Srishilesh P S

Passionate about AI and Blockchain


Phantom News

To solve the problem of spreading fake news, and rumors using Blockchain technologySolidity


PaySol is a chat based non-custodial crypto wallet that empower users to transact SOLs via P2P, keep track of financial records, advertise offerings, earn SPL tokens for every transaction.Heroku, MongoDB Atlas, Netlify, Material-UI, Nodejs, reactjs, PusherJs, solana/web3.js, SerumJS


Gamegon allows an individual to play skill-based PvP games like Chess Tic-tac-toe, where they get a chance to win 2x rewards by staking their desired amount of MATIC tokens.Solidity, Socket.IO, Remix IDE, Web3, Nodejs, reactjs, MaterialUI


Machine Learning
MERN Stack


  • Estreetz Technologies Pvt. Ltd. - Machine learning engineer
    September 2018 - September 2019

    Built a chatbot for business automation (to manage workplace and employees) using an Open Source NLP Platform called RASA. In 2018, the vision of the startup was to focus on automating of task tracking, building a SaaS application for HR management, and other IoT solutions for building an automated workplace.

    πŸ”¨ What did I learn here?

    • Learned to create a RASA chatbot
    • Integrated it with Android app using RESTful Flask APIs
    • Hosting in AWS EC2
    • Git VCS
    • Deep learning NLP models
    • Business pitching and presentation
  • Smart Spaces Lab, Amrita University - Machine Learning Researcher
    September 2017 - September 2019

    With focus on digital buildings, digital campus and digital city, this lab has been setup in 2017 by the Department of Computer Science and Engineering with funding from Department of Science and Technology, Government of India under project id: F.NO NRDMS/01/175/016 G & C.

    πŸ› οΈ What areas did I work on?
    I worked on object tracking, fire detection, smoke, and water leakage detection through image processing.

    πŸ”¨ What did I work on?

    1. Data collection for object tracking, smoke, and water leakage detection
    2. Data annotation for object tracking and smoke detection
    3. Analyzed performance metrics for various deep learning models
    4. Multi-linear regression models for prediction of spread of fire
    5. Implemented Convolutional Neural Networks for detection of cars

    🚧 Final Project:
    Implemented an fire detection algorithm through real-time video processing to detect fire-spread.

    πŸ–₯️ GitHub repo

  • Tata Consultancy Services - Project Intern
    July 2020 - September 2020

    πŸ”¨ What did I build?
    Built a Flutter mobile chatbot application for addressing healthcare related queries from patients, and connecting them with the right doctors for consultation. (A dumb version of PractoπŸ˜‚).

    I was new to mobile app development with Flutter. So, I started learning it from scratch by learning:

    • how to design and layout components
    • how to connect with Google's dialogflow for the chatbot
    • worked only on the front-end

    PS: Discontinued learning mobile-app development since it was boring tbh πŸ˜….

  • Omdena - Junior Machine Learning Engineer
    August 2019 - November 2019

    Worked in collaboration with UNHCR and collaborators from 34 different countries, on finding the Internal Displacements at Somalia using Satellite images.

    πŸ”¨ What did I work on?

    • Exploratory Data Analysis on displacement datasets from UNHCR

    Technically, I didn't learn much, since I was in my sophomore year and wasn't aware of how to work with ML.

  • Mr. Cooper - Software Engineer I
    January 2021 - Present

    Stepped into a new domain altogether. Really grateful to have started my career here as an intern. The learning curve was very steep, and my team never considered me as an "Intern", rather they gave me tasks (opportunities) just like to any other "Software Engineer" in the team.

    πŸ’Ό What is my role?
    Worked as a full-stack developer to build awesome FinTech products related to Housing Mortgage.

    πŸ“š What did I learn?

    • In a period of 6 months, I moved from "Nothing" to "Something" in web development using ReactJS.
    • Explored a bit about the mortgage industry as a whole. Learned how mortgage works.
    • Tried learning a little on SpringBoot. But, couldn't get much hold of it.
    • Brushed up my skills on Python - Flask.
    • Learned to code with lesser bugs during the code reviews (Either my code has fewer bugs or the code reviews were not done properly. I always wish the former to be true. xD)
    • Got an opportunity to present my work to the bigger team.
    • Worked on tasks that were way out of my scope/responsibility - by taking ownership of tasks related to application's performance, resource management, and load testing.
    • Volunteered to be part of a few recruitment drives and as a hackathon judge. (It feels amazing to be on the other side of the interviewee table)
    • Hustled a little more to explore the machine learning side of the product and was seeking opportunities to work on them.
    • Overcame my fear on working with SpringBoot. I voluntarily took up tasks related to it.
    • Got a better hands-on my Python and ReactJS skills.
    • Came up with innovative ideas that could possibly improve the UX of the product.

    πŸ”¨ What did I work on?
    We built products to annotate or re-annotate (feedback loop) mortgage documents for the machine learning model to self-learn, and make predictions/classifications by itself.

    πŸ±β€πŸ’» What technologies did I get to work with?

    • ReactJS
    • SpringBoot
    • Python Flask APIs
    • Google Cloud Platform
    • Azure DevOps