Email Address: [email protected]
Ramakrishna is a highly motivated computer science Researcher currently pursuing a Master’s by Research in Computer Science at Munster Technological University in Ireland. He completed his Bachelor’s degree in Computer Science at the Central Institute of Technology in India, where he showcased his expertise through various Deep Learning and Machine Learning projects. During his undergraduate studies, Ramakrishna developed a strong foundation in Natural Language Processing, Deep Learning, Data Analysis, and Machine Learning. His passion for understanding real-world events led him to focus on estimating the occurrence time of event mentions in text, a crucial aspect with applications in Information Retrieval, Question Answering, document understanding, and other NLP tasks. His current Research on Temporal Information Retrieval, He proposed an innovative approach to temporal profiling of event mentions in text. His method leverages a comprehensive news article archival collection to gather both temporal and textual information, encompassing contemporary and retrospective event references. Notably, his research demonstrated that relying solely on secondary data sources like Wikipedia is insufficient for accurately estimating the event time, especially for lesser-known events in the past. model, showcased through extensive experiments, outperformed existing methods by a significant margin across various temporal granularities, such as day, week, month, or year. The practical implications of his work extend to answering arbitrary questions about past events when integrated into a Question Answering framework operating over news article archives. Ramakrishna’s dedication to advancing the field of computer science and his innovative contributions to temporal profiling make him a promising researcher in the realm of NLP and machine learning.
