Pavan P Ramdya
+41 21 693 69 60
EPFL
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Web site: Site web: https://sv.epfl.ch/education
EPFL SV BMI UPRAMDYA
AAB 1 05 (Bâtiment AAB)
Station 19
CH-1015 Lausanne
+41 21 693 69 60
+41 21 693 40 74
Local:
AAB 1 05
EPFL
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SV
>
BMI
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UPRAMDYA
Web site: Site web: https://ramdya-lab.epfl.ch
EPFL SV IBI-GE
AAB 1 05 (Bâtiment AAB)
Station 19
CH-1015 Lausanne
Web site: Site web: https://bioengineering.epfl.ch/
Publications
Publications Infoscience
Infoscience
The neuromechanics of animal locomotion: From biology to robotics and back
Science Robotics. 2023-05-31. DOI : 10.1126/scirobotics.adg0279.Ascending neurons convey behavioral state to integrative sensory and action selection brain regions
Nature Neuroscience. 2023-03-23. DOI : 10.1038/s41593-023-01281-z.Overcoming the Domain Gap in Neural Action Representations
International Journal Of Computer Vision. 2022-12-19. DOI : 10.1007/s11263-022-01713-6.Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors
Elife. 2022-10-26. DOI : 10.7554/eLife.81527.Microengineered devices enable long-term imaging of the ventral nerve cord in behaving adult Drosophila
Nature Communications. 2022-08-25. DOI : 10.1038/s41467-022-32571-y.NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster
Nature Methods. 2022-05-11. DOI : 10.1038/s41592-022-01466-7.NeuroMechFly: an integrative simulation testbed for studying Drosophila behavioral control
Nature Methods. 2022-05-01. DOI : 10.1038/s41592-022-01411-8.Connecting the dots in ethology: applying network theory to understand neural and animal collectives
Current Opinion In Neurobiology. 2022-04-01. DOI : 10.1016/j.conb.2022.102532.Uncovering the neural substrates of communication between the brain and ventral nerve cord in Drosophila melanogaster (italic)
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9476.Methods for acute and long-term imaging of the ventral nerve cord in behaving adult Drosophila
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9466.Uncovering the neural encoding of behavior in the adult Drosophila motor system
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-8966.Using Animal Motion Capture to Learn Neural Representations
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9124.LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals
Nature Methods. 2021-08-01. DOI : 10.1038/s41592-021-01226-z.Extensive and diverse patterns of cell death sculpt neural networks in insects
Elife. 2020-09-07. DOI : 10.7554/eLife.59566.Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals
2020-09-01. Conference on Computer Vision and Pattern Recognition (CVPR). p. 13155-13165. DOI : 10.1109/CVPR42600.2020.01317.Serotonergic Modulation of Walking in Drosophila
Current Biology. 2019-12-16. DOI : 10.1016/j.cub.2019.10.042.DeepFly3D, a deep learning-based approach for 3D limb and appendage tracking in tethered, adult Drosophila
eLife. 2019-10-04. DOI : 10.7554/eLife.48571.Imaging neural activity in the ventral nerve cord of behaving adult Drosophila
Nature Communications. 2018-10-22. DOI : 10.1038/s41467-018-06857-z.FlyLimbTracker: An Active Contour Based Approach for Leg Segment Tracking in Unmarked, Freely Behaving Drosophila
PLoS One. 2017. DOI : 10.1371/journal.pone.0173433.Climbing favours the tripod gait over alternative faster insect gaits
Nature Communications. 2017. DOI : 10.1038/ncomms14494.Fluctuation-driven neural dynamics reproduce Drosophila locomotor patterns
Plos Computational Biology. 2015. DOI : 10.1371/journal.pcbi.1004577.Mechanosensory interactions drive collective behaviour in Drosophila
Nature. 2015. DOI : 10.1038/nature14024.Fluorescence Behavioral Imaging (FBI) tracks identity in heterogeneous groups of Drosophila
PLOS One. 2012. DOI : 10.1371/journal.pone.0048381.Complementary Function and Integrated Wiring of the Evolutionarily Distinct Drosophila Olfactory Subsystems
Journal Of Neuroscience. 2011. DOI : 10.1523/JNEUROSCI.2360-11.2011.Evolving olfactory systems on the fly
Trends In Genetics. 2010. DOI : 10.1016/j.tig.2010.04.004.The neuromechanics of animal locomotion: From biology to robotics and back
Science Robotics. 2023-05-31. DOI : 10.1126/scirobotics.adg0279.Ascending neurons convey behavioral state to integrative sensory and action selection brain regions
Nature Neuroscience. 2023-03-23. DOI : 10.1038/s41593-023-01281-z.Overcoming the Domain Gap in Neural Action Representations
International Journal Of Computer Vision. 2022-12-19. DOI : 10.1007/s11263-022-01713-6.Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors
Elife. 2022-10-26. DOI : 10.7554/eLife.81527.Microengineered devices enable long-term imaging of the ventral nerve cord in behaving adult Drosophila
Nature Communications. 2022-08-25. DOI : 10.1038/s41467-022-32571-y.NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster
Nature Methods. 2022-05-11. DOI : 10.1038/s41592-022-01466-7.NeuroMechFly: an integrative simulation testbed for studying Drosophila behavioral control
Nature Methods. 2022-05-01. DOI : 10.1038/s41592-022-01411-8.Connecting the dots in ethology: applying network theory to understand neural and animal collectives
Current Opinion In Neurobiology. 2022-04-01. DOI : 10.1016/j.conb.2022.102532.Uncovering the neural substrates of communication between the brain and ventral nerve cord in Drosophila melanogaster (italic)
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9476.Methods for acute and long-term imaging of the ventral nerve cord in behaving adult Drosophila
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9466.Uncovering the neural encoding of behavior in the adult Drosophila motor system
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-8966.Using Animal Motion Capture to Learn Neural Representations
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9124.LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals
Nature Methods. 2021-08-01. DOI : 10.1038/s41592-021-01226-z.Extensive and diverse patterns of cell death sculpt neural networks in insects
Elife. 2020-09-07. DOI : 10.7554/eLife.59566.Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals
2020-09-01. Conference on Computer Vision and Pattern Recognition (CVPR). p. 13155-13165. DOI : 10.1109/CVPR42600.2020.01317.Serotonergic Modulation of Walking in Drosophila
Current Biology. 2019-12-16. DOI : 10.1016/j.cub.2019.10.042.DeepFly3D, a deep learning-based approach for 3D limb and appendage tracking in tethered, adult Drosophila
eLife. 2019-10-04. DOI : 10.7554/eLife.48571.Imaging neural activity in the ventral nerve cord of behaving adult Drosophila
Nature Communications. 2018-10-22. DOI : 10.1038/s41467-018-06857-z.FlyLimbTracker: An Active Contour Based Approach for Leg Segment Tracking in Unmarked, Freely Behaving Drosophila
PLoS One. 2017. DOI : 10.1371/journal.pone.0173433.Climbing favours the tripod gait over alternative faster insect gaits
Nature Communications. 2017. DOI : 10.1038/ncomms14494.Fluctuation-driven neural dynamics reproduce Drosophila locomotor patterns
Plos Computational Biology. 2015. DOI : 10.1371/journal.pcbi.1004577.Mechanosensory interactions drive collective behaviour in Drosophila
Nature. 2015. DOI : 10.1038/nature14024.Fluorescence Behavioral Imaging (FBI) tracks identity in heterogeneous groups of Drosophila
PLOS One. 2012. DOI : 10.1371/journal.pone.0048381.Complementary Function and Integrated Wiring of the Evolutionarily Distinct Drosophila Olfactory Subsystems
Journal Of Neuroscience. 2011. DOI : 10.1523/JNEUROSCI.2360-11.2011.Evolving olfactory systems on the fly
Trends In Genetics. 2010. DOI : 10.1016/j.tig.2010.04.004.Enseignement & Phd
Enseignement
Life Sciences Engineering
Doctorants
Braun Jonas Friedrich, Hurtak Femke Imreh, Lobato Rios Victor, Ozdil Pembe Gizem, Stimpfling Victor Alfred, Wang Sibo,A dirigé les thèses EPFL de
Aymanns Florian , Chen Chin-Lin , Günel Semih , Hermans Laura Joan ,Cours
Neuroscience
Nous commençons avec la signalisation électrique et chimique des neurones. Après, l'étudiant apprendra comment les neurones dans le cerveau reçoivent des informations sensoriels, et comment d'autres neurones contrôlent le comportement d'un animal. Finalement, la mémoire, l l'apprentissage, et des ma
Controlling behavior in animals and robots
Les étudiants acquerront une vision intégrée des algorithmes biologiques et artificiels permettant de contrôler les comportements autonomes. Les étudiants synthétiseront et appliqueront ces connaissances dans le cadre de présentations orales et d'exercices informatiques.