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Shivesh ChaudharyPhD Candidate |
Research Interests
I am an experimentalist and computational scientist bringing in tools from machine-learning and computer vision to neuroscience.
I am particularly interested in how stimulus and behavior is encoded in C. elegans brain, and how global brain activity evolves over long timescales.
My current PhD work areas include:
Automated cell identification in C. elegans whole-brain images
Hybrid probabilistic graphical models for accurate tracking of neurons in whole-brain videos
Deep learning based whole-brain 3D cell segmentation
Microfluidic paradigms for naturalistic chemical-mechanical stimulation and simultaneous whole-brain imaging
I easily get interested in broad scientific areas. Thus I am also interested in Computational Microscopy, Optimization Methods, Optimal Transport, Deep Learning for Combinatorial Optimization etc.
News
[June 2022] Deep denoising for calcium imaging paper is accepted in Nature Communications 2022.
[April 2022] Attended annual Southeast Center for Mathematics and Biology (SCMB) symposium at Flatiron Institute, NYC. Presented 1 poster.
[Jan 2022] Awarded 3rd place prize in 2022 Suddath Awards at Georgia Tech.
[Jan 2022] Code released for Whole-Brain Deep Denoising paper.
[Nov 2021] Presented 3 talks at AICHE 2021
[Jul 2021] Presented 1 talk and 1 poster at MicroTas 2021
[Jan 2021] Paper on automatically identifying cells in C. elegans whole-brain images is accepted in eLife.
Featured in Eureka Alert, Medical Express, Neuroscience News
[Mar 2020] Our paper on automatically identifying cells in C. elegans whole-brain images is released on biorxiv. Code Datasets
Bio
I was trained as a Chemical Engineer at IIT Kanpur where I finished BS-MS dual degree in 2013. There I worked with Prof. P. K. Bhattacharya on computational modelling of water management in PEM fuel cells and effects of Schroeder's Paradox. After graduating, I worked with a Management Consulting firm developing data-driven solutions for international firms like Wolters Kluwers, Assurant, T-Mobile. Since 2016 I am a PhD Candidate at Georgia Tech, advised by Prof. Hang Lu, where I work on developing tools for fast and easy processing of whole-brain functional imaging data.