Rishi

Rishikesh Magar

I am currently a PhD student in the Mechanical Engineering department advised by Professor Amir Barati Farimani. I am broadly interested in using Deep Learning to solve interdisciplinary engineering problems. Fascinated by the impact that AI can have on the human society, I have focused my research on leveraging Deep Learning for applications in healthcare and material discovery. I received bachelor’s degree in Mechanical Engineering from the University of Pune(India). In my spare time, I like to watch and most of globally popular sports. I also enjoy writing, reading and listening to classical music occasionally

Publications

1. Mohammad Reza Karamad, Rishikesh Magar, Yuting Shi, Samira Siahrostami, Ian D. Gates, and A. Barati Farimani "Orbital graph convolutional neural network for material property prediction", Physical Review Materials, 2020, 4, 093801.

Github: https://github.com/RishikeshMagar/OGCNN

2. Mohammadreza Karamad, A. Barati Farimani, Rishikesh Magar, Samira Siahrostami, and Ian D. Gates "Heteroatom-Doped Transition Metal Nitrides for CO Electrochemical Reduction: A Density Functional Theory Screening Study", Journal of Physical Chemistry C, 2020, article ASAP.

3. Rishikesh Magar, Lalit Ghule, Junhan Li, Yang Zhao and A. Barati Farimani, "FaultNet: A Deep Convolutional Neural Network for Bearing Fault Classification," IEEE Access, 2021, vol. 9, pp. 25189-25199, doi: 10.1109/ACCESS.2021.3056944.

Code: https://github.com/BaratiLab/FaultNet

5. Baishali Mullick, Rishikesh Magar, Aastha Jhunjhunwala A. Barati Farimani "Understanding Mutation Hotspots for the SARS-CoV-2 Spike Protein Using Shannon Entropy and K-Means Clustering", Computers in Biology and Medicine, 2021, 104915.



7. Lu Xu, Rishikesh Magar, A. Barati Farimani "Forecasting COVID-19 new cases using deep learning methods", Computers in Biology and Medicine, 2022, 144, 105342.