Hello, My name is Rishitosh. I am an independent, self-motivated thorough student. Being a fast learner, I love to pick up new technologies and tools. I aim to be a perfectionist and this is the reason of my never give up attitude. I am a team man who believes in the excellence of the entire team rather than an individual. I am an open-source enthusiast and have been learning from this platform since my foundation years.

  • Birthday: February 14, 1998
  • Location: New Delhi, India
  • Email: rishitoshs@gmail.com

Skills

Android Application Development

75%

Artificial Neural Networks

75%

Deep Learning

35%

Machine Learning

25%

Python

50%

Kotlin

75%

Flutter

25%

Big Data

50%

Java

50%

C / C++

75%

Education

B.Tech - 8.2

August, 2016 - September, 2020

Ajay Kumar Garg Engineering College

Intermediate (94.8 %)

April, 2014 - March, 2015

BAL BHARATI PUBLIC SCHOOL, NEW DELHI

High School (9.6 CGPA)

April, 2012 - March, 2013

BAL BHARATI PUBLIC SCHOOL, NEW DELHI

Projects

ToWatch - Movies and Playlist

ANDROID | FLASK | KOTLIN | FIREBASE REALTIME DATABASE March, 2018 – July, 2018

ToWatch is a movie directory application that has multiple functionalities. It notifies the user about the latest and upcoming movies. It enables them to watch the trailer of all movies. The user can also create his personalized list of movies that he intends to watch. He can also update this list once he has watched the movies.

Project Link

Saksham'18

ANDROID | KOTLIN August, 2018 – September, 2018

An Android Application for College Inter-Departmental Sports Events. This project was assigned to me by the IT Department of my college. It features news, poll and medal tally of my college's annual sports Event.

Project Link

TEDxAKGEC

ANDROID | KOTLIN February 2019

This project was assigned to me by the IDEA lab of my college. It is a walk-through app for TEDxAKGEC event.

Project Link

Publications

On the learning machine with amplificatory neuron in complex domain

Sushil Kumar, Rishitosh Kumar Singh, Aryan Chaudhary June, 2020

We have proposed amplificatory neurons, using non-linear aggregation of input and weights and compared with conventional neurons using benchmark transformation, time-series and function approximation problems. Read full paper using link given below.

Paper Link

Get In Touch