Rishab Sharma

ISRO - Indian Space Research Organisation

Data Scientist

June 14, 2026 – Present

object_detection

November 25, 2017 – November 25, 2017

A tensorflow model to detect objects in a webcam Video using OpenCV capable of localizing and identifying multiple objects in a single image

ocr_on_android

November 17, 2017 – October 31, 2018

An android app to recognise a hand Written Digit using a Flask , Tensorflow Backend , Model Designed using The coolest and simplest Keras

nidaan

October 14, 2017 – April 22, 2019

A webapp for disease recognition and symptoms analysis || Models : CNN , K-Means , Support Vector Classifier

cnn-hand-written-digit

October 10, 2017 – October 14, 2017

This is the code for a model that recognizes handwritten digit images (MNIST). Developed using TensorFlow and the super simple Keras Library. Wrapped into a Webapp using Flask Micro Framework.

chatbot_tensor

September 28, 2017 – July 20, 2020

[https://rishabbot.herokuapp.com] I implement Tensorflows Sequence to Sequence model to train a chatbot on a reddit/AIML compatible open-source dataset. The bot holds a fun conversation and its just been trained for sometime .

self_driven_future

September 24, 2017 – October 31, 2018

My most ambitious project for simulating a self driving car with EEG. This is the code for my project where I used Udacity's self driving car simulator as a testbed for training an autonomous car.

image_research

September 24, 2017 – November 25, 2017

As observed machine learning, computer vision techniques and other computer science algorithms cannot compete the human level of intelligence in pattern recognition such as hand written digits and traffic signs. But here we have reviewed a biologically plausible deep neural network architecture which can make it possible using a fully parameterizable GPU implementation deep neural network independent of the pre-wired feature extractors designing, which are rather learned in a supervised way. In this method tiny fields of winner neurons gives sparsely connected neural layers which leads to huge network depth as found in human like species between retina and visual cortex. The winning neurons are trained on many columns of deep neurons to attain expertise on pre-processed inputs in many different ways after which their predictions are averaged. Also GPU used, enables the models to be trained faster than usual. Upon testing the proposed method over MNIST handwriting data it achieves a nea

snack_search

September 24, 2017 – October 31, 2018

A machine Learning app for snack suggestion | The goal for this project is to build a system that allows you to identify and then recommend, recipes you're likely to enjoy.

geospatial_map_plotting

July 10, 2017 – September 24, 2017

MAP PLOTTING USING GEOSPATIAL DATABASE is 2 way project in which a geospatial database can be plotted on a map depicting the various polygons which refer to the lease area of a company along with the point data depicting the wells and boreholes.

university_hub

July 1, 2017 – January 17, 2018

University Hub is an App to connect the administration and the students through a simplified webapp . The Schema currently includes three different sections including the announcements section , the general discussion section and the semester forum .