Nagy Máté

Nagy Máté

tudományos főmunkatárs

PhD (Eötvös Loránd Tudományegyetem, Budapest, 2011)

Biológiai Fizika Tanszék
MTA-ELTE Lendület Collective Behaviour Research Group

Szoba: 3.91
Telefon: +36-1-372-2762
Mellék: +36-1-372-2500 / 6362
Honlap: collective.elte.hu
Emailcím: uh.etle.lah@etamygan

Biográfia:

Máté Nagy is the principal investigator of the MTA-ELTE Lendület Collective Behavior Research Group. Máté is a biological physicist interested in collective animal behaviour and applying/developing state-of-the-art automated measurement techniques and analysis methods.
Previously he worked at the Max Planck Institute for Ornithology and Animal Behavior, Konstanz with Prof. Iain Couzin. Prior to that, he was a Royal Society Newton Fellow in the Department of Zoology, University of Oxford working with Dr. Dora Biro. He has been a post-doc and he did his PhD in Physics at Eötvös University, Budapest with Prof. Tamás Vicsek.
The MTA-ELTE Collective Behaviour Research Group focuses on collective sensing, cognition and decision-making and how individuals in groups use social information and combine local sensory input. We are aiming to uncover the mechanisms how group achieves synergistic benefit over the performance of any of its members. The research mainly, but not exclusively concentrate on collective migration and more specifically, the collective thermal soaring of birds. Our goals are twofold: (1) To get biological insight into the collective aspects of wild birds’ thermalling by using high resolution measurements from autonomous soaring drone(s) flying near them; (2) To provide bio-inspiration and a solution that uses information from animals for such robotic system. That will have enormous potential in applications (wildlife monitoring, search and rescue, etc.).

Tudományos adatbázisok profiloldalai:

Az utolsó 5 év válogatott közleményei:

  1. Nagy, M., Horicsányi, A., Kubinyi, E., Couzin, I. D., Vásárhelyi, G., Flack, A., & Vicsek, T. (2020). Synergistic benefits of group search in rats, Current Biology 30, 1-6. link
  2. Li, L., Nagy, M., Graving, J. M., Bak-Coleman, J., Xie, G., & Couzin, I. D. (2020). Vortex phase matching as a strategy for schooling in robots and in fish. Nature Communications, 11(1), 1-9. link
  3. Nagy, M.*, Flack, A.*, Fiedler, W., Couzin, I. D., & Wikelski, M. (2018). From local collective behavior to global migratory patterns in white storks. Science, 360(6391), 911-914. link
  4. Nagy, M., Couzin, I. D., Fiedler, W., Wikelski, M., & Flack, A. (2018). Synchronization, coordination and collective sensing during thermalling flight of freely migrating white storks. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1746), 20170011. link
  5. Virágh, C., Nagy, M., Gershenson, C., & Vásárhelyi, G. (2016, October). Self-organized UAV traffic in realistic environments. In 2016 IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 1645-1652). IEEE. link
  6. Nagy, M.*, Ákos, Z.*, Beck, R.*, Vicsek, T., & Kubinyi, E. (2014). Leadership and path characteristics during walks are linked to dominance order and individual traits in dogs. PLoS computational biology, 10(1), e1003446. link