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Created the cutting-edge RapidFuzz algorithm using NLP, reducing medication errors by 30% and enhancing efficiency. Applied it to data from top pharmacies, processing 697,620 medicines for precision and productivity.Crafted a Python program to scrape data from web from an array of pharmaceutical industry leaders, including Tata1mg, Pharmeasy, Netmeds, Apollo Pharmacy, MrMeds, Medkart, and Kauverymeds. The harvested data was seamlessly integrated into an ElasticSearch database, propelling the organization into a new era of data-driven excellence. Implemented a robust scheduling system for the Python web scraping processes, allowing for periodic data extraction from the pharmaceutical websites every 4 days. This meticulous approach ensured the continuous growth of our database, resulting in the seamless mapping and integration of the newly acquired data with the previous parent dataset while detecting the price change and ultimately expanding our repository by 30% year-on-year, fortifying our data-driven capabilitiesHarnessed the power of multithreading to significantly accelerate the data scraping process, improvingefficiency and throughput. This approach has played a crucial role in achieving our data-driven goals

Developed Advanced Embeddings: Created embeddings for a large dataset of 55,000 medicines using models like LLaMa 3.1, Gemini-Pro, and GEMMA 2, paired with UMAP for dimensionality reduction.Launched MediGlot: Initiated and developed MediGlot, a sub-project of Polyglot, enhancing the analysis and visualization of medicinal data.Contributed to PolyPhy/Polyglot: Played a key role in advancing the PolyPhy/Polyglot project by focusing on 3D clustering of medicinal data, driving new insights into complex medical patterns.

Led a project focusing on the correlation between climate factors andthe spread of vector-borne diseases.Scraped and compiled weekly climate data (2015-2021) for 30 major cities in India, including max temperature, average temperature, min temperature, and sunlight hours.Developed a Python program to extract real-time insights on various diseases in India from the dynamic landscapeof Twitter and Google Newswires.Analyzed the scraped data to identify patterns, correlating climate variables with vector-borne diseases and produced clear visualizations and reports for easy interpretation.

Currently working on a project aimed at monitoring the progression of Parkinson’s disease.Analyzing the presence of protein peptides in bodily fluids as a potential biomarker for disease progression.Implementing vocal cord monitoring in the larynx to complement the analysis of protein peptides.

Developed a state-of-the-art Handwritten Text Recognition (HTR) program using Tesseract, achieving animpressive 94% accuracy on the challenging IAM datasetLeveraged blockchain technology with Solidity, Web3.js, and Metamask to create a secure patient-centric medical blockchain ecosystem. Patients can access their comprehensive medical history with a simple ID, and records are securely stored as unique NFTs on the blockchain