Harsh Gangurde

Developed a novel model combining VGG16 and CNN for deep fake detection, achieving 94% accuracy. Validated the model using confusion matrix analysis on a benchmark dataset, demonstrating high detection efficiency.

Developed a deep learning model for chest cancer classification using TensorFlow, achieving 92.5% accuracy. Integrated MLflow & DVC for experiment tracking and automated CI/CD pipelines for deployment.

Implemented a collaborative filtering-based movie recommender system using Python and Scikit-Learn, evaluating it with cosine similarity and achieving over 1,500 unique user interactions.

Created a web application using Streamlit for analyzing census data, providing insights into demographic trends through interactive visualizations.

Built a Python-based automated trading execution system integrating Angel One SmartAPI for live order management and broker authentication. Developed modular scripts for order lifecycle automation with intelligent filters to prevent duplicates, conflicts, and early exits.

Built a FastAPI-based document matching API using multi-agent LLMs and stored structured JSON outputs in Azure Blob Storage. Implemented secure Azure Blob pipelines with client-side and server-side encryption and designed a modular backend for real-time document analysis.

Grade: 7.3 CGPA

Pursuing a B.Tech in Artificial Intelligence and Data Science, focusing on the integration of AI technologies and data analytics to solve complex problems.

Pursuing a B.Tech in Artificial Intelligence and Data Science at AISSMS IOIT, Pune.

Grade: 77.67%

Completed Higher Secondary Certificate (HSC) with a focus on science subjects, achieving a percentage of 77.67%.

Grade: 92.20%

Achieved Secondary School Certificate (SSC) with a percentage of 92.20%, demonstrating strong foundational knowledge in various subjects.

Grade: 77.67%

Completed HSC with a score of 77.67%.

Grade: 92.20%

Completed SSC with a score of 92.20% in 2022.