Sahil Ashar
Software Engineer @ Microsoft

Software Engineer @ Microsoft
I'm currently a Software Engineer at Microsoft, on the Xbox team. I spend most of my time developing Xbox Live Service SDKs for 3rd party developers, so they can utilize Xbox Live Authentication, Social, Multiplayer, and Player Data services as part of their games.
Additionally, I'm currently volunteering as a consultant at the Texas
Rocket Engineering Lab (TREL).
TREL is a research focused, rocketry start-up based in Austin, Texas; with the primary
goal of getting a liquid, bipropellant rocket to the edge of space by 2021. I spend the majority of my time
in TREL mentoring undergraduate students in best practices in software develpment, hiring/recruiting, and general
leadership values.
I previously worked at Riot Games as an
Systems Software Engineering Intern in 2019, and helped write an article about my experiences on
the Riot
Games Tech Blog!
You can check out more about my past internships and other related
things on my resume.
I'm a recent graduate of The University of Texas at Austin. I received my
B.S. Electrical and Computer Engineering in 2020, with a focus in Software Engineering,
Systems Engineering, and Engineering Management.
At UT, I was a member of the Student Engineering
Council, and the Institute of Electrical and
Electronic Engineers; I was also mildly
involved in studying legislation concerning the University.
Below is a small collection of projects I've worked on. You can click the picture to visit the related GitHub repository.
Justice Samuel Alito is one of the most pro-corporate justices in the Supreme Court,
paving the way for better tax and social benefits for them while not being as friendly
to most middle class Americans.
We hypothesized - what if there was a way to tell, based on the make-up of Congress in a
specific cycle, if the market would react a specific way?
More specifically, would the make-up of the Congressional class, in relation to have
similar physical features as Justice Samuel Alito, have an effect on the market and its
trends?
We analyzed over 3.6k individual photos of 6 Congressional classes. Using the Microsoft
Azure Facial Recognition API, we were able to classify
each Congress member - and thereby each Congressional class - and assign them an 'Alito
Index' based on their similarity to Justice Alito.
Then, using Goldman Sach's Marquee API, we were able to pull 5 years of financial data
for 100 different securities, and attempt to find a correlation
between specific securities/industries and a Congressional class.
Check out our Devpost for
more in-depth info about this project.
Space is a multi-level arcade game, adapted from the classic Space Invaders. Space was built for use on the Texas Instruments TM4C123G Microcontroller, with a codebase of primarily C and ARM Assembly. Unfortunately, Space is not recreatable, due to the amount of custom wiring done for the ADC, DAC, and UART systems.
Dallas Ramen Guide is an Amazon Alexa Skill thats allows the user to discover new ramen places around Dallas. When prompted, the user can ask Alexa for "an overview of Dallas Ramen", or the "top five ramen restaurants", or they can ask for a "random ramen restuarant." Each invocation will give a description of the ramen restaurant in the Alexa App as well. Primarily developed in JavaScript.