About Me


Aakash Jhawar

A Data Scientist and a Full Stack Developer on a mission to joining the dots.

My Career


Developed in-house OCR using Transfer Learning and increased revenue of the product by 70%. Built Aadhaar Number Masking Service with an accuracy of 98.76% and a TAT of 1.04 sec. Implemented RabbitMQ message queues, created and maintained Docker containers on GCP clusters. Won the first prize in a 36hours internal Hackathon.

May 2019 - July 2019, Mumbai
Machine Learning Intern


Increased email deliverability rate by implementing Gmail API. Revamped usage of Google Maps Static API in web app and reduced cost. Implemented and integrated MailCatcher to test sending email.

May 2018 - July 2018, Mumbai
Web Developer Intern


Led a team of designers to design layouts and graphics for the events and social media platform

OCT 2017 - JAN 2018, Jaipur
Lead Graphic Designer


Desportivos is Annual Sports Fest of LNMIIT. Responsible for the setup and execution of social media events and managed the social media account. Led a team of graphic designers to design posters and graphics for the fest.

AUG 2017 - JAN 2018, Jaipur
Organizing Committee

E-Fest APAC 2017

E-Fest is Asia’s biggest fest for Mechanical Engineers organized by ASME.

OCT 2016 - MAR 2017, Jaipur
Graphic Designer

My Skills

My Projects


Identify Commercial Centers using Point of Interest

Gathered all POI using Overpass Python wrapper. Preprocessed the dataset. Removed outliers from the dataset using DBSCAN. Created clusters based on amenities and plot the polygons on Google Maps.


Face Recognition using OpenCV

Extracted face embeddings for each face in the dataset using pretrained OpenFace model. Trained a Neural Network on the face embeddings to recognize faces with an accuracy of 90%.


Fotoxo - Photo Management App

Implemented Sendgrid for sending account verification emails. Used Strip API for receiving card payments from users and AWS S3 Bucket for storing images in production.


SolveSudoku - Sudoku Solver using DL and OpenCV

Extracted and segmented hand region from live video by thresholding. Count the number of fingers from the segmented hand region by using Convex Hull.


Group Chat Web App

Achieved real-time messaging by implemented WebSockets with Action Cable. Used Devise gem for authentication. Used Semantic UI framework for front-end development.


Investry - Stock Tracker App

A web app built using RoR in which users can track stock prices and follow particular stocks according to their choice. User can also connect other users and look up their stocks.


Image Watermarking

Implemented Image Watermarking using Discrete Cosine Transformation in MATLAB and Simulink. The Watermark will be added in the frequency domain of the image.


Event Prediction using Sentiment Analysis

Developed a system that predicts the sentiment of Twitter users towards a specific event/keyword. Collected live tweets using Twitter Streaming API, used NLTK for tokenizing and TextBlob for classification.