Pavan P Ramdya
Nationalité: USA
+41 21 693 69 60
EPFL › SV › SV-SSV › SSV-ENS
Site web: https://sv.epfl.ch/education
EPFL SV BMI UPRAMDYA
AAB 1 05 (Bâtiment AAB)
Station 19
1015 Lausanne
+41 21 693 40 74
+41 21 693 69 60
Office: AAB 1 05
EPFL › SV › BMI › UPRAMDYA
Site web: https://ramdya-lab.epfl.ch
EPFL SV IBI-GE
AAB 1 05 (Bâtiment AAB)
Station 19
1015 Lausanne
+41 21 693 69 60
Office: AAB 1 05
EPFL › SV › IBI-SV › IBI-SV-GE
Site web: https://bioengineering.epfl.ch/
+41 21 693 69 60
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Site web: https://go.epfl.ch/phd-edne
+41 21 693 69 60
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+41 21 693 69 60
EPFL › VPA › VPA-AVP-DLE › AVP-DLE-EDOC › EDNE-ENS
Site web: https://go.epfl.ch/edne
Formation
PhD
| Neurobiology2009 – 2009 Harvard University
Publications représentatives
Imaging neural activity in the ventral nerve cord of behaving adult Drosophila.
Chen C-L*, Hermans L*, Viswanathan MC, Aymanns F, Unser M, Cammarato A, Dickinson MH, Ramdya P
Published in Nature Communications. 2018 Oct 22; 9(1):4390. in
Climbing favours the tripod gait over alternative faster insect gaits.
Ramdya P, Thandiackal R, Cherney R, Asselborn T, Benton R, Ijspeert AJ, Floreano D.
Published in Nature Communications. 2017 Feb 17;8:14494. in
Mechanosensory interactions drive collective behaviour in Drosophila.
Ramdya P, Lichocki P, Cruchet S, Frisch L, Tse W, Floreano D, Benton R.
Published in Nature. 2015 Mar 12;519(7542):233-6. in
Emergence of binocular functional properties in a monocular neural circuit.
Pavan Ramdya & Florian Engert
Published in Nature Neuroscience, 2008 Sep;11(9):1083-90. in
Infoscience
Modeling conditional distributions of neural and behavioral data with masked variational autoencoders
Cell Reports. 2025. DOI : 10.1016/j.celrep.2025.115338.An integrative computational modeling approach for Drosophila motor control
Lausanne, EPFL, 2025. DOI : 10.5075/epfl-thesis-10986.Uncovering neural architectures enabling robust and flexible motor control in Drosophila
Lausanne, EPFL, 2025. DOI : 10.5075/epfl-thesis-11600.NeuroMechFly v2: simulating embodied sensorimotor control in adult <i>Drosophila</i>
NATURE METHODS. 2024. DOI : 10.1038/s41592-024-02497-y.Descending networks transform command signals into population motor control
Nature. 2024. DOI : 10.1038/s41586-024-07523-9.Neural mechanisms of learned sociability in Drosophila
Lausanne, EPFL, 2024. DOI : 10.5075/epfl-thesis-10042.Uncovering interactions between Descending Neurons as a functional principle of behavioural control
Lausanne, EPFL, 2024. DOI : 10.5075/epfl-thesis-10712.The neuromechanics of animal locomotion: From biology to robotics and back
Science Robotics. 2023. DOI : 10.1126/scirobotics.adg0279.Ascending neurons convey behavioral state to integrative sensory and action selection brain regions
Nature Neuroscience. 2023. DOI : 10.1038/s41593-023-01281-z.Overcoming the Domain Gap in Neural Action Representations
International Journal Of Computer Vision. 2022. DOI : 10.1007/s11263-022-01713-6.Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors
Elife. 2022. DOI : 10.7554/eLife.81527.Microengineered devices enable long-term imaging of the ventral nerve cord in behaving adult Drosophila
Nature Communications. 2022. DOI : 10.1038/s41467-022-32571-y.NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster
Nature Methods. 2022. DOI : 10.1038/s41592-022-01466-7.NeuroMechFly: an integrative simulation testbed for studying Drosophila behavioral control
Nature Methods. 2022. 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. 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.Using Animal Motion Capture to Learn Neural Representations
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9124.Uncovering the neural encoding of behavior in the adult Drosophila motor system
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-8966.LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals
Nature Methods. 2021. DOI : 10.1038/s41592-021-01226-z.Extensive and diverse patterns of cell death sculpt neural networks in insects
Elife. 2020. DOI : 10.7554/eLife.59566.Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals
2020. 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. 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. DOI : 10.7554/eLife.48571.Imaging neural activity in the ventral nerve cord of behaving adult Drosophila
Nature Communications. 2018. DOI : 10.1038/s41467-018-06857-z.Climbing favours the tripod gait over alternative faster insect gaits
Nature Communications. 2017. DOI : 10.1038/ncomms14494.Mechanosensory interactions drive collective behaviour in Drosophila
Nature. 2015. DOI : 10.1038/nature14024.Fluctuation-driven neural dynamics reproduce Drosophila locomotor patterns
Plos Computational Biology. 2015. DOI : 10.1371/journal.pcbi.1004577.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
The 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.Modeling conditional distributions of neural and behavioral data with masked variational autoencoders
Cell Reports. 2025. DOI : 10.1016/j.celrep.2025.115338.An integrative computational modeling approach for Drosophila motor control
Lausanne, EPFL, 2025. DOI : 10.5075/epfl-thesis-10986.Uncovering neural architectures enabling robust and flexible motor control in Drosophila
Lausanne, EPFL, 2025. DOI : 10.5075/epfl-thesis-11600.NeuroMechFly v2: simulating embodied sensorimotor control in adult <i>Drosophila</i>
NATURE METHODS. 2024. DOI : 10.1038/s41592-024-02497-y.Descending networks transform command signals into population motor control
Nature. 2024. DOI : 10.1038/s41586-024-07523-9.Neural mechanisms of learned sociability in Drosophila
Lausanne, EPFL, 2024. DOI : 10.5075/epfl-thesis-10042.Uncovering interactions between Descending Neurons as a functional principle of behavioural control
Lausanne, EPFL, 2024. DOI : 10.5075/epfl-thesis-10712.The neuromechanics of animal locomotion: From biology to robotics and back
Science Robotics. 2023. DOI : 10.1126/scirobotics.adg0279.Ascending neurons convey behavioral state to integrative sensory and action selection brain regions
Nature Neuroscience. 2023. DOI : 10.1038/s41593-023-01281-z.Overcoming the Domain Gap in Neural Action Representations
International Journal Of Computer Vision. 2022. DOI : 10.1007/s11263-022-01713-6.Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors
Elife. 2022. DOI : 10.7554/eLife.81527.Microengineered devices enable long-term imaging of the ventral nerve cord in behaving adult Drosophila
Nature Communications. 2022. DOI : 10.1038/s41467-022-32571-y.NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster
Nature Methods. 2022. DOI : 10.1038/s41592-022-01466-7.NeuroMechFly: an integrative simulation testbed for studying Drosophila behavioral control
Nature Methods. 2022. 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. 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.Using Animal Motion Capture to Learn Neural Representations
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9124.Uncovering the neural encoding of behavior in the adult Drosophila motor system
Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-8966.LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals
Nature Methods. 2021. DOI : 10.1038/s41592-021-01226-z.Extensive and diverse patterns of cell death sculpt neural networks in insects
Elife. 2020. DOI : 10.7554/eLife.59566.Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals
2020. 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. 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. DOI : 10.7554/eLife.48571.Imaging neural activity in the ventral nerve cord of behaving adult Drosophila
Nature Communications. 2018. DOI : 10.1038/s41467-018-06857-z.Climbing favours the tripod gait over alternative faster insect gaits
Nature Communications. 2017. DOI : 10.1038/ncomms14494.Mechanosensory interactions drive collective behaviour in Drosophila
Nature. 2015. DOI : 10.1038/nature14024.Fluctuation-driven neural dynamics reproduce Drosophila locomotor patterns
Plos Computational Biology. 2015. DOI : 10.1371/journal.pcbi.1004577.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
The 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.Doctorant·es actuel·les
https://people.epfl.ch/269646?lang=fr, https://people.epfl.ch/320354?lang=fr, https://people.epfl.ch/322956?lang=fr, https://people.epfl.ch/375965?lang=fr
A dirigé les thèses EPFL de
Chin-Lin Chen, Laura Joan Hermans, Florian Aymanns, Victor Lobato Rios, Jonas Braun, http://dx.doi.org/10.5075/epfl-thesis-11600, http://dx.doi.org/10.5075/epfl-thesis-10986
Cours
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.
Planning your scientific journey
Planning Your Scientific Journey: Being successful as a scientist requires more than acquiring knowledge and developing experimental skills. It also requires: (1) asking a good scientific question, (2) establishing a clear plan of action, and (3) seeking advice along the way.
Python Bootcamp
An intensive, hands-on, pragmatic introduction to computer programming. Students learn basic concepts like data types, control structures, string processing, functions, input/output. They perform simulations, write scripts, and analyze and plot biological data. Python is the language of instruction.