Akash Nileem Borgohain

I’m a detail-oriented 3rd-year Data Science student with hands-on experience in Python, R, and SQL for analysing large-scale datasets. I enjoy turning raw data into clear insights using Exploratory Data Analysis, data cleaning, and hypothesis testing.

In my Data Entry & Management Intern role at Advisorkhoj.com, I supported a data team by maintaining and updating large-scale databases, ensuring data quality and accuracy. I also helped generate analytical reports from multi-source data and collaborated to streamline data workflows for better efficiency.

My research interests focus on policy-relevant, geospatial decision support. I’m currently authoring a paper on Differential Privacy, and I conducted a literature review on Stock Market Trend Prediction using Distributed Machine Learning.

I build practical models too—like geospatial & temporal EDA on Indian road accidents to identify high-risk regions, a Multiple Linear Regression model for house pricing, and a queueing theory approach to minimize patient waiting times. I’m also developing an LLM-based project for network vulnerability detection and using K-Means + RFM analysis for customer segmentation.