Pavan N

AI and Machine Learning professional with extensive experience in automating data-intensive processes and delivering AI-driven solutions across diverse sectors, including healthcare, FMCG, oil & gas, and engineering. Adept at leveraging deep learning models, OCR, and document intelligence techniques to drive efficiency and reduce manual effort. Proven track record in successfully implementing solutions that enhance operational workflows and ensure high accuracy in data extraction and analysis.

Cavity Detection in Panoramic Radiographs using Deep Learning

• Built a UNET based deep learning model with 78% IoU for detecting cavities in panoramic radiographs

Comparison of Digital Packaging Labels using AI (FMCG)

• Automated comparison of digital packaging using entity detection for text and symbols.
• Reduced manual processing time from hours to seconds through automation.

Digitization of Piping and Instrument Diagrams (Oil & Gas)

• Extracted regions of interest and metadata, classifying inlet/outlet parts and detection of PID objects.
• Developed arrow detection and metadata extraction using custom models.
• Automated CAD conversion, reducing manual processing time from months to minutes.

Analyzing Engineering Bill of Materials (EBOMs)

• Integrated GPT models to interpret metadata and retain formatting.
• Used OCR and rule-based extraction for scanned documents.

Wiring Chart Analyzer.

• Extracted and computed wire lengths and part numbers across multi page PDFs.
• Automated generation of structured excel output.

Spare Parts Recommendation System.

• Designed a transformer based model to predict next customer purchases from historical data..
• Built and end-to-end training, validation, and inference pipeline.

• Certificate of Recognition for filing a patent at Indian patent Office titled "Method & System of Comparing Digital Labels" (IN202141039416), awarded by L&T Technology Services.
• "Method and System for generating editable schematic illustration of non-editable schematic illustration" (IN202541019135)
• "Method and System for determining pipeline flow in non-editable schematic illustration" (IN202541025242)
• "Method and System for correcting skewness in images" (IN20254103399)

Microsoft Certified, Azure AI Engineer - Microsoft.

• Strong desire to stay updated with the latest advancements in AI/ML technology.
• Actively contributes to team culture fostering diversity, equity, and inclusion.