Presently, as a second Semester student, I am studying courses on Deep Learning, Advanced Quantitative Research Methods, Computational Complexity. In my first semester I took a special-topic course on “Big Data + High Performance Computing HPC + Atmospheric Science”. Through these courses, I am not only learning concepts related to Machine Learning, Supervised and Unsupervised Modeling and Neural Network Architectures, but also practically implementing my learnt concepts in interdisciplinary research such as Climate and Atmospheric Sciences.  I worked on a research project that focuses on studying climatology through CMIP6’s global climate models. Using UMBC’s High Performance Computing environment, the research evaluated the accuracy of simulated models of the Earth's past, present, and future climate states. I have further worked on two research projects on Deep Domain Adaptation based Aerosol Classification for Active and Passive Satellites, published in Deep Spatial Workshop at KDD 2020 and IEEE Conference on Big Data 2020.