HELLO! I’M MANAJIT DAS

The application of computational chemistry is of immense importance to investigate the peculiarities observed in homogenous catalysis and can rationalize the origin of selectivity in asymmetric catalysis. In this regard, recently machine learning has appeared as a new promising tool to solve such chemical problem but with lower cost and greater efficiency. Thus, it has interested me to harness its power for the prediction of output relevant to homogenous catalysis. The wealth of knowledge obtained from the reactions carried out can be exploited to build machine learning model which in turn can predict the output of a new reaction before an experimentalist performs it physically. It can mitigate the labors, time and material required for experimentation and, thus can lead us to a sustainable world. Not only the reaction output predictive model,  but also a class of machine learning model known as generative model can design new molecules. Though it is in earlier stages applied to drug discovery, I am interested to employ its utility in designing new catalysts.

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