Harshit Prasad Compiling Ideas into Reality! 🚀


I’m Harshit. I’m a Software Developer involved in Machine Learning / Deep Learning, Full Stack Development, and Mobile Webapp Development. Currently, I’m working with CERN as Open Source Contributor in Deep Learning area and enrolled in B.Tech programme at LNM Institute Of Information Technology, Jaipur under Dept. Of Electronics and Communication Engineering. During my B.Tech till date, I’ve worked as Google Summer Of Code student for two times and worked on topics like: Deep Learning involving models to deal with sequential/time-series data, Full Stack Development with proper use of container management tools.

I’m passionate to work on real-world software developments and help people in building and delivering technology. I’m looking for such related opportunities involving Machine Learning / Deep Learning, Full Stack Development or Mobile Webapp Development. I’ve experience in contributing in large open source codebase. I’ve collaborated with many teams in my university to promote open source culture and develop useful software products.

In my free time, I like to watch a number of sci-fi and action genre movies and television shows. I love to write technical blogs on a particular topic or on a solution which solves a problem which I’ve experienced and solved successfully in an optimal way. Apart from indoor activities, I like to play Badminton and hang out with my friends. I like to meet new people and love to share thoughts and ideas with them during international conferences and local meetups.

“Talent win games, but teamwork and intelligence win championships.”

Recent Blogs

  • GSoC 2018 Final Work Report

    August 10, 2018 - Technology

    In this blogpost, I’ll be summarising my GSoC 2018 project work. I was working on project ‘Recurrent Neural Networks and LSTM on GPUs for Particle Physics Applications’. [Read more]

  • GSoC 2018: Performance of LSTM Network - Part V

    August 10, 2018 - Technology

    In this blogpost, I’ll be sharing results obtained during testing session of forward propagation and backward propagation. [Read more]