I'm a Computer Engineering student at Thapar Institute of Engineering & Technology, focused on applying machine learning and software engineering to real-world optimization and sustainability challenges.

My work spans EV battery intelligence, graph-based Detection Systems, and full-stack platforms. I approach engineering through first-principles problem solving—understanding constraints, defining architecture, and then building systems that scale.

In 2026, I led the development of an AI sustainability solution that won 1st place at an international hackathon hosted by the Canadian University Dubai among 200+ global teams.

I believe sustainability and optimization are the defining engineering challenges of this decade, and I'm particularly interested in AI systems that create measurable impact in energy, infrastructure, and industrial domains.

Built an end-to-end machine learning platform for EV battery diagnostics and Remaining Useful Life (RUL) prediction.

• Processed 10,000+ battery telemetry records
• Engineered 50+ battery-health features
• Trained regression and LSTM models achieving ~90% prediction accuracy
• Developed FastAPI services for real-time inference
• Containerized deployment using Docker

Tech: Python, Scikit-Learn, LSTM, FastAPI, Docker

Designed a graph-based identity fraud detection framework that models relationships between entities and identifies suspicious patterns through network analysis.

• Built scalable ETL pipelines using Pandas
• Modeled identity relationships as graphs
• Achieved ~82% anomaly detection accuracy
• Visualized anomaly clusters and centrality metrics

Tech: Python, NetworkX, Scikit-Learn, Pandas

A full-stack platform promoting cultural exploration across India.

• Cataloged 3,691+ monuments
• Integrated 42 UNESCO heritage sites
• Built interactive map visualizations
• Implemented digital heritage passport system
• Deployed on Vercel

Tech: Next.js, TypeScript, REST APIs, Vercel

Canadian University Dubai

Led the development of an AI-powered sustainability solution that secured 1st place among 200+ international teams.

Designed and validated a cross-company collaboration business model under extreme time constraints, securing 1st place.

• Machine Learning Systems
• Applied AI for Sustainability
• Data Engineering & Pipelines
• MLOps & Deployment
• Production AI Applications
• Energy & Climate Technology

Languages

Python • C++ • JavaScript • TypeScript

Machine Learning

Scikit-Learn • Regression • Classification • LSTM

Data

Pandas • NumPy • PostgreSQL • OracleDB

Backend

FastAPI • REST APIs

Frontend

Next.js • TypeScript

Infrastructure

Docker • Git • Vercel

Visualization

Matplotlib • Seaborn

Build systems that solve meaningful problems.

Optimize before scaling.

Measure before claiming impact.

• LinkedIn: https://linkedin.com/in/sahil-manglaa
• GitHub: https://github.com/sahil-mangla
• Email: sahilmangla.official@gmail.com