Tammilehto, Pekka Härmä, Minna Kallio, Markus Törmä, Arto Saikkonen, Seppo Tuominen, Mikko Impiö, Mika Heikkinen, Mikko Kervinen, Tytti Jussila, Kristin Böttcher, Elisa Pääkkö, Aira Kokko, Katariina Mäkelä, Saku Anttila
Metsähallituksen luonnonsuojelujulkaisuja, Sarja A 248 & 249, 2024
[report 1] [report 2]

The Riverine Organism Drift Imager: A new technology to study organism drift in rivers and streams
Frédéric de Schaetzen, Mikko Impiö, Basil Wagner, Patryk Nienaltowski, Michael Arnold, Martin Huber, Matthias Meyer, Jenni Raitoharju, Luiz G. M. Silva, Roman Stocker
Methods in Ecology and Evolution, 2023
[paper]

Multi-level reversible encryption for ECG signals using compressive sensing
Mikko Impiö, Mehmet Yamaç, Jenni Raitoharju
ICASSP 2021 – IEEE International Conference on Acoustics, Speech and Signal Processing, 2021
[paper] [code]

Code

Github: [Link]

dinotool
Command-line tool for extracting DINO, CLIP, SigLIP2, TIPSv2, RADIO, features for images and videos
[code] ★

taxonomist
A library for training deep learning models for species classification.
[code] ★

tiers
A hierarchical label handling library for Python
[code] ★

point-eo
A python libary that makes it simple to sample points from large rasters, fit ML models and perform inference on larger-than-memory rasters.
[code] ★