I built an end-to-end pipeline for the IoT Energy & Water Monitor, using 73 days of appliance-level sensor data for time-series transformation and data-quality validation. I added anomaly detection and consumption forecasting, surfaced through an interactive dashboard; the project is associated with published patent 202511133374 A.
For CyberShield AI, I designed, trained, and evaluated three machine-learning models for real-time intrusion detection, reaching up to 99%+ accuracy. The system detects DoS, DDoS, SQL Injection, and Brute Force attacks through a monitoring dashboard.
I also built SmartQuery AI, which translates plain-English questions into queries across 21,900+ rows in five datasets and generates visualizations. My other project work includes a wearable for personnel identification and zone-presence monitoring, which is the basis of a published patent.
As a Data Science Intern at Pavanastr Technologies, I applied machine-learning and data-processing techniques to business datasets, including data collection, cleansing, and validation for model training. I’m completing a B.Tech in Data Science & Engineering at Manipal University Jaipur, and I’m a first inventor on two published patents and an author of three international conference papers.
