About Me πŸ‘‹Svapnil's Face

My name is Svapnil Ankolkar and I am a software engineer from San Francisco currently living in New York City.

I love building things 0 -> 1 and want to work on things that lots of people use that change the world. I'm currently building Woodside Labs, where I'm working on building new types of consumer applications.

I previously worked as a software engineer at Modern Treasury, improving the way technology companies move fiat money through the internet. Earlier I worked as a software engineer at Facebook, where I worked on WhatsApp's Erlang Infrastructure to facilitate peer-to-peer payments in India and Brazil.

Aside from writing code and working to become a better software engineer, I also love:

  • capturing beautiful things through picture
  • biking around pretty places
  • drinking good coffee and making latte art

I'm interested in building technology that scales and building businesses that make a outsized positive impact on the wider world. I love working on cool things, whether it's designing a IoT-enabled embedded system that talks or building software infrastructure that protects the privacy of hundreds of millions of users on the most used photo-sharing app in the world.

I previously studied Computer Engineering at North Carolina State University. During college I spent my spring semester of 2018 studying at Lund University in Sweden, where I had the opportunity to meet motivated and interesting people from everywhere around the world. During the Spring of 2019 I interned as a software engineering intern for Facebook, working on privacy infrastructure at Instagram. After I interned with the Windows organization at Microsoft working on moving Window's testing infrastructure to Azure. My senior year of college I led a club called Tech @ NC State, where we worked on opening access to a career in tech and organized a software enginering team of twenty-six college students to create a webapp for a local non-profit.

Stay tuned to hear about more of my life and projects!

This website showcases a few of the tech projects I have worked on and the photographs I have taken. It also links to my Github, LinkedIn and email.

Personal Projects πŸ’Ό

Clear Health - HackNC 2018

This is the culmination of the work my team and I did during the 2018 HackNC Hackathon, which ended up winning us third place overall in the competition. Our team wanted to build something that would improve the lives of those who struggle with the cost of healthcare in America. What we built is an app that searches public records of Medicare data to find the cheapest cost of treatment near there. We took this data and made it accessible through any web browser. This project could potentially give people better access to cheaper healthcare by empowering users with data that is hard to find elsewhere.

Clear Health Tool Screenshot

Demo the Webapp.

IoT Vehicle Connected to the Amazon Alexa

This is an extension of the work I did on my embedded system class. I connected my IoT vehicle to the Amazon Alexa using AWS Lambda and ngrok. I made it possible to control my MSP430 microcontroller-run vehicle using the Echo. You can find the code and instructions how to recreate it on my Github. This is a video demonstrating my project from the comfortable view of my dorm. (Shoutout to Bagwell Residence Hall!)

Moving the microcontroller vehicle using the Amazon Echo

Bitcoin Enthusiast Twitter Bot

This Twitter bot makes comments and predictions about Bitcoin just as well as your amateur cryptocurrency enthusiast. (Which, in my opinion, means not very well)

The Python script takes the top comments from a list of controversial daily submissions on /r/Bitcoin and tweets one every 30 minutes. The two motivations behind this project were:

1. Learning how to interact with website APIs using Python
2. Making fun of "crypto enthusiasts" while learning a little on the side

US Mental Wellness Visualization

During the 2018 annual Carolina Datathon my team worked on visualizating mental health and poverty data in the United States and how it has changed over time. Using R and Python, the data was collected from the datasets given to us and translated into Z-score values against the mean of all the data given. From there it was converted into JSON and visualized using D3js. This code for this project is on Github and the team members I worked with were Anam Navied, Erin Lyons and Lahari Revuri!

USA Heatmap

Demo the visualization.