Curriculum Vitae

Academic and professional history.

Professional Experience

Researcher

Nov 2023 - Present
Inria-CEA MIND Team, NeuroSpin, CEA Paris-Saclay
Accelerated MRI acquisitions and artifact-free reconstructions: designing and learning non-Cartesian k-space trajectories for high-field imaging, and keeping the reconstruction tooling reproducible.

Doctoral Student (NUMERICS Fellowship)

Nov 2020 - Apr 2023
NeuroSpin, CEA Paris-Saclay
Joint optimization of acquisition and reconstruction algorithms for high-resolution Magnetic Resonance Imaging at 7T and 11.7T. Designed and learned trajectories for accelerated and minimally artifacted 3D high-resolution MRI.

Research Engineer

Jul 2019 - Aug 2020
NeuroSpin, CEA Paris-Saclay
Compressed Sensing for Imaging Applications: compressed sensing for the acquisition and reconstruction of Magnetic Resonance Imaging and Scanning Electron Microscopy data.

Architect, GPU Memory Subsystem

Jun 2018 - Jun 2019
NVIDIA Corporation, Bangalore
Built and tested functionally accurate models and performance models for NVLink.

Education

Doctorate, NUMERICS Fellowship

2020 - 2023
Université Paris-Saclay, Electrical, Optical, Bio-Physics and Engineering (EOBE)
Doctoral research conducted at NeuroSpin (CEA) within the Inria MIND team, on joint design of k-space sampling and learned reconstruction for accelerated MRI.
Thesis: Designing and learning non-Cartesian k-space sampling trajectories for accelerated 3D MRI (defended 25 April 2023)

Masters Equivalence

Dec 2019
Université Paris-Saclay, Electrical, Optical, Bio-Physics and Engineering (EOBE)
Equivalence awarded on entry to the doctoral programme.

B.Tech in Electronics and Communication Engineering

2014 - 2018
National Institute of Technology Karnataka, Surathkal
CGPA 9.96/10.

Skills

  • Signal and image processing, optimization, machine learning and deep learning.
  • MR physics and sequence programming, including IDEA sequence programming for Siemens scanners.
  • Programming: strong programming skills in Python, MATLAB, C and C++, with significant experience of TensorFlow and PyTorch.
  • Research software engineering: the full software development cycle - version control, CI/CD pipelines, packaging and maintaining codebases. Regular contributor to open-source communities.
  • High-performance computing: skilled at isolating computational bottlenecks and accelerating large-scale optimizations.
  • Able to grasp complicated concepts quickly and to work in an interdisciplinary environment; self-motivated and organized, comfortable handling multiple projects at once.

Patents in pipeline

  1. Chaithya G R, G. Daval-Frérot, A. Vignaud, and P. Ciuciu. Method and apparatus for performing accelerated Magnetic Resonance Imaging with reduced off-resonance effect. European Patent Application No. 22305592.2, April 2022.
  2. Chaithya G R, G. Daval-Frérot, A. Vignaud, and P. Ciuciu. Method and apparatus for performing accelerated Magnetic Resonance Imaging through gridded sampling at low frequencies. Patent application in process, September 2022.

Publications

The full list of journal articles, peer-reviewed conference papers and workshop abstracts lives on the publications page. It is regenerated from the BibTeX export of my Google Scholar profile, enriched with OpenAlex, Crossref and arXiv metadata, so it stays up to date without manual editing.

Professional service

Reviewer for IEEE Transactions on Medical Imaging and Magnetic Resonance in Medicine.