Developed a LightGBM gradient boosting classifier model using technical indicators and global market factors to predict Nifty 50 movements. Prevented lookahead bias and data leakage, enhancing profit through combined ETF and futures trading.

Developed a traffic monitoring system that detects and tracks vehicles in video feeds using YOLOv8. Supports zone drawing, zone-based detections, live streaming to the frontend and analytics visualizations.

Built an investment comparison app to evaluate Stocks, ETFs, Mutual Funds, Bonds & FDs using returns, risk and liquidity. Includes scenario simulation, risk-tolerance based asset allocation and Gemini-powered diversification recommendations.

Simulated a distributed SYN flood DDoS attack using a command-and-control server and bots. Built an attacker–victim–legitimate user setup using VMs, and analyzed impact on availability and traffic behavior.

Designed a tamper-resistant voting system using blockchain for transparency and auditability. Implemented vote immutability, one-vote-per-user constraints and verifiable counting.

• Built Python data pipelines and an NSE equity backtesting engine to process 10 years of minute-level data for 3,000+ securities, incorporating transaction costs, slippage, leverage, and risk controls.
• Engineered and evaluated 900+ quantitative factors across momentum, volatility, liquidity, volume, and price action for systematic alpha research and trading-signal discovery.
• Integrated an LLM-driven research workflow to convert market insights into executable strategies and large-scale backtests, while optimizing AWS-based execution, memory usage, and safeguards against look-ahead bias.

• Worked on “Symphony AI Integration” within EY’s Business Consulting – Risk practice.
• Built Python pipelines to generate & validate large-scale synthetic financial exception data for analytics prototyping.
• Developed a GenAI-driven risk analytics assistant using Gemini API + structured prompt engineering across 33+ KRIs.
• Implemented dynamic schema parsing, context construction, and enterprise-ready integration to support exception investigation workflows.
• Focused on scalability, accuracy, and deployment readiness in an enterprise risk environment.

Migrated legacy HDF5 storage pipelines to Apache Parquet with direct integration to Amazon S3 for faster analytics workflows. Built a Streamlit-based financial data visualizer to improve exploratory analysis for strategy research. Automated scheduled SQL pipelines and contributed to backtesting workflows.

Contributed to an AI-based traffic analysis project using computer vision. Assisted with backend pipelines for video analytics and model testing workflows for vehicle detection in Indian traffic environments.

Designed and integrated RESTful APIs using Spring Boot within a microservices architecture. Fixed production-level bugs and improved stability across multiple Spring Boot services. Implemented SQLite-based local data storage and contributed to performance optimization.

Developed a Restaurant Menu Management System using Spring Boot and basic database integration. Completed structured training in Python and backend development fundamentals.