Krishnakanth Alagiri

About

I'm a seasoned software developer, leader and strategist. As a third year student graduate pursuing Computer Science Engineering in SVCE, I take a more creative and conceptual approach to solve any problem given to me. I'm expert in Team Building and Collaboration. The Reason? I like getting people excited about the things I'm excited about. Right now, that's anything that revolves around programming and Data.

Educational Background

Emirates Future International Academy, Abu Dhabi

High Schooling

Velammal Vidyalaya (CBSE), Chennai

Senior High Schooling (Grade 11th and 12th)

Sri Venkateswara College of Engineering (SVCE), Chennai

Bachelor of Engineering in Computer Science

Experience

Bhumi (Non Governmental Organization)

June 2019 - August 2019

Software Developer

Bhumi is one of India’s largest independent youth volunteer non-profit organisations with over 20,000 volunteers across 10 cities in India for causes like education, environment, animals and community welfare. I used my technical expertise to help automate a few of their most tedious tasks thus increasing ease and efficiency within the organisation

Tech4Change

July 2019 - Present

Lead Program Manager

Tech4Change is a volunteer-run program in Bhumi to promote access to a broad spectrum of technologies in NGOs across India. The majority of the work involves supplying support and advice to charitable organizations in order to support and enhance their existing work as well as developing new software solutions to meet their evolving needs.

Notable Projects

Universal Sign Language Translator

An AI model that uses Machine Learning (RNN + KNN Classifiers) and Computer Vision which involved repeatedly gesturing in front of a camera to teach the system the fundamentals of sign language. This is to combat the differences between various Country’s sign languages and their regional dialects without compromising on accuracy while giving way to crowd-sourcing

View Project

Psychological Analysis of Unstructured Messages

An open source Software that uses Sentimental Analysis on a series of Unstructured text messages to predict the probability rate of depression and magnitude of other psychological factors in a person.