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Pritish Chakravarty

Pritish Chakravarty
Max Planck Institute of Animal Behavior · Department for the Ecology of Animal Societies

PhD

About

12
Publications
1,317
Reads
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91
Citations
Citations since 2017
11 Research Items
88 Citations
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20172018201920202021202220230510152025
Introduction
Pritish Chakravarty is a multidisciplinary researcher working in the field of animal behavior and ecology. He trained as an engineer at the Indian Institute of Technology Bombay, and then at the École Polytechnique Fédérale de Lausanne (EPFL), where he specialized in biological signal processing and algorithm development, and wearable sensors. Main projects: meerkat foraging strategies and energetics (EPFL; UZH); fish perception and motion (University of Cambridge); animal sleep (MPI-AB).
Additional affiliations
August 2021 - July 2022
University of Cambridge
Position
  • Postdoc
November 2020 - July 2021
University of Zurich
Position
  • Postdoc
April 2015 - May 2015
Stanford University
Position
  • Researcher
Education
November 2015 - August 2020
École Polytechnique Fédérale de Lausanne
Field of study
  • Movement analysis and measurement
September 2013 - July 2015
July 2008 - July 2012
Indian Institute of Technology Bombay
Field of study
  • Chemical Engineering

Publications

Publications (12)
Article
Full-text available
Animal‐borne accelerometers have been used across more than 120 species to infer biologically significant information such as energy expenditure and broad behavioural categories. While the accelerometer's high sensitivity to movement and fast response times present the unprecedented opportunity to resolve fine‐scale behaviour, leveraging this oppor...
Article
Full-text available
Background: Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magn...
Article
Full-text available
Data from animal‐borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have been the tool of choice for characterising animal behaviour. Although machine learning models perf...
Article
Full-text available
This article presents a comprehensive theoretical model and limited experimental results for describing two-dimensional hydrodynamic focusing in microchannels involving immiscible fluids. It is shown that the normalized focused sample width depends on three non-dimensional parameters - the flow rate ratio, viscosity ratio and aspect ratio. A theory...

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