CSE student at GCET Hyderabad | MERN, Python, ML | Hackathon winner
Hyderabad, Telangana, India
basinasuryasashank@gmail.com
I’m a third-year B.Tech Computer Science student at Geethanjali College of Engineering and Technology in Hyderabad, graduating in 2028. I build full-stack web apps with MongoDB, Express, React and Node.js, and I add a machine learning layer when a project needs one, using Python, scikit-learn and FastAPI. My strongest result so far is Review Guardian, a fake review detection platform that took 1st place at the TECHSYNAPSE NEXTGEN INNOVATORS 24-hour national level hackathon. I built it with a team in one day, from the model to the dashboard. I’ve also done two internships. At Internvision Technology I worked on cloud computing, and at Brain O Vision Solutions I worked on Python, data science, ML and AI. The Brain O Vision work led to TicketSense, a feedback analyzer that uses VADER for sentiment and YAKE for keyword extraction, with Recharts dashboards on top. More recently my team built DealMind, a negotiation intelligence agent that uses Hindsight as long-term memory. It made the top 10 at the finals of a Microsoft hackathon, held at the Microsoft office. We have also submitted our idea for Smart India Hackathon 2026, an AI system for detecting anomalies and fraud in the MPLAD scheme, and we’re waiting on the result. I’m looking for internship and entry-level software roles where I can keep building end to end. Code is on GitHub at github.com/SuryaSashank09
Python, Data Science, ML and AI Intern
Brain O Vision Solutions
Fake review detection platform. Won 1st place at the TECHSYNAPSE NEXTGEN INNOVATORS 24-hour national level hackathon. Built with a team in one day, from the model to the dashboard.
Negotiation intelligence agent that uses Hindsight as long-term organizational memory. SQLite holds structured state, Groq handles language synthesis, and deterministic services calculate economics and confidence. Reached the top 10 at a Microsoft hackathon finals.
Smart India Hackathon 2026 entry for AI-powered anomaly and fraud detection in the MPLAD scheme. Has an Express backend, a React and Vite frontend, a FastAPI ML service, a rule engine, and role-based access control. I handled the frontend and design. Submitted, result pending.
B.Tech
Geethanjali College of Engineering and Technology, Hyderabad · 8.0
Attendee · Oct 24, 2026