Computer Science student building end-to-end intelligent systems — from explainable ML models to robust Django REST APIs — grounded in data and deployed in the real world.
I'm Naveena Sahukari, a Computer Science student at Vardhaman College of Engineering, Hyderabad. I enjoy building things — projects that go from an idea to something actually working and deployed.
I've been learning and applying Machine Learning and Backend Development through hands-on projects. I'm drawn to how ML models can be made explainable — not just accurate — and how clean APIs can tie a full system together.
So far I've built a deployed healthcare prediction system using Django and Scikit-learn, a full-stack timetable scheduler, and contributed to RPA automation at MassMutual India as a team lead. I'm still learning, and I'm looking for an opportunity to grow alongside a real team.
I'm actively seeking internships and entry-level roles where I can contribute meaningfully and keep building my skills in a professional environment.
Built a Random Forest Regressor achieving 98.80% accuracy on 3,000 synthetic records to predict operational losses from cyberattacks in healthcare. Integrated SHAP (Explainable AI) to surface key risk drivers. Deployed as a full-stack Django application on Railway with dynamic dashboards and risk-level classification.
Developed a full-stack application to automate faculty timetable generation, eliminating scheduling conflicts and reducing administrative overhead. Built a constraint-based scheduling engine with RESTful APIs for real-time conflict detection and dynamic updates. Designed a normalized MySQL schema integrated via RESTful architecture, following SDLC best practices.
Open to internships, entry-level positions, and collaborative projects. I'd love to hear about opportunities where I can contribute and grow.