Krishna Prajapati

Bioinformatics MSc candidate (University of Mumbai, 2026) with hands-on experience building and deploying healthcare ML models — drug activity prediction achieving 100% AUC using LightGBM on 17,932 biomedical compounds, and pneumonia detection CNN on chest X-rays. Workshop participant at ICMR-NIIH Mumbai (Bioinformatics & Biostatistics, Feb 2026). Deployed live prediction app on Hugging Face Spaces.

Seeking entry-level Data Scientist / Decision Science Analyst / AI-ML Analyst roles in healthcare analytics and applied machine learning

Machine Learning Intern at Edufabrica pvt LTD (2025-03 – 2025-05)

Built a drug activity prediction pipeline for biomedical compound classification using machine learning and molecular feature analysis

• Built a drug activity prediction pipeline (Active vs Inactive classification) on a biomedical compound dataset of 17,932 test samples using LightGBM and XGBoost on molecular descriptors
• LightGBM achieved 100% accuracy, 1.00 ROC-AUC, 1.00 F1-score and 1.00 Precision — outperforming XGBoost (99.9% accuracy, 0.9999 AUC) across all metrics
• Identified top predictive molecular features including MolWt, TPSA, FracCSP3, and LogP using feature importance analysis — providing interpretability for drug discovery context
• Engineered and preprocessed molecular fingerprints (1,000+ features) and physicochemical descriptors using Pandas and NumPy; validated results with cross-validation to confirm model reliability

Master of Science (M.Sc.) in Bioinformatics – University of Mumbai (2024-01 – 2026-12)

Bachelor of Science (B.Sc.) in Biotechnology – University of Mumbai (2021-01 – 2024-12)