Below is a collection of posts on various topics that may help you learn something technically or otherwise. They are targeted primarily at prospective and future graduate students in the area of wireless and signal processing.

Code Snippet: Subfigures in LaTeX, 06-01-2020
A code snippet for subfigures in LaTeX.

Signal Recovery for Compressed Sensing via OMP, 06-01-2020
In this note, I provide a simple MATLAB example of compressed sensing and signal recovery.

AD9361 Setup and Interfacing, 03-15-2020
This guide will describe how I setup and use the Analog Devices AD9361 software-defined radio platform. I interface with the radio using Python via Analog Device’s library libiio.

Using Git with Overleaf, 02-01-2020
How to use Git on your Overleaf projects.

Tips and Tricks I Find Helpful, 01-30-2020
Here is a list of various tips and tricks I have found to be helpful, primarily related to my time as a graduate student. I have found these things to be useful and hope some of them help you too. Find what works for you.

Short Course on Wireless, 01-25-2020
I have put together a short course on wireless and have made the slides available here. I hope you find them useful in introducing you to wireless or providing you a refresher on the topics covered.

My LaTeX Starters, 01-20-2020
In this note, I provide some of my starter files for LaTeX-based documents. This will be a growing list over time.

Suggested Topics to Look Into, 01-15-2020
During my undergrad, I found it was hard to know what I didn’t know. Once I arrived at graduate school, I was exposed to many topics I hadn’t been aware of before—topics I wish I had known about before to foster my technical interests. I have compiled a list of topics that you may want to look into, especially if you are pursuing a career in signal processing, communications, or the like.

My LaTeX Workflow, 08-20-2019
I provide an overview of the LaTeX practice that I have found to be productive.

A Simple Compressed Sensing Example, 05-01-2019
In this note, I will provide a simple MATLAB script demonstrating compressed sensing.