HELLO, WORLD

I'm Vanya Awasthi

STUDENTDEVELOPERPROBLEM SOLVER

I don't just solve problems,

I reimagine what's possible.

Education

Bachelor's Degree

Aug 2023 - June 2027

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, SRICITY, CHITTOOR

Currently pursuing B.Tech. Degree specialization in Computer Science (CSE)

CGPA: 9.37/10.00

Experience

SDE Intern

May 2025 - Aug 2025

Hoffero, Singapore (Remote)

• Worked with APIs and implemented webhooks to set up automated messaging on creators' and hotels' Instagram accounts, enabling real-time communication and increased engagement.

• Utilized LangChain to enhance the accuracy and efficiency of the app's trip-planning chatbot, improving user experience and reducing response latency.

• Enhanced UI/UX of the webapp. Fetched insights of creators' account for hotels' to make data driven decision for collaboration.

NodeJSFlutterFirebaseLangChainGoogle CloudFast API

My Skills

Languages

C++

Python

Java

HTML

CSS

JavaScript

Dart

Frameworks

Flutter

Firebase

Next.js

React.js

Node.js

Tailwind CSS

REST API

Tools

Git

GitHub

Android Studio

Google Cloud

Database

MySQL

MongoDB

My Projects

Quickart

Developed a full-stack essentials delivery website with real-time tracking, OTP-verified handoffs and AI-assisted shopping. Integrated Gemini AI for visual search, prescription reading, and chat-based shopping assistance. Designed responsive, role-based dashboards with a community-first, zero-profit model for areas underserved by Blinkit, Zepto or PharmEasy.

NextJsReactJSTailwind CSSFirebaseGen AI

🔗 GitHub 🚀 Live Demo

Harvest Hub

Built a cross-platform mobile app to support farmers with crop inventory tracking, equipment requests, and 24/7 AI consultation. Designed for rural accessibility with multilingual support and a simple UI.

FlutterFirebaseOpenStreetMapDart

🔗 GitHub 🚀 Live Demo

Othello Player

Implemented a lightweight, AlphaZero-inspired Othello agent using TD(λ) n-tuple learning, enabling fast and efficient self-play training without GPU acceleration. Applied Monte Carlo Tree Search (MCTS) only during test time to significantly enhance move quality and playing strength without increasing training complexity. Achieved competitive gameplay performance and benchmarking against Edax Othello engine (up to level 5).

PythonNumPyMCTSTD LearningEdaxReinforcement Learning

🔗 GitHub

Achievements & Certifications

🛒

Competition