Yash Jhaveri

I have been learning Web Development for almost a year now and have made many web development projects too!Currently,I am even interning as a backend developer at a company called Sapio Analytics!Along with web-development,I also try and explore different domains like AIML,Data Analysis and Cloud Computing and sometimes I even solve some problems on HackerRank and Leetcode to polish my logic and language skills.I am very passionate about computers and always curious to learn newer technologies!!

Projects

DeLib

Making Web3 accessible to everyone.Solidity, IPFS, Web3, Material-UI, Biconomy, React.js, Truffle Suite, Polygon, Filecoin, Arcana

Skills

JavaScript

React

Django

Flask

Nodejs

Experience

Prixled - Backend Developer
June 2021 - July 2021
Created a real-time chat application with help of Django Channels and sockets.
Orchestrated the real-time notification system for regular feed updates and chat message notifications.
Updated the APIs required for the analysis dashboard which reduced the response time by 20%.
Sapio Analytics - Backend Developer
December 2020 - March 2021
Pioneered the foundations of the database design and authentication system for the Smart Hospital Project.
Built APIs for the smooth interaction between the client and MySQL and MongoDB databases using Django
for the UP-Census Project.
Constructed real-time graphs and managed APIs for the HCBI project thereby increasing the revenue
generated by 50%.
Think360 - Data Analyst
June 2022 - August 2022
Worked on the Algo360 project that predicts the credit score of individuals, enabling banks to make
informed lending decisions.
Assessed and compared various text classification algorithms for the Algo360 Project.
Engineered Machine Learning CI/CD pipelines using AWS SageMaker to streamline and automate the prediction process.
Reduced the overall testing process time by 20% and increased the classifier accuracy by 3%.
Indian Institute of Technology Patna - Research Intern
November 2021 - Present
Researched in the cryptocurrency phisher detection domain using Graph Neural Networks and Machine
Learning algorithms under the guidance of Dr. Raju Halder.
Implemented baseline paper algorithms such as Node2Vec, Trans2Vec, DeepWalk, RiWalk and SIGTRAN on Bitcoin and Ethereum transaction data.
Tested different feature generation strategies that resulted in an increase in model accuracy by 5%.
Generated embeddings from the phisher data by applying GCN, which were passed through an LSTM model to build a classifier.