Research Statement

My research focus lies at the intersection of Data Science and Law with a focus on advancing the field of information retrieval and recommender systems, with particular emphasis on expertise retrieval within social networks. I aim to radically change the field of legal research and decision making through innovative techniques.

The legal field is increasingly becoming complex with the advent of new technologies such as legal text mining, predictive analytics, data visualization, and the development of explainable recommender systems. My goal is to equip the legal institutions as well as the community with the necessary tools to increase efficiency and effectiveness in the legal systems.

NLU Meg promotes the space for multi-disciplinary research and a platform to collaborate and engage with legal practitioners and experts from various fields.

We are fascinated by the incubation of legal entrepreneurship in the technology domain imbibing Generative Artificial Intelligence (GAI). Data science background of mine combined with legal expertise at the University, we are stepping towards the singularity which will be the future norm for the societal process.

Teaching

Computational Thinking (FC10005)
Basic Mathematics (FC10003)

Areas of Interest

Data Science,
Computer Science,
Law and Technology (Text Mining, Legal Document Mining, Recommendation Systems, Information Retrieval, Natural Language Processing, and Machine Learning)