CSE (AI & ML) undergrad at MIT Manipal. Published IEEE researcher. I build ML systems, data pipelines, and robotics solutions that cross from research to production.
I'm Nandipati Vasishta Vardhan Reddy, an AI/ML engineering student at Manipal Institute of Technology, Manipal. I'm passionate about building systems that are intelligent and production-ready.
My work spans ML systems engineering, data pipelines, robotics navigation, and cybersecurity-oriented automation. Currently a Data Analyst at Mangomelon AI LLC, designing AI-driven workflows for healthcare data research.
I've published in IEEE, interned at Algonomy (Bangalore), and built production Python tools with real-world utility. I cross the gap between research-level thinking and deployment-ready code.
Introduces an intelligent robot navigation method combining A* search with potential field optimization, informed by real-time depth image data. Unlike standard A* — which only minimizes path length — this approach incorporates slope analysis and dynamic obstacle avoidance, producing routes that are both geometrically short and physically safe for complex terrain deployment.
View on IEEE →Automated dataset discovery via Kaggle API and LLM-based synthetic data generation. Secure API-key access controls and structured dataset management for repeatable ML workflow automation.
Published CLI tool for detecting leaked secrets and API keys in local codebases and public GitHub repos, including git history. Implements 55+ regex patterns, Shannon entropy detection, live secret verification across 10 services, SARIF output, and pre-commit hook support for CI/CD-native secret hygiene.
Enterprise vendor screening combining web search aggregation, NLP risk detection, and automated PDF evidence archiving. Generates compliance-ready reports for procurement workflows.
Open to ML engineering roles, research collaborations, and interesting projects. Reach out — I reply fast.