Hello, I am Ajay Tripathi. I am 21 years old, born and raised in India. I am currently working to complete my bachelors in Computer Science & Engineering. I have the love of thinking and often find myself flirting with branches of philosophy like existentialism & stoicism. I love to think logically and take pride in engineering solutions of day-to-day inconveniences.
I believe the world to be a positive sum game and hence promote and proudly contribute to the open-source culture. I support the society by helping people gain access to education & information. I mentor students in my college and contribute to OpenWISP to achieve these goals.
I love to meet and understand people and what drives them, and to do the same efficiently, i fancy myself with the study of body language, human psychology, personalities and emotions.
Amongst the hottest debates where i partake in, I am a strong supporter of net neutrality & right to privacy. I am available on the internet with the username atb00ker. Feel free to reach me on Twitter or LinkedIn.
The project aims to solve the problem of complex deployment of OpenWISP application by dockerizing the OpenWISP modules to give users plug-and-play docker images that are compatible and ready to run in kubernetes clusters simply by changing the environment variables.
Worked in Spoken Tutorial Project (spoken-tutorial.org). Optimized data usage to upto 60% less data requirement for users during download.
Web Development: Using Django, added the features to edit / show user testimonials on the main site of spoken-tutorial project.
Contributed to code development of OpenWISP, an open-source Network Management suite for large networks. Learned to write easily maintainable code under the guidance of experienced developers and learned to coordinate with developers from different places around the world. I have worked on ansible-openwisp2 and controller (django) modules to add various features and fix bugs.
Scraped articles from 10+ news websites 24/7 on a Linux server and stored the data in a database server. We collected about 12 million records and used Machine Learning to classify and categorize the news.