I like to continue my research in Astronomy. Basically, I am interested in using various Machine Learning (ML) and Artificial Intillegency (AI) in Astronomy. In graduate school, i analysed Gaia DR3 data and make Color-magnitude deiagram (CMD) of Galactic globular clusters (GCs). After that i used Machine learning (ML) for the classification of the images into different clusters. Globular Cluster being one of the old stellar objects, we studied it, using Gaia DR3 datasets. We make CMD for about 150 GCs. By our selection criterian we are able to get 57 CMDs whic gives the promising results. We use the information of RA, DEC, distance, half light of GC from Holger and Baumgdart. GC link

During my research, i use Python for data analysis and plotting. Several packages and module like NumPy, SciPy, Pandas, Matplotlib were used for research.

I used TensorFlow plateform and Keras API as backend for our model. We used Sci-kit learn for making ML models. I did computer vision to recognise images, extract features and finally make different classes according to their similarities.

Some of the results from the ML/ Computer Vision.

Morphologically similar CMDs (Class 1).

• NGC 6637 and NGC 6624 are the morphologically similar CMDs from our algorithm.

Morphologically similar CMDs (Class 2) and many more.

• NGC 6752, NGC 6218 and NGC 288 are the morphologically similar CMDs from our algorithm.

Here is the latest poster in ASROC Taiwan 2023.

Here is the poster for TPS Taiwan 2023.

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