Rakshith Sathish

Research Scholar (MS) @ Indian Institute of Technology Kharagpur

Hey! I am currently pursuing a Master of Science(MS) degree at Advanced Technology Development Centre (ATDC), Indian Institute of Technology Kharagpur, India. I am a member of the Kharagpur Learning, Imaging & Visualization (KLIV), a group of researchers working in Deep Learning for Medical Imaging, led by my supervisor Dr Debdoot Sheet. My broad area of research is in the domain of Explainable Deep Learning- specifically for Medical Imaging. My research work is guided by Dr Debdoot Sheet and Swanand Khare. I’m also working on a project entitled MIRIAD, sponsored by Intel India Ltd.

News

October 2022 Paper titled "Designing Deep Neural High Density Compression Engines for Radiology Images" has been accepted for publication at Circuits, Systems, and Signal Processing. [Journal]

September 2022 Presented paper at MICCAI 2022, Singapore

July 2022 Paper titled "Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks" has been accepted for publication at aFfordable healthcare and AI for Resource diverse global health (FAIR 2022), Singapore.

September 2020 Joined MS program at Indian Institute of Technology Kharagpur

July 2020 Presented paper at 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) [Virtually]

March 2020 Started working with Covid19ActionRadiology team

August 2019 Joined Kharagpur Learning, Imaging & Visualization (KLIV) research group, Indian Institute of Technology Kharagpur

June 2019 Completed Undergraduate degree (B Tech) from A P J Abdul Kalam Technological University.

Publications

Designing Deep Neural High Density Compression Engines for Radiology Images

Aditya Raj*, Rakshith Sathish*, Tandra Sarkar, Ramanathan Sethuraman, Debdoot Sheet

Circuits, Systems, and Signal Processing (CSSP Journal)

*Authors have equal contribution

Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks

Rakshith Sathish, Swanand Khare, Debdoot Sheet

aFfordable healthcare and AI for Resource diverse global health (FAIR 2022) [MICCAI 2022 Workshop]

Lung Segmentation and Nodule Detection in Computed Tomography Scan using a Convolutional Neural Network Trained Adversarially using Turing Test Loss

Rakshith Sathish, Rachana Sathish, Ramanathan Sethuraman, Debdoot Sheet

42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)