At the Academy of Technology (AOT), research in NLP combines linguistic theory, statistical modeling, and machine learning to address challenges in text and speech processing. Faculty and students work on areas such as sentiment analysis, text classification, machine translation, named entity recognition, and question-answering systems. Cutting-edge deep learning models, including transformers like BERT and GPT, are explored for tasks involving contextual language understanding and generation. Applications of AOT’s NLP research span multiple sectors. In business, NLP-driven analytics help organizations understand customer sentiment and improve service quality. In healthcare, NLP is used to process clinical notes, extract critical patient information, and support medical decision-making. Educational applications include automated essay grading and intelligent tutoring systems. Additionally, NLP contributes to information retrieval, enabling users to efficiently access relevant content from vast databases. 

A key research priority at AOT is the development of multilingual and low-resource language models, particularly for Indian languages, to ensure that technological advancements are inclusive and culturally relevant. Efforts also focus on improving model interpretability, robustness against adversarial attacks, and reducing biases in language models. Research is supported by high-performance computing facilities, NLP toolkits, and collaborative projects with technology companies and research institutions. Students gain hands-on experience in building and deploying NLP solutions, equipping them with skills highly sought after in the AI industry. Looking forward, AOT aims to explore conversational AI, multimodal NLP, and cross-lingual transfer learning, driving innovation toward more natural, accessible, and human-like language technologies.