Computer Science at Northeastern University | Software Development • AI Engineering • Backend Systems | Skilled in Java, CPP, Python, SQL, Cloud, CI/CD
Introduction
I am an MS in Artificial Intelligence student at Northeastern University, currently looking for software engineering and AI/ML internships.
Most of my experience is backend. At Aditya Birla Group I worked on an internal supply chain platform, building transaction processing, REST endpoints, and request queuing in Spring Boot for a system handling 500K+ transactions a month from multiple upstream sources, along with validation and retry handling for the failures that came with that volume. At Lanxess I worked on document ingestion, extending MongoDB models for metadata retrieval and adding Redis caching to cut repeated database reads. I have also built frontend in React and TypeScript, and an Android app in Java with BLE communication to embedded irrigation hardware.
On the AI side, I have built an agentic job application assistant with LangGraph and a RAG pipeline over ChromaDB, and published VersionIO, a Python versioning package. My undergrad thesis applied computer vision to road safety and traffic surveillance, logging offences, and routing reports to the relevant authorities.
Java, Spring Boot, Python, PostgreSQL, MongoDB, Redis, React, TypeScript, Docker, AWS. Open to conversations - reach me at shekhawat.n@northeastern.edu
What I have done so far
Academic background
My work
A selection of projects spanning security tooling, optimization systems, reinforcement learning, and computer vision.
Recognition & leadership
Received the Top Performer Award for the Batch of 2021–25, SRMIST.
View CertificateWon the Tenacity Award at the TAC Challenge, an international subsea drone competition in Norway.
View CertificateServed as Student Team Lead, overseeing the development and execution of projects focused on subsea docking, pipeline inspection, and valve intervention (2023–2025).
Research collaborator at SRMIST's Directorate of Entrepreneurship and Innovation on an AI Driven Debris Cleaning System, backed by DRDO and NIOT with INR 9,00,000 in funding.
Research
A novel approach for layered data aggregation in underwater acoustic sensors, with improved transmission and optimized energy efficiency.
Read PaperImplemented LSTM and GRU deep learning algorithms to capture sequential patterns and long-term dependencies in traffic data for improved forecasting accuracy.
Read PaperGet in touch
Open to Software Engineering and AI/ML Engineering opportunities. Let's build something together.