Computer Engineering student at Thapar Institute of Engineering & Technology passionate about AI systems, machine learning, backend engineering, and database infrastructure.

I enjoy building production-ready software that combines machine learning, databases, distributed systems, and modern AI tooling. My recent work spans NLP, time-series forecasting, database administration, telemetry pipelines, MLOps, and open-source software.

• Building production AI and data infrastructure
• Designing scalable telemetry and monitoring systems
• Exploring Agentic AI and Model Context Protocol (MCP)
• Contributing to open source and production engineering projects

An NLP platform that analyzes Hacker News discussions to identify emerging technology trends.

• Clustered 2,000+ Hacker News discussions into 85 semantic topics using Sentence Transformers, UMAP, and HDBSCAN.
• Built forecasting pipelines using Linear Regression, XGBoost, and LSTM with MLflow experiment tracking.
• Generated natural-language trend summaries using Gemini.

Stack: Python • PyTorch • Sentence Transformers • HDBSCAN • UMAP • MLflow • Streamlit

Production-oriented database monitoring framework developed during my internship at DCM Infotech.

• Built a modular health monitoring engine using SQL Server DMVs and Extended Events to analyze index fragmentation, storage utilization, transaction log health, and deadlock telemetry.
• Designed a configuration-driven architecture with reusable T-SQL views, stored procedures, historical snapshot collection, and executive health reporting.
• Developed a reproducible validation laboratory covering fragmentation, storage, Write-Ahead Logging (WAL), recovery models, deadlock detection, and end-to-end dashboard validation.

Stack: SQL Server • T-SQL • DMVs • Extended Events • Database Administration

Database auditing and disaster recovery automation platform built during my internship.

• Automated backup verification and restore validation across production databases.
• Developed trigger-based field-level auditing using PostgreSQL and PL/pgSQL.
• Implemented SHA-256 integrity verification for backup validation and disaster recovery workflows.

Stack: PostgreSQL • PL/pgSQL • Python • Docker

I enjoy contributing to production-grade open-source software and learning from large engineering codebases.

Recent contributions include Codebase Memory MCP, Pytorch, where I investigated indexing failures on large repositories, identified memory bottlenecks, proposed production fixes, and contributed improvements to developer tooling.

Python • C/C++ • JavaScript • TypeScript • SQL

PyTorch • Scikit-learn • XGBoost • LSTM • Sentence Transformers • HDBSCAN • UMAP • MLflow

Gemini API • Prompt Engineering • Model Context Protocol (MCP)

FastAPI • REST APIs • Next.js • Streamlit

SQL Server • PostgreSQL • Oracle Database • T-SQL • PL/pgSQL • Database Administration • Query Optimization • Backup & Recovery • Performance Monitoring

Docker • Git • GitHub • Hugging Face Spaces • Firebase • Vercel

• 🏆 Winner — International AI for Sustainability Hackathon 2026 (1st Place among 200+ teams)
• 🏆 Winner — TIET Business Hackathon 2024

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