My Ph.D. dissertation (University of Tennessee, 2025) develops a machine-learning-driven demand forecasting framework implemented at HP Inc., improving forecast accuracy by 34% and reducing inventory by 28%. 🔗 PDF
Jailbreaking my Kindle to run Python, draw, and block lockscreen ads.
A quick rundown of my doctoral research presented at the BA Forum 2023
A new playlist of random songs that I haven’t listened in a while generated automatically every Monday
Creating ML demand forecast for print products at HP Inc. using LightGBM and pushing it to production for wide adoption.
We proposed a novel end-to-end approach, the Neural Lagrangian Selling (NLS) model, to improve Guaranteed Delivery (GD) advertising by concurrently predicting ad impression inventory and optimizing contract allocation
Predicting race, age and gender of faces using Variational Autoencoders and Convolutional Neural Networks.
Building a customizable chatbot that brings unique characters to life
Support vector machines (SVM) are remarkable for the unification of geometric theory, elegant mathematics, theoretical guarantees with strong practical use cases. In this blog post, I demonstrate certain properties of SVM and how to use them with caret package in R.
Introduction to using Git & GitHub with RStudio for MS (Business Analytics) Class of Fall 2022
Introduction to R Markdown for MS (Business Analytics) Class of Fall 2022