Deepanshu Tolani

Integrated six heterogeneous forensic log sources into a unified NTFS Master File Table (MFT) using Python, enabling structured data indexing, faster querying, and improved forensic traceability. Implemented a scalable Python-based parsing engine to ingest, validate, and normalize multi-source NTFS logs, eliminating processing bottlenecks and improving pipeline throughput and data reliability. Pioneered and hardened ETL data pipelines in Python with modular processing stages, reducing manual intervention and improving reproducibility, fault tolerance, and analytical accuracy.

Research Intern - National Institute of Technology, Raipur - Raipur, India

(2025-05 - 2025-07)

• Integrated six heterogeneous forensic log sources into a unified NTFS Master File Table (MFT) using Python, enabling structured data indexing, faster querying, and improved forensic traceability.
• Implemented a scalable Python-based parsing engine to ingest, validate, and normalize multi-source NTFS logs, eliminating processing bottlenecks and improving pipeline throughput and data reliability.
• Pioneered and hardened ETL data pipelines in Python with modular processing stages, reducing manual intervention and improving reproducibility, fault tolerance, and analytical accuracy.

B.Tech. - Computer Science and Engineering - SRM Institute of Science and Technology (2023-08 - 2027-05)