Developer and a student.
Bachelor of Engineering in Computer Science & Engineering
2020-2024
FedEx Express
May 2023 - Aug 2023 · 3 mos
Indie Developer / Self-Employed
Sep 2014 - Jul 2020 · 5 yrs 11 mos
Built and published over 12 Android apps in the Play Store.
They've over 21.5K cumulative installs, and about 17K installs come from the top 2 apps
published.
Most of the apps were made in Java, while some were built using Flutter and no-code tools.
A project developed with the primary objective of helping the visually impaired
with
their mobility. It helps to recognize and detect objects in front of them.
Object Detection:
The PDFChat app allows you to chat with your PDF files using the power of langchain, OpenAI Embeddings, and GPT3.5 in the backend. It uses Streamlit for the user interface.
One of its standout features is converting uploaded PDFs into vector embeddings, which help connect the PDF content with the language models. Langchain and OpenAI API work together to gather important information from the vector store. This information becomes context for GPT-3.5.
When you use the app, you can type in questions or statements about the PDF's content.
The app combines what you input with the context from Langchain and OpenAI Embeddings. This combined context is used to talk with GPT-3.5, generating responses that make sense within the context.
In a nutshell, the PDFChat app transforms how you interact with PDFs. It lets you not only read them but also have meaningful conversations. Whether you want to understand complex details, ask things, or get insights, the PDFChat app makes working with PDFs more interactive and engaging.
I built a basic, anonymous and decentralized version of Twitter on Solidity.
The smart contract is deployed on Ethereum Rinkeby Testnet using Alchemy.
Users can connect their Metamask wallets and tweet on the website.
There's a random chance for users to win some ETH (Test ETH) when they tweet.
digest is an app that lets you summarize articles using NLP.
It cuts down about 75% of an article and retains only the key bits. It puts
together content & make them more easy to consume in a beautiful reader view,
eliminating all intrusive ads.
Moreover all articles you save in digest are stored
offline enabling the users to read them anytime, even if the article is pulled
from
the
source site.
✓ Designed with elegance
A minimalistic approach to the web.
✓ Privacy
digest throws cookies and trackers off your trail. Articles stored in digest can
only be
read by user.
We've created a 'virtual clinic' mobile application for Android and iOS (using
Flutter and Firebase) for our participation in the KFAS & CODED Virtual
Hackathon.
The main goal of the project is to eliminate the pressure created on medical
systems
during the COVID-19 pandemic by creating digital queues for consulting a doctor.
This'd help in resolving the mild cases over a video call and bringing the
serious
cases to the hospital.
Out of the 40 teams that took place, we stood in the top 7.
The application's features include:
It is an app that makes meeting teachers a
frictionless process.
Meeting professors in college can sometimes be a hassle due to clashes in
timetables.
The objective of the app is to solve this problem.
It lets you find when your teachers are available and enables
you to request a meet with a click.
Teachers will be able to upload their timetable, which can be edited at any
time.
And students get to search for a teacher they want, either by their name or by
their
department, and can request to meet their teacher in their free time. If a meet
is being requested for clearing up doubts, then students will be able to upload
images of their assignments, homework, etc.
Teachers will be able to accept or reject the request, which will also be
indicated
to the students.
It is a project that I built during the Abacus Hackathon, an inter-college
hackathon conducted by CEG and sponsored by Visa.
Out of the various teams that took part, I participated individually and secured
first place.
A Platform Where Sellers Find Buyers
Hyper lets you post an item that you're looking for along with the price range,
and
then a person who wishes to sell that item contacts you to make a deal.
The app was built for Android using Java. All the UI elements were
prototyped initially with the help of Sketch. Parse by FaceBook was used for the
app's backend.