Research library

Research teams

Papers, datasets, models, and field notes are connected into a practical research map for digital beekeeping, from academic references to applied Gratheon experiments.

Research map

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Worldwide, several interdisciplinary research teams work on precision beekeeping and computational apidology on a recurring basis. The list below is based on repeated appearances in the Gratheon research-paper library, not on citation counts. One-off paper authors are intentionally excluded.

Portraits are included only when they are published by official university or lab pages. Rows without a reliable official portrait source stay text-only to avoid using personal or unofficial photos.

Team / university Recurring people Evidence in the local library Main areas
🇩🇪 Freie Universität Berlin, Dahlem Center for Machine Learning and Robotics / University of Konstanz, Centre for the Advanced Study of Collective Behaviour
Tim Landgraf Benjamin Wild Pranav Kedia Marie Messerich
Tim Landgraf, Benjamin Wild, Fernando Wario, Pranav Kedia, Marie Messerich
~9 papers around FU Berlin, plus Konstanz follow-up work Waggle-dance decoding, lifetime tracking of tagged bees, social-network analysis, in-hive robotics, Landgraf Lab, COMB modular robot platform
🇱🇻 Latvia University of Life Sciences & Technologies, Faculty of Engineering and Information Technologies Aleksejs Zacepins, Vitalijs Komasilovs, Armands Kviesis, Valentina Komasilova ~8 papers Precision-beekeeping systems, hive scales, temperature/sound/weight sensors, ESP-NOW and GSM/GPRS telemetry, data warehouses, apiary-location and GIS support
🇨🇿 Brno University of Technology, Faculty of Information Technology Simon Bilik, Adam Ligocki, Karel Horak, Tomas Zemcik, Lukas Kratochvila ~7 papers Computer vision for bee and Varroa detection, hyperspectral / narrow-spectrum imaging, Raspberry Pi monitoring hardware, surveys of ML in beehive monitoring
🇺🇸 Utah State University, School of Computing Vladimir Kulyukin, Anastasiia Tkachenko, Aleksey V. Kulyukin, Sarbajit Mukherjee ~6 papers BeePi datasets, continuous electronic beehive monitoring, audio/image/video/weather datasets, hive entrance traffic, BeePIV, energy-efficient object inference
🇵🇷 University of Puerto Rico at Mayagüez Rémi Mégret, José L. Agosto, Tugrul Giray, Ivan Rodriguez, Edgar Acuña ~5 papers BigDBee / LabelBee, entrance-video annotation, multi-animal tracking, pollen-bearing bee recognition, honeybee re-identification datasets
🇦🇹 University of Graz, Artificial Life Lab + 🇨🇿 Czech Technical University, Center for Machine Perception consortium
Thomas Schmickl
Thomas Schmickl, Tomáš Krajník, Martin Stefanec, Farshad Arvin, Ali Emre Turgut
~4 Graz papers, ~3 CTU consortium papers RoboRoyale, Hiveopolis, autonomous in-hive robotics, queen-behaviour tracking, robotic comb mapping, bio-hybrid ecosystem interventions
🇩🇪 Karlsruhe Institute of Technology Frederic Tausch, Jan Wagner, Simon Klaus ~3 KIT papers, plus apic.ai outputs apic.ai, DeepBees, scalable visual hive monitoring, edge/cloud bee tracking pipelines, pollinators as computer-vision data collectors, ecotoxicology monitoring
🇱🇹 Vilnius Gediminas Technical University Tomyslav Sledevič, Artūras Serackis, Dalius Matuzevičius ~3 papers Hive-entrance computer vision, bee detection and direction datasets, keypoint-based orientation estimation, fanning-behaviour detection
🇨🇦 Institut National de la Recherche Scientifique / Université Laval Mahsa Abdollahi, Yi Zhu, Tiago H. Falk, Ségolène Maucourt, Pierre Giovenazzo 2 dataset papers Longitudinal acoustic and multi-sensor datasets, phenotypic trait measurements, urban beehive monitoring benchmarks, Nectar Technologies
🇯🇵 Okinawa Institute of Science and Technology, Biological Physics Theory Unit / 🇳🇱 Vrije Universiteit Amsterdam Katarzyna Bozek, Alexander S. Mikheyev, Greg J. Stephens 2 high-impact tracking papers Markerless full-colony tracking, dense object tracking on comb, brood-cell and bee-position inference from long-term observation-hive video

Notes

  • Groups are ranked primarily by repeated presence in the local Gratheon paper library and secondarily by direct relevance to Gratheon products.
  • Shared consortium projects are grouped together when the same research programme appears across multiple institutions.
  • General-purpose animal-pose-estimation labs are not listed unless their work is repeatedly connected to honeybee monitoring in the library.

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