#Research Enthusiast #GraphML, #Geometric DL, #3-D Computer Vision, #Diffusion Models, #GANs, #Generative AI. #Computer Vision, #ML , #RL #LLM, #MultiModal Fusion #Generative Flow Networks. -- Proficient in C++, Java, Python, TensorFlow, Keras, PyTorch, PyTorch Geometric, Network X, -- Hands on Machine learning & Deep learning Models and worked on different baseline algorithms such as Decision Tree, Logistic Regression, and Support Vector Machines (with the linear kernel) using packages present in Python. Worked on various Image-Preprocessing Techniques and created a deep-learning novel architecture that may be configured with or without Adversarial Training. Explored RNN, LSTM Neural Network to find temporal correlations in time series prediction. I have done two research-based applications of deep learning models and somewhat amalgamation of Natural Language Processing too. Currently I'm working on the intersection of both deep learning and their implementations to biomedical and biometric research.I'm working closely on a Project titled "Contactless Palm Print Recognition" in which I have done semantic segmentation over the image dataset and later on I have implemented the palm alignment techniques using deep learning algorithms and currently working to came with the most optimized model which can predict or somewhat scalable at most in terms of their overall prediction. For now I'm exploring the Graph ML and Geometric Deep Learning area to research upon. I'm seeking opportunities related to it.