A B.Tech (AI & Data Science) graduate and software developer working across deep learning, LLM applications and full-stack web & mobile. Published IEEE researcher, 20+ projects shipped.
Leukemia detection on C-NMC, 84% acc, 0.90 ROC-AUC, 95% recall; custom GAN augments scarce medical data.
Mental-health screening for 100+ students, chatbot + psychometrics at 95% accuracy, drop-off cut 30%.
Railway platform & track-assignment optimizer, constraint programming yields conflict-free schedules.
Bank-statement analyzer, LLM extraction from PDFs/images, insights via FastAPI + Streamlit.
Desktop AI assistant, conversational GUI + voice commands, 70% faster task execution.
Android app for committee task & attendance tracking with real-time Firebase sync.
+ the full set on the portfolio and GitHub ↗
Comparative Analysis of Psychometric Data for Assessing Mental Health Testing Needs Using Machine Learning Models
Benchmarked 5 ML models (Logistic Regression, Random Forest, SVM, XGBoost, LightGBM) on PHQ-9 / GAD-7 psychometric data with cross-validation and SHAP interpretability for clinically meaningful pre-screening.
Python, Java, C, C++, JavaScript, HTML/CSS, SQL
PyTorch, TensorFlow, Flask, FastAPI, Next.js, React, Node.js, Streamlit
Git, Firebase, OR-Tools, Jupyter, Postman, Power BI, Android Studio
Machine Learning, Deep Learning, GANs, LLM Integration, REST APIs
+ full record on certificates