About Me

I excel in several key areas of research, particularly in deep learning, natural language processing (NLP), and computer vision. My work has involved developing advanced neural network architectures such as CNNs, GRUs, LSTMs, and Transformers, which I have applied to solve complex problems across various domains. I have made significant contributions to artificial intelligence (AI), particularly in real-world applications like Automatic License Plate Recognition (ALPR), human activity recognition, and sentiment analysis. These projects have demonstrated my expertise in building intelligent systems that can address practical challenges.

Additionally, my research in NLP has focused on detecting hate sentiment using models like BERT and DistilBERT, reflecting my strong understanding of text classification and data analysis. I have also explored sentiment analysis from social media data, providing insights into public sentiment through deep learning techniques. Overall, my work combines theoretical knowledge and practical skills, with a strong focus on applying AI-driven solutions to real-world challenges.