Batthula Sirijahnavi

I've built and debugged Python applications spanning real-time bidding optimization, deep learning, and enterprise-support workflows. During my ServiceNow virtual internship with AICTE and SmartBridge, I worked with IT workflow automation, enterprise application support, incident handling, and process automation concepts.

For a multi-agent Q-learning real-time bidding simulation, I tested and tuned three competing agents against a 53,885-record dataset; the best agent won 85.3% of contested impressions. I used Pandas and NumPy for data validation, verified roughly 50% click-through rate and 99.9% budget utilization, and documented and visualized the findings.

I've also built a Swin Transformer-based lung health prediction solution with a React.js frontend, MySQL, and blockchain-backed medical records. In a separate task manager project, I developed authentication, CRUD operations, deadline tracking, and reliable multi-user PHP/MySQL sessions.

I'm an upcoming Computer Science Engineering graduate who enjoys systematic debugging, root-cause analysis, technical documentation, and collaborating across teams to resolve business-critical issues.