Vikraman Sathiyanarayanan

Experience

• 

  Central Electrochemical Research Institute (cecri)

  May 2016 - Jun 2016

  Backend Engineer

  · Developed an interactive application that fetches information from the user.· A backend querying mechanism was built and the desired results will be published in the developed User Interface.

• 

  Amazon

  Jun 2017 - Jul 2017

  SDE Intern

  · Developed new features with the help of voice recognition functionality for next generation devices that leveraged Alexa based voice search operations.· Built a wand like application with client server architecture for drawing in a television screen based on smartphone’s movement.

• 

  Swinburne University of Technology

  May 2018 - Jun 2018

  Foreign Technical Training Program

  · A program funded by Government of Tamil Nadu to understand the working and development of smart cities.· worked on comprehending and strategizing the fire safety mechanisms in smart cities.

• 

  Amazon

  Jun 2018 - Aug 2018

  SDE Intern

  · Worked on Alexa’s Automated Speech Recognition and Natural Language Unit for supporting new market place.· Worked on new feature for enabling frustration free initial setup of FireTv devices.

• 

  Dhaksha UAV Team

  Sept 2018 - Apr 2019

  Software Developer

  · Implemented Dynamic no fly zone module for the Unmanned Aerial Vehicle(UAV) team as a part of UAV Medical challenge and won the second place in the competition.· Implemented NPNT (No Permission No Takeoff), restricting the takeoff and fly time of UAVs based on the obtained permit.· Implemented an android application that can control drones using the mobile phone when both the drone and the phone is connected to the same network.

• 

  USC Automatic Coordination of Teams Lab

  Sept 2019 - Apr 2021

  Graduate Research Assistant

  • Working on Algorithm Selection techniques for Multi Agent Path Finding Optimization problem using Convolutional Neural Networks and Graph Convolutional Network with an emphasis on one shot learning.• Worked on Integrating multiple optimal solvers for MAPF problem with Unified Interface including CBS, BCP, ICTS and SAT based solvers.• Worked on multi agent path planning using DQN and Policy Gradient technique for Flatland Challenge to optimize multiple train’s path to avoid collision and reducing the total time taken for each of the train to reach its destination.• Simulations are done using the flatland-rl package in python. Show less

• 

  Apple

  Jun 2021 - now

  Software Engineer