I am a PhD student in Artificial Intelligence with three years of experience working with Deep Neural Networks, Machine Learning Models, Graph Embedding Algorithms, Graph Convolutional Networks, Reinforcement Learning Models, Large Language Models (LLMs), and MLOps.

I regularly participate in online hackathons and Kaggle competitions. My current research focuses on scalability in Multi-Agent Reinforcement Learning (MARL), as well as Machine Unlearning and its applicability in Reinforcement Learning (RL), Natural Language Processing (NLP), and Complex Systems. I am passionate and resilient about the work I do.

Lately, I've been busy learning the ropes of GitHub Actions, KubeFlow, Docker, Kubernetes, and also getting familiarized with Cloud Technologies like AWS Glue, Amazon SageMaker, GCloud AutoML, and GCloud DataStore.

Looking ahead, I'm excited about completing my PhD program. My goal is to become an expert in transforming complex data challenges into practical, deployable, and impactful software solutions for real-world applications.