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Mohan Raj

@mohanraj2

AI/ML intern at Pantech Solutions India Pvt Ltd who shipped explainable PCOS screening and ultrasound models as a secure FastAPI service.

India

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At Pantech Solutions India Pvt Ltd, I built Maitri AI, a PCOS risk screening product that achieved 92.7% accuracy and 0.97 ROC-AUC. I also trained an ultrasound classification model that reached 0.997 ROC-AUC and checked its results on a de-duplicated test set.

I shipped both models as a secure REST service with FastAPI, per-patient SHAP explanations, and row-level security across cloud-hosted PostgreSQL tables. I added automated tests for the service.

At Take It Smart (OPC) Pvt. Ltd., I delivered a Django Hospital Management System with role-based access and an automated patient workflow. I also built CareerMap, a career guidance platform combining resume skill extraction, role recommendations, readiness scoring, and personalized roadmaps.

Experience

Work history, roles, and key accomplishments

AI/ML Intern

Pantech Solutions India Pvt Ltd

Mar 2026 - Jul 2026 (4 months)

Built an end-to-end PCOS risk screening product (Maitri AI) achieving 92.7% accuracy and 0.97 ROC-AUC by training a stacked XGBoost, LightGBM, and CatBoost ensemble on 541 clinical records. Achieved 98.5% accuracy on ultrasound classification across 7451 images using EfficientNetB0 transfer learning and shipped both models as a secure FastAPI REST service with SHAP explainability and row-level sec

XGBoost LightGBM CatBoost EfficientNetB0 fastAPI SHAP PostgreSQL Supabase Pytest Vitest

Python Django Intern

Take It Smart (OPC) Pvt. Ltd.

Sep 2025 - Nov 2025 (2 months)

Delivered a production-style Hospital Management System for 3 user roles (Admin, Doctor, Patient) by implementing secure authentication and role-based access control (RBAC) on Django's MVT architecture. Automated the complete patient lifecycle and built live dashboards for all roles by tuning Django ORM queries.

Django Python RBAC ORM HTML5 CSS

Machine Learning Intern

Take It Smart (OPC) Pvt. Ltd.

Apr 2024 - May 2024 (1 month)

Transformed 50,000+ raw records into a model-ready dataset by building a pandas/NumPy preprocessing pipeline covering missing value treatment, IQR-based outlier detection, and feature engineering. Delivered 10+ business recommendations from statistical EDA visualized in Matplotlib and Seaborn.

Pandas NumPy Matplotlib SeaBorn EDA Feature Engineering